ALBERT

Description: The time synchronization protocol is indispensable in various applications of wireless sensor networks, such as scheduling, monitoring, and tracking. Numerous protocols and algorithms have been proposed in recent decades, and many of them provide micro-scale resolutions. However, designing and implementing a time synchronization protocol in a practical wireless network is very challenging compared to implementation in a wired network; this is because its performance can be deteriorated significantly by many factors, including hardware quality, message delay jitter, ambient environment, and network topology. In this study, we measure the performance of the Flooding Time Synchronization Protocol (FTSP) and Gradient Time Synchronization Protocol (GTSP) in terms of practical network conditions, such as message delay jitter, synchronization period, network topology, and packet loss. This study provides insights into the operation and optimization of time synchronization protocols. In addition, the performance evaluation identifies that FTSP is highly affected by message delay jitter due to error accumulation over multi-hops. We demonstrate that the proposed extended version of the FTSP (E-FTSP) alleviates the effect of message delay jitter and enhances the overall performance of FTSP in terms of error, time, and other factors.

Description: The Internet of Things (IoT) will feature pervasive sensing and control capabilities via the massive deployment of machine-type communication devices in order to greatly improve daily life. However, machine-type communications can be illegally used (e.g., by criminals or terrorists) which is difficult to monitor, and thus presents new security challenges. The information exchanged in machine-type communications is usually transmitted in short packets. Thus, this paper investigates a legitimate surveillance system via proactive eavesdropping at finite blocklength regime. Under the finite blocklength regime, we analyze the channel coding rate of the eavesdropping link and the suspicious link. We find that the legitimate monitor can still eavesdrop the information sent by the suspicious transmitter as the blocklength decreases, even when the eavesdropping is failed under the Shannon capacity regime. Moreover, we define a metric called the effective eavesdropping rate and study the monotonicity. From the analysis of monotonicity, the existence of a maximum effective eavesdropping rate for a moderate or even high signal-to-noise (SNR) is verified. Finally, numerical results are provided and discussed. In the simulation, we also find that the maximum effective eavesdropping rate slowly increases with the blocklength.

Description: GNSS receiver data crowdsourcing is of interest for multiple applications, e.g., weather monitoring. The bottleneck in this technology is the quality of the GNSS receivers. Therefore, we lay out in an introductory manner the steps to estimate the performance of an arbitrary GNSS receiver via the measurement errors related to its instrumentation. Specifically, we do not need to know the position of the receiver antenna, which allows also for the assessment of smartphone GNSS receivers having integrated antennas. Moreover, the method is independent of atmospheric errors so that no ionospheric or tropospheric correction services provided by base stations are needed. Error models for performance evaluation can be calculated from receiver RINEX (receiver independent exchange format)data using only ephemeris corrections. For the results, we present the quality of different receiver grades through parametrized error models that are likely to be helpful in stochastic modeling, e.g., for Kalman filters, and in assessing GNSS receiver qualities for crowdsourcing applications. Currently, the typical positioning precision for the latest smartphone receivers is around the decimeter level, while for a professional-grade receiver, it is within a few millimeters.

Description: The power transmission lines are the link between power plants and the points of consumption, through substations. Most importantly, the assessment of damaged aerial power lines and rusted conductors is of extreme importance for public safety; hence, power lines and associated components must be periodically inspected to ensure a continuous supply and to identify any fault and defect. To achieve these objectives, recently, Unmanned Aerial Vehicles (UAVs) have been widely used; in fact, they provide a safe way to bring sensors close to the power transmission lines and their associated components without halting the equipment during the inspection, and reducing operational cost and risk. In this work, a drone, equipped with multi-modal sensors, captures images in the visible and infrared domain and transmits them to the ground station. We used state-of-the-art computer vision methods to highlight expected faults (i.e., hot spots) or damaged components of the electrical infrastructure (i.e., damaged insulators). Infrared imaging, which is invariant to large scale and illumination changes in the real operating environment, supported the identification of faults in power transmission lines; while a neural network is adapted and trained to detect and classify insulators from an optical video stream. We demonstrate our approach on data captured by a drone in Parma, Italy.

Description: The number of connected sensors and devices is expected to increase to billions in the near future. However, centralised cloud-computing data centres present various challenges to meet the requirements inherent to Internet of Things (IoT) workloads, such as low latency, high throughput and bandwidth constraints. Edge computing is becoming the standard computing paradigm for latency-sensitive real-time IoT workloads, since it addresses the aforementioned limitations related to centralised cloud-computing models. Such a paradigm relies on bringing computation close to the source of data, which presents serious operational challenges for large-scale cloud-computing providers. In this work, we present an architecture composed of low-cost Single-Board-Computer clusters near to data sources, and centralised cloud-computing data centres. The proposed cost-efficient model may be employed as an alternative to fog computing to meet real-time IoT workload requirements while keeping scalability. We include an extensive empirical analysis to assess the suitability of single-board-computer clusters as cost-effective edge-computing micro data centres. Additionally, we compare the proposed architecture with traditional cloudlet and cloud architectures, and evaluate them through extensive simulation. We finally show that acquisition costs can be drastically reduced while keeping performance levels in data-intensive IoT use cases.

Description: One of the most significant challenges in Internet of Things (IoT) environments is the protection of privacy. Failing to guarantee the privacy of sensitive data collected and shared over IoT infrastructures is a critical barrier that delays the wide penetration of IoT technologies in several user-centric application domains. Location information is the most common dynamic information monitored and lies among the most sensitive ones from a privacy perspective. This article introduces a novel mechanism that aims to protect the privacy of location information across Data Centric Sensor Networks (DCSNs) that monitor the location of mobile objects in IoT systems. The respective data dissemination protocols proposed enhance the security of DCSNs rendering them less vulnerable to intruders interested in obtaining the location information monitored. In this respect, a dynamic clustering algorithm is that clusters the DCSN nodes not only based on the network topology, but also considering the current location of the objects monitored. The proposed techniques do not focus on the prevention of attacks, but on enhancing the privacy of sensitive location information once IoT nodes have been compromised. They have been extensively assessed via series of experiments conducted over the IoT infrastructure of FIT IoT-LAB and the respective evaluation results indicate that the dynamic clustering algorithm proposed significantly outperforms existing solutions focusing on enhancing the privacy of location information in IoT.

Description: There is strong demand for real-time suspicious tracking across multiple cameras in intelligent video surveillance for public areas, such as universities, airports and factories. Most criminal events show that the nature of suspicious behavior are carried out by un-known people who try to hide themselves as much as possible. Previous learning-based studies collected a large volume data set to train a learning model to detect humans across multiple cameras but failed to recognize newcomers. There are also several feature-based studies aimed to identify humans within-camera tracking. It would be very difficult for those methods to get necessary feature information in multi-camera scenarios and scenes. It is the purpose of this study to design and implement a suspicious tracking mechanism across multiple cameras based on correlation filters, called suspicious tracking across multiple cameras based on correlation filters (STAM-CCF). By leveraging the geographical information of cameras and YOLO object detection framework, STAM-CCF adjusts human identification and prevents errors caused by information loss in case of object occlusion and overlapping for within-camera tracking cases. STAM-CCF also introduces a camera correlation model and a two-stage gait recognition strategy to deal with problems of re-identification across multiple cameras. Experimental results show that the proposed method performs well with highly acceptable accuracy. The evidences also show that the proposed STAM-CCF method can continuously recognize suspicious behavior within-camera tracking and re-identify it successfully across multiple cameras.

Description: The paper proposes a sensors platform to control a barrier that is installed for vehicles entrance. This platform is automatized by image-based license plate recognition of the vehicle. However, in situations where standardized license plates are not used, such image-based recognition becomes non-trivial and challenging due to the variations in license plate background, fonts and deformations. The proposed method first detects the approaching vehicle via ultrasonic sensors and, at the same time, captures its image via a camera installed along with the barrier. From this image, the license plate is automatically extracted and further processed to segment the license plate characters. Finally, these characters are recognized with the help of a standard optical character recognition (OCR) pipeline. The evaluation of the proposed system shows an accuracy of 98% for license plates extraction, 96% for character segmentation and 93% for character recognition.

Description: Wireless sensor networks are widely used in many fields. Nodes in the network are typically powered by batteries. Because the energy consumption of wireless communication is related to the transmission distance, the energy consumption of nodes in different locations is different, resulting in uneven energy distribution of nodes. In some special applications, all nodes are required to work at the same time, and the uneven energy distribution makes the effective working time of the system subject to the node with the largest energy consumption. The commonly used clustering protocol can play a role in balancing energy consumption, but it does not achieve optimal energy consumption. This paper proposes to use the power supply line to connect the nodes to fully balance the energy. The connection scheme with the shortest power line length is also proposed. On the basis of energy balance, the method of transmitting data with the best hop count is proposed, which fully reduces the power consumption of the data transmission. The simulation results show that the proposed method can effectively reduce the energy consumption and prolong the lifetime of wireless sensor networks.

Description: High frequency guided-waves offer a trade-off between the high sensitivity of local bulk ultrasonic thickness measurements and the large area scanning of lower frequency guided-waves, so it has been a growing interest for corrosion inspection with the dispersive SH1 mode. However, according to the dispersive curve, it is hard to generate the pure SH1 mode since the non-dispersive SH0 mode will be excited simultaneously. Thus, this paper investigates a transducer design method to generate a pure SH1 guided-wave, where the dual periodic-permanent-magnet electromagnetic acoustic transducers (PPM EMATs) are placed on exactly opposite positions either side of the plate symmetrically. The suppression effect for SH0 and the enhancement effect for SH1 of the dual PPM EMATs are mainly discussed by theoretical analysis and simulation analysis, and the influence of positioning errors of PPM EMATs placed on opposite sides of the plate on its performances are analyzed. Employing the proposed dual PPM EMATs, some experiments are performed to verify the reliability of finite element simulation. The results indicate that the dual PPM EMATs can suppress the SH0 mode and generate the pure SH1 mode effectively. Moreover, the longitudinal and lateral positioning errors can affect the dual PPM EMATs performances significantly.

Description: In this paper, we report a wireless gas sensor based on surface acoustic waves (SAW). For room temperature detection of oxygen gas, a novel nanostructured ZnxFeyO gas-sensitive film was deposited on the surface of a SAW resonator by an oblique magnetron co-sputtering method. The measurements of X-ray diffraction (XRD) and a scanning electron microscope (SEM) showed that the crystal phase composition and the microstructures of ZnxFeyO films were significantly affected by the content of Fe. The experimental results showed that the sensors had a good response to O2 at room temperature. The max frequency shift of the sensors reached 258 kHz as the O2 partial pressure was 20%. Moreover, X-ray photoelectron spectroscopy (XPS) was performed to analyze the role of Fe in the sensitization process of the ZnxFeyO film. In addition, the internal relationship between the Fe content of the film and the sensitivity of the sensor was presented and discussed. The research indicates that the nanostructured ZnxFeyO film has a good potential for room temperature O2 gas detection applications.

Description: According to the survey on various health centres, smart log-based multi access physical monitoring system determines the health conditions of humans and their associated problems present in their lifestyle. At present, deficiency in significant nutrients leads to deterioration of organs, which creates various health problems, particularly for infants, children, and adults. Due to the importance of a multi access physical monitoring system, children and adolescents’ physical activities should be continuously monitored for eliminating difficulties in their life using a smart environment system. Nowadays, in real-time necessity on multi access physical monitoring systems, information requirements and the effective diagnosis of health condition is the challenging task in practice. In this research, wearable smart-log patch with Internet of Things (IoT) sensors has been designed and developed with multimedia technology. Further, the data computation in that smart-log patch has been analysed using edge computing on Bayesian deep learning network (EC-BDLN), which helps to infer and identify various physical data collected from the humans in an accurate manner to monitor their physical activities. Then, the efficiency of this wearable IoT system with multimedia technology is evaluated using experimental results and discussed in terms of accuracy, efficiency, mean residual error, delay, and less energy consumption. This state-of-the-art smart-log patch is considered as one of evolutionary research in health checking of multi access physical monitoring systems with multimedia technology.

Description: Smart grids incorporating internet-of-things are emerging solutions to provide a reliable, sustainable and efficient electricity supply, and electric vehicle drivers can access efficient charging services in the smart grid. However, traditional electric vehicle charging systems are vulnerable to distributed denial of service and privileged insider attacks when the central charging server is attacked. The blockchain-based charging systems have been proposed to resolve these problems. In 2018, Huang et al. proposed the electric vehicle charging system using lightning network and smart contract. However, their system has an inefficient charging mechanism and does not guarantee security of key. We propose a secure charging system for electric vehicles based on blockchain to resolve these security flaws. Our charging system ensures the security of key, secure mutual authentication, anonymity, and perfect forward secrecy, and also provides efficient charging. We demonstrate that our proposed system provides secure mutual authentication using Burrows–Abadi–Needham logic and prevents replay and man-in-the-middle attacks using automated validation of internet security protocols and applications simulation tool. Furthermore, we compare computation and communication costs with previous schemes. Therefore, the proposed charging system efficiently applies to practical charging systems for electric vehicles.

Description: Electron Beam Melting (EBM) is a metal powder bed fusion (PBF) process in which the heat source is an electron beam. Differently from other metal PBF processes, today, EBM is used for mass production. As-built EBM parts are clearly recognisable by their surface roughness, which is, in some cases, one of the major limitations of the EBM process. The aim of this work is to investigate the effects of the orientation and the slope of the EBM surfaces on the surface roughness. Additionally, the machine repeatability is studied by measuring the roughness of surfaces built at different positions on the start plate. To these aims, a specific artefact was designed. Replicas of the artefact were produced using an Arcam A2X machine and Ti6Al4V powder. Descriptive and inferential statistical methods were applied to investigate whether the surface morphology was affected by process factors. The results show significant differences between the upward and downward surfaces. The upward surfaces appear less rough than the downward ones, for which a lower standard deviation was obtained in the results. The roughness of the upward surfaces is linearly influenced by the sloping angle, while the heat distribution on the cross-section was found to be a key factor in explaining the roughness of the downward surfaces.

Description: The aim of this work was to study expansively the process of the eutectoidal phase transformation of 2507-type super-duplex stainless steel. Three sample sets were prepared. The first sample set was made to investigate the effect of the previous cold rolling and heat treatment for the eutectoidal phase transformation. Samples were cold rolled at seven different rolling reductions which was followed by heat treatment at five different temperatures. The second sample set was prepared to determine the activation energy of the eutectoidal decomposition process using the Arrhenius equation. Samples were cold rolled at seven different rolling reductions and were heat treated at the same temperature during eight different terms. A third sample set was made to study how another plastic-forming technology, beside the cold rolling, can influence the eutectoidal decomposition. Samples were elongated by single axis tensile stress and were heat treated at the same temperature. The results of the first and the third sample sets were compared. The rest δ-ferrite contents were calculated using the results of AC and DC magnetometer measurements. DC magnetometer was used as a feritscope device in this work. Light microscope and electron back scattering diffraction (EBSD) images demonstrated the process of the eutectoidal decomposition. The thermoelectric power and the hardness of the samples were measured. The results of the thermoelectric power measurement were compared with the results of the δ-ferrite content measurement. The accurate value of the coercive field was determined by a Foerster-type DC coercimeter device.

Description: The purpose of this study is to explore the association between proximity to open space and adult renal function. This was a cross-sectional study. Adult residents of Taipei metropolis were recruited in the analysis. The proximity of each subject to open space was measured using the Geographic Information System. Residents were divided into two groups: with and without chronic kidney disease (CKD). We made univariable comparisons between the two groups. The logistic regression models were used to estimate the odds ratio of CKD. Forest plot was used to examine the effect of interaction between distance to open space and subgroup variable on CKD. A total number of 21,656 subjects with mean age 53.6 years were enrolled in the study. Of the subjects, 2226 (10.28%) had CKD. The mean and standard deviation of distance to open space were 117.23 m and 80.19 m, respectively. Every 100 m distance to open space was associated with an odds ratio of 1.071 for CKD. Subgroup analysis revealed that residents of female, without hypertension, or without impaired fasting glucose (IFG) living more than 200 m from open spaces have greater odds of CKD than those living less than 200 m. Conclusions: Proximity to open space was associated with a lower prevalence of CKD among adults in Taiwan. Such association was enhanced among females and healthy adults without hypertension or impaired fasting glucose (IFG).

Description: Population groups vulnerable to adverse effects of traffic-related air pollution correspond to children, pregnant women and elderly. Despite these effects, literature is limited in terms of studies focusing on these groups and a reason often cited is the limited information on their mobility important for exposure assessment. The current study presents a method for assessing individual-level exposure to traffic-related air pollution by integrating mobility patterns tracked by global positioning system (GPS) devices with dynamics of air pollutant concentrations. The study is based on a pool of 17 pregnant women residing in Hidalgo County, Texas. The traffic-related particulate matter with diameter of less than 2.5 micrometer (PM2.5) emissions and air pollutant concentrations are predicted using MOVES and AERMOD models, respectively. The daily average traffic-related PM2.5 concentration was found to be 0.32 µg/m3, with the highest concentration observed in transit (0.56 µg/m3), followed by indoors (0.29 µg/m3), and outdoor (0.26 µg/m3) microenvironment. The obtained exposure levels exhibited considerable variation between time periods, with higher levels during peak commuting periods, close to the US–Mexico border region and lower levels observed during midday periods. The study also assessed if there is any difference between traffic-related dynamic exposure, based on time-varying mobility patterns, and static exposure, based solely on residential locations, and found a difference of 9%, which could be attributed to the participants’ activity patterns being focused mostly indoors.

Description: The inoculation of beneficial microorganisms to improve plant growth and soil properties is a promising strategy in the soil amendment. However, the effects of co-inoculation with phosphate-solubilizing bacteria (PSB) and N2-fixing bacteria (NFB) on the soil properties of typical C-deficient soil remain unclear. Based on a controlled experiment and a pot experiment, we examined the effects of PSB (M: Bacillus megaterium and F: Pseudomonas fluorescens), NFB (C: Azotobacter chroococcum and B: Azospirillum brasilence), and combined PSB and NFB treatments on C, N, P availability, and enzyme activities in sterilized soil, as well as the growth of Cyclocarya Paliurus seedlings grow in unsterilized soil. During a 60-day culture, prominent increases in soil inorganic N and available P contents were detected after bacteria additions. Three patterns were observed for different additions according to the dynamic bacterial growth. Synergistic effects between NFB and PSB were obvious, co-inoculations with NFB enhanced the accumulation of available P. However, decreases in soil available P and N were observed on the 60th day, which was induced by the decreases in bacterial quantities under C deficiency. Besides, co-inoculations with PSB and NFB resulted in greater performance in plant growth promotion. Aimed at amending soil with a C supply shortage, combined PSB and NFB treatments are more appropriate for practical fertilization at intervals of 30–45 days. The results demonstrate that co-inoculations could have synergistic interactions during culture and application, which may help with understanding the possible mechanism of soil amendment driven by microorganisms under C deficiency, thereby providing an alternative option for amending such soil.

Description: Evidence shows that there are many work-related accidents and injuries happening in construction projects and governments have taken a series of administrative measures to reduce casualties in recent years. However, traditional approaches have reached a bottleneck due to ignoring market forces, and thus new measures should be conducted. This study develops a perspective of safety performance (SP) for construction projects in China and puts forward a conception of the safety information system by using several brainstorming sessions to strengthen the safety supervision of participants in the construction industry. This system provides rating information to the public, and bad performance contractors enter into a blacklist which will influence their economic activities. Considering the limited rationality of government and various contractors, this paper builds a reasonable evolutionary game model to verify the feasibility of the safety information system. The analysis results show that there is not a single set of evolutionarily stable strategies (ESSs), as different situations may lead to different ESSs. The efficiency of applying the safety information system (the blacklist) in the construction industry can be proved by reducing the government’s safety supervision cost and by enhancing construction safety at the same time.

Description: The Yezidis who represent a religious minority living in Northern Iraq were particularly affected by the persecution by ISIS (Islamic state of Iraq and Syria, syn.: ISIL—Islamic state of Iraq and the Levant) that gained power after 2013. This paper gives an overview of the events and the mental health consequences on the Yezidi community as well as associated influences on affected female Yezidis. Based on a systematic literature search, the aspects of “Persecution by ISIS and actual situation of the Yezidi community”, “Gender-specific aspects of the persecution and its consequences”, “Mental health of the affected women”, and “Cultural–historical and religious context” are worked out. Research indicates a high burden of health strain and mental health problems in the surviving Yezidi women, especially post-traumatic stress disorders (PTSD) and depression. Concerning transgenerational trauma, the recent genocide has revived past experiences in the history of the community. Like the narrow cultural and religious rules of the community, this can be both a resource and a burden. The actual extent of the attacks is neither predictable for the affected individuals nor for the community, consequences could also be passed onto descendants. Long-term care and support of the affected persons, their descendants, and the Yezidi community seems indispensable.

Description: This study aims to examine the association of adverse childhood experiences (ACE) with emotional and behavioral problems (EBP) among adolescents and the degree to which this association is stronger for more ACE. In addition, we assessed whether socioeconomic position (SEP) modifies the association of ACE with EBP. We obtained data from 341 adolescents aged 10–16 (mean age = 13.14 years; 44.0% boys), the baseline of a cohort study. We measured EBP with the strengths and difficulties questionnaire and socioeconomic position (SEP) with self-reported financial status. We used generalized linear models to analyze the association between ACE (0 vs. 1–2 vs. 3 and more) and EBP, and the modifying effect of SEP. Adolescents with 1–2 ACE (regression coefficient: 0.19; 95%-confidence interval (CI): 0.06–0.32) and with 3 ACE and over (0.35; 0.17–0.54) reported more overall problems compared with adolescents without ACE. Moreover, adolescents with 1–2 ACE (0.16; −0.01–0.32, and 0.16; 0.03–0.29) and with 3 and over ACE (0.33; 0.10–0.56, and 0.28; 0.09–0.47) reported more emotional problems and behavioral problems, respectively. The interactions of SEP with ACE were not significant. ACE are related to EBP among adolescents, with a clear dose-response association, and this association similarly holds for all SEP categories.

Description: Background: Canadian Inuit have transited from a physically active hunter-gatherer subsistence lifestyle into sedentary ways of life. The purpose of the current study was to measure physical activity levels among Nunavut Inuit adults, and explore the socio-cognitive and environmental factors influencing the number of steps taken per day. Method: Inuit and non-Inuit adults (N = 272) in Nunavut participated in a seven-day pedometer study during summer and winter seasons. Participants were asked to complete the Neighbourhood Environmental Walkability Scale (NEWS) and Behavioral Regulation in Exercise Questionnaire (BREQ-3). Data analyses included descriptive statistics, hierarchical linear regression, and tests of mediation effects. Results: Participants had limited to low activity at a rate of 5027 ± 1799 and 4186 ± 1446 steps per day, during summer and winter, respectively. There were no seasonal and age effects on the number of steps. Gender effects and community differences were observed. Perceived infrastructure and safety as well as land use mix diversity were found to be positive environmental correlates of steps taken, which were partially mediated by identified motivational regulation. Conclusion: Physical activity levels among Nunavut adults are generally low, but can be promoted by improving the external physical environment and internal motivational regulation.

Description: Two endemic fish in the upper Yangtze River, the Rock Carp (Procypris rabaudi) and Prenant’s Schizothoracin (Schizothorax prenanti), were used as research objects in this study to assess the effects of total dissolved gas (TDG) supersaturation on fish of varying sizes. Fish were exposed to TDG-supersaturated water at the levels of 145, 140, 135, 130, and 125%. The results showed that fish swam slowly, responded clumsily, and then exhibited spiral swimming performance after a period of exposure to TDG-supersaturated water. Fish exhibited exophthalmos, body swelling, gill bleeding, and caudal fin bleeding when they died in the TDG-supersaturated water. With the increase in TDG supersaturation, the tolerance capacity of fish to supersaturated TDG significantly reduced. At high supersaturation, the difference in survival time between species was not significant, while fish with smaller sizes showed greater tolerance capacity. At low supersaturation, the tolerance capacity of fish was mainly affected by species, and the influence of size was relatively small. With the decrease in TDG supersaturation, the catalase (CAT) activity first increased and then decreased. Rock Carp displayed significantly less activity than Prenant’s Schizothoracin on exposure to TDG-supersaturated water. At high supersaturation levels, the CAT activity of Prenant’s Schizothoracin of small size was greater than that of large Prenant’s Schizothoracin. In contrast, small Prenant’s Schizothoracin showed less CAT activity at low TDG levels than did large individuals.

Description: A ‘generation’ is an identifiable group sharing birth years and significant life events at critical developmental ages. There is a paucity of literature examining how parental cognitions and lifestyle behaviors differ by generation and whether generational differences are substantial enough to warrant consideration during the development of health interventions. This study compared generational differences in weight-related cognitions and lifestyle behaviors of mothers of young children who were categorized as Generation X (born 1965–1981, n = 158) and Generation Y (aka Millennials; born 1982–1999, n = 162). Survey results indicated that Generation X had significantly higher family affluence; thus, this was controlled in subsequent analyses. Analysis of covariance indicated that Millennials had more positive expectations about the benefits of engaging in healthy eating and physical activity than comparators, but not significantly so. Millennial mothers placed significantly higher value on physical activity for themselves than Generation X mothers, but both generations were neutral on the value of personal physical activity. No generational differences were noted in self-efficacy of mothers for promoting childhood obesity-prevention practices to children and self-efficacy for personally engaging in weight-protective behaviors. Millennial mothers had significantly more family meals/week, however generations did not differ on the value placed on family meals, where family meals were eaten, or whether media devices were used at mealtime. Few differences were noted between the generations for most child feeding behaviors, except that Millennials reported placing significantly less pressure on children to eat. Mothers’ modeling of weight-related behaviors as a means for children’s observational learning about healthy eating, physical activity, and sedentary behaviors did not differ by generational group. The eating behaviors of mothers differed little between generations. Millennial mothers allowed significantly more media devices in children’s bedrooms and personally engaged in more screen time daily than comparators. Overall, the two generational groups were more similar than different in weight-related cognitions as well as for personal and parenting lifestyle behaviors. The results suggest that tailoring interventions for individuals at a similar life-stage (e.g., mothers of young children) by generation may not be warranted.

Description: Limited progress in nutrition policy action is often blamed on the close relationships the food industry has with health policy decision-makers. This analysis sought to examine this belief through the analysis of health ministers’ diaries. Entries were downloaded from health ministers’ diaries from two states in Australia from January 2013 to June 2018. Entries were coded according to which interest group met with the minister or whether general parliamentary business was undertaken. Coding was also undertaken for any meeting topics related to nutrition policy. Analysis of health ministers’ diaries found that the food industry has limited documented interaction with the two state health ministers in Australia. Instead, medical associations, private hospitals and health services, and sporting associations (rugby league associations) had the most interactions with health ministers. Poor representation was seen on nutrition issues, and there was an apparent lack of nutrition advocates interacting with the health ministers. There are opportunities for nutrition advocates to increase their level of interaction with state health ministers. This could include building alliances with medical associations, as they are in a powerful position, to advocate directly to health ministers. Health ministers’ diaries can provide valuable insights into who is meeting officially with ministers. However, there are also limitations with the dataset.

Description: Background: All objects put into a child’s mouth could be hazardous in terms of trauma and toxic substance exposure. The aims of this study were to evaluate morphological characteristics of the primary teeth bite marks inflicted on various materials and to assess material wear using experimental model. Methods: Bite marks were analyzed on five materials: rubber, plastic, foil, wood, and silicone. In order to mimic children mouthing behavior an experimental setup has been designed using primary teeth placed in dentures and children’s equipment specimens. Results: Deciduous teeth make visible and recognizable traces when using physiological forces on all investigated materials. The most significant material loss was revealed in silicone samples, but it has been observed in all material groups, while mouthing with incisors using higher mastication forces were identified as significant predictors for material wear. There were no significant differences between type, species, and morphological-morphometric characteristics of the bite marks which are made by incisors, canines, and molars. Conclusions: In the range of physiological bite forces, deciduous teeth lead to wear of material from which toys are made while the analysis of bite marks in children equipment could give some information regarding the risk of trauma and exposure.

Description: Due to some harmful effects on humans and the environment, particulate matter (PM) has recently become among the most studied atmospheric pollutants. Given the growing sensitivity to the problem and, since production and accumulation phenomena involving both primary and secondary P M 10 fractions are complex and non-linear, environmental authorities need tools to assess their plans designed to improve the air quality as requested from environmental laws. Multi-criteria decision analysis (MCDA) can be applied to support decision makers, by processing quantitative opinions provided by pools of experts, especially when different views on social aspects should be considered. The results obtained through this approach, however, can be highly dependent on the subjectivity of experts. To partially overcome these challenges, this paper suggests a two-step methodology in which an MCDA is fed with the solution of a multi-objective analysis (MOA). The methodology has been applied to a test case in northern Italy and the results show that this approach is a viable solution for the inclusion of subjective criteria in decision making, while reducing the impact of uncertain expert opinions for data that can be computed through the MOA.

Description: Both the global circulation model (GCM) and regional climate model (RCM) simulations suffer from model biases that eventually result in significant errors in regional forecasts. This model bias issue is addressed using the bias correction approach. This study examines the influence of bias correction on the performance of downscaling simulations of the East Asian winter climate using the Global/Regional Integrated Model system (GRIMs). To assess the bias correction approach, we conducted three sets of simulations for 25 winters (December to February) from 1982 to 2006 over East Asia. The GRIMs were forced by the (1) National Centers for Environmental Prediction (NCEP) Department of Energy (DOE) reanalysis data, (2) original NCEP Climate Forecast System (CFS) data, and (3) bias-corrected CFS data. The GCM climatological means were adjusted based on the NCEP–DOE reanalysis data. The bias correction method was applied to zonal and meridional wind, temperature, geopotential height, specific humidity, and sea surface temperature of the CFS data. The GCM-driven experiments with/without bias correction were compared with the reanalysis-driven simulation. The results of this comparison suggest that the application of bias correction improves the downscaled climate in terms of the climatological mean, inter-annual variability, and extreme events owing to the elimination of errors in large-scale circulations. The effect of bias correction on the simulated extreme event is not as significant as those on the climatological mean and inter-annual variability, but the increased skill appears to be a clue for potential use for predicting extreme events.

Description: Composite indicators are becoming more relevant for evaluating the performance of water companies from a holistic perspective. Some of them are related with economic aspects, and others focus on social and environmental features. Consequently, a multidimensional evaluation is necessary for handling the great amount of information provided by multiple single indicators of a different nature. This paper presents a two-phase approach to evaluate the sustainability of water companies. First, a partial composite indicator for each dimension (social, environmental, economic) is obtained using multi-criteria decision making (MCDM). Then, a global indicator is obtained, in terms of the values reached in the previous stage for every partial indicator, by means an optimization problem rooted in data envelopment analysis (DEA). Our proposal offers the possibility of analyzing the performance of each water company under each dimension that characterizes the concept of sustainability, as well as a joint assessment including all the dimensions, facilitating the decision-making process. We apply it to evaluate the sustainability of 163 Portuguese water companies. The results show the strengths and weaknesses of each unit and serve as a guideline to decision-makers on the aspects for improving the performance of water utilities.

Description: This study investigates the preferences of Italian home-owners when choosing a new domestic heating system. The focus is on understanding the influence on consumer choice of a potential label certifying the effect of the heating system on the greenhouse effect. To this end, we designed a survey including a discrete choice experiment and administered it to residents in north-eastern Italy. Our findings reveal that, on average, respondents pay particular attention to the green effect of their purchase. The carbon dioxide reduction label was considered second in terms of importance after cost. Further analysis found that our sample presents three clusters of customers, with intra-cluster homogeneous preferences. The cluster analysis showed that while the initial system costs are considered to varying degrees by the whole sample, the carbon dioxide reduction label was considered important by 79% of respondents (members of clusters 1 and 2). To achieve greater results in reducing the greenhouse effect of the domestic heating sector, a combination of policies should be used simultaneously to achieve greater effectiveness. Our simulations support the hypothesis that policymakers should achieve greater results in terms of reducing the domestic greenhouse gas emissions by applying a combined policy that leverages the importance citizens accord to the different characteristics of a heating system. From our results, the application of a ‘low carbon dioxide ( C O 2 ) emissions’ label will amplify the effect of a subsidy that reduces the initial system costs.

Description: In view of the randomness in the selection of kernel parameters in the traditional kernel independent component analysis (KICA) algorithm, this paper proposes a CPSO-KICA algorithm based on Chaotic Particle Swarm Optimization (CPSO) and KICA. In CPSO-KICA, the maximum entropy of the extracted independent component is first adopted as the fitness function of the PSO algorithm to determine the optimal kernel parameters, then the chaotic algorithm (CO) is used to avoid the local optimum existing in the traditional PSO algorithm. Finally, this proposed algorithm is compared with Weighted KICA (WKICA) and PSO-KICA with Tennessee Eastman Process (TEP) as the benchmark. Simulation results show that the proposed algorithm can determine the optimal kernel parameters and perform better in terms of false alarm rates (FAR), detection latency (DL) and fault detection rates (FDR).

Description: Underwater deployed sensors nodes are energy-constrained. Therefore, energy efficiency becomes crucial in underwater wireless sensor networks (U-WSNs). The adverse channel corrupts the packets and challenges their reliability. To handle these challenges, two routing schemes are introduced in this paper. They are effective energy and reliable delivery (EERD) and cooperative effective energy and reliable delivery (CoEERD). In EERD, the packets follow single-path routing and the best forwarder node is selected using a weight function such that packets are transferred via the reliable paths with low energy usage. Packet transfer via a single route in EERD has, however, compromised reliability as the undersea links bear harshness and unpredictability. Therefore, the CoEERD scheme adds cooperative routing to EERD, in which a relay node is introduced between a source–destination pair. The destination requests the relay when the packets it gets from the source are corrupted beyond a threshold value. Selection of weight function is unique and considers many factors to ensure low energy usage with reliability while considering nodes for data transfer. This also helps in selecting a single relay node rather than many relays in the conventional cooperative routing model. Based on simulation results, the EERD and CoEERD protocols have improved performance in energy usage, reliable packet transfer and delay.

Description: We explore the dissipative dynamics of two coupled qubits placed inside a coherent cavity-field under dipole-dipole interplay and 2-photon transitions. The generated non-classical correlations (NCCs) beyond entanglement are investigated via two measures based on the Hilbert-Schmidt norm. It is found that the robustness of the generated NCCs can be greatly enhanced by performing the intrinsic dissipation rate, dipole-dipole interplay rate, initial coherence intensity and the degree of the coherent state superpositions. The results show that the intrinsic decoherence stabilize the stationarity of the non-classical correlations while the dipole interplay rate boost them. The non-classical correlations can be frozen at their stationary correlations by increasing the intrinsic dissipation rate. Also NCCs, can be enhanced by increasing the initial coherent intensity.

Description: Thermodynamic aspects of the theory of nucleation are commonly considered employing Gibbs’ theory of interfacial phenomena and its generalizations. Utilizing Gibbs’ theory, the bulk parameters of the critical clusters governing nucleation can be uniquely determined for any metastable state of the ambient phase. As a rule, they turn out in such treatment to be widely similar to the properties of the newly-evolving macroscopic phases. Consequently, the major tool to resolve problems concerning the accuracy of theoretical predictions of nucleation rates and related characteristics of the nucleation process consists of an approach with the introduction of the size or curvature dependence of the surface tension. In the description of crystallization, this quantity has been expressed frequently via changes of entropy (or enthalpy) in crystallization, i.e., via the latent heat of melting or crystallization. Such a correlation between the capillarity phenomena and entropy changes was originally advanced by Stefan considering condensation and evaporation. It is known in the application to crystal nucleation as the Skapski–Turnbull relation. This relation, by mentioned reasons more correctly denoted as the Stefan–Skapski–Turnbull rule, was expanded by some of us quite recently to the description of the surface tension not only for phase equilibrium at planar interfaces, but to the description of the surface tension of critical clusters and its size or curvature dependence. This dependence is frequently expressed by a relation derived by Tolman. As shown by us, the Tolman equation can be employed for the description of the surface tension not only for condensation and boiling in one-component systems caused by variations of pressure (analyzed by Gibbs and Tolman), but generally also for phase formation caused by variations of temperature. Beyond this particular application, it can be utilized for multi-component systems provided the composition of the ambient phase is kept constant and variations of either pressure or temperature do not result in variations of the composition of the critical clusters. The latter requirement is one of the basic assumptions of classical nucleation theory. For this reason, it is only natural to use it also for the specification of the size dependence of the surface tension. Our method, relying on the Stefan–Skapski–Turnbull rule, allows one to determine the dependence of the surface tension on pressure and temperature or, alternatively, the Tolman parameter in his equation. In the present paper, we expand this approach and compare it with alternative methods of the description of the size-dependence of the surface tension and, as far as it is possible to use the Tolman equation, of the specification of the Tolman parameter. Applying these ideas to condensation and boiling, we derive a relation for the curvature dependence of the surface tension covering the whole range of metastable initial states from the binodal curve to the spinodal curve.

Description: This paper presents a numerical investigation of thermal response of mortar panels, incorporating macro-encapsulated paraffin in different forms. Two types of macro capsules were fabricated and tested in this study using an instrumented hot plate device. The experimental results show that macro encapsulated paraffin reduced the temperature and increased time lag in the mortar panels due to the latent heat capacity of paraffin. Finite element models adopting the effective heat capacity method to model phase change effects were able to capture the overall thermal response of panels incorporated with paraffin well. Then, a parametric study was conducted using the validated finite element (FE) modelling technique to investigate the effects of different forms of macro capsules, the quantity of paraffin and the position of macro capsules. It was found that the tube and sphere macro capsules showed similar thermal responses, while the plate shaped capsules may cause a non-uniform temperature distribution in mortar panels. The quantity and position of paraffin have significant effects on the thermal response of the mortal panels. A higher paraffin content results in a significantly longer temperature lag and a lower temperature during the phase transition of paraffin. Furthermore, placing the paraffin away from the heating face can cause a longer temperature lag on the other face, which is desirable for building façade applications.

Description: Single room ventilation units with heat recovery is one of the ventilation solutions that have been used in renovated residential buildings in Estonia. In multi-story buildings, especially in a cold climate, the performance of units is affected by the stack effect and wind-induced pressure differences between the indoor and the outdoor air. Renovation of the building envelope improves air tightness and the impact of the pressure conditions is amplified. The aim of this study was to predict the air pressure conditions in typical renovated multi-story apartment buildings and to analyze the performance of room-based ventilation units. The field measurements of air pressure differences in a renovated 5-story apartment building during the winter season were conducted and the results were used to simulate whole-year pressure conditions with IDA-ICE software. Performance of two types of single room ventilation units were measured in the laboratory and their suitability as ventilation renovation solutions was assessed with simulations. The results show that one unit stopped its operation as a heat recovery ventilator. In order to ensure satisfactory indoor climate and heat recovery using wall mounted units the pressure difference values were determined and proposed for correct design.

Description: The growth effects of mixtures are generally assumed to be a result of canopy structure and crown plasticity. Thus, the distribution of leaf area at tree and stand level helps to explain these mixing effects. Therefore, we investigated the leaf area distribution in 12 stands with a continuum of proportions of European larch (Larix decidua Mill.) and Norway spruce (Picea abies (L.) Karst.). The stands were between 40 and 170 years old and located in the northern part of the Eastern Intermediate Alps in Austria at elevations between 900 and 1300 m asl A total of 200 sample trees were felled and the leaf area distribution within their crowns was evaluated. Fitting beta distributions to the individual empirical leaf area distributions, the parameters of the beta distributions were shown to depend on the leaf area of the individual trees and, for spruce, on the proportion of spruce in the stands. With the equations determined, the leaf area distribution of all trees in the stand, and thus its distribution in the stands, was calculated by species and in 2 m height classes. For the individual trees, we found that the leaf area distribution of larch is more symmetric, and its peak is located higher in the crown than it is the case for spruce. Furthermore, the leaf area distribution of both species becomes more peaked and skewed when the leaf area of the trees increases. The mixture only influences the leaf area distribution of spruce in such a way that the higher the spruce proportion of the stand, the higher the leaf area is located within the crown. At the stand level, a strong relationship was found between the proportion of spruce and the distance between the peaks of the leaf area distributions of larch and spruce.

Description: Consumers’ clothing consumption is the cause of many social and environmental consequences, especially in emerging economies where consumption continues to escalate. It is therefore vital that consumers adopt more voluntary simplistic lifestyles with sustainable clothing practices. This study relies on the self-determination theory to explore the influence of basic psychological needs (i.e., competence, autonomy, and connectedness) and self-determined motivation (i.e., identified- and integrated regulation as well as intrinsic motivation) on female consumers’ voluntary simplistic clothing practices. Data were derived from 469 online questionnaires and structural equation modeling was employed to test the hypotheses. Competence was identified as the most influential basic psychological need, followed by the need for connectedness and autonomy. Moreover, intrinsic motivation is the strongest predictor of voluntary simplistic clothing practices, while integrated regulation is deemed insignificant and identified regulation has a negative association with the practices in question. In summary, it would seem that female consumers are keen on adopting voluntary simplistic clothing behaviors. This may be due to their intrinsic motivation and competence rather than their exposure to extrinsic influences. This study provides valuable insight into the motivational determinants of voluntary simplistic clothing consumption in South Africa and may thus serve as a platform for further investigation into other emerging markets.

Description: Over the years, the cellular mobile network has evolved from a wireless plain telephone system to a very complex system providing telephone service, Internet connectivity and many interworking capabilities with other networks. Its air interface performance has increased drastically over time, leading to high throughput and low latency. Changes to the core network, however, have been slow and incremental, with increased complexity worsened by the necessity of backwards-compatibility with older-generation systems such as the Global System for Mobile communication (GSM). In this paper, a new virtualized Peer-to-Peer (P2P) core network architecture is presented. The key idea of our approach is that each user is assigned a private virtualized copy of the whole core network. This enables a higher degree of security and novel services that are not possible in today’s architecture. We describe the new architecture, focusing on its main elements, IP addressing, message flows, mobility management, and scalability. Furthermore, we will show some significant advantages this new architecture introduces. Finally, we investigate the performance of our architecture by analyzing voice-call traffic available in a database of a large U.S. cellular network provider.

Description: The aged properties of Reclaimed Asphalt (RA) binders are one of the main factors working against their utilisation in high-RA content (〉30%) mixes for surface courses. Fatigue cracking is the main distress of surface courses that are manufactured with a high percentage of RA. This investigation presents results of the rheological and fatigue results of different asphalt mixtures and their recovered binders. The binders were recovered from asphalt mixtures that had been manufactured in asphalt plants using different amounts of RA with contents up to 60% with and without rejuvenators. Two different sources of RA were used, representing a moderately aged RA and an extremely aged RA. The Dynamic Shear Rheometer (DSR) was used to assess the fatigue-characteristics of the binders using time sweep tests while the fatigue characteristics of their mixtures were assessed using the Indirect Tensile Fatigue Test (ITFT). The fatigue data was analysed based on the cumulative dissipated energy approach in addition to traditional fatigue analysis. Results have shown that the ageing condition of RA significantly affects the fatigue properties of recovered binders. Binder and asphalt mixture fatigue results showed that RA contents up to 60% can produce comparable fatigue performance compared to lower percentages of RA in road surface course if the aged RA binder is sufficiently rejuvenated.

Description: Currently, ultrasonic measurement is a widely used nondestructive approach to determine wood elastic properties, including the dynamic modulus of elasticity (DMOE). DMOE is determined based on wood density and ultrasonic wave velocity measurement. The use of wood average density to estimate DMOE introduces significant imprecision: Density varies due to intra-tree and intra-ring differences and differing silvicultural treatments. To ensure accurate DMOE assessment, we developed a prototype device to measure ultrasonic wave velocity with the same resolution as that provided by the X-ray densitometer for measuring wood density. A nondestructive method based on X-ray densitometry and the developed prototype was applied to determine radial and intra-ring wood DMOE profiles. This method provides accurate information on wood mechanical properties and their sources of variation. High-order polynomials were used to model intra-ring wood density and DMOE profiles in black spruce and jack pine wood. The transition from earlywood to latewood was defined as the inflection point. High and highly significant correlations were obtained between predicted and measured wood density and DMOE. An examination of the correlations between wood radial growth, density, and DMOE revealed close correlations between density and DMOE in rings, earlywood, and latewood

Description: The framework of product life cycle (PLC) cost analysis is one of the most important evaluation tools for a contemporary high-tech company in an increasingly competitive market environment. The PLC-purchasing strategy provides the framework for a procurement plan and examines the sourcing strategy of a firm. The marketing literature emphasizes that ongoing technological change and shortened life cycles are important elements in commercial organizations. From a strategic viewpoint, the vendor has an important position between supplier, buyer and manufacturer. The buyer seeks to procure the products from a set of vendors to take advantage of economies of scale and to exploit opportunities for strategic relationships. However, previous studies have seldom considered vendor selection (VS) based on PLC cost (VSPLCC) analysis. The purpose of this paper is to solve the VSPLCC problems considering the situation of a single buyer–multiple supplier. For this issue, a new VSPLCC procurement model and solution procedure are derived in this paper to minimize net cost, rejection rate, late delivery and PLC cost subject to vendor capacities and budget constraints. Moreover, a real case in Taiwan is provided to show how to solve the VSPLCC procurement problem.

Description: South American rivers have become intensely affected by the construction of hydroelectric dams that block the river’s connectivity for migratory fish species. In order to mitigate the problems caused by dams and to reestablish connections between habitats, fishways are implemented. Fishways are structures that aid fish in overcoming obstacles and help preserve migratory, reproductive, and feeding routes. This study performed an inventory of all hydropower plants—present and future—in the Upper Paraná River, with the objective of identifying fishways unknown to scientific literature, as well as the task of mapping them. By doing so, the current situation of structural connectivity via fishways in the Upper Paraná River Basin was described. Overall, 389 dams along 209 rivers were identified; of these, only 9% (35 dams) have fishways. In addition, an alarming explosion of future medium-sized hydropower plants was observed, with an expectation of an almost 500% increase in relation to those existing. This data reveals a trend of reduction of free-flowing river stretches, which are crucial habitats for Neotropical potamodromous species, and point to a deficiency in the structural connectivity of existing hydropower dams. Furthermore, if the implementations of these expected constructions are associated with limited connectivity as a result of the absence of fishways, the management of fisheries and their resources in the Upper Paraná River may become unsustainable.

Description: Sustainability is a topic that is at the center of current discussions in the political, economic, social, and environmental fields. For its analysis, an integral and multidisciplinary vision is needed. This work aims to assess the sustainability of agricultural systems in Paraguay through a comparison applying SAFA (Sustainability Assessment of Food and Agriculture Systems) indicators. The research focuses on 15 case studies on the territory of the Eastern Region of Paraguay divided into five classes of agricultural systems: agribusiness, conventional peasant family farming, agroecological peasant family farming, neo-rural farming, and indigenous agriculture. Data were collected through interviews with producers and key informants, direct observation, and scientific literature research in order to assess, through the SAFA Tool Software, the level of sustainability of each agricultural system as a whole and for each sustainability dimension (political, environmental, economic, and social dimension) in a comparative way. It has emerged that producers belonging to conventional peasant family farming, agroecological peasant family farming, neo-rural farming, and indigenous agriculture have achieved levels of sustainability that are similar to each other and very good in all four dimensions of sustainability. Meanwhile, agribusiness achieved moderate scores in the dimensions of governance and environmental integrity, and was good in the economic and social dimension.

Description: Integrated reporting is becoming increasingly popular. The focus of this study was to assess the overall integrated reporting quality of global companies and find determinants of high-level integrated reporting. Qualitative text analysis was performed on the 2017 integrated reports of 110 global organizations to determine in what way companies report on specific topics related to the six capitals: social and relationship, human, intellectual, manufacturing, natural, and financial. Using a novel assessment technique, scores were then assigned according to the details provided in the integrated reports on the various topics. This was done for each form of capital, and the total integrated score was subsequently calculated as the average between all the capital scores. Finally, a regression analysis was performed to determine the characteristics of high-quality integrated reporters. The results of univariate analysis and two-stage least squares instrumental variable (2SLS) regression indicate that companies of a larger size with a higher female board ratio and listing in the International Integrated Reporting Committee (IIRC) examples database are more likely to publish a higher quality integrated report. The results imply that these variables are the main disclosure drivers. However, a significant negative correlation was found between integrated report quality and the variables related to female executive ratio, external board member ratio, profitability, leverage, and previous report experience, as well as report length. No significant association was found between the location and industry group and report quality. The empirical evidence of this study shows that even though integrated reporting has become more common overall, the comparability and quality of the reports still remain low.

Description: This study investigates the trends in economic damages caused by three types of inland floods (flash flood, flood, and heavy rain) in the United States and the variations in related hazard and vulnerability indicators between 1996 and 2016. We explore the underlying mechanisms based on a survey-based dataset maintained by the National Oceanic and Atmospheric Administration (NOAA) National Weather Service. An annual average of 6518 flood occurrences was reported, which caused economic damages of 3351 million USD per year. Flash flood and flood contributed to 53% and 32% of total occurrences and was associated with a larger share of damaging events (SDE). Results show that the higher impacts by flood and flash flood on property and crop are partly attributed to the greater intensity of rainfall. In addition, flood has the highest unit cost of damages. Notably, despite an upward tendency in economic damages by flash floods, no evident change trend is observed for inland floods as a whole. Further analysis shows changes in economic damages by heavy rain and flash flood are mainly governed by the increased annual frequency and hazard intensity, but the change of trend in their vulnerability indicators (i.e., SDE and Damage Per Event (DPE)) is not obvious. Regarding floods, it was not possible to attribute the variations in economic losses to hazard and vulnerability, as no significant tendency is found except for an increasing SDE. Despite limitations of length of records, data collection, and methodology, the difference in economic impacts and the related hazard and vulnerability revealed in this study can help better target future adaptation and mitigation measures.

Description: Ulansuhai, the largest shallow lake of the Yellow River of China, is an important component of the Hetao region irrigation system. Many concerns have concentrated on its water quality, which affects the local water security and sustainable economic development. In this study, the water pollution index (WPI), an effective water quality evaluation method, was used to compare the pollution levels among pollution indicators and to determine the major pollution indicators. The regime shift index (RSI) approach was employed to identify the water quality trends. Cluster analysis and Daniel trend test methods were employed to analyse the inner-annual and inter-annual spatio-temporal trends of the typical water quality indicators (e.g., total nitrogen (TN), total phosphorus (TP), dissolved oxygen (DO), and chemical oxygen demand (COD)) in Lake Ulansuhai. The results show that the water quality of Ulansuhai improved from 1998 to 2017; spatial variations in the WPITN, WPITP, and WPIDO followed the order of inlet 〉 centre and outlet, while spatial variations in the WPICOD showed the order of outlet 〉 inlet 〉 centre. TN was the critical pollution indicator throughout the year. In 2017, the dry season and wet season were determined using cluster analysis. The WPICOD was higher than the WPITN, WPITP, and WPIDO in the dry season, while the WPITN, WPITP, and WPIDO were higher than the WPICOD in the wet season. WPI was grouped into three clusters: highly polluted regions, moderately polluted regions, and less polluted regions, However, there is a discrepancy between the three polluted regions that were divided into the dry season and the wet season. The WPICOD was highest among all pollution indicators in 2017. Major sources of pollution that contribute to the deterioration of water quality include inner-annual or inter-annual pollution, agricultural non-point pollution, point source pollution, and internal pollution. This study provides useful information for authorities to effectively manage water quality and control water pollution.

Description: Culverts, as an essential part of drainage networks worldwide, provide an efficient solution for flowing waters to cross man-made barriers including roads. Existing structures can be many years old and changes in rainfall patterns due to global warming might not have been considered in their original design. While correctly designed culverts can effectively drain water during high-intensity rainfall events, poorly designed or outdated structures could cause upstream flooding resulting in costly damage and losses. Hydraulic improvements to prepare existing culverts for greater discharge rates could be a favorable alternative to rebuilding every failing structure. Modern design guidelines calculate the performance for inlet and outlet controlled flows on the basis of established hydraulic theories. After calculating the headwater levels for both flow controls, the inferior one is then chosen, based on the assumption that the culvert will operate in its least efficient state. Flow improvements could be made by enforcing the better performing option. Outlet control can be ensured by raising the tailwater levels as high as the outlet thereby utilizing the entire cross-sectional area of the culvert. It was found that, in some cases, an enforced outlet control enables culverts to perform better than operation under inlet control. However, only smooth and short culverts with high losses at the inlet were identified as benefiting from this approach and many existing structures could be improved by better inlet designs.

Description: The alley-cropping systems (ACSs), which integrate parallel tree strips at varying distances on an agricultural field can result, complementarity of resource use, in an increased land-use efficiency. Practitioners’ concerns have been directed towards the productivity of such systems given a reduced area covered by agricultural crops. The land equivalent ratio (LER) serves as a valuable productivity indicator of yield performance and land-use efficiency in ACSs, as it compares the yields achieved in monocultures to those from ACSs. Consequently, the objective of this combined experimental and simulation study was to assess the tree- and crop-yields and to derive the LER and gross energy yield for two temperate ACSs in Germany under different design scenarios, i.e., tree arrangements (lee- or wind-ward) and ratios of tree area to crop area. Both LER and gross energy yields resulted in a convex curve where the maximum values were achieved when either the tree or crop component was dominant (〉75% of the land area) and minimum when these components shared similar proportions of land area. The implications of several design scenarios have been discussed in order to improve the decision-making, optimization, and adaptation of the design of ACSs with respect to site-specific characteristics.

Description: The present paper deals with a field experiments on evaporite rock samples and groundwater investigations in the Quinis test site, a hamlet of the Enemonzo municipality in NE Italy, were sinkholes occurred in the past and are still occurring causing severe damage to the existing infrastructures. The area is characterised by a Carnian evaporitic bedrock made of gypsum and anhydrite mantled by alluvial and colluvial deposits. In order to evaluate the loss of weight and volume of the subcropping evaporites as responsible for sinkholes, a field-experiment was carried out. Inside seven piezometers, at different depths, evaporitic rock samples were exposed to the naturally occurring variable climatic conditions such as degree of humidity, different air flow and hydrodynamic. The rock samples were installed at the beginning of April 2017 in the dry sections of piezometric tubes, in the vadose zone and in the phreatic zone. Data related to water level fluctuations were recorded by using data-logger devices and highlight significant changes in the water table. After 13 months of data recording (May 2018), rock samples were removed, reweighted and the volume loss measured. In addition, water from piezometer-experiment, representative of the groundwater circulation, were collected at different depths. The obtained results indicate that rock sample reduction is dependent on the hydrological regime and water chemistry and not on the number of days during which the samples remained submersed. In particular, the water geochemistry highlights the possible role in gypsum/anhydrite dissolution due to NaCl water admixing in a complex scenario. In additional, the geochemical data highlight the occurrence of some potentially toxic elements (As, Fe, Mn) at concentrations of concern in some water. This approach represents a novel contribution in the study of karst hazard in evaporites adding a tile to the knowledge of the fast evolutionary processes which cause sinkhole formation.

Description: In order to provide a good theoretical guidance for the development and utilization of weathered phosphorite resources, we investigated the geochemical and mineralogical characteristics of primary and weathered phosphorites. The analysis of trace elements showed that the primary ore has hydrothermal sedimentation effect in the later stage, the weathered ore has obvious residual enrichment and the phosphate ore belongs to clastic lithologic phosphate rock. In addition, through leaching test method, it was shown that rare earth elements are present in fluorapatite in the form of isomorphic substitution, and the proportion of rare earth elements adsorbed on clay and other minerals was likely to be between 2% and 3%. The light rare earth elements are relatively enriched in both primary and weathered phosphorite, and Ce and Eu have obvious negative anomalies. The primary phosphorite is a dolomitic phosphorite containing rare earth elements, which are naturally enriched by weathering, and its weathered ore has obvious residual enrichment, while the deposit was characterized by normal marine sedimentation and hydrothermal action.

Description: Haiyang-2A (HY-2A) has been working in-flight for over seven years, and the accuracy of HY-2A calibration microwave radiometer (CMR) data is extremely important for the wet troposphere delay correction (WTC) in sea surface height (SSH) determination. We present a comprehensive evaluation of the HY-2A CMR observation using the numerical weather model (NWM) for all the data available period from October 2011 to February 2018, including the WTC and the precipitable water vapor (PWV). The ERA(ECMWF Re-Analysis)-Interim products from European Centre for Medium-Range Weather Forecasts (ECMWF) are used for the validation of HY-2A WTC and PWV products. In general, a global agreement of root-mean-square (RMS) of 2.3 cm in WTC and 3.6 mm in PWV are demonstrated between HY-2A observation and ERA-Interim products. Systematic biases are revealed where before 2014 there was a positive WTC/PWV bias and after that, a negative one. Spatially, HY-2A CMR products show a larger bias in polar regions compared with mid-latitude regions and tropical regions and agree better in the Antarctic than in the Arctic with NWM. Moreover, HY-2A CMR products have larger biases in the coastal area, which are all caused by the brightness temperature (TB) contamination from land or sea ice. Temporally, the WTC/PWV biases increase from October 2011 to March 2014 with a systematic bias over 1 cm in WTC and 2 mm in PWV, and the maximum RMS values of 4.62 cm in WTC and 7.61 mm in PWV occur in August 2013, which is because of the unsuitable retrieval coefficients and systematic TB measurements biases from 37 GHz band. After April 2014, the TB bias is corrected, HY-2A CMR products agree very well with NWM from April 2014 to May 2017 with the average RMS of 1.68 cm in WTC and 2.65 mm in PWV. However, since June 2017, TB measurements from the 18.7 GHz band become unstable, which led to the huge differences between HY-2A CMR products and the NWM with an average RMS of 2.62 cm in WTC and 4.33 mm in PWV. HY-2A CMR shows high accuracy when three bands work normally and further calibration for HY-2A CMR is in urgent need. Furtherly, 137 global coastal radiosonde stations were used to validate HY-2A CMR. The validation based on radiosonde data shows the same variation trend in time of HY-2A CMR compared to the results from ECMWF, which verifies the results from ECMWF.

Description: Crop yield estimation at a regional scale over a long period of time is of great significance to food security. In past decades, the integration of remote sensing observations and crop growth models has been recognized as a promising approach for crop growth monitoring and yield estimation. Optical remote sensing data are susceptible to cloud and rain, while synthetic aperture radar (SAR) can penetrate through clouds and has all-weather capabilities. This allows for more reliable and consistent crop monitoring and yield estimation in terms of radar sensor data. The aim of this study is to improve the accuracy for winter wheat yield estimation by assimilating time series soil moisture images, which are retrieved by a water cloud model using SAR and optical data as input, into the crop model. In this study, SAR images were acquired by C-band SAR sensors boarded on Sentinel-1 satellites and optical images were obtained from a Sentinel-2 multi-spectral instrument (MSI) for Hengshui city of Hebei province in China. Remote sensing data and ground data were all collected during the main growing season of winter wheat. Both the normalized difference vegetation index (NDVI), derived from Sentinel-2, and backscattering coefficients and polarimetric indicators, computed from Sentinel-1, were used in the water cloud model to derive time series soil moisture (SM) images. To improve the prediction of crop yields at the field scale, we incorporated remotely sensed soil moisture into the World Food Studies (WOFOST) model using the Ensemble Kalman Filter (EnKF) algorithm. In general, the trend of soil moisture inversion was consistent with the ground measurements, with the coefficient of determination (R2) equal to 0.45, 0.53, and 0.49, respectively, and RMSE was 9.16%, 7.43%, and 8.53%, respectively, for three observation dates. The winter wheat yield estimation results showed that the assimilation of remotely sensed soil moisture improved the correlation of observed and simulated yields (R2 = 0.35; RMSE =934 kg/ha) compared to the situation without data assimilation (R2 = 0.21; RMSE = 1330 kg/ha). Consequently, the results of this study demonstrated the potential and usefulness of assimilating SM retrieved from both Sentinel-1 C-band SAR and Sentinel-2 MSI optical remote sensing data into WOFOST model for winter wheat yield estimation and could also provide a reference for crop yield estimation with data assimilation for other crop types.

Description: Urban areas globally are vulnerable to warming climate trends exacerbated by their growing populations and heat island effects. The Local Climate Zone (LCZ) typology has become a popular framework for characterizing urban microclimates in different regions using various classification methods, including a widely adopted pixel-based protocol by the World Urban Database and Access Portal Tools (WUDAPT) Project. However, few studies to date have explored the potential of object-based image analysis (OBIA) to facilitate classification of LCZs given their inherent complexity, and few studies have further used the LCZ framework to analyze land cover changes in urban areas over time. This study classified LCZs in the Salt Lake Metro Region, Utah, USA for 1993 and 2017 using a supervised object-based analysis of Landsat satellite imagery and assessed their change during this time frame. The overall accuracy, measured for the most recent classification period (2017), was equal to 64% across 12 LCZs, with most of the error resulting from similarities among highly developed LCZs and non-developed classes with sparse or low-stature vegetation. The observed 1993–2017 changes in LCZs indicated a regional tendency towards primarily suburban, open low-rise development, and large low-rise and paved classes. However, despite the potential for local cooling with landscape transitions likely to increase vegetation cover and irrigation compared to pre-development conditions, summer averages of Landsat-derived top-of-atmosphere brightness temperatures showed a pronounced warming between 1992–1994 and 2016–2018 across the study region, with a 0.1–2.9 °C increase among individual LCZs. Our results indicate that future applications of LCZs towards urban change analyses should develop a stronger understanding of LCZ microclimate sensitivity to changes in size and configuration of urban neighborhoods and regions. Furthermore, while OBIA is promising for capturing the heterogeneous and multi-scale nature of LCZs, its applications could be strengthened by adopting more generalizable approaches for LCZ-relevant segmentation and validation, and by incorporating active remote sensing data to account for the 3D complexity of urban areas.

Description: An important application of airborne- and satellite-based hyperspectral imaging is the mapping of the spatial distribution of vegetation biophysical and biochemical parameters in an environment. Statistical models, such as Gaussian processes, have been very successful for modeling vegetation parameters from captured spectra, however their performance is highly dependent on the amount of available ground truth. This is a problem because it is generally expensive to obtain ground truth information due to difficulties and costs associated with sample collection and analysis. In this paper, we present two Gaussian processes based approaches for improving the accuracy of vegetation parameter retrieval when ground truth is limited. The first is the adoption of covariance functions based on well-established metrics, such as, spectral angle and spectral correlation, which are known to be better measures of similarity for spectral data owing to their resilience to spectral variabilities. The second is the joint modeling of related vegetation parameters by multitask Gaussian processes so that the prediction accuracy of the vegetation parameter of interest can be improved with the aid of related vegetation parameters for which a larger set of ground truth is available. We experimentally demonstrate the efficacy of the proposed methods against existing approaches on three real-world hyperspectral datasets and one synthetic dataset.

Description: Spatial features retrieved from satellite data play an important role for improving crop classification. In this study, we proposed a deep-learning-based time-series analysis method to extract and organize spatial features to improve parcel-based crop classification using high-resolution optical images and multi-temporal synthetic aperture radar (SAR) data. Central to this method is the use of multiple deep convolutional networks (DCNs) to extract spatial features and to use the long short-term memory (LSTM) network to organize spatial features. First, a precise farmland parcel map was delineated from optical images. Second, hundreds of spatial features were retrieved using multiple DCNs from preprocessed SAR images and overlaid onto the parcel map to construct multivariate time-series of crop growth for parcels. Third, LSTM-based network structures for organizing these time-series features were constructed to produce a final parcel-based classification map. The method was applied to a dataset of high-resolution ZY-3 optical images and multi-temporal Sentinel-1A SAR data to classify crop types in the Hunan Province of China. The classification results, showing an improvement of greater than 5.0% in overall accuracy relative to methods without spatial features, demonstrated the effectiveness of the proposed method in extracting and organizing spatial features for improving parcel-based crop classification.

Description: The classification of very-high-resolution (VHR) remote sensing images is essential in many applications. However, high intraclass and low interclass variations in these kinds of images pose serious challenges. Fully convolutional network (FCN) models, which benefit from a powerful feature learning ability, have shown impressive performance and great potential. Nevertheless, only classification results with coarse resolution can be obtained from the original FCN method. Deep feature fusion is often employed to improve the resolution of outputs. Existing strategies for such fusion are not capable of properly utilizing the low-level features and considering the importance of features at different scales. This paper proposes a novel, end-to-end, fully convolutional network to integrate a multiconnection ResNet model and a class-specific attention model into a unified framework to overcome these problems. The former fuses multilevel deep features without introducing any redundant information from low-level features. The latter can learn the contributions from different features of each geo-object at each scale. Extensive experiments on two open datasets indicate that the proposed method can achieve class-specific scale-adaptive classification results and it outperforms other state-of-the-art methods. The results were submitted to the International Society for Photogrammetry and Remote Sensing (ISPRS) online contest for comparison with more than 50 other methods. The results indicate that the proposed method (ID: SWJ_2) ranks #1 in terms of overall accuracy, even though no additional digital surface model (DSM) data that were offered by ISPRS were used and no postprocessing was applied.

Description: Low Earth orbit (LEO) satellites play an important role in human space activities, and market demands for commercial uses of LEO satellites have been increasing rapidly in recent years. LEO satellites mainly consist of Earth observation satellites (EOSs), the major commercial applications of which are various sorts of Earth observations, such as map making, crop growth assessment, and disaster surveillance. However, the success rates of observation tasks are influenced considerably by uncertainties in local weather conditions, inadequate sunlight, observation dip angle, and other practical factors. The available time windows (ATWs) suitable for observing given types of targets and for transmitting data back to ground receiver stations are relatively narrow. In order to utilize limited satellite resources efficiently and maximize their commercial benefits, it is necessary to evaluate the overall effectiveness of satellites and planned tasks considering various factors. In this paper, we propose a method for determining the ATWs considering the influence of sunlight angle, elevation angle, and the type of sensor equipped on the satellite. After that, we develop a satellite effectiveness evaluation (SEE) model for satellite observation and data-downlink scheduling (SODS) based on the Availability–Capacity–Profitability (ACP) framework, which is designed to evaluate the overall performance of satellites from the perspective of time resource utilization, the success rate of tasks, and profit return. The effects of weather uncertainties on the tasks’ success are considered in the SEE model, and the model can be applied to support the decision-makers on optimizing and improving task arrangements for EOSs. Finally, a case study is presented to demonstrate the effectiveness of the proposed method and verify the ACP-based SEE model. The obtained ATWs by the proposed method are compared with those by the Systems Tool Kit (STK), and the correctness of the method is thus validated.

Description: In real-time onboard hyperspectral-image(HSI) anomalous targets detection, processing speed and accuracy are equivalently desirable which is hard to satisfy at the same time. To improve detection accuracy, deep learning based HSI anomaly detectors (ADs) are widely studied. However, their large scale network results in a massive computational burden. In this paper, to improve the detection throughput without sacrificing the accuracy, a pruning–quantization–anomaly–detector (P-Q-AD) is proposed by building an underlying constraint formulation to make a trade-off between accuracy and throughput. To solve this formulation, multi-objective optimization with nondominated sorting genetic algorithm II (NSGA-II) is employed to shrink the network. As a result, the redundant neurons are removed. A mixed precision network is implemented with a delicate customized fixed-point data expression to further improve the efficiency. In the experiments, the proposed P-Q-AD is implemented on two real HSI data sets and compared with three types of detectors. The results show that the performance of the proposed approach is no worse than those comparison detectors in terms of the receiver operating characteristic curve (ROC) and area under curve (AUC) value. For the onboard mission, the proposed P-Q-AD reaches over 4.5 × speedup with less than 0.5 % AUC loss compared with the floating-based detector. The pruning and the quantization approach in this paper can be referenced for designing the anomalous targets detectors for high efficiency.

Description: Traditional plug-flow anaerobic reactors (PFRs) are characterized by lacking a mixing system and operating at high total solid concentrations, which limits their applicability for several kinds of manures. This paper studies the performance of a novel modified PFR for the treatment of pig manure, characterized by having an internal sludge mixing system by biogas recirculation in the range of 0.270–0.336 m3 m−3 h−1. The influence on the methane yield of four operating parameters (recirculation rate, hydraulic retention time, organic loading rate, and total solids) was evaluated by running four modified PFRs at the pilot scale in mesophilic conditions. While the previous biodegradability of organic matter by biochemical methane potential tests were between 31% and 47% with a methane yield between 125 and 184 LCH4 kgVS−1, the PFRs showed a suitable performance with organic matter degradation between 25% and 51% and a methane yield of up to 374 LCH4 kgVS−1. Operational problems such as solid stratification, foaming, or scum generation were avoided.

Description: In the eddy current braking system of high-speed maglev, the peak braking force and the critical speed are key factors determining the performance of eddy current braking force. In this paper, the analytical formula of eddy current braking force is derived by a subdomain method considering the skin effect of the induction plate, and, subsequently, the characteristics of peak braking force and critical speed are analyzed. The analytical model is set up in a 2D Cartesian coordinate system. The Poisson equations in each subdomain are listed by treating the vector magnetic potential as a variable. By combining the boundary conditions between two adjacent subdomains, the expressions of eddy current density and magnetic density in the induction plate are obtained. Then, the analytical formula of the eddy current braking force is obtained by the Ampere force formula. The results of finite-element analysis confirm the validity of the analytical calculation. The methods of improving the performance of eddy current braking force under high speed are proposed by parametric analysis of peak braking force and critical speed, which provides guidance for the design of the eddy current braking system in high-speed maglev.

Description: This paper proposes an input voltage disturbance suppression control strategy for the unidirectional matrix converter (UMC) with a new modulation scheme enhancing the stability. In the new scheme, the modulation index is directly, rather than reversely, proportional to the instantaneous amplitude of input filter capacitor voltages. Contrary to traditional schemes, the stability of the UMC with this new scheme is even better with the increase of the transferred active power, which is particularly suitable for applications with sinusoidal and balanced input conditions. As to the disturbed input conditions, the new scheme could introduce low-frequency harmonics into output currents. To address this issue, a feedback control strategy of output current amplitude is further proposed to eliminate the additional harmonics. Stability analysis of a UMC with the proposed modulation scheme and feedback control strategy is presented. Experimental results have verified the validity of the proposed control solution.

Description: The interest in pellets utilization for households heating has been growing significantly in the last several years. However, the pellets need to meet certain quality requirements, including the mechanical durability (DU) index. In the winter seasons, the pellets are very often stored in unheated in-door systems or are transported by trucks over long distances. As a result, the pellets are exposed to external weather factors, including very low temperatures (even freezing ones), which can have a negative impact on the quality parameters of the fuel. There are several parameters affecting mechanical durability, but little is known about the influence of a very low temperature on the pellet properties. The aim of this research was to analyze the influence of freezing temperature storage on the mechanical durability of commercial pellets made of different biomass. The research was carried out in accordance with the international standard for solid biofuels PN-EN ISO 17831-1:2016-02. The samples were investigated under three different conditions: after normal storage conditions (20 °C), after frozen storage conditions (−28 °C) and after the defrosting of the pellets. The results revealed that the freezing process and subsequent defrosting of the pellets only causes a small drop in their mechanical durability in comparison to the normal storage conditions. The highest mechanical durability was established for digestate pellet and pine sawdust pellet, at 99.0 ± 0.1% and 98.7 ± 0.1% respectively (p 〈 0.05). The greatest change of mechanical durability was observed after the defrosting process of pellets, which in the initial stage and at the normal storage temperature were characterized by low mechanical durability. The pellets made of sunflower husk (DU = 87.4%) and coal/straw blend (DU = 96.2%) were distinguished by the highest change in their mechanical durability (ΔDU = 1.7%, p 〈 0.05). Based on the obtained results, it was concluded that the storage of pellets at freezing temperature does not significantly affect their mechanical durability. However, if the mechanical durability decreases, this result is related to pellets with low initial mechanical durability.

Description: The present study scrutinized the impacts of terrain-induced turbulence on wind turbine blades, examining measurement data regarding wind conditions and the strains of wind turbine blades. Furthermore, we performed a high-resolution large-eddy simulation (LES) and identified the three-dimensional airflow structures of terrain-induced turbulence. Based on the LES results, we defined the Uchida-Kawashima Scale_1 (the U-K scale_1), which is a turbulence evaluation index, and clarified the existence of the terrain-induced turbulence quantitatively. The threshold value of the U-K scale_1 was determined as 0.2, and this index was confirmed to not be dependent on the inflow profile, the influence of the horizontal grid resolution, and the influence of the computed azimuth. In addition, we defined the Uchida-Kawashima Scale_2 (the U-K scale_2), which is a fatigue damage evaluation index based on the measurement data and the design value obtained by DNV GL’s Bladed. DNV GL (Det Norske Veritas Germanischer Lloyed) is a third party certification body in Norway, and Bladed has been the industry standard aero-elastic wind turbine modeling software. Using the U-K scale_2, the following results were revealed: the U-K scale_2 was 0.86 〈 1.0 (within the designed value) in the case of northerly wind, and the U-K scale_2 was 1.60 〉 1.0 (exceeding the designed value) in the case of easterly wind. As a result, it was revealed that the blades of the target wind turbine were directly and strongly affected by terrain-induced turbulence when easterly winds occurred.

Description: This paper proposes a harmonic compensation control with disturbance rejection function for a standalone inverter. Due to the LC type three-phase three-leg inverter is connected to nonlinear loads, low-order harmonic components appears in the inverter output current. These harmonic current generate harmonic voltage drops when flowing through the filter inductor and the feeder impedance, which causes the output voltage of the inverter distorted. In order to compensate harmonics and produce sinusoidal voltage without additional compensation devices, virtual harmonic impedance method can be added to the fundamental voltage control. Due to the compensation effect of virtual harmonic impedance are very sensitive to the fluctuation of filter inductance. Therefore, inductance variation, as a disturbance in physical system, should be considered. In this paper, linear active disturbance rejection control (LADRC) is proposed in the fundamental voltage control loop to reduce the sensitivity of virtual harmonic impedance and decouple the model. Compared with traditional dual-loop PI control, the proposed strategy has faster dynamic response in control performance and fewer acquisition modules in engineering applications. The whole design process of virtual harmonic impedance and stability analyses of this strategy are provided. The simulation and experiment results show the good performance of the proposed strategy.

Description: This work explores the possibility to adopt in organic Rankine cycle (ORC) plants mixtures of water (acting as solvent) plus an organic compound (acting as solute) as the working fluid. Initially an evaluation of the thermodynamic properties of the mixtures is performed, in order to assess their properties, and to point out the molar fractions which entail a near-azeotropic behaviour. Four species from three different classes of chemical compounds are investigated: 2,2,2-trifluoroethanol and n-butanol for alcohols, where the first is fluorinated, acetonitrile for nitrile class and 2-methylpyrazine as a heterocyclic aromatic compound. Simultaneously, the thermal stability of the pure substances considered as the possible solute for the mixtures is experimentally investigated in order to estimate the temperature applicability range. The ORC plant performance, from a low-enthalpy geothermal heat source (hot water stream from 100 to 200 °C), adopting the selected mixtures as the working fluid is finally evaluated, and the analysis includes a preliminary discussion on the turbine design; results are compared with respect to the reference case of a hypothetical plant adopting water as the working fluid.

Description: In this paper, the optimal site and size selection of wind turbines (WTs) is presented considering the maximum allowable capacity constraint with the objective of loss reduction and voltage profile improvement of distribution grids based on particle swarm optimization (PSO as a multi-objective problem using weighted coefficients method. The optimal site, size, and power factor of the WTs are determined using PSO. The proposed method is implemented on 84- and 32-bus standard grids. In this study, PSO algorithm is applied to determine the size, site, and power factor of WTs considering their maximum size constraint (with constraint, variant size) and also not considering their maximum size constraint (without constraint, constant size). The simulation results showed that the PSO is effective to find the site, size, and power factor of WTs optimally in the single and multi-objective problem. The results of this method showed that the power loss is reduced more and voltage profile improved more considering WTs maximum allowable size versus not considering this constraint. Additionally, the multi-objective results showed that there is a compromise between the objectives in the multi-objective WTs site selection and the multi-objective problem solution is a more realistic and accurate approach in comparison with the single-objective problem solution.

Description: Aiming to maximize the transmission efficiency of inductively coupled power transmission (ICPT) system with the designed output power, a frequency locking method for an ICPT system based on LCC/S compensation topology is proposed in this paper. Firstly, the relationship between compensation component Lf1 and output power was deduced by the lossless model, and the initial value of Lf1 was obtained. Then, considering the system loss, the designed output power and frequency were input into the frequency locking program, and Lf1 and other compensation parameters were dynamically tracked. At the same time, the transmission efficiency of the system was calculated, and the frequency that achieved maximum efficiency was automatically locked when the system met the requirements of the designed output power. Finally, based on the method, the output characteristics of the system were verified by experiments.

Description: Wind Energy Conversion System (WECS) plays an inevitable role across the world. WECS consist of many components and equipment’s such as turbines, hub assembly, yaw mechanism, electrical machines; power electronics based power conditioning units, protection devices, rotor, blades, main shaft, gear-box, mainframe, transmission systems and etc. These machinery and devices technologies have been developed on gradually and steadily. The electrical machine used to convert mechanical rotational energy into electrical energy is the core of any WECS. Many electrical machines (generator) has been used in WECS, among the generators the Permanent Magnet Synchronous Generators (PMSGs) have gained special focus, been connected with wind farms to become the most desirable due to its enhanced efficiency in power conversion from wind energy turbine. This article provides a review of literatures and highlights the updates, progresses, and revolutionary trends observed in WECS-based PMSGs. The study also compares the geared and direct-driven conversion systems. Further, the classifications of electrical machines that are utilized in WECS are also discussed. The literature review covers the analysis of design aspects by taking various topologies of PMSGs into consideration. In the final sections, the PMSGs are reviewed and compared for further investigations. This review article predominantly emphasizes the conceptual framework that shed insights on the research challenges present in conducting the proposed works such as analysis, suitability, design, and control of PMSGs for WECS.

Description: Calcium looping is a promising technology to capture CO2 from the process of coal-fired power generation and gasification of coal/biomass for hydrogen production. The decay of CO2 capture activities of calcium-based sorbents is one of the main problems holding back the development of the technology. Taking carbide slag as a main raw material and Ca12Al14O33 as a support, highly active CO2 sorbents were prepared using the hydrothermal template method in this work. The effects of support ratio, cycle number, and reaction conditions were evaluated. The results show that Ca12Al14O33 generated effectively improves the cyclic stability of CO2 capture by synthetic sorbents. When the Al2O3 addition is 5%, or the Ca12Al14O33 content is 10%, the synthetic sorbent possesses the highest cyclic CO2 capture performance. Under harsh calcination conditions, the CO2 capture capacity of the synthetic sorbent after 30 cycles is 0.29 g/g, which is 80% higher than that of carbide slag. The superiority of the synthetic sorbent on the CO2 capture kinetics mainly reflects at the diffusion-controlled stage. The cumulative pore volume of the synthetic sorbent within the range of 10–100 nm is 2.4 times as high as that of calcined carbide slag. The structure of the synthetic sorbent reduces the CO2 diffusion resistance, and thus leads to better CO2 capture performance and reaction rate.

Description: Direct dependencies and conditional dependencies in restricted Bayesian network classifiers (BNCs) are two basic kinds of dependencies. Traditional approaches, such as filter and wrapper, have proved to be beneficial to identify non-significant dependencies one by one, whereas the high computational overheads make them inefficient especially for those BNCs with high structural complexity. Study of the distributions of information-theoretic measures provides a feasible approach to identifying non-significant dependencies in batch that may help increase the structure reliability and avoid overfitting. In this paper, we investigate two extensions to the k-dependence Bayesian classifier, MI-based feature selection, and CMI-based dependence selection. These two techniques apply a novel adaptive thresholding method to filter out redundancy and can work jointly. Experimental results on 30 datasets from the UCI machine learning repository demonstrate that adaptive thresholds can help distinguish between dependencies and independencies and the proposed algorithm achieves competitive classification performance compared to several state-of-the-art BNCs in terms of 0–1 loss, root mean squared error, bias, and variance.

Description: Renewable energy sources can help the countries to achieve some of the Sustainable Development Goals (SDGs) provided from the recent 2030 Agenda, allowing for clean, secure, reliable and affordable energy. Biomass technology is a relevant renewable energy to contribute to reach a clean and affordable energy production system with important emissions reduction of greenhouse gases (GHG). An innovative technological application of biomass energy consisting of a burner coupled with an external fired gas turbine (EFGT) has been developed for the production of electricity. This paper shows the results of the plant modelling by Aspen Plus environment and preliminary experimental tests; the validation of the proposed model allows for the main parameters to be defined that regulate the energy production plant supplied by woodchips.

Description: Several window functions are currently applied to improve the performance of the discrete Fourier transform (DFT) harmonic detection method. These window functions exhibit poor accuracy in measuring the harmonic contents of a signal with high-order and weak-amplitude components when the power frequency fluctuates within a small range. In this paper, a minimum side-lobe optimization window function that is aimed at overcoming the abovementioned issue is proposed. Moreover, an improved DFT harmonic detection algorithm based on the six-term minimum side-lobe optimization window and four-spectrum-line interpolation method is proposed. In this context, the minimum side-lobe optimization window is obtained by optimizing the conventional cosine window function according to the optimization rules, and the characteristics of the new proposed window are provided to analyze its performance. Then, the proposed optimization window function is employed to improve the DFT harmonic detection algorithm based on the six-term minimum side-lobe optimization window and four-spectrum-line interpolation method. The proposed technique is used to detect harmonics of an electricity gird in which the six-term minimum side-lobe optimization window is utilized to eliminate the influence of spectrum leakage caused by nonsynchronous sampling of signal processing. The four-spectrum-line interpolation method is employed to eliminate or mitigate the fence effect caused by the inherent measurement error of the DFT method. Simulation experiments in two complex conditions and an experiment test are carried out to validate the improved performance of the proposed window. Results reveal that the six-term minimum side-lode optimization window has the smallest peak side lobe when compared with existing windows, which can effectively reduce the interaction influence of spectrum leakage, improve the measurement accuracy of the DFT harmonic detection method, and meet the standard requirement of harmonic measurement in complex situations.

Description: Apart from electric vehicles, most internal combustion (IC) engines are powered while burning petroleum-based fossil or alternative fuels after mixing with inducted air. Thereby the operations of mixing and combustion evolve in a turbulent flow environment created during the intake phase and then intensified by the piston motion and influenced by the shape of combustion chamber. In particular, the swirl and turbulence levels existing immediately before and during combustion affect the evolution of these processes and determine engine performance, noise and pollutant emissions. Both the turbulence characteristics and the bulk flow pattern in the cylinder are strongly affected by the inlet port and valve design. In the present paper, large eddy simulation (LES) is appraised and applied to studying the turbulent fluid flow around the intake valve of a single cylinder IC-engine as represented by the so called magnetic resonance velocimetry (MRV) flow bench configuration with a relatively large Reynolds number of 45,000. To avoid an intense mesh refinement near the wall, various subgrid scale models for LES; namely the Smagorinsky, wall adapting local eddy (WALE) model, SIGMA, and dynamic one equation models, are employed in combination with an appropriate wall function. For comparison purposes, the standard RANS (Reynolds-averaged Navier–Stokes) k- ε model is also used. In terms of a global mean error index for the velocity results obtained from all the models, at first it turns out that all the subgrid models show similar predictive capability except the Smagorinsky model, while the standard k- ε model experiences a higher normalized mean absolute error (nMAE) of velocity once compared with MRV data. Secondly, based on the cost-accuracy criteria, the WALE model is used with a fine mesh of ≈39 millions control volumes, the averaged velocity results showed excellent agreement between LES and MRV measurements, revealing the high prediction capability of the suggested LES tool for valve flows. Thirdly, the turbulent flow across the valve curtain clearly featured a back flow resulting in a high speed intake jet in the middle. Comprehensive LES data are generated to carry out statistical analysis in terms of (1) evolution of the turbulent morphology across the valve passage relying on the flow anisotropy map, (2) integral turbulent scales along the intake-charge stream, (3) turbulent flow properties such as turbulent kinetic energy, turbulent velocity and its intensity within the most critical zone in intake-port and along the port length, it further transpires that the most turbulence are generated across the valve passage and these are responsible for the in-cylinder turbulence.

Description: Identification of denatured biological tissue is crucial to high intensity focused ultrasound (HIFU) treatment. It is not easy for intercepting ultrasonic scattered echo signals from HIFU treatment region. Therefore, this paper employed time-frequency entropy based on generalized S-transform (GST) to intercept ultrasonic echo signals. First, the time-frequency spectra of ultrasonic echo signal is obtained by GST, which is concentrated around the real instantaneous frequency of the signal. Then the time-frequency entropy is calculated based on time-frequency spectra. The experimental results indicate that the time-frequency entropy of ultrasonic echo signal will be abnormally high when ultrasonic signal travels across the boundary between normal region and treatment region in tissues. Ultrasonic scattered echo signals from treatment region can be intercepted by time-frequency entropy. In addition, the refined composite multi-scale weighted permutation entropy (RCMWPE) is proposed to evaluate the complexity of nonlinear time series. Comparing with multi-scale permutation entropy (MPE) and multi-scale weighted permutation entropy (MWPE), RCMWPE not only measures complexity of signal including amplitude information, but also improves the stability and reliability of multi-scale entropy. The RCMWPE and MPE are applied to 300 cases of actual ultrasonic scattered echo signals (including 150 cases in normal status and 150 cases in denatured status). It is found that the RCMWPE and MPE values of denatured tissues are higher than those of the normal tissues. Both RCMWPE and MPE can be used to distinguish normal tissues and denatured tissues. However, there are fewer feature points in the overlap region between RCMWPE of denatured tissues and normal tissues compared with MPE. The intra-class distance and the inter-class distance of RCMWPE are less and greater respectively than MPE. The difference between denatured tissues and normal tissues is more obvious when RCMWPE is used as the characteristic parameter. The results of this study will be helpful to guide doctors to obtain more accurate assessment of treatment effect during HIFU treatment.

Description: Gas-liquid two-phase flow behavior in horizontal channel under heaving motion showed unique dynamic characteristics due to the complex nonlinear interaction. To further establish a description model and investigate the effects of heaving motion on horizontal gas-liquid flow, experiments in a wide range of vibration parameters and working conditions were carried out by combining vibration platform with two-phase flow loop. It was found that the flow regimes under heaving motion showed significant differences compared to the ones expected in steady state flow under the same working conditions. Increasing vibration parameters showed an obvious impact on fluctuation degree of gas-liquid interface by visualizing high-speed photographs. A method based on multi-scale entropy was applied to identify flow regimes and reveal the underlying dynamic characteristics by collecting signals of pressure-difference. The results indicated that the proposed method was effective to analyze gas-liquid two-phase flow transition in horizontal channel under heaving motion by incorporating information of flow condition and change rate of multi-scale entropy, which provided a reliable guide for flow pattern control design and safe operation of equipment. However, for slug-wave and boiling wave flow, an innovative method based on multi-scale marginal spectrum entropy showed more feasible for identification of transition boundary.

Description: The ongoing digital transformation has the potential to revolutionize nearly all industrial manufacturing processes. However, its concrete requirements and implications are still not sufficiently investigated. In order to establish a common understanding, a multitude of initiatives have published guidelines, reference frameworks and specifications, all intending to promote their particular interpretation of the Industrial Internet of Things (IIoT). As a result of the inconsistent use of terminology, heterogeneous structures and proposed processes, an opaque landscape has been created. The consequence is that both new users and experienced experts can hardly manage to get an overview of the amount of information and publications, and make decisions on what is best to use and to adopt. This work contributes to the state of the art by providing a structured analysis of existing reference frameworks, their classifications and the concerns they target. We supply alignments of shared concepts, identify gaps and give a structured mapping of regarded concerns at each part of the respective reference architectures. Furthermore, the linking of relevant industry standards and technologies to the architectures allows a more effective search for specifications and guidelines and supports the direct technology adoption.

Description: To date, several algorithms for the retrieval of cyanobacterial phycocyanin (PC) from ocean colour sensors have been presented for inland waters, all of which claim to be robust models. To address this, we conducted a comprehensive comparison to identify the optimal algorithm for retrieval of PC concentrations in the highly optically complex waters of Lake Balaton (Hungary). MEdium Resolution Imaging Spectrometer (MERIS) top-of-atmosphere radiances were first atmospherically corrected using the Self-Contained Atmospheric Parameters Estimation for MERIS data v.B2 (SCAPE-M_B2). Overall, the Simis05 semi-analytical algorithm outperformed more complex inversion algorithms, providing accurate estimates of PC up to ±7 days from the time of satellite overpass during summer cyanobacteria blooms (RMSElog 〈 0.33). Same-day retrieval of PC also showed good agreement with cyanobacteria biomass (R2 〉 0.66, p 〈 0.001). In-depth analysis of the Simis05 algorithm using in situ measurements of inherent optical properties (IOPs) revealed that the Simis05 model overestimated the phytoplankton absorption coefficient [aph(λ)] by a factor of ~2. However, these errors were compensated for by underestimation of the mass-specific chlorophyll absorption coefficient [a*chla(λ)]. This study reinforces the need for further validation of algorithms over a range of optical water types in the context of the recently launched Ocean Land Colour Instrument (OLCI) onboard Sentinel-3.

Description: In recent years, with more open data platforms and tools available to store and process satellite imagery, Earth Observation data have become widely accessible and usable especially for countries previously not in the possession of tasking rights to satellites and the needed processing capacity. Due to its ideal scanning and acquisition conditions for low cloud coverage imagery, Namibia aims to make use of this new development and integrate Earth Observation data into its national monitoring system of sustainable development goals (SDG). The purpose of this study is to assess the potential of open source tools and global datasets to estimate the national SDG indicators on Change of water-related ecosystems (6.6.1), Rural population with access to roads (9.1.1), Forest coverage (15.1.1) and Land degradation (15.3.1). The results are set into perspective of existing information in each particular sector. The study shows that, in the absence of in-situ measurements or data collected through surveys, the Earth Observation-based results represent a high potential to supplement the national statistics for Namibia or to serve as primary data sources once validated through ground-truthing. Furthermore, examples are given for the limitations of the assessed Earth Observation solutions in the context of Namibia. Hence, the study also serves as valuable input for discussions on a consensus on national definitions and standards by all stakeholders responsible for releasing official statistics.

Description: Electronic load (e-load) is essential equipment for power converter performance test, where a designated load profile is executed. Electronic load is usually implemented with the analog controller for fast tracking of the load profile reference. In this paper, a low-power low-cost electronic load is proposed. MOSFETs (metal-oxide-semiconductor field-effect transistors) are used as the power consumption devices, which are regulated to the active region as controlled current-sink. In order to achieve fast transient response using the low-cost digital signal controller (DSC) PWM peripherals, the interleaving PWM method is proposed to achieve active current ripple mitigation. To obtain the system open-loop gain for current-sink operation, an offline digital system identification method, followed by model reduction, is proposed by applying Pseudo-Random Binary Sequence (PRBS) excitation. Pole-zero cancelation method is used in the control system design and later implemented in a DSC. The prototype is built and tested, in which meaningful testing scenarios under constant current-sink mode, pulse current sink mode, and double line-frequency current mode are verified. The experimental results indicate that the proposed e-load can sink pre-programmed current profile with well-attenuated ripple for static and dynamic load testing, and is applicable to fully digitalized power testing equipment.

Description: A centrifugal carbon dioxide compressor is a kind of general machine with extensive applications. The geometry of the side chambers of the compressors can be determined by studying the rotor-stator cavity with centripetal through-flow. In this paper, numerical simulations were conducted to predict the characteristics of flow and heat transfer. Three different speeds of rotation and two axial gap widths were considered. The correlations of the core swirl ratios were determined by fitting the results for two axial gap widths. The amounts of the moment coefficients of the disk were predicted. In order to better analyze the temperature field, the radial distributions of the local heat transfer coefficient were numerically investigated. According to the simulation results, the average Nusselt number was found to be dominated by the turbulent flow parameter. It also seemed to be proportional to the moment coefficient at a fixed circumferential Reynolds number.

Description: The pattern of micro-electricity production of simple two-chamber microbial fuel cells (MFC) was monitored in this study. Piggery wastewater and anaerobic sludge served as fuel and inocula for the MFC, respectively. The output power, including voltage and current generation, of triplicate MFCs was measured using an on-line monitoring system. The maximum voltage obtained among the triplicates was 0.663 V. We also found that removal efficiency of chemical oxygen demand (COD) and biochemical oxygen demand (BOD) in the piggery wastewater was 94.99 and 98.63%, respectively. Moreover, analytical results of Fast Fourier Transform (FFT) demonstrated that the output current comprised alternating current (AC) and direct current (DC) components, ranging from mA to μA.

Description: When the offshore wind energy industry attempts to develop in cold regions, ice load becomes the main technological challenge for offshore wind turbine foundation design. Dynamic ice loads acting on wind turbine foundations should be calculated in a reasonable way. The scope of this study is to present a numerical model that considers the non-simultaneous ice crushing failure acting on the vertical structure of a wind turbine’s foundation. The local ice crushing force at the contact surface between the ice sheet and structure is calculated. The boundary of the ice sheet is updated at each time step based on the indentation length of the ice sheet according to its structure. Ice loads are validated against two model tests with three different structure models developed by other researchers. The time series of the ice forces derived from the simulation and model tests are compared. The proposed numerical model can capture the main trends of ice–wind turbine foundation interaction. The simulation results agree well with measured data from the model tests in terms of maximum ice force, which is a key factor for wind turbine design. The proposed model will be helpful for assisting the initial design of wind turbine foundations in cold regions.

Description: The optimum nitrogen concentration for media supplementation and strain dominance are aspects of key importance to the industrial production of ethanol with a view to reducing costs and increasing yields. In this work, these two factors were investigated for four ethanologenic Saccharomyces cerevisiae strains (CLQCA-INT-001, CLQCA-INT-005, CLQCA-10-099, and UCLM 325), selected from the screening of 150 isolates, mostly from Ecuadorian yeast biodiversity. The effect of nitrogen concentration was assessed in terms of cellular growth, glucose consumption and ethanol production, and the yeast strains’ dominance was evaluated in continuous co-fermentation with cellular recycling by mitochondrial DNA analyses. Among the four selected yeast strains under study, CLQCA-INT-005 presented the highest glucose consumption at a nitrogen supplement concentration as low as 0.4 g·L−1, attaining an ethanol yield of up to 96.72% in 24 h. The same yeast strain was found to be highly competitive, showing a dominance of 80% after four cycles of fermentation in co-culture. Thus, CLQCA-INT-005 may be deemed as a very promising candidate to be used both at pilot-plant scale and at industrial scale cellulosic ethanol production.

Description: In the past decade, the condensation of internal air humidity in automotive headlamps has become more prevalent than ever due to the increased usage of a new light source—LEDs. LEDs emit far less heat than previously-used halogen lamps, which makes them far more susceptible to fogging. This fogging occurs when the internal parts of the headlamp fall to a temperature below the dew point. The front glass is most vulnerable to condensation due to its direct exposure to ambient conditions. Headlamp fogging leads to a decrease in performance and the possibility of malfunctions, which has an impact not only on the functional aspect of the product’s use but also on traffic safety. There are currently several technical solutions available which can determine the effectivity of ventilation systems applied for headlamp defogging. Another approach to this problem may be to use a numerical simulation. This paper proposes a CFD (computational fluid dynamics) simulation with a slightly simplified 3D model of an actual headlamp, which allows simulation of all the phenomena closely connected with fluid flow and phase change. The results were validated by real experiments on a special fogging–defogging test rig. This paper compares three different simulations and their compliance with real experiments.

Description: The depletion and usage of fossil fuels causes environmental issues and alternative fuels and technologies are urgently required. Therefore, thermal arc water vapor plasma for a fast and robust waste/biomass treatment is an alternative to the syngas method. Waste cooking oil (WCO) can be used as an alternative potential feedstock for syngas production. The goal of this experimental study was to conduct experiments gasifying waste cooking oil to syngas. The WCO was characterized in order to examine its properties and composition in the conversion process. The WCO gasification system was quantified in terms of the produced gas concentration, the H2/CO ratio, the lower heating value (LHV), the carbon conversion efficiency (CCE), the energy conversion efficiency (ECE), the specific energy requirements (SER), and the tar content in the syngas. The best gasification process efficiency was obtained at the gasifying agent-to-feedstock (S/WCO) ratio of 2.33. At this ratio, the highest concentration of hydrogen and carbon monoxide, the H2/CO ratio, the LHV, the CCE, the ECE, the SER, and the tar content were 47.9%, 22.42%, 2.14, 12.7 MJ/Nm3, 41.3% 85.42%, 196.2 kJ/mol (or 1.8 kWh/kg), and 0.18 g/Nm3, respectively. As a general conclusion, it can be stated that the thermal arc-plasma method used in this study can be effectively used for waste cooking oil gasification to high quality syngas with a rather low content of tars.

Description: Liriodendron chinense (Hemsl.), a Tertiary relic tree, is mainly distributed in subtropical China. The causes of the geographical distribution pattern of this species are poorly understood. In this study, we inferred historical dispersal routes and glacial refugia of this species by combining genetic data (chloroplast DNA (cpDNA), nuclear ribosomal DNA (nrDNA), and nuclear DNA (nDNA)) and geospatial data (climate and geology) with the methods of landscape genetics. Additionally, based on sequence variation at multiple loci, we employed GenGIS and Barrier software to analyze L. chinense population genetic structure. Dispersal corridors and historical gene flow between the eastern and western populations were detected, and they were located in mountainous regions. Based on species distribution model (SDMs), the distribution patterns in paleoclimatic periods were consistent with the current pattern, suggesting the presence of multiple refuges in multiple mountainous regions in China. The genetic structure analysis clustered most eastern populations into a clade separated from the western populations. Additionally, a genetic barrier was detected between the eastern and western populations. The dispersal corridors and historical gene flow detected here suggested that the mountains acted as a bridge, facilitating gene flow between the eastern and western populations. Due to Quaternary climatic fluctuations, the habitats and dispersal corridors were frequently inhabited by warm-temperate evergreen forests, which may have fragmented L. chinense habitats and exacerbated the differentiation of eastern and western populations. Ultimately, populations retreated to multiple isolated mountainous refugia, shaping the current geographical distribution pattern. These dispersal corridors and montane refugia suggested that the mountains in subtropical China play a crucial role in the conservation of genetic resources and migration of subspecies or related species in this region.

Description: We propose a derivative-free iterative method with fifth order of convergence for solving systems of nonlinear equations. The scheme is composed of three steps, of which the first two steps are that of third order Traub-Steffensen-type method and the last is derivative-free modification of Chebyshev’s method. Computational efficiency is examined and comparison between the efficiencies of presented technique with existing techniques is performed. It is proved that, in general, the new method is more efficient. Numerical problems, including those resulting from practical problems viz. integral equations and boundary value problems, are considered to compare the performance of the proposed method with existing methods. Calculation of computational order of convergence shows that the order of convergence of the new method is preserved in all the numerical examples, which is not so in the case of some of the existing higher order methods. Moreover, the numerical results, including the CPU-time consumed in the execution of program, confirm the accurate and efficient behavior of the new technique.

Description: The elementary symmetric functions play a crucial role in the study of zeros of non-zero polynomials in C [ x ] , and the problem of finding zeros in Q [ x ] leads to the definition of algebraic and transcendental numbers. Recently, Marques studied the set of algebraic numbers in the form P ( T ) Q ( T ) . In this paper, we generalize this result by showing the existence of algebraic numbers which can be written in the form P 1 ( T ) Q 1 ( T ) ⋯ P n ( T ) Q n ( T ) for some transcendental number T, where P 1 , … , P n , Q 1 , … , Q n are prescribed, non-constant polynomials in Q [ x ] (under weak conditions). More generally, our result generalizes results on the arithmetic nature of z w when z and w are transcendental.

Description: Machine learning algorithms have been widely used in the field of client credit assessment. However, few of the algorithms have focused on and solved the problems of concept drift and class imbalance. Due to changes in the macroeconomic environment and markets, the relationship between client characteristics and credit assessment results may change over time, causing concept drift in client credit assessments. Moreover, client credit assessment data are naturally asymmetric and class imbalanced because of the screening of clients. Aiming at solving the joint research issue of concept drift and class imbalance in client credit assessments, in this paper, a novel sample-based online learning ensemble (SOLE) for client credit assessment is proposed. A novel multiple time scale ensemble classifier and a novel sample-based online class imbalance learning procedure are proposed to handle the potential concept drift and class imbalance in the client credit assessment data streams. The experiments are carried out on two real-world client credit assessment cases, which present a comprehensive comparison between the proposed SOLE and other state-of-the-art online learning algorithms. In addition, the base classifier preference and the computing resource consumption of all the comparative algorithms are tested. In general, SOLE achieves a better performance than other methods using fewer computing resources. In addition, the results of the credit scoring model and the Kolmogorov–Smirnov (KS) test also prove that SOLE has good practicality in actual client credit assessment applications.

Description: This paper adapts the multivariate optimal control theory to a Riemannian setting. In this sense, a coherent correspondence between the key elements of a standard optimal control problem and several basic geometric ingredients is created, with the purpose of generating a geometric version of Pontryagin’s maximum principle. More precisely, the local coordinates on a Riemannian manifold play the role of evolution variables (“multitime”), the Riemannian structure, and the corresponding Levi–Civita linear connection become state variables, while the control variables are represented by some objects with the properties of the Riemann curvature tensor field. Moreover, the constraints are provided by the second order partial differential equations describing the dynamics of the Riemannian structure. The shift from formal analysis to optimal Riemannian control takes deeply into account the symmetries (or anti-symmetries) these geometric elements or equations rely on. In addition, various submanifold integral cost functionals are considered as controlled payoffs.

Description: Positioning devices allow users’ movement to be recorded. The GPS (Global Positioning System) trajectory data typically consists of spatiotemporal points, which make up the major part of the big data concerning urban life. Existing knowledge extraction methods about the trajectory share a general limitation—they only investigate data from a spatiotemporal aspect, but fail to take the semantic information of trajectories into consideration. Therefore, extracting the semantic information of trajectories with the context of big data is challenging pattern recognition task that has practical application prospects. In this paper, a system is proposed to extract the semantic trajectory patterns of positioning device users. Firstly, a spatiotemporal threshold and clustering based pre-processing model is proposed to process the raw data. Then, we design a probabilistic generative model to annotate the semantic information of each trajectory after the pre-processing procedure. Finally, we apply the PrefixSpan algorithm to mine the semantic trajectory patterns. We verify our system on a large dataset of users’ real trajectories over a period of 5 years in Beijing, China. The results of the experiment indicate that our system produces meaningful patterns.

Description: This paper presents a mathematical model of measuring blood flow based on electromagnetic induction for predicting the rate of arterial stenosis. Firstly, an electrode sensor was used to collect the induced potential differences from human skin surface in a uniform magnetic field. Then, the inversion matrix was constructed by the weight function theory and finite element method. Next, the blood flow volume inversion model was constructed by combining the induction potential differences and inversion matrix. Finally, the rate of arterial stenosis was predicted based on mathematical relationship between blood flow and the area of arterial stenosis. To verify the accuracy of the model, a uniform magnetic field distribution of Helmholtz coil and a 3D geometric model of the ulnar artery of the forearm with different rates of stenosis were established in COMSOL, a finite element analysis software. Simulation results showed that the inversion model had high accuracy in the measurement of blood flow and the prediction of rate of stenosis, and is of great significance for the early diagnosis of arterial stenosis and other vessel diseases.

Description: Magnetic Induction Tomography (MIT) is a non-invasive imaging technique that has been widely applied for imaging materials with high electrical conductivity contrasts. Steel production is among an increasing number of applications that require a contactless method for monitoring the casting process due to the high temperature of hot steel. In this paper, an MIT technique is proposed for detecting defects and deformations in the external surfaces of metal, which has the potential to be used to monitor the external surface of hot steel during the continuous casting process. The Total Variation (TV) reconstruction algorithm was developed to image the conductivity distributions. Nonetheless, the reconstructed image of the deformed square metal obtained using the TV algorithm directly does not yield resonable images of the surface deformation. However, differential images obtained by subtracting the image of a perfect square metal with no deformations from the image obtained for a deformed square metal does provide accurate and repeatable deformation information. It is possible to obtain a more precise image of surface deformation by thresholding the differential image. This TV-based threshold-differencing method has been analysed and verified from both simulation and experimental tests. The simulation results reported that 0.92 % of the image region can be detected, and the experimental results indicated a 0.57 % detectability. Use of the proposed method was demonstareted in a MIT device which was used in continuous casting set up. The paper shows results from computer simulation, lab based cold tests, and real life data from continoeus cating demonstating the effectiveness of the proposed method.

Description: Three-way decisions, as a decision-making mode which is consistent with human cognition, have been widely used in various fields. In this paper, we fuse the theory of reliability into the three-way decisions method, replace the conditional probability in the three-way decisions method with reliability, and then propose a novel three-way decisions method. We also describe the loss functions with single-valued triangular neutrosophic numbers (SVTNNs) and propose an operator to calculate the score function of triangular neutrosophic numbers. Then, the result of decision is attained according to the principle of minimizing loss. Finally, we apply this method to the overhaul of machines in a factory, which proves the practicability and effectiveness of the proposed methods.

Description: The solutions for many real life problems may be obtained by interpreting the given problem mathematically in the form f ( x ) = x . One such example is that of the famous Borsuk–Ulam theorem in which, using some fixed point argument, it can be guaranteed that at any given time we can find two diametrically opposite places in a planet with same temperature. Thus, the correlation of symmetry is inherent in the study of fixed point theory. In this article, some new results concerning coincidence and a common fixed point for an A φ -contraction and a generalized ϕ -type weak contraction are established. We prove our results for set valued maps without using continuity of the corresponding maps and completeness of the relevant space. Our results generalize and extend several existing results. Some new examples are given to demonstrate the generality and non-triviality of our results.

Description: Gas mixture quantification is essential for the recording and reproducing odors, because an odor consists of multiple chemical compounds. Gas mixture quantification using field asymmetric ion mobility spectrometry (FAIMS) was studied. Acetone, ethanol, and diethyl ether were selected as components of a ternary gas mixture sample as representatives of the ketone, alcohol, and ether chemical classes, respectively. One hundred and twenty-five points with different concentrations were measured. The results were evaluated by error hypersurface, variance, and the coefficient of variation. The error hypersurface showed that it is possible to reach the target composition by following the error-hypersurface gradient. Successful convergence was achieved with the gradient descent method in a simulation based on the measurement data. This result verified the feasibility of the quantification of a gas mixture using FAIMS.

Description: In this study, a novel strain gauge arrangement and error reduction techniques were proposed to minimize crosstalk reading and simultaneously increase sensitivity on a decoupled six-axis force–moment (F/M) sensor. The calibration process that comprises the least squares method and error reduction techniques was implemented to obtain a robust decoupling matrix. A decoupling matrix is very crucial for minimizing error and crosstalk. A novel strain gauge arrangement that comprised double parallel strain gauges in the decoupled six-axis force–moment sensor was implemented to obtain high sensitivity. The experimental results revealed that the maximum calibration error, F/M sensor measurement error, and crosstalk readings were reduced to 3.91%, 1.78%, and 4.78%, respectively.

Description: Studies related to pattern recognition and visualization using computer technology have been introduced. In particular, deep neural networks (DNNs) provide good performance for image, speech, and pattern recognition. However, a poisoning attack is a serious threat to a DNN’s security. A poisoning attack reduces the accuracy of a DNN by adding malicious training data during the training process. In some situations, it may be necessary to drop a specifically chosen class of accuracy from the model. For example, if an attacker specifically disallows nuclear facilities to be selectively recognized, it may be necessary to intentionally prevent unmanned aerial vehicles from correctly recognizing nuclear-related facilities. In this paper, we propose a selective poisoning attack that reduces the accuracy of only the chosen class in the model. The proposed method achieves this by training malicious data corresponding to only the chosen class while maintaining the accuracy of the remaining classes. For the experiment, we used tensorflow as the machine-learning library as well as MNIST, Fashion-MNIST, and CIFAR10 as the datasets. Experimental results show that the proposed method can reduce the accuracy of the chosen class by 43.2%, 41.7%, and 55.3% in MNIST, Fashion-MNIST, and CIFAR10, respectively, while maintaining the accuracy of the remaining classes.

Description: Conventional eddy current testing (ECT) using a pickup coil probe is widely employed for the detection of structural cracks. However, the inspection of conventional ECT for steel structures is difficult because of the magnetic noise caused by the nonuniform permeability of steel. To combat this challenge, we have developed a small magnetic sensor probe with a dual-channel tunneling magnetoresistance sensor that is capable of reducing magnetic noise. Applying this probe to a complicated component of steel structures—such as the welds joining a U-shaped rib and deck plate together—requires the reduction of signal fluctuation caused by the distance (liftoff) variations between the sensor probe and the subject. In this study, the fundamental crack signal and the liftoff signal were investigated with the dual-channel sensor. The results showed that the liftoff signals could be reduced and differentiated from the crack signals by the differential parameters of the dual-channel sensor. In addition, we proposed an extraction technique for the crack signal using the Lissajous curve of the differential parameters. The extraction technique could be applied to the inspections not only for flat plates but also for welded angles to detect cracks without the influence of the liftoff signal.