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: 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: 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: 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.

Description: The objective of this paper is to study the ability of polymer optical fiber (POF) to be inserted in a knitted fabric and to measure both pressure and friction when walking. Firstly, POF, marketed and in development, have been compared in terms of the required mechanical properties for the insertion of the fiber directly into a knitted fabric on an industrial scale, i.e. elongation, bending rigidity, and minimum bending radius before plastic deformation. Secondly, the chosen optical fiber was inserted inside several types of knitted fabric and was shown to be sensitive to friction and compression. The knitted structure with the highest sensitivity has been chosen for sock prototype manufacturing. Finally, a feasibility study with an instrumented sock showed that it is possible to detect the different phases of walking in terms of compression and friction.

Description: Dielectric grating-based sensors are usually based on the guided mode resonance (GMR) obtained using a thin planar waveguide layer (PWL) adjacent to a thin subwavelength grating layer. In this work, we present a detailed investigation of thick subwavelength dielectric grating structures that exhibit reflection resonances above a certain thickness without the need for the waveguide layer, showing great potential for applications in biosensing and tunable filtering. Analytic and numerical results are thoroughly discussed, as well as an experimental demonstration of the structure as a chemical sensor in the SWIR (short wave infrared) spectral range (1200–1800 nm). In comparison to the GMR structure with PWL, the thick grating structure has several unique properties: (i) It gives higher sensitivity when the spaces are filled, with the analyte peaking at certain space values due to an increase in the interaction volume between the analyte and the evanescent optical field between the grating lines; (ii) the TM (transverse magnetic) resonance, in certain cases, provides a better figure of merit; (iii) the sensitivity increases as the grating height increases; (iv) the prediction of the resonance locations based on the effective medium approximation does not give satisfactory results when the grating height is larger than a certain value, and the invalidity becomes more severe as the period increases; (v) a sudden increase in the Q-factor of the resonance occurs at a specific height value accompanied by the high local field enhancement (~103) characteristic of a nano-antenna type pattern. Rigorous numerical simulations of the field distribution are presented to explain the different observed phenomena.

Description: In 2016, the IEEE task group ah (TGah) released a new standard called IEEE 802.11ah, and industrial Internet of Things (IoT) is one of its typical use cases. The restricted access window (RAW) is one of the core MAC mechanisms of IEEE 802.11ah, which aims to address the collision problem in the dense wireless networks. However, in each RAW period, stations still need to contend for the channel by Distributed Coordination Function and Enhanced Distributed Channel Access (DCF/EDCA), which cannot meet the real-time requirements of most industrial applications. In this paper, we propose a channel-aware contention window adaption (CA-CWA) algorithm. The algorithm dynamically adapts the contention window based on the channel status with an external interference discrimination ability, and improves the real-time performance of the IEEE 802.11ah. To validate the real-time performance of CA-CWA, we compared CA-CWA with two other backoff algorithms with an NS-3 simulator. The results illustrate that CA-CWA has better performance than the other two algorithms in terms of packet loss rate and average delay. Compared with the other two algorithms, CA-CWA is able to support industrial applications with higher deadline constraints under the same channel conditions in IEEE 802.11ah.

Description: Existing correlations between features extracted from Electroencephalography (EEG) signals and emotional aspects have motivated the development of a diversity of EEG-based affect detection methods. Both intra-subject and inter-subject approaches have been used in this context. Intra-subject approaches generally suffer from the small sample problem, and require the collection of exhaustive data for each new user before the detection system is usable. On the contrary, inter-subject models do not account for the personality and physiological influence of how the individual is feeling and expressing emotions. In this paper, we analyze both modeling approaches, using three public repositories. The results show that the subject’s influence on the EEG signals is substantially higher than that of the emotion and hence it is necessary to account for the subject’s influence on the EEG signals. To do this, we propose a data transformation that seamlessly integrates individual traits into an inter-subject approach, improving classification results.

Description: Depth cameras play a vital role in three-dimensional (3D) shape reconstruction, machine vision, augmented/virtual reality and other visual information-related fields. However, a single depth camera cannot obtain complete information about an object by itself due to the limitation of the camera’s field of view. Multiple depth cameras can solve this problem by acquiring depth information from different viewpoints. In order to do so, they need to be calibrated to be able to accurately obtain the complete 3D information. However, traditional chessboard-based planar targets are not well suited for calibrating the relative orientations between multiple depth cameras, because the coordinates of different depth cameras need to be unified into a single coordinate system, and the multiple camera systems with a specific angle have a very small overlapping field of view. In this paper, we propose a 3D target-based multiple depth camera calibration method. Each plane of the 3D target is used to calibrate an independent depth camera. All planes of the 3D target are unified into a single coordinate system, which means the feature points on the calibration plane are also in one unified coordinate system. Using this 3D target, multiple depth cameras can be calibrated simultaneously. In this paper, a method of precise calibration using lidar is proposed. This method is not only applicable to the 3D target designed for the purposes of this paper, but it can also be applied to all 3D calibration objects consisting of planar chessboards. This method can significantly reduce the calibration error compared with traditional camera calibration methods. In addition, in order to reduce the influence of the infrared transmitter of the depth camera and improve its calibration accuracy, the calibration process of the depth camera is optimized. A series of calibration experiments were carried out, and the experimental results demonstrated the reliability and effectiveness of the proposed method.

Description: Two types of urea biosensors were integrated with a wireless measurement system and microfluidic measurement system. The two biosensors used were (i) a magnetic beads (MBs)-urease/graphene oxide (GO)/titanium dioxide (TiO2)-based biosensor and (ii) an MBs-urease/GO/ nickel oxide (NiO)-based biosensor, respectively. The wireless measurement system work exhibited the feasibility for the remote detection of urea, but it will require refinement and modification to improve stability and precision. The microchannel fluidic system showed the measurement reliability. The sensing properties of urea biosensors at different flow rates were investigated. From the measurement results, the decay of average sensitivity may be attributed to the induced vortex-induced vibrations (VIV) at the high flow rate. In the aspect of wireless monitoring, the average sensitivity of the urea biosensor based on MBs-urease/GO/NiO was 4.780 mV/(mg/dl) and with the linearity of 0.938. In the aspect of measurement under dynamic conditions, the average sensitivity of the urea biosensor based on MBs-urease/GO/NiO were 5.582 mV/(mg/dl) and with the linearity of 0.959. Both measurements performed NiO was better than TiO2 according to the comparisons.

Description: Radio frequency (RF) based wireless power transfer provides an attractive solution to extend the lifetime of power-constrained wireless sensor networks. Through harvesting RF energy from surrounding environments or dedicated energy sources, low-power wireless devices can be self-sustaining and environment-friendly. These features make the RF energy harvesting wireless communication (RF-EHWC) technique attractive to a wide range of applications. The objective of this article is to investigate the latest research activities on the practical RF-EHWC design. The distribution of RF energy in the real environment, the hardware design of RF-EHWC devices and the practical issues in the implementation of RF-EHWC networks are discussed. At the end of this article, we introduce several interesting applications that exploit the RF-EHWC technology to provide smart healthcare services for animals, wirelessly charge the wearable devices, and implement 5G-assisted RF-EHWC.

Description: Complex environments pose great challenges for autonomous mobile robot navigation. In this study, we address the problem of autonomous navigation in 3D environments with staircases and slopes. An integrated system for safe mobile robot navigation in 3D complex environments is presented and both the perception and navigation capabilities are incorporated into the modular and reusable framework. Firstly, to distinguish the slope from the staircase in the environment, the robot builds a 3D OctoMap of the environment with a novel Simultaneously Localization and Mapping (SLAM) framework using the information of wheel odometry, a 2D laser scanner, and an RGB-D camera. Then, we introduce the traversable map, which is generated by the multi-layer 2D maps extracted from the 3D OctoMap. This traversable map serves as the input for autonomous navigation when the robot faces slopes and staircases. Moreover, to enable robust robot navigation in 3D environments, a novel camera re-localization method based on regression forest towards stable 3D localization is incorporated into this framework. In addition, we utilize a variable step size Rapidly-exploring Random Tree (RRT) method which can adjust the exploring step size automatically without tuning this parameter manually according to the environment, so that the navigation efficiency is improved. The experiments are conducted in different kinds of environments and the output results demonstrate that the proposed system enables the robot to navigate efficiently and robustly in complex 3D environments.

Description: In this work, we isolate individual wurtzite InAs nanowires and fabricate electrical contacts at both ends, exploiting the single nanostructures as building blocks to realize two different architectures of conductometric sensors: (a) the nanowire is drop-casted onto—supported by—a SiO2/Si substrate, and (b) the nanowire is suspended at approximately 250 nm from the substrate. We test the source-drain current upon changes in the concentration of humidity, ethanol, and NO2, using synthetic air as a gas carrier, moving a step forward towards mimicking operational environmental conditions. The supported architecture shows higher response in the mid humidity range (50% relative humidity), with shorter response and recovery times and lower detection limit with respect to the suspended nanowire. These experimental pieces of evidence indicate a minor role of the InAs/SiO2 contact area; hence, there is no need for suspended nanostructures to improve the sensing performance. Moreover, the sensing capability of single InAs nanowires for detection of NO2 and ethanol in the ambient atmosphere is reported and discussed.

Description: Displacement is crucial for structural health monitoring, although it is very challenging to measure under field conditions. Most existing displacement measurement methods are costly, labor-intensive, and insufficiently accurate for measuring small dynamic displacements. Computer vision (CV)-based methods incorporate optical devices with advanced image processing algorithms to accurately, cost-effectively, and remotely measure structural displacement with easy installation. However, non-target-based CV methods are still limited by insufficient feature points, incorrect feature point detection, occlusion, and drift induced by tracking error accumulation. This paper presents a reference frame-based Deepflow algorithm integrated with masking and signal filtering for non-target-based displacement measurements. The proposed method allows the user to select points of interest for images with a low gradient for displacement tracking and directly calculate displacement without drift accumulated by measurement error. The proposed method is experimentally validated on a cantilevered beam under ambient and occluded test conditions. The accuracy of the proposed method is compared with that of a reference laser displacement sensor for validation. The significant advantage of the proposed method is its flexibility in extracting structural displacement in any region on structures that do not have distinct natural features.

Description: This paper presents the results of investigations into the effect of freeze–thaw cycling on the failure of fibre-cement boards and on the changes taking place in their structure. Fibre-cement board specimens were subjected to one and ten freeze–thaw cycles and then investigated under three-point bending by means of the acoustic emission method. An artificial neural network was employed to analyse the results yielded by the acoustic emission method. The investigations conclusively proved that freeze–thaw cycling had an effect on the failure of fibre-cement boards, as indicated mainly by the fall in the number of acoustic emission (AE) events recognized as accompanying the breaking of fibres during the three-point bending of the specimens. SEM examinations were carried out to gain better insight into the changes taking place in the structure of the tested boards. Interesting results with significance for building practice were obtained.

Description: This paper presents the forecasting of the wear of working elements in an abrasive soil mass using the theoretical wear model. One of the widely used models providing a basis for the relationships describing wear is the Holm-Archard model. This relationship describes abrasive wear because of the contact between two bodies. The model assumes that the wear of an operating part is directly proportional to the sliding force and distance and inversely proportional to the hardness of the material of the part. To date, the model has not been verified in the wear of a soil mass, which is a discrete friction surface. Four grades of steel resistant to abrasive wear, intended for the manufacturing of operating parts exposed to wear within a soil mass, Hardox 500, XAR 600, TBL Plus and B27, were subjected to testing. TBL Plus steel was characterised by the smallest wear irrespective of the soil type. In turn, the highest values of the wear were noted in the light soil for Hardox 500, in the medium soil for XAR 600, while in the heavy soil for B27. Based on the obtained results, a high correlation coefficient was noted, with the highest values obtained for light and heavy soils.

Description: The genus Yersinia contains three well-recognized human pathogens, including Y. enterocolitica, Y. pestis, and Y. pseudotuberculosis. Various domesticated and wild animals carry Yersinia in their intestines. Spread to individuals arises from eating food or water contaminated by infected human or animal faeces. Interaction with infected pets and domestic stock may also lead to infection. Yersinia is able to multiply at temperatures found in normal refrigerators; hence, a large number of the bacteria may be present if meat is kept without freezing. Yersinia is also rarely transmitted by blood transfusion, because it is able to multiply in stored blood products. Infection with Yersinia can cause yersiniosis, a serious bacterial infection associated with fever, abdominal pain and cramps, diarrhea, joint pain, and symptoms similar to appendicitis in older children and adults. This paper describes a novel immunosensor approach using graphene quantum dots (GQDs) as enzyme mimics in an electrochemical sensor set up to provide an efficient diagnostic method for Y. enterecolitica. The optimum assay conditions were initially determined and the developed immunosensor was subsequently used for the detection of the bacterium in milk and human serum. The GQD-immunosensor enabled the quantification of Y. enterocolitica in a wide concentration range with a high sensitivity (LODmilk = 5 cfu mL−1 and LODserum = 30 cfu mL−1) and specificity. The developed method can be used for any pathogenic bacteria detection for clinical and food samples without pre-sample treatment. Offering a very rapid, specific and sensitive detection with a label-free system, the GQD-based immunosensor can be coupled with many electrochemical biosensors.

Description: In this paper, a 2-node beam element is developed based on Quasi-3D beam theory and mixed formulation for static bending of functionally graded (FG) beams. The transverse shear strains and stresses of the proposed beam element are parabolic distributions through the thickness of the beam and the transverse shear stresses on the top and bottom surfaces of the beam vanish. The proposed beam element is free of shear-looking without selective or reduced integration. The material properties of the functionally graded beam are assumed to vary according to the power-law index of the volume fraction of the constituents through the thickness of the beam. The numerical results of this study are compared with published results to illustrate the accuracy and convenience rate of the new beam element. The influence of some parametrics on the bending behavior of FGM beams is investigated.

Description: The high-temperature deformation behavior of Q345 steel is detected by a Gleeble-3800 thermal simulator. The Arrhenius constitutive equation for high-temperature flow stress and the dynamic recrystallization model are constructed. With the secondary development technology, customized modifications are made on existing Deform-3D software. The constructed constitutive model and dynamic recrystallization model are embedded into Deform-3D to realize the secondary development of Deform-3D. The grain size and volume percentage distribution of dynamic recrystallization are obtained by simulating the shear connection process at high temperature and high speed. The results show that the constitutive equation and the dynamic recrystallization model constructed in this paper can be used to predict the evolution of the microstructure. The difference between the prediction results and the experimental data is about 3%. The accuracy of Arrhenius constitutive equation, dynamic recrystallization model and the feasibility of software secondary development are verified.

Description: Bio-inspired functionally graded cellular materials (FGCM) have improved performance in energy absorption compared with a uniform cellular material (UCM). In this work, sheet-based and strut-based gyroid cellular structures with graded densities are designed and manufactured by stereo-lithography (SLA). For comparison, uniform structures are also designed and manufactured, and the graded structures are generated with different gradients. The mechanical behaviors of these structures under compressive loads are investigated. Furthermore, the anisotropy and effective elastic modulus of sheet-based and strut-based unit gyroid cellular structures are estimated by a numerical homogenization method. On the one hand, it is found from the numerical results that the sheet-based gyroid tends to be isotropic, and the elastic modulus of sheet-based gyroid is larger than the strut-based gyroid at the same volume fraction. On the other hand, the graded cellular structure has novel deformation and mechanical behavior. The uniform structure exhibits overall deformation and collapse behavior, whereas the graded cellular structure shows layer-by-layer deformation and collapse behavior. Furthermore, the uniform sheet-based gyroid is not only stiffer but also better in energy absorption capacity than the uniform strut-based gyroid structure. Moreover, the graded cellular structures have better energy absorption capacity than the uniform structures. These significant findings indicate that sheet-based gyroid cellular structure with graded densities have potential applications in various industrial applications, such as in crashworthiness.

Description: Convenient indoor positioning has become an urgent need due to the improvement it offers to quality of life, which inspires researchers to focus on device-free indoor location. In areas covered with Wi-Fi, people in different locations will to varying degrees have an impact on the transmission of channel state information (CSI) of Wi-Fi signals. Because space is divided into several small regions, the idea of classification is used to locate. Therefore, a novel localization algorithm is put forward in this paper based on Deep Neural Networks (DNN) and a multi-model integration strategy. The approach consists of three stages. First, the local outlier factor (LOF), the anomaly detection algorithm, is used to correct the abnormal data. Second, in the training phase, 3 DNN models are trained to classify the region fingerprints by taking advantage of the processed CSI data from 3 antennas. Third, in the testing phase, a model fusion method named group method of data handling (GMDH) is adopted to integrate 3 predicted results of multiple models and give the final position result. The test-bed experiment was conducted in an empty corridor, and final positioning accuracy reached at least 97%.

Description: To address the increasing air pollution caused by vehicle exhaust, environment-friendly pavement materials that possesses exhaust-purifying properties were prepared using common cement concrete and porous cement concrete as the base of photocatalyst nano-titanium dioxide (TiO2), respectively. Firstly, Fe3+-doped TiO2 powder was prepared by applying planetary high-energy ball milling in order to improve the efficiency of the semiconductor photocatalyst for degrading vehicle exhausts. Two nano-TiO2, namely the original and modified nanomaterials, were adopted to produce the photocatalytic cement concretes subsequently. The physicochemical properties of the modified powder, as well as the mechanical and photocatalytic properties of TiO2-modified concrete, were characterized using a suite of complementary techniques, including X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS), compressive strength and degradation efficiency tests. The results show that the ball milling method not only successfully doped Fe3+ into catalysts but also caused significant changes in: (1) decreased particle sizes, (2) more amorphous morphology, (3) decreased percentage of the most thermodynamically stable crystal facet, and (4) increased percentage of other high gas sensing crystal facets. Both the original and modified nano-TiO2 can improve the concrete strength while the strengthening effect of modified nanomaterials is superior. It is pronounced that the photocatalytic property of the modified nano-TiO2 is much better than that of the original nano particles, and the degradation rate of porous concrete is also better than common concrete when exposed to the same photocatalyst content. In a comprehensive consideration of both mechanical performance and degradation efficiency, the recommended optimum dosage of TiO2 is 3% to 4% for exhaust-purifying concrete.

Description: An experimental study was conducted to investigate the effect ofnano-SiO2 and steel fiber content on the durability of concrete. Five different dosages of nano-SiO2 particles and five volume dosages of steel fiber were used. The durability of concretes includes permeability resistance, cracking resistance, carbonation resistance, and freezing-thawing resistance, and these were evaluated by the water permeation depth, number of cracks, total cracking area per unit area of the specimens, carbonation depth of the specimens, and the relative dynamic elastic modulus of the specimens after freezing-thawing cycles, respectively. The results indicate that the addition of nano-SiO2 particles significantly improves the durability of concrete when the content of nano-SiO2 is limited within a certain range. With the increase of nano-SiO2 content, the durability of concrete first increases and then decreases. An excessive number of nano-SiO2 particles could have an adverse effect on the durability of the concrete. The addition of the correct amount of steel fibers improves the carbonation resistance of concrete containing nano-particles, but excessive steel fiber reduces the carbonation resistance. Moreover, the addition of steel fibers reduces the permeability resistance of concrete containing nano-particles. The incorporation of steel fiber enhanced the freezing-thawing resistance and cracking resistance of concrete containing nano-particles. With increasing steel fiber content, the freezing-thawing resistance of the concrete containing nano-particles increases, and the cracking resistance of the concrete decreases gradually.

Description: This work deals with the feasibility and reliability about the use of shape memory alloys (SMAs) as mechanical actuators for solar sail self-deployment instead of heavy and bulky mechanical booms. Solar sails exploit radiation pressure a as propulsion system for the exploration of the solar system. Sunlight is used to propel space vehicles by reflecting solar photons from a large and light-weight material, so that no propellant is required for primary propulsion. In this work, different small-scale solar sail prototypes (SSP) were studied, manufactured, and tested for bending and in three different environmental conditions to simulate as much as possible the real operating conditions where the solar sails work. Kapton is the most suitable material for sail production and, in the space missions till now, activated booms as deployment systems have always been used. In the present work for the activation of the SMA elements some visible lamps have been employed to simulate the solar radiation and time-temperature diagrams have been acquired for different sail geometries and environmental conditions. Heat transfer mechanisms have been discussed and the minimum distance from the sun allowing the full self-deployment of the sail have also been calculated.

Description: Due to the recent rise in the use of lower-limb exoskeletons as an alternative for gait rehabilitation, gait phase detection has become an increasingly important feature in the control of these devices. In addition, highly functional, low-cost recovery devices are needed in developing countries, since limited budgets are allocated specifically for biomedical advances. To achieve this goal, this paper presents two gait phase partitioning algorithms that use motion data from a single inertial measurement unit (IMU) placed on the foot instep. For these data, sagittal angular velocity and linear acceleration signals were extracted from nine healthy subjects and nine pathological subjects. Pressure patterns from force sensitive resistors (FSR) instrumented on a custom insole were used as reference values. The performance of a threshold-based (TB) algorithm and a hidden Markov model (HMM) based algorithm, trained by means of subject-specific and standardized parameters approaches, were compared during treadmill walking tasks in terms of timing errors and the goodness index. The findings indicate that HMM outperforms TB for this hardware configuration. In addition, the HMM-based classifier trained by an intra-subject approach showed excellent reliability for the evaluation of mean time, i.e., its intra-class correlation coefficient (ICC) was greater than 0.75 . In conclusion, the HMM-based method proposed here can be implemented for gait phase recognition, such as to evaluate gait variability in patients and to control robotic orthoses for lower-limb rehabilitation.

Description: Traditional compensation methods based on temperature-related parameters are not effective for complex total reflection prism laser gyro (TRPLG) bias variation. Because the high frequency oscillator voltage (UHFO) fundamentally affects the TRPLG bias, and the UHFO has a stronger correlation with the TRPLG bias when compared with the temperature, an introduction of UHFO into the TRPLG bias compensation can be evaluated. In consideration of the limitations of least squares (LS) regression and multivariate stepwise regression, we proposed a compensation method for TRPLG bias based on iterative re-weighted least squares support vector machine (IR-LSSVM) and compared with LS regression, stepwise regression, and LSSVM algorithm in large temperature cycling experiments. When temperature, slope of temperature variation, and UHFO were selected as inputs, the IR-LSSVM based on myriad weight function improved the TRPLG bias stability by 61.19% to reach the maximum and eliminated TRPLG bias drift. In addition, the UHFO proved to be the most important parameter in the process of TRPLG bias compensation; accordingly, it can alleviate the shortcomings of traditional compensation based on temperature-related parameters and can greatly improve the TRPLG bias stability.

Description: A convolutional neural network (CNN) algorithm was developed to retrieve the land surface temperature (LST) from Advanced Microwave Scanning Radiometer 2 (AMSR2) data in China. Reference data were selected using the Moderate Resolution Imaging Spectroradiometer (MODIS) LST product to overcome the problem related to the need for synchronous ground observation data. The AMSR2 brightness temperature (TB) data and MODIS surface temperature data were randomly divided into training and test datasets, and a CNN was constructed to simulate passive microwave radiation transmission to invert the surface temperature. The twelve V/H channel combinations (7.3, 10.65, 18.7, 23.8, 36.5, 89 GHz) resulted in the most stable and accurate CNN retrieval model. Vertical polarizations performed better than horizontal polarizations; however, because CNNs rely heavily on large amounts of data, the combination of vertical and horizontal polarizations performed better than a single polarization. The retrievals in different regions indicated that the CNN accuracy was highest over large bare land areas. A comparison of the retrieval results with ground measurement data from meteorological stations yielded R2 = 0.987, RMSE = 2.69 K, and an average relative error of 2.57 K, which indicated that the accuracy of the CNN LST retrieval algorithm was high and the retrieval results can be applied to long-term LST sequence analysis in China.

Description: The flux pinning properties of reacted-and-pressed Ba0.6K0.4Fe2As2 powder were measured using magnetic hysteresis loops in the temperature range 20 K ≤ T ≤ 35 K. The scaling analysis of the flux pinning forces ( F p = j c × B , with j c denoting the critical current density) following the Dew-Hughes model reveals a dominant flux pinning provided by normal-conducting point defects ( δ l -pinning) with only small irreversibility fields, H irr , ranging between 0.5 T (35 K) and 16 T (20 K). Kramer plots demonstrate a linear behavior above an applied field of 0.6 T. The samples were further characterized by electron backscatter diffraction (EBSD) analysis to elucidate the origin of the flux pinning. We compare our data with results of Weiss et al. (bulks) and Yao et al. (tapes), revealing that the dominant flux pinning in the samples for applications is provided mainly by grain boundary pinning, created by the densification procedures and the mechanical deformation applied.

Description: This work investigates and improves the thermal dynamics of autoclaved aerated concrete (AAC) wall containing phase change material (PCM). The PCM is paraffin wax loaded into conical holes drilled into the AAC. Filled AAC with three different numbers of PCM-filled holes (2, 3, and 4 conical holes, which are designated as AAC-2H, AAC-3H, and AAC-4H, respectively) as well as the unfilled original AAC were both tested under two different conditions: indoors (with controlled temperature) and outdoors (with actual weather). For the indoor experiment, a heater was used as a thermal source and set up to maintain the testing temperature at one of three levels: 40 °C, 50 °C, or 60 °C. The wall temperature was then measured on the surface with each horizontally-positioned wall as well as four different positions at various depths below the surface of the wall. It was found that AAC-4H was the optimum condition, which can produce outstandingly a time lag of approximately 27%, reduce a decrement factor of approximately 31%, and also decrease the room temperature. This reached approximately 9% when compared with that of ordinary AAC at the controlled testing temperature of 60 °C. All samples were further tested in actual weather to confirm the thermal performances of AAC-4H. Thermal effectiveness of AAC-4H was improved by extending approximately a 14.3% time lag, which reduces approximately a 4.3% decrement factor and achieving approximately 5% lower room temperature when compared with ordinary AAC.

Description: This paper investigates mobile relaying in wireless powered communication networks (WPCN), where an unmanned aerial vehicle (UAV) is employed to help information delivery from multiple sources to destination with communication channels severely blocked. The sources are low-power without energy supply. To support information transmission, the UAV acts as a hybrid access point (AP) to provide wireless power transfer (WPT) and information reception for sources. We set the issue of system throughput maximization as the optimization problem. On the one hand, the system is subject to the information causality constraint due to the dependent processes of information reception and transmission for the UAV. On the other hand, the sources are constrained by a so-called neutrality constraints due to the dependent processes of energy harvesting and energy consumption. In addition, we take account of the access delay issue of all ground nodes. Specifically, two paradigms of delay-tolerant case and delay-sensitive case are presented. However, the formulated problem including optimizations for time slot scheduling, power allocation and UAV trajectory is non-convex and thus is difficult to obtain its optimal solution. To tackle this problem, we apply the successive convex approximation (SCA) technique and propose an iterative algorithm by which a suboptimal solution can be achieved. Simulation results validate our proposed design, and show that the obtained suboptimal solution is high-quality, as compared to benchmark scheme.

Description: In this paper, the hot deformability and mechanical properties of a novel Mn- and Nb- containing TiAl alloy were studied systematically with the use of isothermal compression experiments. The results show that the alloy has low deformation resistance and a low activation energy (392 KJ/mol), suggesting that the alloy has good hot deformability. A processing map was established, which shows that the present alloy has a smaller instability region and wider hot working window compared with other TiAl alloys. Microstructural observation shows that the initial lamellae completely transformed into fine equiaxial γ grains when the alloy was compressed at 1200 °C/0.01 s−1, which corresponds to the optimum deformation condition. Based on the above results, an intact TiAl billet was successfully fabricated by one-step large deformation using a four-column hydraulic machine. The microstructure of the billet is almost completely composed of recrystallized γ grains with large angle boundaries. Tensile testing shows the billet exhibits high tensile strength (780 MPa) and high elongation (1.44%) simultaneously, which benefits from fine γ grains with an average size of 4.9 μm. The ductile–brittle transition temperature is between 750–800 °C.

Description: A piezoelectric fiber patch (PFP) is a transducer type that is suitable for guided-wave-based structural health monitoring (SHM) due to its light, thin, and flexible characteristics. In our previous work, a PFP-based transducer design for selective excitation of the zero-order shear horizontal wave mode (SH0) was introduced (shear horizontal PFP (SHPFP)). In this work, two modified SH0 wave PFP transducer designs are proposed: the rounded corner design and the dual design. The degree of improvement is determined by a numerical simulation and the dual design—the design with the most promise—is experimentally realized. Laser Vibrometry measured the generated wave field, confirming the results from the simulation. The new designs can generate an almost pure SH0 wave. The dual design has a very strong directivity that is useful for several guided-wave-based SHM applications. The conclusions on the design’s properties as a transmitter are also valid for its properties as a sensor due to the reciprocity of piezoelectric transducers.

Description: Nanoporous metals represent a fascinating class of materials. They consist of a bi-continuous three-dimensional network of randomly intersecting pores and ligaments where the ligaments form the skeleton of the structure. The open-pore structure allows for applying a thin electrolytic coating on the ligaments. In this paper, we will investigate the stiffening effect of a polymer coating numerically. Since the coating adds an additional difficulty for the discretization of the microstructure by finite elements, we apply the finite cell method. This allows for deriving a mesh in a fully automatic fashion from the high resolution 3D voxel model stemming from the 3D focused ion beam-scanning electron microscope tomography data of nanoporous gold. By manipulating the voxel model in a straightforward way, we add a thin polymer layer of homogeneous thickness numerically and study its effect on the macroscopic elastic properties systematically. In order to lower the influence of the boundary conditions on the results, the window method, which is known from homogenization procedures, is applied. In the second part of the paper, we fill the gap between numerical simulations and experimental investigations and determine real material properties of an electrolytic applied polypyrrole coating by inverse computations. The simulations provide an estimate for the mechanical properties of the ligaments and the polymeric coating and are in accordance with experimental data.

Description: In order to better provide a theoretical basis for the machining of luxury vinyl tiles, a helical milling experiment was conducted by using diamond cutting tools, and special attention was given to the trends of cutting force and surface roughness in respect to tool geometry and cutting parameters. The results showed that the resultant force was negatively correlated to the helix angle and cutting speed, but positively correlated with the cutting depth. Then, that the surface roughness increased with a decrease of the helix angle and an increase of cutting depth, while as cutting speed raised, the surface roughness first declined and then increased. Thirdly, the cutting depth was shown to have the greatest influence on both cutting force and surface roughness, followed by helix angle and cutting speed. Fourth, the contribution of cutting depth only was significant to cutting force, while both the helix angle and cutting speed had insignificant influence on the cutting force and surface roughness. Finally, the optimal cutting conditions were proposed for industrial production, in which the helix angle, cutting speed and cutting depth were 70°, 2200 m/min and 0.5 mm, respectively.

Description: A Ru-doped phospho-tungstic Wells–Dawson polyoxometalate (POM) was successfully applied as homogeneous catalyst for glycerol hydrogenolysis in aqueous media. The synthesized compound showed superior catalytic activity compared to classical homogeneous/heterogeneous Ru catalysts like RuCl3 and Ru/C under identical reaction conditions, whereas the analogous POM doped with Pd or Pt proved far less activity. Detailed characterization of the POMs was performed using 31P-NMR to identify characteristic phosphorous peaks of the heteroatoms, infrared spectroscopy (ATR-FTIR) to confirm characteristic P-O and W-O-W vibrations, powder XRD for comparison of crystal structures, and X-ray fluorescence (XRF) and inductive-coupled plasma (ICP) analysis to determine elemental composition. Variation of the reaction parameters for the best performing Ru-doped POM catalyst showed that substrate concentration played an important role for both product selectivity and conversion. Moreover, medium hydrogen pressure and high stirring speed were key factors to obtain highly selective conversion of glycerol to 1,2-propanediol.

Description: Bone defects repair represents a public and urgent problem in clinical practice, in fact, every year, more than two million patients required new treatments for bone injuries. Today a complete vascularization is strategic in bone formation, representing a new frontier for clinical application. Aim of this research has been developed a three-dimensional (3D) coculture platform using a bovine pericardium collagen membrane (BioR) loaded with human periodontal ligament stem cells (hPDLSCs) and endothelial differentiated cells from hPDLSCs (E-hPDLSCs) able to undergo toward osteoangiogenesis differentiation process. First, we have characterized at confocal laser scanning microscopy (CLSM) level the E-hPDLSCs phenotype profile, through CD31 and CD34 markers expression and the ability to tube vessel formation. Real Time-Polimerase Chain Reaction (RT-PCR) and western blotting analyses revealed the upregulation of Runt-related transcription factor 2 (RUNX2), Collagen 1A1 (COL1A1), Vascular Endothelial Growth Factor-A (VEGF-A) genes and proteins in the living construct composed by hPDLSCs + E-hPDSCs/BioR. Human PDLSCs + E-hPDLSCs/BioR construct showed also an enhacement of de novo synthesis of osteocalcin. Given that, the extracellular-signal-regulated kinase (ERK)/mitogen activated protein kinase (MAPK) transduction signaling was involved in the osteogenesis and angiogenesis process, the ERK1/2 protein level at biochemical level, in our experimental model, has been investigated. Our results evidenced an upregulation of ERK1/2 proteins level born in the living construct. In conclusion, we believe that the use of the hPDLSCs and E-hPDLSCs coculture togheter with BioR as substrate, could represent an efficient model able to activate through ERK1/2 signaling pathway the osteoangiogenesis process, and then representing a new potential engineered platform for surgeons during the repair and the healing of bone defects.

Description: The instability of diafiltration is a widespread problem in the practical application of microporous ceramic filtration membranes. In this paper, a series of microporous ceramic filter membranes were prepared using inexpensive standard sand and river sand as matrix materials. Semi-empirical formula for the effective permeability radius of ceramic membranes with respect to time was established from analysis of the response mechanism between water flow and material properties. Finally, on the basis of theoretical analysis, some measures were proposed to improve permeate flux. The experimental results showed that during the initial stage of filtration, the microporous ceramic filter membrane had a large change in permeate flux, and during the late stage of filtration, permeate flux tended to be stable. Over time, open porosity and closed porosity changed the actual seepage area of the ceramic membrane, and this affected the stability of permeate flux and final stable permeate flux. The roughness of the inner wall of microporous ceramic pores affected the hydraulic loss coefficient, and this controlled the outflow process. Trace elements that were rich in sand produced a large amount of glass phase after sintering. The glass phase was rich in polar groups and formed a temporary hydrogen bond with the small flow of water molecules. It led to an increase in viscous resistance effect of the side wall along the water flow and the extent of the permeate flux of the ceramic membrane changed with time.

Description: Smart cities can effectively improve the quality of urban life. Intelligent Transportation System (ITS) is an important part of smart cities. The accurate and real-time prediction of traffic flow plays an important role in ITSs. To improve the prediction accuracy, we propose a novel traffic flow prediction method, called AutoEncoder Long Short-Term Memory (AE-LSTM) prediction method. In our method, the AutoEncoder is used to obtain the internal relationship of traffic flow by extracting the characteristics of upstream and downstream traffic flow data. Moreover, the Long Short-Term Memory (LSTM) network utilizes the acquired characteristic data and the historical data to predict complex linear traffic flow data. The experimental results show that the AE-LSTM method had higher prediction accuracy. Specifically, the Mean Relative Error (MRE) of the AE-LSTM was reduced by 0.01 compared with the previous prediction methods. In addition, AE-LSTM method also had good stability. For different stations and different dates, the prediction error and fluctuation of the AE-LSTM method was small. Furthermore, the average MRE of AE-LSTM prediction results was 0.06 for six different days.

Description: Radio frequency identification is one of the key techniques for Internet of Things, which has been widely adopted in many applications for identification. However, there exist various security and privacy issues in radio frequency identification (RFID) systems. Particularly, one of the most serious threats is to clone tags for the goal of counterfeiting goods, which causes great loss and danger to customers. To solve these issues, lots of authentication protocols are proposed based on physical unclonable functions that can ensure an anti-counterfeiting feature. However, most of the existing schemes require secret parameters to be stored in tags, which are vulnerable to physical attacks that can further lead to the breach of forward secrecy. Furthermore, as far as we know, none of the existing schemes are able to solve the security and privacy problems with good scalability. Since many existing schemes rely on exhaustive searches of the backend server to validate a tag and they are not scalable for applications with a large scale database. Hence, in this paper, we propose a lightweight RFID mutual authentication protocol with physically unclonable functions (PUFs). The performance analysis shows that our proposed scheme can ensure security and privacy efficiently in a scalable way.

Description: Sensors provide the foundation of many smart applications and cyber–physical systems by measuring and processing information upon which applications can make intelligent decisions or inform their users. Inertial measurement unit (IMU) sensors—and accelerometers and gyroscopes in particular—are readily available on contemporary smartphones and wearable devices. They have been widely adopted in the area of activity recognition, with fall detection and step counting applications being prominent examples in this field. However, these sensors may also incidentally reveal sensitive information in a way that is not easily envisioned upfront by developers. Far worse, the leakage of sensitive information to third parties, such as recommender systems or targeted advertising applications, may cause privacy concerns for unsuspecting end-users. In this paper, we explore the elicitation of age and gender information from gait traces obtained from IMU sensors, and systematically compare different feature engineering and machine learning algorithms, including both traditional and deep learning methods. We describe in detail the prediction methods that our team used in the OU-ISIR Wearable Sensor-based Gait Challenge: Age and Gender (GAG 2019) at the 12th IAPR International Conference on Biometrics. In these two competitions, our team obtained the best solutions amongst all international participants, and this for both the age and gender predictions. Our research shows that it is feasible to predict age and gender with a reasonable accuracy on gait traces of just a few seconds. Furthermore, it illustrates the need to put in place adequate measures in order to mitigate unintended information leakage by abusing sensors as an unanticipated side channel for sensitive information or private traits.

Description: Three-dimensional finite element-based numerical analysis of Vickers indenter hardness test was conducted to investigate the effect of frictional conditions and material anisotropy on indentation results of deep drawing quality steel sheets. The strain hardening properties and Lankford’s coefficient were determined through the uniaxial tensile tests. The numerical computations were carried out using ABAQUS nonlinear finite element (FE) analysis software. Numerical simulations taken into account anisotropy of material described by Hill (1948) yield a criterion. The stress and strain distributions and loading–unloading characteristics were considered to study the response of the material. It was found that the hardness values seemed to be influenced by the value of the friction coefficient due to the pile-up phenomenon observed. The increasing of the friction coefficient led to a decrease of the pile-up value. Moreover, the width of the pile-ups differed from each other in the two perpendicular directions of measurement. Frictional conditions did not significantly affect the maximum force and the character of load–displacement curves. Frictional regime between the indenter and workpiece caused that the region of maximum residual stresses to be located in the subsurface.

Description: In rehabilitation procedures related to the lower limbs, gait monitoring is an important source of information for the therapist. However, many of the approaches proposed in the literature require the use of uncomfortable and invasive devices. In this work, an instrumented tip is developed and detailed, which can be connected to any crutch. The instrumented tip provides objective data of the crutch motion, which, combined with patient movement data, might be used to monitor the daily activities or assess the recovery status of the patient. For that purpose, the tip integrates a two-axis inclinometer, a tri-axial gyroscope, and a force sensor to measure the force exerted on the crutch. In addition, a novel algorithm to estimate the pitch angle of the crutch is developed. The proposed approach is tested experimentally, obtaining acceptable accuracies and demonstrating the validity of the proposed lightweight, portable solution for gait monitoring.

Description: The distribution of total electron content (TEC) in the ionosphere is irregular and complex, and it is hard to model accurately. The polynomial (POLY) model is used extensively for regional ionosphere modeling in two-dimensional space. However, in the active period of the ionosphere, the POLY model is difficult to reflect the distribution and variation of TEC. Aiming at the limitation of the regional POLY model, this paper proposes a new ionosphere modeling method with combining the support vector machine (SVM) regression model and the POLY model. Firstly, the POLY model is established using observations of regional continuously operating reference stations (CORS). Then the SVM regression model is trained to compensate the model error of POLY, and the TEC SVM-P model is obtained by the combination of the POLY and the SVM. The fitting accuracies of the models are verified with the root mean square errors (RMSEs) and static single-frequency precise point positioning (PPP) experiments. The results show that the RMSE of the SVM-P is 0.980 TECU (TEC unit), which produces an improvement of 17.3% compared with the POLY model (1.185 TECU). Using SVM-P models, the positioning accuracies of single-frequency PPP are improved over 40% compared with those using POLY models. The SVM-P is also compared with the back-propagation neural network combined with POLY (BPNN-P), and its performance is also better than BPNN-P (1.070 TECU).

Description: In the last years, several attempts to combine the Internet of Things (IoT) and social networking have been made. In the meantime, things involved in IoT are becoming increasingly sophisticated and intelligent, showing a behavior that tends to look like the one of users in social networks. Therefore, it is not out of place to talk about profiles of things and about information and topics exchanged among them. In such a context, constructing topic-driven virtual communities starting from the real ones operating in a Multi-IoT scenario is an extremely challenging issue. This paper aims at providing some contributions in this setting. First of all, it presents the concept of profile of a thing. Then, it introduces the concept of topic-guided virtual IoT. Finally, it illustrates two approaches (one supervised and one unsupervised) to constructing topic-guided virtual IoTs in a Multi-IoT scenario.

Description: As an important development direction of star sensor technology, the All-Time star sensor technology can expand the application of star sensors to flight platforms inside the atmosphere. Due to intense atmospheric background radiation during the daytime, the commonly used star sensors operating in the visible wavelength range are significantly limited in their ability to detect stars, and hence the All-Time star sensor technology which is based on the shortwave infrared (SWIR) imaging system has become an effective research direction. All-Time star sensor detection capability is significantly affected by observation conditions and, therefore, an optimized selection of optical parameters, which mainly includes the field of view (FOV) and the detection wavelength band, can effectively improve the detection performance of All-Time star sensors under harsh observation conditions. This paper uses the model simulation method to analyze and optimize the optical parameters under various observation conditions in a high-altitude environment. A main parameter among those discussed is the analysis of detection band optimization based on the SWIR band. Due to the huge cost constraints of high-altitude experiments, we conducted experiments near the ground to verify the effectiveness of the detection band selection and the correctness of the SWIR star sensor detection model, which thereby proved that the optimization of the optical parameters for high altitudes was effective and could be used as a reference.

Description: Device-free human gesture recognition (HGR) using commercial off the shelf (COTS) Wi-Fi devices has gained attention with recent advances in wireless technology. HGR recognizes the human activity performed, by capturing the reflections of Wi-Fi signals from moving humans and storing them as raw channel state information (CSI) traces. Existing work on HGR applies noise reduction and transformation to pre-process the raw CSI traces. However, these methods fail to capture the non-Gaussian information in the raw CSI data due to its limitation to deal with linear signal representation alone. The proposed higher order statistics-based recognition (HOS-Re) model extracts higher order statistical (HOS) features from raw CSI traces and selects a robust feature subset for the recognition task. HOS-Re addresses the limitations in the existing methods, by extracting third order cumulant features that maximizes the recognition accuracy. Subsequently, feature selection methods derived from information theory construct a robust and highly informative feature subset, fed as input to the multilevel support vector machine (SVM) classifier in order to measure the performance. The proposed methodology is validated using a public database SignFi, consisting of 276 gestures with 8280 gesture instances, out of which 5520 are from the laboratory and 2760 from the home environment using a 10 × 5 cross-validation. HOS-Re achieved an average recognition accuracy of 97.84%, 98.26% and 96.34% for the lab, home and lab + home environment respectively. The average recognition accuracy for 150 sign gestures with 7500 instances, collected from five different users was 96.23% in the laboratory environment.

Description: Local administrations demand real-time and continuous pollution monitoring in sewer networks. Spectroscopy is a non-destructive technique that can be used to continuously monitor quality in sewers. Covering a wide range of wavelengths can be useful for improving pollution characterization in wastewater. Cost-effective and in-sewer spectrophotometers would contribute to accomplishing discharge requirements. Nevertheless, most available spectrometers are based on incandescent lamps, which makes it unfeasible to place them in a sewerage network for real-time monitoring. This research work shows an innovative calibration procedure that allows (Light-Emitting Diode) LED technology to be used as a replacement for traditional incandescent lamps in the development of spectrophotometry equipment. This involves firstly obtaining transmittance values similar to those provided by incandescent lamps, without using any optical components. Secondly, this calibration process enables an increase in the range of wavelengths available (working range) through a better use of the LED’s spectral width, resulting in a significant reduction in the number of LEDs required. Thirdly, this method allows important reductions in costs, dimensions and consumptions to be achieved, making its implementation in a wide variety of environments possible.

Description: Calcium sulfoaluminate (CSA) cement has recently gained increased attention due to its lower amount of CO2 emissions, as compared to that of the ordinary Portland cement (OPC). This paper evaluates the impact of different types of fibers on the engineering features of CSA-based concretes at different water-cement ratios of 0.35 and 0.28. In this study, metallic fibers including double hooked-end steel fibers and hooked-end steel fibers, and non-metallic fibers (i.e., polyvinyl alcohol (PVA) fibers) were utilized at fiber content of 1%. The mechanical properties of concretes were assessed at different curing ages. Dimensional stability of the concrete mixes was also examined. The morphology of the fractured specimens was studied by using the SEM method. The results indicate that the engineering properties of concrete were improved by introducing fibers to the concrete, irrespective of fiber type. The results show that DHE steel fiber has an important effect on the flexural performance of CSA cement-based concretes and results in deflection-hardening behavior. It was observed that fibers and particularly PVA fibers cause a decrease in shrinkage deformation. Microstructure tests demonstrate that prismatic ettringite is the main hydration product of CSA cement-based concrete. The SEM observation also confirms that the inclusion of CSA cement in concrete improves the cohesiveness between the fibers and cement matrix.

Description: Cloud providers such as Amazon Web Services (AWS) stand out as useful platforms to teach distributed computing concepts as well as the development of Cloud-native scalable application architectures on real-world infrastructures. Instructors can benefit from high-level tools to track the progress of students during their learning paths on the Cloud, and this information can be disclosed via educational dashboards for students to understand their progress through the practical activities. To this aim, this paper introduces CloudTrail-Tracker, an open-source platform to obtain enhanced usage analytics from a shared AWS account. The tool provides the instructor with a visual dashboard that depicts the aggregated usage of resources by all the students during a certain time frame and the specific use of AWS for a specific student. To facilitate self-regulation of students, the dashboard also depicts the percentage of progress for each lab session and the pending actions by the student. The dashboard has been integrated in four Cloud subjects that use different learning methodologies (from face-to-face to online learning) and the students positively highlight the usefulness of the tool for Cloud instruction in AWS. This automated procurement of evidences of student activity on the Cloud results in close to real-time learning analytics useful both for semi-automated assessment and student self-awareness of their own training progress.

Description: As an intrinsic property, elasticity of soft material is affected significantly by the externally applied alternating magnetic field. Magnetostrictive properties of the grain-oriented (GO) silicon steel under DC-biased and multisinusoidal magnetizations are measured by using a laser-based measuring system. Magnetostriction curves of the GO silicon steel sheet under different magnetizations are obtained and the influence of frequency and DC bias on the magnetostrictive property is observed and analyzed based on the measured data. In addition, the spectrum of magnetostriction under harmonic magnetization is obtained, and the acoustic noise level of the GO silicon steel sheet represented by the A-weighted decibel value caused by magnetostriction is measured under DC-biased and multisinusoidal magnetizations. The measurement results are applied to the simulation of the three-limb laminated core model, and the effects of DC bias and harmonics on magnetic flux density and displacement are analyzed.

Description: The detection of cable corrosion is of great significance to the evaluation of cable safety performance. Based on the principle of spontaneous magnetic flux leakage (SMFL), a new method for predicting the corrosion width of cables is proposed. In this paper, in order to quantify the width of corrosion, the parameter about intersecting point distance between curves of magnetic flux component of x direction at different lift off heights (Dx) is proposed by establishing the theoretical model of the magnetic dipole of the rectangular corrosion defect. The MATLAB software was used to analyze the influencing factors of Dx. The results indicate that there exists an obvious linear relationship between the Dx and the y (lift off height), and the Dx–y curves converge to near the true corrosion width when y = 0. The 1/4 and 3/4 quantiles of the Dx–y image were used for linear fitting, which the intercept of the fitting equation was used to represent the predicted corrosion width. After the experimental study on the corrosion width detection for the parallel steel wire and steel strand, it is found that this method can effectively improve the detection accuracy, which plays an important role in cable safety assessment.

Description: This paper presents the concept of repairing the stand of a motorbike speedway stadium. The synchronized dancing of fans cheering during a meeting brought the stand into excessive resonance. The main goal of this research was to propose a method for the structural tuning of stadium stands. Non-destructive testing by vibration methods was conducted on a selected stand segment, the structure of which recurred on the remaining stadium segments. Through experiments, we determined the vibration forms throughout the stand, taking into account the dynamic impact of fans. Numerical analyses were performed on the 3-D finite element method (FEM) stadium model to identify the dynamic jump load function. The results obtained on the basis of sensitivity tests using the finite element method allowed the tuning of the stadium structure to successfully meet the requirements of the serviceability limit state.

Description: Abstract In this work, cobalt phosphide (CoP) nanoparticles were successfully decorated on an ultrathin g‐C3N4 nanosheet photocatalysts by in situ chemical deposition. The built‐in electric field formed by heterojunction interface of the CoP/g‐C3N4 composite semiconductor can accelerate the transmission and separation of photogenerated charge‐hole pairs and effectively improve the photocatalytic performance. TEM, HRTEM, XPS, and SPV analysis showed that CoP/g‐C3N4 formed a stable heterogeneous interface and effectively enhanced photogenerated electron‐hole separation. UV‐vis DRS analysis showed that the composite had enhanced visible light absorption than pure g‐C3N4 and was a visible light driven photocatalyst. In this process, NaH2PO2 and CoCl2 are used as the source of P and Co, and typical preparation of CoP can be completed within 3 hours. Under visible light irradiation, the optimal H2 evolution rate of 3.0 mol% CoP/g‐C3N4 is about 15.1 μmol h−1. The photocatalytic activity and stability of the CoP/g‐C3N4 materials were evaluated by photocatalytic decomposition of water. The intrinsic relationship between the microstructure of the composite catalyst and the photocatalytic performance was analyzed to reveal the photocatalytic reaction mechanism.

Description: Abstract High volume fraction SiC nanowires‐reinforced SiC composites (SiCNWs/SiC) were prepared by hybrid process of chemical vapor infiltration and polymer impregnation/pyrolysis in this research. SiCNWs networks are first to be made promising a high volume fraction (20 vol%), and the pyrolytic carbon (PyC) interphase with 5 nm is designed on SiCNWs surface to optimize the bonding condition between SiCNWs and SiC matrix. Nanoindentation shows a modulus of 494 ± 14 GPa of SiCNWs/SiC composites without interphase comparing to the one with PyC interphase of 452 ± 13 GPa. However, the 3‐point bending test shows a higher strength of the composite with PyC interphase (273 ± 32 MPa) comparing with the one without interphase (240 ± 38 MPa). The fracture surface is observed under SEM, which shows a longer SiCNWs pullout of the composite with PyC interphase. The energy dissipation during the 3‐point bending test is calculated by the length of nanowire pull‐out, it demonstrates that the SiCNWs with PyC interphase possess better performance for toughening composite. Further characterization proves that the PyC interphase can give SiCNWs/SiC composites higher fracture toughness (4.49 ± 0.44 MPa·m1/2) than the composites without interphase (3.66 ± 0.28 MPa·m1/2).

Description: Here, we report a multicolor PersL phosphor Sr Ga GeO :Pr .The PersL color can be tuned from deep red to blue. It reveals that the multicolor luminescence of the phosphor is essentially associated with the crossrelaxation effect of Pr . What's more,the PersL lifetime of the multicolor phosphor can be also tuned. Based on the unique features of Sr Ga GeO :Pr phosphor, some luminescent images are fabricated for dynamic multicolor anticounterfeiting. Abstract Persistent luminescence (PersL) phosphor is a glow‐in‐the‐dark material that has been widely applied. Here, we report a multicolor PersL phosphor Sr2Ga2GeO7:Pr3+. The PersL color can be tuned from deep red to blue. It reveals that the luminescent color modulation of the Sr2Ga2GeO7:Pr3+ phosphor is essentially associated with the cross‐relaxation effect of Pr3+ in the host with low‐phonon assistance energy. The PersL lifetime of the multicolor phosphors can be also tuned. Based on the unique features of Sr2Ga2GeO7:Pr3+ phosphor, some simple PersL images are fabricated to emit dynamic multicolor information, and it shows that the PersL image even depicts dynamic multicolor anticounterfeiting.

Description: Sloshing experiments have increasingly received academic attention. Understanding the measurement errors in the sloshing impact pressures is an important parts of the sloshing experiments since these errors, which arise from experimental conditions, affect the subsequent results. As part of the research on the sources of the measurement errors, focused on the effects of surface conditions of pressure sensors on the measurement of impact pressures. Thirty-six integrated circuit piezoelectric pressure sensors were placed on the upper surfaces of a two-dimensional tank to measure the sloshing impact pressures under surge or pitch motions. For each motion, the experimental conditions were divided in two based on whether the surfaces of the sensors were dry or wet. The peak pressures of each test were measured as twenty repeated experiments to ensure reliability. The flow in the tank was visualized using a high-speed camera to observe and analyze macroscopic and microscopic phenomena along the sensor surface. Thermal shock effects were confirmed by varying the experimental temperature and that of the sensor surface. The effects of the wet surface and droplets formed on the sensor surface on pressure measurements are discussed.

Description: Abstract Although great advance has been made in glass science, predicting luminescence properties of laser glass poses a significant challenge for scientists due to the complex relationship between the composition, structure, and properties of the rare earth ions doped laser glasses. The development of high‐performance laser glass usually relies on intuition and trial‐and‐error. Recently, with the proposal of the materials genome engineering, the “glass genome” has also attracted much attention. Here, the structure of the Nd3+ doped B2O3‐Li2O laser glasses was analyzed using Fourier transform infrared spectra and nuclear magnetic resonance, revealing that the glass contains similar glass‐forming ion‐centered coordination polyhedron structure groups to the neighbor congruent glassy compounds. The structure and properties of glass largely depend on the neighbor congruent glassy compounds. Therefore, the structure and luminescence properties of Nd3+ doped B2O3‐Li2O and B2O3‐MgO‐Li2O laser glasses can be quantitatively predicted via the neighbor congruent glassy compounds. The predictive values are in good agreement with the experimental data, which indicates that our approach is an effective way to predict the structure and luminescence properties of Nd3+ doped borate laser glasses.

Description: Fullerene-based materials including C60 and doped C60 have previously been proposed as anodes for lithium ion batteries. It was also shown earlier that n- and p-doping of small molecules can substantially increase voltages and specific capacities. Here, we study ab initio the attachment of multiple lithium atoms to C60, nitrogen-doped C60 (n-type), and boron doped C60 (p-type). We relate the observed attachment energies (which determine the voltage) to changes in the electronic structure induced by Li attachment and by doping. We compare results with a GGA (generalized gradient approximation) functional and a hybrid functional and show that while they agree semi-quantitatively with respect to the expected voltages, there are qualitative differences in the electronic structure. We show that, contrary to small molecules, single atom n- and p-doping will not lead to practically useful modulation of the voltage–capacity curve beyond the initial stages of lithiation.

Description: Recent advances in high-resolution three-dimensional X-ray CT imaging have made it possible to visualize fluid configurations during multiphase displacement at the pore-scale. However, there is an inherited difficulty in image-based curvature measurements: the use of voxelized image data may introduce significant error, which has not—to date—been quantified. To find the best method to compute curvature from micro-CT images and quantify the likely error, we performed drainage and imbibition direct numerical simulations for an oil/water system on a bead pack and a Bentheimer sandstone. From the simulations, local fluid configurations and fluid pressures were obtained. We then investigated methods to compute curvature on the oil/water interface. The interface was defined in two ways; in one case the simulated interface with a sub-resolution smoothness was used, while the other was a smoothed interface extracted from synthetic segmented data based on the simulated phase distribution. The curvature computed on these surfaces was compared with that obtained from the simulated capillary pressure, which does not depend on the explicit consideration of the shape of the interface. As distinguished from previous studies which compared an average or peak curvature with the value derived from the measured macroscopic capillary pressure, our approach can also be used to study the pore-by-pore variation. This paper suggests the best method to compute curvature on images with a quantification of likely errors: local capillary pressures for each pore can be estimated to within 30% if the average radius of curvature is more than 6 times the image resolution, while the average capillary pressure can also be estimated to within 11% if the average radius of curvature is more than 10 times the image resolution.

Description: The use of new developed high-strength steel in concrete members can reduce steel bar congestion and construction costs. This research aims to study the behavior of concrete columns reinforced with new developed high-strength steel under eccentric loading. Ten reinforced concrete columns were fabricated and tested. The test variables were the transverse reinforcement amount and yield strength, eccentricity, and longitudinal reinforcement yield strength. The failure patterns were compression and tensile failure for columns subjected to small eccentricity and large eccentricity, respectively. The same level of post-peak deformability and ductility could only be obtained with a lower amount of transverse reinforcement when high-strength transverse reinforcements were used in columns subjected to small eccentricity. The high-strength longitudinal reinforcement improved the bearing capacity and post-peak deformability of the concrete columns. Furthermore, three different equivalent rectangular stress block (ERSB) parameters for predicting the bearing capacity of columns with high-strength steel are discussed based on test and simulated results. It is concluded that the China Code GB 50010-2010 overestimates the bearing capacity of columns with high-strength steel, whereas the bearing capacities computed using the America Code ACI 318-14 and Canada Code CSA A23.3-04 agree well with the test results.

Description: The design and operation of a custom-built LIDAR-compatible, four-channel Raman spectrometer integrated to a 532 nm pulsed laser is presented. The multichannel design allowed for simultaneous collection of Raman photons at two spectral regions identified as highly sensitive to changes in water temperature. For each of these spectral bands, the signals having polarization parallel to (∥) and perpendicular to (⟂), the excitation polarization were collected. Four independent temperature markers were calculated from the Raman signals: two-colour(∥), two-colour(⟂), depolarization(A) and depolarization(B). A total of sixteen datasets were analysed for one ultrapure (Milli-Q) and three samples of natural water. Temperature accuracies of ±0.4 °C–±0.8 °C were achieved using the two-colour(∥) marker. When multiple linear regression models were constructed (linear combination) utilizing all simultaneously acquired temperature markers, improved accuracies of ±0.3 °C–±0.7 °C were achieved.

Description: Wave run-up and dune overwash are typically assessed using empirical models developed for a specific range of often-simplistic conditions. Field experiments are essential in extending these formulae; yet obtaining comprehensive field data under extreme conditions is often challenging. Here, we use XBeach Surfbeat (XB-SB)—a shortwave-averaged but wave-group resolving numerical model—to complement a field campaign, with two main objectives: i) to assess the contribution of infragravity (IG) waves to washover development in a partially-sheltered area, with a highly complex bathymetry; and ii) to evaluate the unconventional nested-modeling approach that was applied. The analysis shows that gravity waves rapidly decrease across the embayment while IG waves are enhanced. Despite its exclusion of gravity-band swash, XB-SB is able to accurately reproduce both the large-scale hydrodynamics—wave heights and mean water levels across the 30 × 10 km embayment; and the local morphodynamics—steep post-storm dune profile and washover deposit. These findings show that the contribution of IG waves to dune overwash along the bay is significant and highlight the need for any method or model to consider IG waves when applied to similar environments. As many phase-averaged numerical models that are typically used for large-scale coastal applications exclude IG waves, XB-SB may prove to be a suitable alternative.

Description: The article proposes the design of a test bench simulator to test a parallel hybrid propulsion architecture for aeronautical applications. The virtual test bench simulates, in a scaled version, the real test bench, designed for a power of about 0.4 MW. After presenting the architecture of the real propulsion system, the virtual test bench is described. The real system is basically composed by a paralleled electric motor and thermal engine which provide mechanical power to the propeller. Saving cost and volume the test bench is composed by electric motors simulates the behaviors of the real propulsion system despite their differences. The dynamic relationships expressing the transmission of torque between the components, and the method of down-sizing the power delivered are highlighted. Particular attention is given to the real inertia actions that must be simulated on the virtual test bench. An application of the proposed methodology is then presented through the simulation of the take-off phase, and the torque time histories, angular velocities and powers generated on the virtual test bench are used to verify the corresponding time histories expected in the real system.

Description: The objective of this paper is to present an integrated picture of the relationship between the waves and the modifications induced by them in the Romanian shoreline. Thus, the hydrodynamic processes at the Mangalia beaches, located in the southern side of the Romanian nearshore, are simulated using the modeling system Mike 21 SW (MIKE 21 Spectral Waves), developed by the Danish Hydration Institute (DHI). This is one of the newest spectral wave models, which can be used for regional- and local-scale simulations. The model has been calibrated and validated using buoy measurements. The analysis of the statistical parameters shows a good match between the model and the observed data. Furthermore, a model to compare the differences that occur on the beach profiles between the cold and warm seasons was developed. The results obtained indicate a reinforcement of the coastal erosion in the winter, when the waves are stronger (especially in January and February).

Description: The low energy adaptive clustering hierarchy (LEACH) is the classical hierarchical topology control algorithm and still widely used today in wireless sensor networks. There are some problems in LEACH such us an unreasonable selection and uneven distribution of cluster heads, not considering the residual energy of nodes, the cluster head is overloaded and there is a high energy consumption of data transmission. In this paper, a topology control algorithm with double cluster heads and multi-hop based on affinity propagation clustering (APDC-M) was proposed. In APDC-M, firstly, a cluster head election algorithm with double choices based on the affinity propagation clustering algorithm (AP) and reference node strategy (APDC) was proposed. APDC is responsible to elect the fusion cluster head for node clustering. Secondly, a forwarding cluster head is elected within each cluster. The forwarding cluster head is responsible for the data transmission in order to reduce the energy consumption of a single cluster head. Lastly, the forwarding cluster heads complete the data transmission from a cluster to the base station by the shortest path inter-cluster multi-hop mode. The comparison simulation results show that APDC-M can make the cluster head election more reasonable and the cluster head distribution more uniform, and effectively reduce the energy consumption of the cluster head nodes when transmitting data, thus prolonging the network life.

Description: This study investigates the potential of the limb ballistocardiogram (BCG) for unobtrusive estimation of cardiovascular (CV) parameters. In conjunction with the reference CV parameters (including diastolic, pulse, and systolic pressures, stroke volume, cardiac output, and total peripheral resistance), an upper-limb BCG based on an accelerometer embedded in a wearable armband and a lower-limb BCG based on a strain gauge embedded in a weighing scale were instrumented simultaneously with a finger photoplethysmogram (PPG). To standardize the analysis, the more convenient yet unconventional armband BCG was transformed into the more conventional weighing scale BCG (called the synthetic weighing scale BCG) using a signal processing procedure. The characteristic features were extracted from these BCG and PPG waveforms in the form of wave-to-wave time intervals, wave amplitudes, and wave-to-wave amplitudes. Then, the relationship between the characteristic features associated with (i) the weighing scale BCG-PPG pair and (ii) the synthetic weighing scale BCG-PPG pair versus the CV parameters, was analyzed using the multivariate linear regression analysis. The results indicated that each of the CV parameters of interest may be accurately estimated by a combination of as few as two characteristic features in the upper-limb or lower-limb BCG, and also that the characteristic features recruited for the CV parameters were to a large extent relevant according to the physiological mechanism underlying the BCG.

Description: Hand pose estimation is a critical technology of computer vision and human-computer interaction. Deep-learning methods require a considerable amount of tagged data. Accordingly, numerous labeled training data are required. This paper aims to generate depth hand images. Given a ground-truth 3D hand pose, the developed method can generate depth hand images. To be specific, a ground truth can be 3D hand poses with the hand structure contained, while the synthesized image has an identical size to that of the training image and a similar visual appearance to the training set. The developed method, inspired by the progress in the generative adversarial network (GAN) and image-style transfer, helps model the latent statistical relationship between the ground-truth hand pose and the corresponding depth hand image. The images synthesized using the developed method are demonstrated to be feasible for enhancing performance. On public hand pose datasets (NYU, MSRA, ICVL), comprehensive experiments prove that the developed method outperforms the existing works.

Description: Based on the situation that the traditional SINS (strapdown inertial navigation system)/CNS (celestial navigation system) integrated navigation system fails to realize all-day and all-weather navigation, this paper proposes a SINS/Landmark integrated navigation method based on landmark attitude determination to solve this problem. This integrated navigation system takes SINS as the basic scheme and uses landmark navigation to correct the error of SINS. The way of the attitude determination is to use the landmark information photographed by the landmark camera to complete feature matching. The principle of the landmark navigation and the process of attitude determination are discussed, and the feasibility of landmark attitude determination is analyzed, including the orthogonality of the attitude transform matrix, as well as the influences of the factors such as quantity and geometric position of landmarks. On this basis, the paper constructs the equations of the SINS/Landmark integrated navigation system, testifies the effectiveness of landmark attitude determination on the integrated navigation by Kalman filter, and improves the navigation precision of the system.

Description: Ground-based arc-scanning synthetic aperture radar (ArcSAR) is the novel ground-based synthetic aperture radar (GBSAR). It scans 360-degree surrounding scenes by the antenna attached to rotating boom. Therefore, compared with linear scanning GBSAR, ArcSAR has larger field of view. Although the feasibility of ArcSAR has been verified in recent years, its imaging algorithm still presents difficulties. The imaging accuracy of ArcSAR is affected by terrain fluctuation. For rotating scanning ArcSAR, even if targets in scenes have the same range and Doppler with antenna, if the heights of targets are different, their range migration will be different. Traditional ArcSAR imaging algorithms achieve imaging on reference plane. The height difference between reference plane and target in scenes will cause the decrease of imaging quality or even image defocusing because the range migration cannot be compensated correctly. For obtaining high-precision ArcSAR image, we propose interferometric DEM (digital elevation model)-assisted high precision imaging method for ArcSAR. The interferometric ArcSAR is utilized to acquire DEM. With the assist of DEM, target in scenes can be imaged on its actual height. In this paper, we analyze the error caused by ArcSAR imaging on reference plane. The method of extracting DEM on ground range for assisted ArcSAR imaging is also given. Besides, DEM accuracy and deformation monitoring accuracy of proposed method are analyzed. The effectiveness of the proposed method was verified by experiments.

Description: The validation of significant wave height (SWH) data measured by the Sentinel-3A/3B SAR Altimeter (SRAL) is essential for the application of the data in ocean wave monitoring, forecasting and wave climate studies. Sentinel-3A/3B SWH data are validated by comparisons with U. S. National Data Buoy Center (NDBC) buoys, using a spatial scale of 25 km and a temporal scale of 30 min, and with Jason-3 data at their crossovers, using a time difference of less than 30 min. The comparisons with NDBC buoy data show that the root-mean-square error (RMSE) of Sentinel-3A SWH is 0.30 m, and that of Sentinel-3B is no more than 0.31 m. The pseudo-Low-Resolution Mode (PLRM) SWH is slightly better than that of the Synthetic Aperture Radar (SAR) mode. The statistical analysis of Sentinel-3A/3B SWH in the bin of 0.5 m wave height shows that the accuracy of Sentinel-3A/3B SWH data decreases with increasing wave height. The analysis of the monthly biases and RMSEs of Sentinel-3A SWH shows that Sentinel-3A SWH are stable and have a slight upward trend with time. The comparisons with Jason-3 data show that SWH of Sentinel-3A and Jason-3 are consistent in the global ocean. Finally, the piecewise calibration functions are given for the calibration of Sentinel-3A/3B SWH. The results of the study show that Sentinel-3A/3B SWH data have high accuracy and remain stable.

Description: Magnetic resonance (MR) images are often corrupted by Rician noise which degrades the accuracy of image-based diagnosis tasks. The nonlocal means (NLM) method is a representative filter in denoising MR images due to its competitive denoising performance. However, the existing NLM methods usually exploit the gray-level information or hand-crafted features to evaluate the similarity between image patches, which is disadvantageous for preserving the image details while smoothing out noise. In this paper, an improved nonlocal means method is proposed for removing Rician noise in MR images by using the refined similarity measures. The proposed method firstly extracts the intrinsic features from the pre-denoised image using a shallow convolutional neural network named Laplacian eigenmaps network (LEPNet). Then, the extracted features are used for computing the similarity in the NLM method to produce the denoised image. Finally, the method noise of the denoised image is utilized to further improve the denoising performance. Specifically, the LEPNet model is composed of two cascaded convolutional layers and a nonlinear output layer, in which the Laplacian eigenmaps are employed to learn the filter bank in the convolutional layers and the Leaky Rectified Linear Unit activation function is used in the final output layer to output the nonlinear features. Due to the advantage of LEPNet in recovering the geometric structure of the manifold in the low-dimension space, the features extracted by this network can facilitate characterizing the self-similarity better than the existing NLM methods. Experiments have been performed on the BrainWeb phantom and the real images. Experimental results demonstrate that among several compared denoising methods, the proposed method can provide more effective noise removal and better details preservation in terms of human vision and such objective indexes as peak signal-to-noise ratio (PSNR) and structural similarity index measure (SSIM).

Description: An experimental wideband chaotic ground penetrating radar is proposed to locate underground pipes. A chaotic signal with a bandwidth of 1.56 GHz is utilized as the probe signal. The localization of the pipes is achieved by correlating the chaotic echo signal with its delayed duplicate and back-projection algorithm. Experimental results demonstrate that plastic pipe, metallic pipe, and multiple pipes can be located with a range resolution of 10 cm. Limited by the height of the sand, the detectable range is estimated to be 0.7 m for both the plastic pipes and the metallic pipes when the transmitting power is −12 dBm. The proposed system has the potential to detect buried pipes, and it is suitable for geological and civil engineering applications.

Description: Electrode reversal errors in standard 12-lead electrocardiograms (ECG) can produce significant ECG changes and, in turn, misleading diagnoses. Their detection is important but mostly limited to the design of criteria using ECG databases with simulated reversals, without Wilson’s central terminal (WCT) potential change. This is, to the best of our knowledge, the first study that presents an algebraic transformation for simulation of all possible ECG cable reversals, including those with displaced WCT, where most of the leads appear with distorted morphology. The simulation model of ECG electrode swaps and the resultant WCT potential change is derived in the standard 12-lead ECG setup. The transformation formulas are theoretically compared to known limb lead reversals and experimentally proven for unknown limb–chest electrode swaps using a 12-lead ECG database from 25 healthy volunteers (recordings without electrode swaps and with 5 unicolor pairs swaps, including red (right arm—C1), yellow (left arm—C2), green (left leg (LL) —C3), black (right leg (RL)—C5), all unicolor pairs). Two applications of the transformation are shown to be feasible: ‘Forward’ (simulation of reordered leads from correct leads) and ‘Inverse’ (reconstruction of correct leads from an ECG recorded with known electrode reversals). Deficiencies are found only when the ground RL electrode is swapped as this case requires guessing the unknown RL electrode potential. We suggest assuming that potential to be equal to that of the LL electrode. The ‘Forward’ transformation is important for comprehensive training platforms of humans and machines to reliably recognize simulated electrode swaps using the available resources of correctly recorded ECG databases. The ‘Inverse’ transformation can save time and costs for repeated ECG recordings by reconstructing the correct lead set if a lead swap is detected after the end of the recording. In cases when the electrode reversal is unknown but a prior correct ECG recording of the same patient is available, the ‘Inverse’ transformation is tested to detect the exact swapping of the electrodes with an accuracy of (96% to 100%).

Description: Magnesium phosphate cements (MPC) have been demonstrated to have a superior bone regeneration capacity due to their good solubility under in vivo conditions. While in the past only aqueous MPC pastes have been applied, the current study describes the fabrication and in vitro/in vivo testing of an oil-based calcium doped magnesium phosphate (CaMgP) cement paste. Premixed oil-based pastes with CaMgP chemistry combine the advantages of conventional MPC such as high mechanical strength and good resorbability with a prolonged shelf-life and an easier clinical handling. The pastes set in an aqueous environment and predominantly form struvite and achieve a compressive strength of ~8–10 MPa after setting. The implantation into a drill-hole defect at the distal femoral condyle of New Zealand white rabbits over a course of 6 and 12 weeks demonstrated good biocompatibility of the materials without the formation of soft connective tissue or any signs of inflammation. In contrast to a hydroxyapatite forming reference paste, the premixed CaMgP pastes showed subsequent degradation and bony regeneration. The CaMgP cement pastes presented herein are promising bone replacement materials with excellent material properties for an improved and facilitated clinical application.

Description: The present paper reports a novel method to improve the properties of polyethylene (PE) and polypropylene (PP) polymer foils suitable for applications in food packaging. It relates to the adsorption of chitosan-colloidal systems onto untreated and oxygen plasma-treated foil surfaces. It is hypothesized that the first coated layer of chitosan macromolecular solution enables excellent antibacterial properties, while the second (uppermost) layer contains a network of polyphenol resveratrol, embedded into chitosan nanoparticles, which enables antioxidant and antimicrobial properties simultaneously. X-ray photon spectroscopy (XPS) and infrared spectroscopy (FTIR) showed successful binding of both coatings onto foils as confirmed by gravimetric method. In addition, both attached layers (chitosan macromolecular solution and dispersion of chitosan nanoparticles with incorporated resveratrol) onto foils reduced oxygen permeability and wetting contact angle of foils; the latter indicates good anti-fog foil properties. Reduction of both oxygen permeability and wetting contact angle is more pronounced when foils are previously activated by O2 plasma. Moreover, oxygen plasma treatment improves stability and adhesion of chitosan structured adsorbates onto PP and PE foils. Foils also exhibit over 90% reduction of Staphylococcus aureus and over 77% reduction of Escherichia coli as compared to untreated foils and increase antioxidant activity for over a factor of 10. The present method may be useful in different packaging applications such as food (meat, vegetables, dairy, and bakery products) and pharmaceutical packaging, where such properties of foils are desired.

Description: Hierarchical Temporal Memory (HTM) has been known as a software framework to model the brain’s neocortical operation. However, mimicking the brain’s neocortical operation by not software but hardware is more desirable, because the hardware can not only describe the neocortical operation, but can also employ the brain’s architectural advantages. To develop a hybrid circuit of memristor and Complementary Metal-Oxide-Semiconductor (CMOS) for realizing HTM’s spatial pooler (SP) by hardware, memristor defects such as stuck-at-faults and variations should be considered. For solving the defect problem, we first show that the boost-factor adjustment can make HTM’s SP defect-tolerant, because the false activation of defective columns are suppressed. Second, we propose a memristor-CMOS hybrid circuit with the boost-factor adjustment to realize this defect-tolerant SP by hardware. The proposed circuit does not rely on the conventional defect-aware mapping scheme, which cannot avoid the false activation of defective columns. For the Modified subset of National Institute of Standards and Technology (MNIST) vectors, the boost-factor adjusted crossbar with defects = 10% shows a rate loss of only ~0.6%, compared to the ideal crossbar with defects = 0%. On the contrary, the defect-aware mapping without the boost-factor adjustment demonstrates a significant rate loss of ~21.0%. The energy overhead of the boost-factor adjustment is only ~0.05% of the programming energy of memristor synapse crossbar.

Description: The extract of honeycomb waste was studied as a corrosion inhibitor on 304 stainless steel in H2SO4 solutions. The honeycomb waste was obtained from beekeeping at Lawang-Malang, East Java, Indonesia. Electrochemical and scanning electron microscopy methods were used to investigate the performance of the corrosion inhibition process. The inhibition efficiency of the inhibitor (2000 mg/L) reached 97.29% in 0.5 M H2SO4 and decreased with the acid concentration. Kinetic parameters were calculated to explain the effect of acid concentration on the inhibition process. The study on the adsorption behavior of the extracts followed the Frumkin isotherm model. The adsorption of the inhibitor on the 304 stainless steel surface was confirmed by the negative and lower values of Gibbs free energy. The obtained scanning electron microscopy (SEM) images were confirmed by comparing the surface of the specimens with and without inhibitor after corroding for one week. The results indicated that the extract acted as a good inhibitor for 304 stainless steel in acid corrosion.

Description: The aim of this work is to study the activity of novel TiO2-based photocatalysts doped with either phosphorus or zirconium under a UV-Vis source. A set of mesoporous catalysts was prepared by the direct synthesis: TiO2_A and TiO2_B (titanium oxide synthesized by two different procedures), P-TiO2 and Zr-TiO2 (binary oxides with either nonmetal or metal into the TiO2 framework). Complementary characterizations (N2 physisorption at 77 K, X-ray powder diffraction (XRD), field emission scanning electron microscopy (FESEM), energy dispersive X-ray (EDX) analysis, X-ray Photoelectron Spectroscopy (XPS), and (DR)UV-Vis spectroscopy) were used to investigate the physicochemical properties of the prepared catalysts. Then, the photocatalysts were tested for the oxidation of propylene and ethylene under UV-Vis light. As a result, the most promising catalyst for both the propylene and ethylene oxidation reactions was the P-TiO2 (propylene conversion = 27.8% and ethylene conversion = 13%, TOS = 3 h), thus confirming the beneficial effect of P-doping into the TiO2 framework on the photocatalytic activity.

Description: Abstract Ba2Ti9O20 single‐phase ceramics were prepared by reaction sintering method using TiO2 and BaCO3 as raw materials after heat treating at 1150°C for 10h. Furthermore, the formation mechanism and microstructure evolution of Ba2Ti9O20 ceramics prepared by reaction sintering method were investigated. The formation behavior of Ba2Ti9O20 phase was analyzed from the perspective of diffusion, where the reaction activation energy required for the process was calculated to be about 386.17kJ/mol. Combined with the scanning electron microscopy and the energy dispersive spectrometer, it was revealed that the pores on Ba2Ti9O20 grains in the process of reaction sintering might be caused by the absence of oxygen element. Meanwhile, the reason for the roughness of ceramic surface was that the local inhomogeneous distribution of barium on the surface of Ba2Ti9O20 grain leaded to the enrichment of titanium.

Description: Abstract Two dimensional (2D) SnS2/MoS2 heterojunction with a 2D/2D novel structure were used as electrodes materials for enhanced supercapacitor performance. Compared with the sole SnS2, the as‐prepared 2D/2D SnS2/MoS2 layered heterojunction has exhibited great improvement in supercapacitor properties. This novel structure can effectively prevent agglomeration and stacking in electrochemical process, and 2D/2D structure is beneficial to intercalation and desorption of ions in electrochemical processes. The experiment result shows that MoSn5 (Samples with 5% Mo:Sn mole ratios) display a specific capacitance of 466.6 F/g at the current Density of 1 A/g in 0.5M Potassium hydroxide solution, an impressive cycling stability with 88.2 % capacitance retention at current density of 4 A/g. In addition, the as‐fabricated symmetric supercapacitor exhibited high energy density of 115 Wh kg‐1 at the power density of 2230 W kg‐1. This work provides a fundamental investigation of 2D/2D layered material synergistic effect on the electrochemical process.

Description: In this paper, a model for dynamic analysis of array of floating breakwaters is developed and tested. Special attention is given to modeling connections between neighboring elements of the array. A linear three-dimensional floating multi-body formulation is used as a foundation for the presented model. An additional stiffness matrix is derived which introduces the influence of the connections onto motion of the array. The stiffness matrix is used to couple motions in vertical and horizontal planes i.e. the connections are modeled in three-dimensions. The equation of motion is solved in the frequency domain. The newly developed model is tested on an array of three connected breakwaters. The motion and the performance of the breakwater array are investigated under different significant heights and directions of the incoming waves.

Description: In the past few years, unmanned aerial systems (UAS) have achieved great popularity for civil uses. One of the present main uses of these devices is low-cost aerial photogrammetry, being especially useful in coastal environments. In this work, a high-resolution 3D model of a beach section in Guardamar del Segura (Spain) has been produced by employing a low maximum takeoff mass (MTOM) UAS, in combination with the use of structure-from-motion (SfM) techniques. An unprecedented extensive global navigation satellite system (GNSS) survey was simultaneously carried out to statistically validate the model by employing 1238 control points for that purpose. The results show good accuracy, obtaining a vertical root mean square error (RMSE) mean value of 0.121 m and a high point density, close to 30 pt/m2, with similar or even higher quality than most coastal surveys performed with classical techniques. UAS technology permits the acquisition of topographic data with low time-consuming surveys at a high temporal frequency. Coastal managers can implement this methodology into their workflow to study the evolution of complex, highly anthropized dune-beach systems such as the one presented in this study, obtaining more accurate surveys at lower costs.

Description: Automatic controls refer to the application of control theory to regulate systems or processes without human intervention, and the notion is often usefully applied to space applications. A key part of controlling flexible space robotics is the control-structures interaction of a light, flexible structure whose first resonant modes lie within the bandwidth of the controller. In this instance, the designed-control excites the problematic resonances of the highly flexible structure. This manuscript reveals a novel compensator capable of minimum-time performance of an in-plane maneuver with zero residual vibration (ZV) and zero residual vibration-derivative (ZVD) at the end of the maneuver. The novel compensator has a whiplash nature of first commanding maneuver states in the opposite direction of the desired end state. For a flexible spacecraft simulator (FSS) free-floating planar robotic arm, this paper will first derive the model of the flexible system in detail from first principles. Hamilton’s principle is augmented with the adjoint equation to produce the Euler–Lagrange equation which is manipulated to prove equivalence with Newton’s law. Extensive efforts are expended modeling the free–free vibration equations of the flexible system, and this extensive modeling yields an unexpected control profile—a whiplash compensator. Equations of motion are derived using both the Euler–Lagrange method and Newton’s law as validation. Variables are then scaled for efficient computation. Next, general purposed pseudospectral optimization software is used to seek an optimal control, proceeding afterwards to validate optimality via six theoretical optimization necessary conditions: (1) Hamiltonian minimization condition; (2) adjoint equations; (3) terminal transversality condition; (4) Hamiltonian final value condition; (5) Hamiltonian evolution equation; and lastly (6) Bellman’s principle. The results are novel and unique in that they initially command full control in the opposite direction from the desired end state, while no such results are seen using classical control methods including classical methods augmented with structural filters typically employed for controlling highly flexible multi-body systems. The manuscript also opens an interesting question of what to declare when the six optimality necessary conditions are not necessarily in agreement (we choose here not to declare finding the optimal control, instead calling it suboptimal).

Description: Abstract Freeze casting is an established method for fabricating porous ceramic structures with controlled porosity and pore geometries. Herein, we developed a novel freeze casting and freeze drying process to fabricate tubular anode supports for solid oxide fuel cells (SOFCs). Freeze casting was performed by injecting aqueous anode slurry to a dual‐purpose freeze casting and freeze drying mold wrapped with peripheral coils for flowing a coolant. With the use of an ice barrier layer, proper control of the experimental setup, and adjustments in the drying temperature profile, complete drying of the individual anode tubes was achieved in four hours. The freeze‐cast anode tubes contained radially aligned columnar pore channels, thus significantly enhancing the gaseous diffusion. SOFC single cells with conventional Ni/yttria‐stabilized zirconia (YSZ)/strontium‐doped lanthanum manganite (LSM) materials were prepared by dip coating the thin functional layers onto the anode support. Single‐cell tests showed that the concentration polarization was low owing to the highly porous anode support with directional pores. With H2/N2 (1:1) fuel, maximum power densities of 0.47, 0.36, and 0.27 W/cm2 were recorded at 800, 750, and 700 °C, respectively. Our results demonstrate the feasibility of using freeze casting to obtain tubular SOFCs with desired microstructures and fast turn‐around times. This article is protected by copyright. All rights reserved.