ALBERT

Description: Automated seizure detection system based on electroencephalograms (EEG) is an interdisciplinary research problem between computer science and neuroscience. Epileptic seizure affects 1% of the worldwide population and can lead to severe long-term harm to safety and life quality. The automation of seizure detection can greatly improve the treatment of patients. In this work, we propose a neural network model to extract features from EEG signals with a method of arranging the dimension of feature extraction inspired by the traditional method of neurologists. A postprocessor is used to improve the output of the classifier. The result of our seizure detection system on the TUSZ dataset reaches a false alarm rate of 12 per 24 hours with a sensitivity of 59%, which approaches the performance of average human detector based on qEEG tools.

Description: Fast factorized backprojection (FFBP) takes advantage of high accuracy of time-domain algorithms while also possessing high efficiency comparable with conventional frequency domain algorithms. When phase errors need to be compensated for high-resolution synthetic aperture radar (SAR) imaging, however, neither polar formatted subimages within FFBP flow nor the final Cartesian image formed by FFBP is suitable for phase gradient autofocus (PGA). This is because these kinds of images are not capable of providing PGA with a clear Fourier transform relationship (FTR) between image domain and range-compressed phase history domain. In this paper, we make some essential modifications to the original FFBP and present a scheme to incorporate overlapped-subaperture frame for an accurate PGA processing. The raw data collected by an airborne high-resolution spotlight SAR are used to demonstrate the performance of this algorithm.

Description: Due to the fast attenuation of the magnetic field along with the distance, the magnetic anomaly generated by the remote magnetic target is usually buried in the magnetic noise. In order to improve the performance of magnetic anomaly detection (MAD) with low SNR, we propose an adaptive method of MAD with ensemble empirical mode decomposition (EEMD) and minimum entropy (ME) feature. The magnetic data is decomposed into the multiple intrinsic modal functions (IMFs) with different scales by EEMD. According to a defined criterion, the magnetic noise and magnetic signal are reconstructed based on IMFs, respectively. Entropy feature of reconstructed magnetic signal is extracted based on the probability density function (PDF) of the noise which is updated by the reconstructed magnetic noise. Compared to the traditional minimum entropy method, the entropy feature extracted by the proposed method is more obvious. The magnetic anomaly is detected whenever the entropy feature drops below the threshold. Thus, it is effective for revealing the weak magnetic anomaly by the proposed method. The measured magnetic noise is used to validate the performance of the proposed method. The results show that the detection probability of the proposed method is higher with low input SNR.

Description: For the traditional target localization algorithms of frequency diverse array (FDA), there are some problems such as angle and distance coupling in single-frequency receiving FDA mode, large amount of calculation, and weak adaptability. This paper introduces a good learning and predictive method of target localization by using BP neural network on FDA, and FDA-IPSO-BP neural network algorithm is formed. The improved particle swarm optimization (IPSO) algorithm with nonlinear weights is developed to optimize the neural network weights and biases to prevent BP neural network from easily falling into local minimum points. In addition, the decoupling of angle and distance with single frequency increment is well solved. The simulation experiments show that the proposed algorithm has better target localization effect and convergence speed, compared with FDA-BP and FDA-MUSIC algorithms.

Description: The influences of doping amounts of TiO2 on the structure and electrical properties of In2O3 films were experimentally studied. In this study, titanium-doped indium oxide (ITiO) conductions were deposited on glass substrate by the dual-target-type radio frequency magnetron sputtering (RFS) system under different conditions of Ti-doped In2O3 targets, from Ti-0.5 wt% to Ti-5.0 wt%, along with 10 mTorr and 300 W pressure of RF power control that was used as a cost-effective transparent electrochemiluminescence (ECL) cell. From this process, the correlation between structural, optical, and electrical properties is reported. It was found that the best 1.14×10−4 Ω cm of resistivity was from Ti-2.5 wt% with the highest carrier concentration (1.15 × 1021 cm-3), Hall mobility (46.03 cm2/V·s), relatively transmittance (82%), and ECL efficiency (0.43 lm·W-1) with well crystalline structured and smooth morphology. As a result, researchers can be responsible for preparing ITiO thin films with significantly improved microstructure and light intensity performance for the effectiveness of the display devices, as well as its simple process and high performance.

Description: In order to study the regularity of overburden deformation and mining pressure changes in the stope. Take the geological conditions of Hanglaiwan coal mine in Yushen mining area as the background, a 3000 mm×1340 mm×200 mm physical similar material model was established in laboratory. Eight fiber Bragg grating sensors were embedded in the model, used to monitor the movement and deformation of the overburden key stratum and the change of mining abutment pressure in real time and then to determine the influencing factors and strain transfer coefficients of the fiber grating through theoretical analysis and calibration experiments. The results show the following. (1) The changes in value, position, and shape of the strain can reflect the dynamic evolution process of bending deformation, breaking, and rotation of the key strata. When the key layer breaks for the first time, the strain curve shows a peak shape; when the key layer breaks periodically, the strain curve of the fiber grating sensor showed a plateau shape for a period of time. (2) The strain curve has a good corresponding relationship with the change in supporting pressure. When the strain curve of the fiber Bragg grating sensor was at the trough stage, the abutment pressure was at the peak stage, with the increase of sensor buried height, and the supporting pressure and the strain value had a linear relationship within the range of the advanced abutment pressure. The conclusion shows that the fiber Bragg grating sensor monitoring technology has good effect on the internal strain and key supporting pressure monitoring of the overburden in the model test; it provides new monitoring methods and means for the model tests.

Description: Generally, there are mainly two methods to solve the image restoration task in low-level computer vision, i.e., the model-based optimization method and the discriminative learning method. However, these two methods have clear advantages and disadvantages. For example, it is flexible for the model-based optimization method to handle different problems, but large quantity of computing time is required for better performance. The discriminative learning approach has high computing efficiency, but the application scope is seriously limited by the fixed training model. It would be better to combine the advantages of these two methods. Luckily, with the variable splitting techniques, we insert the trained convolutional neural network (CNN) for denoising as one model to the model-based optimization method to solve other image restoration problems (e.g., deblurring and super-resolution). Final experimental results show that our denoising network is able to provide strong prior information for image restoration tasks. The image restoration effects can reach or approximate the most advanced algorithm in such three tasks as denoising, deblurring, and super-resolution. Moreover, the algorithm proposed in this paper is also the most competitive in terms of computational efficiency.

Description: Solar photovoltaic (PV) and solar thermal systems are most widely used renewable energy technologies. Theoretical study indicates that the energy conversion efficiency of solar photovoltaic gets reduced about 0.3% when its temperature increases by 1°C. In this regard, solar PV and thermal (PVT) hybrid systems could be a solution to draw extra heat from the solar PV panel to improve its performance by reducing its temperature. Here, we have designed a new type of heat exchanger for solar PV and thermal (PVT) hybrid systems and have studied the performance of the system. The PVT system has been investigated in comparison with an identical solar PV panel at outdoor condition at Dhaka, Bangladesh. The experiments show that the average improvement of open circuit voltage (Voc) is 0.97 V and the highest improvement of Voc is 1.3 V. In addition, the overall improvement of output power of solar PV panel is 2.5 W.

Description: Two hypotheses for the blocking effect mechanisms under the electromagnetic radiation are presented, and the corresponding dual-frequency interference prediction models are proposed, which can be used to predict the working state of equipment under the condition that the single-frequency susceptibility is known. By taking a radar and a communication radio as the EUT, the experiments of dual-frequency continuous wave electromagnetic radiation are designed and carried out to verify the prediction models. The test results show that the sensitive bandwidth of blocking interference effect for the tested radar and the communication station is consistent with their working bandwidth, respectively. By substituting the test data into the proposed prediction models, the prediction errors of the models are less than 13%. Moreover, it can be found that the tested radar is more sensitive to the peak value of electric field, and the tested communication station is more sensitive to the effective value of electric field.

Description: With the development of remote sensing technology, the application of hyperspectral images is becoming more and more widespread. The accurate classification of ground features through hyperspectral images is an important research content and has attracted widespread attention. Many methods have achieved good classification results in the classification of hyperspectral images. This paper reviews the classification methods of hyperspectral images from three aspects: supervised classification, semisupervised classification, and unsupervised classification.

Description: Particulate matters (PM) have become one of the important pollutants that deteriorate public health. Since PM is ubiquitous in the atmosphere, it is closely related to life quality in many different ways. Thus, a system to accurately monitor PM in diverse environments is imperative. Previous studies using digital images have relied on individual atmospheric images, not benefiting from both spatial and temporal effects of image sequences. This weakness led to undermining predictive power. To address this drawback, we propose a predictive model using the deep dehazing cascaded CNN and temporal priors. The temporal prior accommodates instantaneous visual moves and estimates PM concentration from residuals between the original and dehazed images. The present method also provides, as by-product, high-quality dehazed image sequences superior to the nontemporal methods. The improvements are supported by various experiments under a range of simulation scenarios and assessments using standard metrics.

Description: Rapid urbanization has become a major urban sustainability concern due to environmental impacts, such as the development of urban heat island (UHI) and the reduction of urban security states. To date, most research on urban sustainability development has focused on dynamic change monitoring or UHI state characterization, while there is little literature on UHI change analysis. In addition, there has been little research on the impact of land use and land cover changes (LULCCs) on UHI, especially simulates future trends of LULCCs, UHI change, and dynamic relationship of LULCCs and UHI. The purpose of this research is to design a remote sensing-based framework that investigates and analyzes how the LULCCs in the process of urbanization affected thermal environment. In order to assess and predict the impact of LULCCs on urban heat environment, multitemporal remotely sensed data from 1986 to 2016 were selected as source data, and Geographic Information System (GIS) methods such as the CA-Markov model were employed to construct the proposed framework. The results showed that (1) there has been a substantial strength of urban expansion during the 40-year study period, (2) the farthest distance urban center of gravity moves from north-northeast (NEE) to west-southwest (WSW) direction, (3) the dominate temperature was middle level, sub-high level, and high level in the research area, (4) there was a higher changing frequency and range from east to west, and (5) there was a significant negative correlation between land surface temperature and vegetation and significant positive correlation between temperature and human settlement.

Description: “Tea” is a beverage which has a unique taste and aroma. The conventional method of tea manufacturing involves several stages. These are plucking, withering, rolling, fermentation, and finally firing. The quality parameters of tea (color, taste, and aroma) are developed during the fermentation stage where polyphenolic compounds are oxidized when exposed to air. Thus, controlling the fermentation stage will result in more consistent production of quality tea. The level of fermentation is often detected by humans as “first” and “second” noses as two distinct smell peaks appear during fermentation. The detection of the “second” aroma peak at the optimum fermentation is less consistent when decided by humans. Thus, an electronic nose is introduced to find the optimum level of fermentation detecting the variation in the aroma level. In this review, it is found that the systems developed are capable of detecting variation of the aroma level using an array of metal oxide semiconductor (MOS) gas sensors using different statistical and neural network techniques (SVD, 2-NM, MDM, PCA, SVM, RBF, SOM, PNN, and Recurrent Elman) successfully.

Description: We present experimental results of fluctuation-enhanced gas sensing by low-cost resistive sensors made of a mixture of graphene flakes and TiO2 nanoparticles. Both components are photocatalytic and activated by UV light. Two UV LEDs of different wavelengths (362 and 394 nm) were applied to modulate the gas sensing of the layers. Resistance noise was recorded at low frequencies, between 8 Hz and 10 kHz. The sensors’ response was observed in an ambient atmosphere of synthetic air and toxic NO2 at selected concentrations (5, 10, and 15 ppm). We observed that flicker noise changed its frequency dependence at different UV light wavelengths, thereby providing additional information about the ambient atmosphere. The power spectral density changed by a few times as a result of UV light irradiation. The sensors were operated at 60 and 120°C, and the effect of UV light on gas sensing was most apparent at low operating temperature. We conclude that UV light activates the gas-sensing layer and improves gas detection at low concentrations of NO2. This result is desirable for the detection of the components of gas mixtures, and the modulated sensor can replace an array of independent resistive sensors which would consume much more energy for heating. We also suggest that a more advanced technology for preparing the gas-sensing layer, by use of spin coating, will produce corresponding layers with thickness of about a few μm, which is about ten times less than that for the tested samples. The effects induced by the applied UV light, having a penetration depth of only a few μm, would then be amplified.

Description: Though the solar photovoltaic (PV) module is used for power production, it usually works at high temperatures, decreasing its efficiency and therefore its output. So if an effective cooling method is to be implemented, it would reduce the heat from the solar PV module and increase its power production. Significant research in water cooling on both top and bottom surfaces of the PV module widen the scope for uniform cooling with constant module temperature throughout at any instant. In this work, uniform flow is maintained by means of overflow water from a tank fitted on the top of the PV module. Experiments were carried out with and without cooling. Performance parameters in terms of power output and efficiency have been presented for the PV module without cooling and cooling with three different mass flow rates. The results show that there is a significant rise in efficiency of the PV module by reducing its temperature. An accelerated output power of 23 W has been observed for a higher mass flow rate of 5.3 kg/min which is 15% higher than the photovoltaic module operating without cooling. Results were compared with previous researchers’ work and found to be a good enhancement. Theoretical results agree well with experiments.

Description: A radio frequency identification reader antenna having multitag identification for medical systems is presented, which consists of four PIFAs, two hybrid couplers, and four power dividers. The high isolation is achieved by the symmetric design of the antenna geometry and four power dividers, which are fed by two hybrid couplers. The experimental results show an isolation of more than 40 dB in the North American (902–928 MHz), Korean (917–923.5 MHz), and Japanese (916.7–923.5 MHz) RFID frequency bands.

Description: The performance of direction-of-arrival (DOA) estimation for sparse arrays applied to the distributed source is worse than that applied to the point source model. In this paper, we introduce the coprime array with a large array aperture into the DOA estimation algorithm of the exponential-type coherent distributed source. In particular, we focus on the fourth-order cumulant (FOC) of the received signal which can provide more useful information when the signal is non-Gaussian than when it is Gaussian. The proposed algorithm extends the array aperture by combining the sparsity of array space domain with the fourth-order cumulant characteristics of signals, which improves the estimation accuracy and degree of freedom (DOF). Firstly, the signal-received model of the sparse array is established, and the fourth-order cumulant matrix of the received signal of the sparse array is calculated based on the characteristics of distributed sources, which extend the array aperture. Then, the virtual array is constructed by the sum aggregate of physical array elements, and the position set of its maximum continuous part array element is obtained. Finally, the center DOA estimation of the distributed source is realized by the subspace method. The accuracy and DOF of the proposed algorithm are higher than those of the distributed signal parameter estimator (DSPE) algorithm and least-squares estimation signal parameters via rotational invariance techniques (LS-ESPRIT) algorithm when the array elements are the same. Complexity analysis and numerical simulations are provided to demonstrate the superiority of the proposed method.

Description: Impervious surface (IS) is a key indicator to measure the urbanization process and ecological environment. Many studies have observed an urbanization process based on IS at the city scale. Understanding the changes in the IS over a period at a regional level offers an alternative and effective approach to characterize and quantify the spatial process of urban agglomeration. This study focuses on the urban agglomeration of the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) by utilizing the sensor-based Landsat data during 1987-2017 and investigates the spatiotemporal distribution of IS expansion at both regional and city scales. The modified linear spectral mixture analysis (MLSMA) method is used to extract the IS of the GBA. Then, the IS mapping accuracies were assessed after comparison with high-resolution historical data. The spatiotemporal and directional changes of IS surfaces for GBA are analyzed by using Gravity Center (GC) and Standard Deviational Ellipse (SDE). Finally, Shannon’s Diversity Index (SHDI) is used to analyze the overall characteristics of landscape level, and the Patch Density (PD) and Landscape Shape Index (LSI) are used to describe the characteristics of different classes of the IS. The results show that the IS of the whole region experienced rapid and massive expansion during the past 30 years and exhibited a distinct characteristic along the Pearl River Delta (PRD) and the coastline. Furthermore, the IS area increased rapidly in the PRD, while it is relatively stable in Hong Kong and Macao. We believe that the findings of this study can help policy makers to better understand and maintain the sustainable development of the GBA.

Description: Structural health monitoring (SHM) technology is a monitoring process and early warning method for the health status or damage of special workpiece structures by deploying sensors. In recent years, there have been many studies on SHM, such as ultrasonic, pulsed eddy current, optical fiber, magnetic powder, and other nondestructive testing technologies. Due to their sensor deployment, testing environment, power supply, and transmission line wiring mechanism, they bring problems such as detection efficiency, long-term monitoring, and unreliable systems. The combination of wireless sensing technology and intelligent detection technology is used to solve the above problems. Therefore, this paper studies the tag antenna smart sensor, which is used to characterize the extension of metal defects in SHM. Then, it presents a wireless passive three-dimensional sensing antenna, and simulations verify the feasibility of the antenna. The simulation results show that the antenna can characterize the two extension directions of depth and width of the metal surface structure smooth defect. At the same time, the antenna can characterize the position of smooth defects on the surface of metal structures relative to the antenna and then realize the smooth defect positioning.

Description: We intend to report an interesting phenomenon related to the different interfacial transfer processes between ellipsoidal-like ZnO (E-ZnO) and rod-like ZnO (R-ZnO) nanoheterojunctions witness by the nanosecond time-resolved transient photoluminescence (NTRT-PL) spectra. Fristly, E-ZnO and R-ZnO nanoarchitectures were fabricated via facilitating the electrochemical route; and then, they decorated it with dispersed Au nanoparticles (NPs) by the methods of ion-sputtering deposition, constituting Au/E-ZnO and Au/R-ZnO Schottky-heterojunction nanocomplex, which is characterized by SEM, XRD, Raman analysis, and UV-vis absorption spectra. Steady-state photoluminescence and NTRT-PL spectra of as-fabricated Au/E-ZnO and Au/R-ZnO nanocomposites were probed for interfacial charge transfer process under 266 nm femtosecond (fs) light irradiation. Simultaneously, a distinct diversification for the NTRT-PL spectra is observed, closely associating with oxygen vacancies (Vo), which is confirmed by X-ray photoelectron spectroscopy (XPS) and electron spin resonance (ESR) spectra. Furthermore, Au NPs act as an “annular bridge” and “transit depot” for interfacial charge transfer through local surface plasmon resonance (LSPR) effect and Schottky barrier, respectively, which is identified by NTRT-PL and time-resolved PL (TRPL) decay spectrum. Moreover, this mechanism is responsible for the enhanced photoelectrochemical (PEC) performances of methyl orange (MO) photodegradation under UV light irradiation.

Description: High-intensity underground mining generates considerable surface subsidence in mining areas, including ground cracks and collapse pits on roads and farmland, threatening the safety of buildings. Large-amplitude subsidence (e.g., 〉2 m) is usually characterized by a large phase gradient in interferograms, leading to severe phase decorrelation and unwrapping errors. Therefore, the subsidence on the surface cannot be well derived simply using conventional differential interferometric synthetic aperture radar (DInSAR) or other geodetic measurements. We propose a new method that combines both DInSAR and subpixel offset-tracking technology to improve mine subsidence monitoring over large areas. We utilize their respective advantages to extract both the spatial boundaries and the amplitude of displacements. Using high-resolution RADARSAT-2 SAR images (5 m) acquired on February 13, 2012, and November 27, 2012, in the Shendong Coalfield located at the border between Shaanxi Province and Inner Mongolia Province, China, we obtain the subcentimetre-level subsidence of the mine boundary by DInSAR and resolve the metre-level mine subsidence centre based on subpixel offset tracking. The whole subsidence field is obtained by combining and analyzing the subcentimetre-level and the metre-level subsidence. We use the probability integral method (PIM) function model to fit the boundary and central mine subsidence to reconstruct the spatial distribution of the mine subsidence. Our results show that the maximum central subsidence reaches ~4.0 m (beyond the monitoring capabilities of DInSAR), which is generally in agreement with the maximum subsidence of ~4.0-5.0 m from field investigation. We also model the boundary and the central subsidence (the final fitting coefficient is 0.978). Our findings indicate that the offset-tracking method can compensate for the deficiency of DInSAR in large-amplitude subsidence extraction, and the inclusion of the PIM technique helps reconstruct the whole subsidence field in mining areas.

Description: To increase productivity in agricultural production, speed, and accuracy is the key requirement for long-term economic growth, competitiveness, and sustainability. Traditional manual paddy rice seed classification operations are costly and unreliable because human decisions in identifying objects and issues are inconsistent, subjective, and slow. Machine vision technology provides an alternative for automated processes, which are nondestructive, cost-effective, fast, and accurate techniques. In this work, we presented a study that utilized machine vision technology to classify 14 Oryza sativa rice varieties. Each cultivar used over 3,500 seed samples, a total of close to 50,000 seeds. There were three main processes, including preprocessing, feature extraction, and rice variety classification. We started the first process using a seed orientation method that aligned the seed bodies in the same direction. Next, a quality screening method was applied to detect unusual physical seed samples. Their physical information including shape, color, and texture properties was extracted to be data representations for the classification. Four methods (LR, LDA, k-NN, and SVM) of statistical machine learning techniques and five pretrained models (VGG16, VGG19, Xception, InceptionV3, and InceptionResNetV2) on deep learning techniques were applied for the classification performance comparison. In our study, the rice dataset were classified in both subgroups and collective groups for studying ambiguous relationships among them. The best accuracy was obtained from the SVM method at 90.61%, 82.71%, and 83.9% in subgroups 1 and 2 and the collective group, respectively, while the best accuracy on the deep learning techniques was at 95.15% from InceptionResNetV2 models. In addition, we showed an improvement in the overall performance of the system in terms of data qualities involving seed orientation and quality screening. Our study demonstrated a practical design of rice classification using machine vision technology.

Description: This paper presents two novel UHF RFID near-field reader antennas with uniform vertical electric field distribution. The two antennas have the following common characteristics. First, the radiating parts of the two antennas are simulated and fabricated by the microstrip lines and work using the leakage wave principle of microstrip lines. Second, the end of microstrip lines match the load to form a traveling wave mode of operation, so the two antennas have broadband characteristics. Third, both antennas are fed in a coaxial manner at the center of the antenna. The simulation and measurement results can show that the proposed three-branch antenna and four-branch antenna achieve good impedance matching in the range of 883–960 MHz and 870–960 MHz, respectively, and achieve uniform distribution of the vertical electric field component in a certain area. The reading areas of the three-branch antenna and the four-branch antenna are 70 mm × 70 mm × 90 mm and 100 mm × 100 mm × 120 mm (length × width × height), respectively. Due to the introduction of the ground plate, the antenna gain is low, which meets the design requirements of near-field antennas.

Description: A simplified notched design method for the Vivaldi antenna is exhibiting high frequency-band-selectivity characteristics. By suitably introducing half-wavelength resonator (HWR) and complementary capacitively loaded loop (CCLL), the notched-band selectivity is promoted while maintaining the wide impedance bandwidth of the antenna applicable for wireless communications. HWR is bent in the middle to focus the first notch pole, and the second notch pole is obtained by CCLL on the radiating patch. Additionally, the resonant frequency of the notched pole can be determined by the position and size of two loaded resonators in theoretical analysis, thereby realizing a wideband antenna with the desired notched band. Finally, the Vivaldi antenna of loading resonator was fabricated to verify the feasibility of this new method. Measured and simulated experimental results reveal that the antenna exhibits directional pattern in the passband, low gain at the band-rejection, and excellent selectivity within a frequency range. The simulation and measurement results are in good agreement. The proposed antenna achieves S11

Description: In this paper, an IoT-based indoor air quality monitoring platform, consisting of an air quality-sensing device called “Smart-Air” and a web server, is demonstrated. This platform relies on an IoT and a cloud computing technology to monitor indoor air quality in anywhere and anytime. Smart-Air has been developed based on the IoT technology to efficiently monitor the air quality and transmit the data to a web server via LTE in real time. The device is composed of a microcontroller, pollutant detection sensors, and LTE modem. In the research, the device was designed to measure a concentration of aerosol, VOC, CO, CO2, and temperature-humidity to monitor the air quality. Then, the device was successfully tested for reliability by following the prescribed procedure from the Ministry of Environment, Korea. Also, cloud computing has been integrated into a web server for analyzing the data from the device to classify and visualize indoor air quality according to the standards from the Ministry. An application was developed to help in monitoring the air quality. Thus, approved personnel can monitor the air quality at any time and from anywhere, via either the web server or the application. The web server stores all data in the cloud to provide resources for further analysis of indoor air quality. In addition, the platform has been successfully implemented in Hanyang University of Korea to demonstrate its feasibility.

Description: Broilers produce abnormal sounds such as cough and snore when they suffer from respiratory diseases. The aim of this research work was to develop a method for broiler abnormal sound detection. The sounds were recorded in a broiler house for one week (24/7). There were 20 thousand white feather broilers reared on the floor in a building. Results showed that the developed recognition algorithm, using wavelet transform Mel frequency cepstrum coefficients (WMFCCs), correlation distance Fisher criterion (CDF), and hidden Markov model (HMM), provided an average accuracy, precision, recall, and F1 of 93.8%, 94.4%, 94.1%, and 94.2%, respectively, for broiler sound samples. The results indicate that sound analysis can be used in broiler respiratory assessment in a commercial broiler farm.

Description: Perillae has attracted an increasing interest of study due to its wide usage for medicine and food. Estimating quality and maturity of a perillae requires the information with respect to its size. At present, measuring and sorting the size of perillae mainly depend on manual work, which is limited by low efficiency and unsatisfied accuracy. To address this issue, in this study, we develop an approach based on the machine vision (MV) technique for online measuring and size sorting. The geometrical model and the corresponding mathematical model are built for perillae and imaging, respectively. Based on the built models, the measuring and size sorting method is proposed, including image binarization, key point determination, information matching, and parameter estimation. Experimental results demonstrate that the average time consumption for a captured image, the average measuring error, the variance of measuring error, and the overall sorting accuracy are 204.175 ms, 1.48 mm, 0.07 mm, and 93%, respectively, implying the feasibility and satisfied accuracy of the proposed approach.

Description: A novel passive wireless integrated SAW-based antenna sensor for strain sensing is presented in this paper. A SAW delay line scheme is proposed for signal modulation, which could distinguish the backscattered data from environmental clutter in time domain. The theoretical relationship between the antenna resonance frequency shifts, the temperature, and the applied strain was established. A multiphysical coupled simulation process is proposed to improve the simulation accuracy. By comparing the phase shift of adjacent echoed data which is generated by SAW reflective grating, the temperature information could be extracted exactly and the effect of temperature fluctuation on the resonance frequency could be compensated. A more accurate passive (battery-free) wireless strain sensing could be provided by this proposed integrated antenna sensor than the previous proposed methods. Simulation and experimental results demonstrate the effectiveness of the sensor.

Description: The material parameters of a metamaterial (MTM) are determined by the transformation function used in the optical transformation. Some previously reported MTMs, such as the invisibility cloak, the field rotator, and the field concentrator, were designed by a linear transformation. Their impedance was matched to the background so that no reflection was found; however, the material parameters were mismatched to the background due to the linear transformation function. In the present work, the parameters were matched by using high-order polynomial functions as the transformation function. Since similar materials are filled in boundary cells of the finite-difference time-domain (FDTD) algorithm, the stair-casing error was reduced and the tolerance against boundary abrasion was increased. The frequency response of the proposed method was analyzed. The proposed method is applicable to MTM structures that have complex boundary shapes. In this work, circular and elliptic boundary shapes were considered as examples.

Description: Correct extraction of the equivalent circuit model parameters of photovoltaic modules is of great significance for power prediction, fault diagnosis, and system optimization of photovoltaic power generation systems. Although there are many methods developed to extract the equivalent circuit model parameters of the photovoltaic module, it is still challenging to ensure the stability and operational efficiency of the extract method. In order to effectively extract the parameters of photovoltaic modules, this paper proposes a hybrid algorithm combining analytical methods and differential evolution algorithms for the extraction parameters of PV module. Firstly, the analytical method is applied to simplify the equivalent circuit model and improve the efficiency of the algorithm. Then, the adaptive algorithm is used to adjust the parameters of the differential evolution algorithm. Through the algorithm proposed in this paper, the parameters of the equivalent circuit model of the photovoltaic module can be extracted by the open-circuit voltage, short-circuit current, and maximum power point current and voltage provided by the manufacturer. The proposed method is applied to the extraction of the parameters of the dual-diode equivalent circuit model of different types of photovoltaic modules. The reliability and computational efficiency of the proposed algorithm are verified by comparison and analysis.

Description: A novel low-profile dual-polarization frequency-selective rasorber (FSR) with a transmissive window in the absorption band is proposed in this paper. Based on the equivalent circuit model (ECM), the principles of the impedance design are theoretically derived. Then, a two-layer structure model is constructed. The top layer is composed of a lossy three-legged loaded element (TLLE), and the bottom layer is composed of a square ring bandpass frequency-selective surface (FSS). Furthermore, the strips are folded to reduce the unit cell size to stabilize the angular response. The maximum stable response angle increases from 20 to 40° due to the miniaturized design under both TE and TM polarization. The experimental results of the prototype are in good agreement with the simulation results, which validates the rationality of our design.

Description: A novel two-iteration binary tree fractal bionic structure antenna is proposed for the third generation (3G), fourth generation (4G), WLAN, and Bluetooth wireless applications in the paper, which is based on the principles of conventional microstrip monopole antenna and resonant coupling technique, combined with the advantages of fractal geometry. A new fractal structure was presented for antenna radiator, similar to the tree in nature. The proposed antenna adapted two iterations on a fractal structure radiator, which covers mobile applications in two broad frequency bands with a bandwidth of 44.2% (1.85–2.9 GHz) for TD-SCDMA, WCDMA, CDMA2000, LTE33-41, and Bluetooth frequency bands, and 11.5% (4.9–5.5 GHz) for WLAN frequency band. The proposed antenna was fabricated on a G10/FR4 substrate with a dielectric constant of 4.4 and a size of 50 × 40 mm2. The good agreement between the measurement results and the simulation results validate that the proposed design approach meet the requirements for various wireless applications.

Description: Chad is like many African countries with no meteorological station at the moment to measure solar radiation throughout the country. Thus, theoretical models are used to estimate incident solar radiation. These models are established in correlation form. Our objective was to present a model, which allows the determination of the solar component on two surfaces (horizontal and inclined). This model allowed us to determine, over time, the component of global, direct, and diffuse solar radiation over a period that will cover the different seasons of the year. The calculation is done according to Klein’s days over all the months of the year. The hourly results of the global, direct, and diffuse radiation obtained for all the planes going from January to December are satisfactory compared to the results of the other authors quoted in the literature, which give the maximum and minimum values very close to theirs. These results allowed us to validate the applicability of this model in a climate other than the desert climate.

Description: The main factor affecting the localization accuracy is nonline of sight (NLOS) error which is caused by the complicated indoor environment such as obstacles and walls. To obviously alleviate NLOS effects, a polynomial fitting-based adjusted Kalman filter (PF-AKF) method in a wireless sensor network (WSN) framework is proposed in this paper. The method employs polynomial fitting to accomplish both NLOS identification and distance prediction. Rather than employing standard deviation of all historical data as NLOS detection threshold, the proposed method identifies NLOS via deviation between fitted curve and measurements. Then, it processes the measurements with adjusted Kalman filter (AKF), conducting weighting filter in the case of NLOS condition. Simulations compare the proposed method with Kalman filter (KF), adjusted Kalman filter (AKF), and Kalman-based interacting multiple model (K-IMM) algorithms, and the results demonstrate the superior performance of the proposed method. Moreover, experimental results obtained from a real indoor environment validate the simulation results.

Description: Diabetes is one of today’s greatest global problems, and it is only becoming bigger. Constant measuring of blood glucose level is a prerequisite for monitoring glucose blood level and establishing diabetes treatment procedures. The usual way of glucose level measuring is by an invasive procedure that requires finger pricking with the lancet and might become painful and obeying, especially if this becomes a daily routine. In this study, we analyze noninvasive glucose measurement approaches and present several classification dimensions according to different criteria: size, invasiveness, analyzed media, sensing properties, applied method, activation type, response delay, measurement duration, and access to results. We set the focus on using machine learning and neural network methods and correlation with heart rate variability and electrocardiogram, as a new research and development trend.

Description: The Direction-of-Arrival (DoA) and bandwidth (BW) estimation strategy impinging on a linear array using multiple snapshots data is addressed within the multitask Bayesian Compressive Sensing (MT-BCS). The DoA estimation is used as the reconstruction of sparse signal constrained by the Laplace prior through multitask Bayesian Compressive Sensing. Receiving wideband signal data through linear array, the space is divided into I parts according to the equal interval. The data of interest are assumed to be represented as I-dimensional vector, and the wideband signal can be reconstructed accurately using only a small number M. The receiving antenna operates in the frequency range . Starting from the voltages measured at the output of the array elements at a multiple time instants at , the retrieval of the DoAs is addressed by means of a customized strategy based on MT-BCS in order to correlate the solutions obtained over different frequency samples. The bandwidth of the signals is obtained as a byproduct by identifying at which frequencies the MT-BCS estimations include a signal along the ith (i = 1,…, I) sampling direction. From the outputs of different frequencies, we can know the DoA and BW of signals. A preliminary numerical result is reported to show the behavior of the proposed approach in multiple snapshots data.

Description: One of the advantages of a netted airborne radar system (NARS) is escaping interception of the passive detection system (PDS) while tracking a target. A significant tactic to realize tracking without PDS interception is to study the low probability of interception (LPI) time of NARS. Firstly, this paper analyses the power, frequency, and platform interception probabilities of a combined PDS consisting of a radar-warning receiver (RWR) and an electronic support measurement (ESM). Secondly, this paper takes interactive multiple models (IMM) to describe the target tracking process and introduces a binary hypothesis test for chi square as well as noncentralized chi square distributions as a detection criterion of NARS during target tracking after the design of adaptive dwell time and the maximum illumination interval algorithm. Finally, based on experiential moving platform interception probabilities of a RWR and an ESM, a simplified math model is presented to estimate LPI time of NARS when the parameters are partially known. Simulations illustrate that the simultaneous management of radiation power and time is crucial for NARS against combined PDS interception.

Description: Bifacial solar cells based on organic-inorganic perovskite are fabricated with a laminating process. The structure of the devices is ITO/SnO2/CH3NH3PbI3/NiO/ITO, in which both electrodes are the transparent ITO layer. Therefore, the device can receive light from both sides. By laminating the two half-devices, ITO/SnO2/CH3NH3PbI3 and CH3NH3PbI3/NiO/ITO, at high temperature with pressure, the merging of the middle perovskite layers is enhanced. The optimized bifacial PSCs show a Voc of 0.85 V, FF of 0.58, Jsc of 17.53 mA/cm2, and PCE of 8.47%. The photovoltaic performance varies when the light is illuminated from different sides of the bifacial PSCs. With illumination from the SnO2 side, the Voc and Jsc of the PSCs are apparently higher than those from the NiO side, suggesting more severe electron-hole recombination at the NiO/perovskite interface than at the SnO2/perovskite interface.

Description: The performance of seventeen sunshine-duration-based models has been assessed using data from seven meteorological stations in Croatia. Conventional statistical indicators are used as numerical indicators of the model performance: mean absolute percentage error (MAPE), mean bias error (MBE), mean absolute error (MAE), and root-mean-square error (RMSE). The ranking of the models was done using the combination of all these parameters, all having equal weights. The Rietveld model was found to perform the best overall, followed by Soler and Dogniaux-Lemoine monthly dependent models. For three best-performing models, new adjusted coefficients are calculated, and they are validated using separate dataset. Only the Dogniaux-Lemoine model performed better with adjusted coefficients, but across all analysed locations, the adjusted models showed improvement in reduced maximum percentage error.

Description: To achieve a rational allocation of limited water resources, and formulation of an appropriate irrigation system, this research studied the change characteristics of stem water content (StWC) in plant and its response to environmental factors. In this study, the StWC and environmental factors of Lagerstroemia indica in Beijing were continuously observed by a BD-IV plant stem water content sensor and a forest microclimate monitoring station from 2017 to 2018. The variation of StWC and its correlation with environmental factors were analyzed. The results showed that the StWC of Lagerstroemia indica varies regularly day and night during the growth cycle. Meanwhile, the rising time, valley time, and falling time of StWC were various at the different growth stages of Lagerstroemia indica. The results of correlation analysis between StWC and environmental factors indicated that the StWC of Lagerstroemia indica was positively correlated with air relative humidity, while it was negatively correlated with total radiation and air temperature. The multiple regression equation of StWC and environmental factors of Lagerstroemia indica was , and the coefficient of determination of the equation was of 0.87. Furthermore, the results illustrated that the irrigation should pay attention to supplementing irrigation in time during the peak growing season of fruit.

Description: The aluminized layer of 321 stainless steel was treated by laser shock processing (LSP). The effects of constituent distribution and microstructure change of the aluminized layer in 321 stainless steel on creep performance at high temperature were investigated. SEM and EDS results reveal that aluminized coating is mainly composed of an Al2O3 outer layer, the transition layer of the Fe-Al phase, and the diffusion layer. Additionally, LSP conducted on coating surface not only improves the density of the layer structure, resulting in an increment on the bonding strength of both infiltration layer and substrate, but also leaves higher residual compressive stress in the aluminized layer which improves its creep life effectively. Experimental results indicate that the microhardness of the laser-shocked region is improved strongly by the refined grains and the reconstruction of microstructures. Meanwhile, the roughness and microhardness of aluminized steel are found to increase with the laser impact times. On the other hand, the intermetallic layers, whose microstructure is stable enough to inhibit crack initiation, reinforce strength greatly. The anticreep life of aluminized sample with three times LSP was increased by 232.1% as compared to aluminized steel, which could attribute to the increased dislocation density in the peened sample as well as the decrease of creep voids in size and density.

Description: Radiation-induced defects are responsible for solar cell degradation. The effects of radiation and annealing on the defects of a GaAs/Ge solar cell are modeled and analyzed in this paper. The electrical performance and spectral response of solar cells irradiated with 150 keV proton are examined. Then, thermal annealing was carried out at 120°C. We found that the proportion of defect recovery after annealing decreases with increasing irradiation fluence. The minority carrier lifetime increases with decreasing defect concentration, which means that the electrical performance of the solar cell is improved. We calculated the defect concentration and minority carrier lifetime with numerical simulation and modeled an improved annealing kinetic equation with experimental results.

Description: At present, precision agriculture and smart agriculture are the hot topics, which are based on the efficient data collection by using wireless sensor networks (WSNs). However, agricultural WSNs are still facing many challenges such as multitasks, data quality, and latency. In this paper, we propose an efficient solution for multiple data collection tasks exploiting edge computing-enabled wireless sensor networks in smart agriculture. First, a novel data collection framework is presented by merging WSN and edge computing. Second, the data collection process is modeled, including a plurality of sensors and tasks. Next, according to each specific task and correlation between task and sensors, on the edge computing server, a double selecting strategy is established to determine the best node and sensor network that fulfills quality of data and data collection time constraints of tasks. Furthermore, a data collection algorithm is designed, based on set values for quality of data. Finally, a simulation environment is constructed where the proposed strategy is applied, and results are analyzed and compared to the traditional methods. According to the comparison results, the proposal outperforms the traditional methods in metrics.

Description: This paper proposes Lion Optimized Cognitive Acoustic Network (LOCAN) to reduce packet delay and packet loss during packet transmission in Underwater Acoustic Sensor Network (UWASN). Packet delay and packet loss in UWASN are because of water column variations such as Doppler effect and geometric spreading (GS). Doppler effect forms due to sensor node’s motion and sea surface variations such as salinity and temperature. Geometric spreading (GS) occurs due to sediment drift wave fronts and frequent changes in node’s location and depth. Water column variations change the amplitude of sound propagation, causing channel coherence and multipath interference, which affect packet transmission. The existing UWASN algorithms focus only on temperature and salinity variations. In LOCAN, channel selection through Lion Optimization Algorithm solves the problems of water column variation and improves the battery life, network lifetime, and throughput. The proposed algorithms show a better result in terms of efficiency, when compared to existing UWASN algorithms.

Description: Human motion capture is widely used in exoskeleton robots, human-computer interaction, sports analysis, rehabilitation training, and many other fields. However, soft-sensor-based wearable dynamic measurement has not been well achieved. In this paper, the dynamic measurements of legs were investigated by using dielectric elastomers as stain sensors, and an alternating signal was applied to detect the dynamic rotational angles of the legs. To realize a quick response, parameters of the sensors were optimized by circuit analysis. The sensor can detect hip, knee, and ankle joint motions with a sample frequency of 200 Hz. The measurements of the sensors were compared with a commercial motion capture system from PhaseSpace, and dynamic errors between them were smaller than 3° when squatting and walking at low speed and smaller than 5° when walking at high speed. Experiments therefore demonstrate the feasibility of the integrated wearable stretch sensors with pants.

Description: A single-layer waveguide slotted array antenna is proposed for W-band applications. To eliminate the alignment errors, all structures including the radiation slots, radiation waveguides, and power divider network are realized in one layer based on the milling process, and a planar metal plate is employed to cover the bottom. For example, an 8 × 9 array is designed with 1-to-8 power divider network to validate the proposed technology. The effective radiation aperture size of the array is 24 mm × 21 mm, and the height is only 8 mm. The measured reflection coefficient of the antenna is larger than 3 GHz for  

Description: This work presents a series representation for the mutual inductance of two coaxial pancake coils which remains accurate in non-quasi-static regime under the hypothesis that the current in the source coil is uniformly distributed. Making use of Gegenbauer’s addition theorem and a term-by-term analytical integration, the mutual inductance between two generic turns belonging to distinct coils is expressed as a sum of spherical Hankel functions with algebraic coefficients. The accuracy and efficiency of the resulting expression is proved through pertinent numerical examples.

Description: Leymus chinensis is a perennial rhizomatous clonal plant with strong tolerance to mowing, grazing, drought, and salt-alkali. However, with patchy soil environment, how mowing affect the photosynthesis of L. chinensis in heterogeneous patches is largely unknown. In this experiment, we tested the effects of mowing intensity (0, 35%, and 70% removal of aboveground biomass) on plant photosynthesis under different heterogeneous patches with different saline-alkali soil. We found that moderate concentrations of salt-alkali under heterogeneous patches have no significant effect on the photosynthesis of L. chinensis. Moderate mowing can maintain photosynthesis under no heterogeneity soil and moderate salt-alkali patch condition. In addition, heavy mowing and high salt-alkali soil under heterogeneous patches both inhibited net photosynthetic rate () and transpiration rate (), reduced leaf area, and plant height. L. chinensis responded to extreme soil conditions and strong disturbance by increasing water-use efficiency (WUE), reducing relative water content (RWC), and changing stomatal conductance (Gsw). Therefore, our results imply that moderate grazing or mowing can be used to maintain the productivity and economic benefits of grassland when the soil heterogeneous patches with moderate saline-alkali conditions.

Description: The maximum power point tracking (MPPT) is a strategy that allows imposing the PV array operation point on the maximum power point (MPP) or close to it under any environmental condition. The conventional incremental conductance (INC) algorithm is the most popular algorithm. But due to the fixed step size, its response speed is low under the rapid change of the solar irradiation level or load resistance. In this paper, a new MPPT technique is proposed to enhance the response speed. It consists of two stages: (1) the computing stage and (2) the regulating stage. The computing stage includes the coarse positioning operation and fine positioning operation. And an initial value of the duty cycle is generated in the computing stage, according to the characteristics of the DC-DC converter and the characteristics of the curve. The regulating stage regulates the duty cycle of the DC-DC converter with a small step size, which can improve the tracking efficiency. And the computing stage can enhance the response speed. A simulation comparison of the proposed MPPT technique with other techniques is carried out in MATLAB/Simulink under different scenarios. The simulation results reveal that the response of the proposed algorithm is 4.6 times faster than that of the INC under these scenarios, and the proposed algorithm has higher efficiency.

Description: Improving the performance of pool boiling with critical heat flux of pool boiling and enhancing the coefficient of heat transfer through surface modification technique have gained a lot of attention. These surface modifications can be done at different scales using various techniques. However, along with the performance improvement, the durability and stability of the surface modification are very crucial. Laser machining is an attractive option in this aspect and is gaining a lot of attention. In the present experimentation research work, pool boiling attributed performance of copper-grooved surfaces obtained through picosecond laser machining method is investigated. The performance of the modified surfaces was compared with the plain surface serving as reference. In this, three square grooved patterns with the same pitch (100 μm) and width (100 μm) but different depths (30, 70, and 100 μm) were investigated. Different depths were obtained by varying the scanning speed of the laser machine. In addition to the microchannel effect, the grain structuring during the laser machining process creates additional nucleation sites which has proven its effectiveness in improving the pool boiling performance. In all aspects, the pool boiling performance of the grooved laser-textured surface has showed increased surface characterisation as compared with the surface of copper.

Description: We report on a small-size light detection and ranging (LiDAR) sensor, which offers the possibility of being used in the field during oil spill incidents. In the present study, we develop an algorithm that can distinguish between seawater and oil through the use of a laser at 905 nm wavelength. We investigate the ability of the sensor to detect three different oil types (light crude, bunker A, and bunker C) through experiments and analyze the differences between the types and volumes of spilled oil (1, 5, 10, 15, 20, 25, 30, 35, 40, and 50 mL). The results showed that our algorithm for detecting oil spills over seawater was successful: the LiDAR sensor was able to detect different oil types and volumes. Spilled oil area coverage ranged by more than 50% of the detected area, and the viscosity of bunker C oil reached up to 73%. In addition, the experimental oil spills were mainly formed of oil films of 1 mm and 2 mm thicknesses, which confirmed geometrical properties. Follow-up research should further investigate the characteristics of oil slick thickness measured by the LiDAR system and undertake field tests to assess the feasibility of using the LiDAR system in pollution incidents.

Description: The land surface model SURFEX 7.3 was used to study climate effect of urban expansion located in oasis in arid area of Northwest China by surface and 2 m urban heat island (UHI) intensity and available energy ratio (). We performed a true regional development scenario and three assumed scenario simulations in 1978, 1993, 2004, and 2014, respectively. The results show that 2 m UHI always displays positive twin peaks during whole day, while surface UHI only displays a positive single peak with several hours during daytime at four seasons in the four years. Moreover, 2 m UHI intensity during night is higher than that during daytime, indicating that UHI intensity is contributed more by “trap effect” from urban complex geometry or anthropogenic heat and that surface UHI according to land surface temperature cannot reflect UHI comprehensively. The oasis-urban development resulted in local warming and increasing of , and compared with the original undeveloped environment, local climate in the study area was in a relatively balanced state in 1978 and 1993 due to the “heating effect” of urban area and the “cooling effect” of oasis, but the offsetting effect from oasis would become weaker after1993.

Description: Guided wave transducers, such as electromagnetic acoustic transducers and piezoelectric transducers, generate multimode waves at a given excitation frequency in a cylindrical structure, making it difficult to detect flaws in such structures. To accurately identify the flaws, the transducers must be well designed to suppress the nonaxisymmetric modes. Instead of using the normal mode expansion (NME) method, a spatial Fourier transform (SFT) method is proposed to analyze source influence on the guided wave excitation in a cylindrical structure. A two-dimensional SFT is performed on the spatial distribution function of the surface loading applied to the cylindrical structure. The spatial distribution function is represented in a cylindrical coordinate system. The circumferential-direction SFT is carried out from the angular coordinate to the circumferential orders of the guided wave modes. The axial-direction SFT is carried out from the axial coordinate to the wavenumbers of the guided wave modes. The results of the two-dimensional SFT represent guided wave excitation capabilities for different circumferential orders and wavenumbers. The specific surface loading conditions on the outer surface of a pipe are analyzed to predict source influence on the guided wave excitation. The results are consistent with those obtained using the NME method. Experiments corresponding to the specific surface loading conditions are carried out on a stainless steel pipe. The results confirm the effectiveness of the SFT method.

Description: Falls from a bed often occur when an elderly patient attempts to get out of bed or comes close to the edge of a bed. These mishaps have a high possibility of serious injuries, such as bruises, soreness, and bone fractures. Moreover, a lack of repositioning the body of a bedridden elderly person may cause bedsores. To avoid such a risk, a continuous activity monitoring system is needed for taking care of the elderly. In this study, we propose a bed position classification method based on the sensor signals collected from only four sensors that are embedded in a panel (composed of two piezoelectric sensors and two pressure sensors). It is installed under the mattress on the bed. The bed positions considered are classified into five different classes, i.e., off-bed, sitting, lying center, lying left, and lying right. To collect the training dataset, three elderly patients were asked for consent to participate in the experiment. In our approach, a neural network combined with a Bayesian network is adopted to classify the bed positions and put a constraint on the possible sequences of the bed positions. The results from both the neural network and Bayesian network are combined by the weighted arithmetic mean. The experimental results have a maximum accuracy of position classification of 97.06% when the proportion of coefficients for the neural network and the Bayesian network is 0.3 and 0.7, respectively.

Description: Wireless sensor networks (WSNs) are becoming one of the demanding platforms, where sensor nodes are sensing and monitoring the physical or environmental conditions and transmit the data to the base station via multihop routing. Agriculture sector also adopted these networks to promote innovations for environmental friendly farming methods, lower the management cost, and achieve scientific cultivation. Due to limited capabilities, the sensor nodes have suffered with energy issues and complex routing processes and lead to data transmission failure and delay in the sensor-based agriculture fields. Due to these limitations, the sensor nodes near the base station are always relaying on it and cause extra burden on base station or going into useless state. To address these issues, this study proposes a Gateway Clustering Energy-Efficient Centroid- (GCEEC-) based routing protocol where cluster head is selected from the centroid position and gateway nodes are selected from each cluster. Gateway node reduces the data load from cluster head nodes and forwards the data towards the base station. Simulation has performed to evaluate the proposed protocol with state-of-the-art protocols. The experimental results indicated the better performance of proposed protocol and provide more feasible WSN-based monitoring for temperature, humidity, and illumination in agriculture sector.

Description: In Belgium, and many other countries, rooftop solar panels are becoming a ubiquitous form of decentralised energy production. The increasing share of these distributed installations however imposes many challenges on the operators of the low-voltage distribution grid. They must keep the voltage levels and voltage balance on their grids in check and are often regulatory required to provide sufficient reception capacity for new power producing installations. By placing solar panels in different inclinations and azimuth angles, power production profiles can possibly be shifted to align more with residential power consumption profiles. In this article, it is investigated if the orientation of solar panels can have a mitigating impact on the integration problems on residential low voltage distribution grids. An improved simulation model of a solar panel installation is constructed, which is used to simulate the impact on a residential distribution grid. To stay as close to real-life conditions as possible, real irradiation data and a model of an existing grid are used. Both the developed model as the results on grid impact are evaluated.

Description: As an important chemical raw material, ammonia is mainly produced by the traditional Haber-Bosch process, which has certain limitations such as high energy consumption, high safety responsibility, and severe pollution, thereby having negative impacts on ecosystem. The synthesis of ammonia from dinitrogen at ambient temperature and pressure is one of the most attractive topics in the field of chemistry. As a new two-dimensional nanomaterial, MXene has excellent electrochemical properties and is a potential catalytic material for electrocatalytic nitrogen fixation. In this review, we firstly introduce the crystal, electronic structures of two-dimensional MXenes and summarize the synthesis methods, N2 reduction, and simulation computation, as well as have insight into the challenges of MXenes, which shed light on the development of highly efficient MXene-based electrocatalysts in the reduction of N2 to ammonia.

Description: The combination of traditional retail channel with direct channel adds a new dimension of competition to manufacturers’ distribution system. In this paper, we consider a make-to-order manufacturer with two channels of sale, sale through retailers and online direct sale. The customers are classified into different classes, based on their sensitivity to price and due date. The orders of traditional retail channel customers are fulfilled in the same period of ordering. However, price and due date are quoted to the online customers based on the available capacity as well as the other orders in the pipeline. We develop two different structures of the supply chain: centralized and decentralized dual-channel supply chain which are formulated as bilevel binary nonlinear models. The Particle Swarm Optimization algorithm is also developed to obtain a satisfactory near-optimal solution and compared to a genetic algorithm. Through various numerical analyses, we investigate the effects of the customers’ preference of a direct channel on the model’s variables.

Description: In this paper, on the basis of multifunctional reconfigurable pixel antenna (RPA) elements, a novel linear sparse array with an attractive compound reconfigurability is presented. It has the potential advantages of its beam scanning with low gain fluctuation, low sidelobe in two orthogonal planes, and polarization reconfigurable performance. Specifically, an RPA with simultaneous polarization and pattern reconstruction capabilities, consisting of the driven patch and the parasitic pixels on the same layer of dielectric substrate, is firstly designed, which can work in several operation modes corresponding to steerable beam directions θ=0°;θxoz=25°, 45°;θyoz=15° with two circular polarizations in X-band. Cross-slot coupling feed is used to improve polarization reconstruction capability and reduce the complexity of hybrid reconstruction topology optimization. Then, those RPAs are integrated into the 1×8 linear sparse array to realize the reconfiguration of two circular polarizations and beam steering in xoz- and yoz-plane. Simulation results show that the gain fluctuation and sidelobe level of the array during beam scanning have significant advantages over the previous phased array, and the generation of antenna grating lobes is avoided. Moreover, both RPA element and RPA array prototypes have been fabricated and measured to testify the efficiency. The measured results agree well with the simulated ones, which indicates the application potential in the field of modern wireless communication system of the proposed linear sparse array.

Description: Recently, there has been increasing interest in the field of underwater wireless sensor networks (UWSNs), which is a basic source for the exploration of the ocean environment. A range of military and civilian applications is anticipated to assist UWSN. The UWSN is being developed by the extensive wireless sensor network (WSN) applications and wireless technologies. Therefore, in this paper, a review has been presented which unveils the existing challenges in the underwater environment. In this review, firstly, an introduction to UWSN is presented. After that, underwater localizations and the basics are presented. Secondly, the paper focuses on the architecture of UWSN and technologies used for underwater acoustic sensor network (UASN) localization. Various localization techniques are discussed in the paper classified by centralized and distributed localizations. They are further classified into estimated and prediction-based localizations. Also, various underwater localization algorithms are discussed, which are grouped by the algorithms based on range and range-free schemes. Finally, the paper focuses on the challenges existing in underwater localizations, underwater acoustic communications with conclusions.

Description: The aim of the research is to propose a new optimization method for the multiconstrained optimization of sparse linear arrays (including the constraints of the number of elements, the aperture of arrays, and the minimum distance between adjacent elements). The new method is a modified wolf pack optimization algorithm based on the quantum theory. In the new method, wolves are coded by Bloch spherical coordinates of quantum bits, updated by quantum revolving gates, and selectively adaptively mutated when performing poorly. Because of the three-coordinate characteristics of the sphere, the number of global optimum solutions is greatly expanded and ultimately can be searched with a higher probability. Selective mutation enhances the robustness of the algorithm and improves the search speed. Furthermore, because the size of each dimension of Bloch spherical coordinates is always [−1, 1], the variables transformed by solution space must satisfy the constraints of the aperture of arrays and the minimum distance between adjacent elements, which effectively avoids infallible solutions in the process of updating and mutating the position of the wolf group, reduces the judgment steps, and improves the efficiency of optimization. The validity and robustness of the proposed method are verified by the simulation of two typical examples, and the optimization efficiency of the proposed method is higher than the existing methods.

Description: Inertial navigation systems/Doppler velocity log (INS/DVL) integrated navigation systems are widely used in underwater environments where GPS is unavailable. An INS/DVL integrated navigation system is generally loosely coupled; however, this does not work if any of the DVL transducers do not work. If a system is tightly coupled, velocity error can be estimated with fair accuracy even if some of the transducers fail. However, despite the robustness of a tightly coupled system compared to a loosely coupled one, velocity error estimation accuracy of the former decreases as the number of faulty transducers increases. Therefore, this paper proposes an INS/DVL/revolutions per minute (RPM) integrated navigation filter designed to improve the performance of conventional tightly coupled integrated systems by estimating data from faulty transducers using RPM data. Two salient features of the proposed filter are (1) estimating RPM data accounting for error from the effect of tidal currents and (2) continuous estimation of error in RPM data by selectively converting only the measurements of faulty transducers. The performance of the proposed filter was first verified using Monte Carlo numerical simulations with the analysis range set to 1 standard deviation (1σ, 68%) and then with real sea test measurement data.

Description: Control accuracy significantly affects the performances of boom sprayer. In this study, we develop a precise autocontrol technology based on the vehicle speed feedback. We utilize the auxiliary antidrift system of wind-curtain type air flow and the variable spraying control system for adaptive fertilizing and online measuring of working conditions. Experimental results demonstrate that the variable spraying control system could keep the speed error less than 3%. The air flow significantly improves the penetration of spraying, decreases the fog drip, and increases the pesticide utility. Benefitting from the auxiliary air flow, the average utility of pesticide is improved from 26.76% to 37.98%. Additionally, the speed feedback control reduces the consumption of pesticide by more than 12%.

Description: The availability of suitable native plant species for local animal husbandry development and ecological restoration is limited on the Qinghai-Tibetan Plateau. Therefore, comparisons of the ecological adaptability of native species to alternative habitats and their introduction into new habitats are of high importance. This study is aimed at identifying the alteration in morphological and physiological characteristics by measuring photosynthetic physiology, nutrient content, and growth associated with adaptation of plants to conditions at different altitudes 2450, 2950, 3100, and 3300 m above sea level (a. s. l.) on the plateau. Seeds of the dominant grass, Elymus nutans, were collected from locations at these altitudes and grown at a test location of 2950 m a. s. l. Results indicated that altitude had no significant effect on plant height and root depth. However, the leaf area and total root surface area of plants derived from 2950 and 3300 m a. s. l. showed a parabolic response, being greater than those of plants derived from the lowest (2450 m) and highest (3300 m a. s. l.). Total (root plus shoot) dry matter reduced progressively from 2450 to 3300 m a. s. l, while root : shoot ratio increased progressively with altitude. Seed yield of plants originating from the test altitude (2950 m a. s. l) was significantly higher than at any other altitude, being 20% lower at 2450 m, and 38% and 58% less in populations originating from the higher altitudes (3100 and 3300 m a. s. l.). There was also a parabolic decline in response of Elymus nutans germplasm from 3100, 3300, and 2450 m, compared with plants from 2950 m a. s. l., to photosynthetic rate, total N, soluble sugar, and starch contents. Germplasm from 2450 m a. s. l. had significantly lower shoot and higher root carbon content, lower shoot nitrogen, and lower root carbon-to-nitrogen ratio compared with plants derived from the other three altitudes. It is suggested that the stable, genetically determined morphological and physiological features of ecotypes showed parabolic responses which means these ecotypes have become adapted to local habitats, whereas parameters such as dry matter, total root : shoot ratio, photosynthetic rate, and intercellular CO2 concentration of plants reflected phenotypic linear response to current abiotic conditions. It is postulated that introduced ecotypes from 2450, 3100, and 3300 m could adapt to the environment at 2950 m a. s. l. gradually. We conclude that the increased thermal regime experienced by plants introduced from high altitude to low altitude may facilitate the increased growth of Elymus nutans subtypes. It is important to preserve local strains of native species, or ecotypes, for reintroduction into degraded environments and to maintain the greatest ecosystem stability in the northeastern Tibetan Plateau.

Description: Traditionally, routing decisions have been based on minimizing travel time as the associated cost. Ecorouting considers the environmental aspects (e.g., emissions and fuel) as part of the travel cost to mitigate the undesirable impact of transportation systems on the environment. Unlike the exiting ecorouting review papers, this research work is aimed at providing a three-factor taxonomy at a more disaggregated level from the optimization prospective and map ecorouting studies to the proposed taxonomy. Furthermore, the strengths and weaknesses of the presented models are summarized. Our main findings include (a) a majority of studies optimized one objective at a time; (b) the microscopic level of aggregation of the flow and emission/fuel models was rarely employed for large case studies, due to the associated complexity; and (c) all of the reviewed studies were applied in a centralized routing system environment. In the near future, when intelligent vehicles will be on the roads, a multiobjective distributed routing framework can be employed with a microscopic level of aggregation for both traffic and emission models, which is capable of operating on largescale networks in real time. Additionally, short-term spatiotemporal prediction of GHG cost is a crucial aspect to be tackled.

Description: Ultrahigh-resolution optical coherence tomography provides an axial resolution of 1-2 μm for resolving cellular structures of biological tissues critical for the diagnosis of diseases. However, it requires a relatively large spectral bandwidth which is not supported by the key components of the imaging system. We propose a novel spectral-domain OCT design, termed interferometer-in-spectrometer, which is able to compensate the bandwidth limitations of the grating and the line scan sensor by spectral shaping without compromising the signal intensity and adding the system cost. The advantage of axial resolution and ranging depth over the standard design is experimentally validated using the standard testing method and fresh swine cornea ex vivo. Moreover, opportunities that opened up by this new scheme for improving the performances of spectral-domain OCT are also discussed.

Description: Tractor front-end loaders are an essential part of the equipment used on farms. At present, there are an important number of small- and medium-sized companies involved in the manufacturing of this equipment. These companies rely heavily on experience for innovative designs, as in the vast majority of cases they lack access to adequate methodology for the optimal design of new front-end loaders. The study conducted has developed a methodology to design tractor front-end loaders with a view of obtaining their accurate design during the bucket loading process. The methodology comprises two phases: the first phase involves a numerical analysis of the structural behaviour of the front-end loader components by means of the Finite Element Method; the second phase, the experimental phase, makes use of low-cost sensors, in particular, strain gauges, to analyse existing strains at selected points in the front-end loader structure. The experimental results obtained by means of low-cost sensors fitted onto the front-end loader allow analysing the existing strains at the points measured, as well as validate the numerical model developed. This methodology is validated by applying it to a commercial front-end loader, more specifically to model 430E2 of the company Maquinaria Agrícola El León S.A (Spain).

Description: In recent decades, global and local vegetation phenology has undergone significant changes due to the combination of climate change and human activities. Current researches have revealed the temporal and spatial distribution of vegetation phenology in large scale by using remote sensing data. However, researches on spatiotemporal differentiation of remote sensing phenology and its changes are limited which involves high-dimensional data processing and analysing. A new data model based on data cube technologies was proposed in the paper to efficiently organize remote sensing phenology and related reanalysis data in different scales. The multidimensional aggregation functions in the data cube promote the rapid discovery of the spatiotemporal differentiation of phenology. The exploratory analysis methods were extended to the data cube to mine the change characteristics of the long-term phenology and its influencing factors. Based on this method, the case study explored that the spring phenology of Qinba Mountains has a strong dependence on the topography, and the temperature plays a leading role in the vegetation green-up date distribution of the high-altitude areas while human activities dominate the low-altitude areas. The response of green-up trend slope seems to be the most sensitive at an altitude of about 2000 meters. This research provided a new approach for analysing phenology phenomena and its changes in Qinba Mountains that had the same reference value for other regional phenology studies.

Description: This paper considers a passive target localization problem in Wireless Sensor Networks (WSNs) using the noisy time of arrival (TOA) measurements, obtained from multiple receivers and a single transmitter. The objective function is formulated as a maximum likelihood (ML) estimation problem under the Gaussian noise assumption. Consequently, the objective function of the ML estimator is a highly nonlinear and nonconvex function, where conventional optimization methods are not suitable for this type of problem. Hence, an improved algorithm based on the hybridization of an adaptive differential evolution (ADE) and Nelder-Mead (NM) algorithms, named HADENM, is proposed to find the estimated position of a passive target. In this paper, the control parameters of the ADE algorithm are adaptively updated during the evolution process. In addition, an adaptive adjustment parameter is designed to provide a balance between the global exploration and the local exploitation abilities. Furthermore, the exploitation is strengthened using the NM method by improving the accuracy of the best solution obtained from the ADE algorithm. Statistical analysis has been conducted, to evaluate the benefits of the proposed modifications on the optimization performance of the HADENM algorithm. The comparison results between HADENM algorithm and its versions indicate that the modifications proposed in this paper can improve the overall optimization performance. Furthermore, the simulation shows that the proposed HADENM algorithm can attain the Cramer-Rao lower bound (CRLB) and outperforms the constrained weighted least squares (CWLS) and differential evolution (DE) algorithms. The obtained results demonstrate the high accuracy and robustness of the proposed algorithm for solving the passive target localization problem for a wide range of measurement noise levels.

Description: Wireless sensor networks (WSNs) are a huge number of sensors, which are distributed in area monitoring to collect important signals. WSNs are widely used in several applications such as home automation, environment, and healthcare monitoring. However, most of these applications face various difficulties due to sensor design. Therefore, the major challenge of designing WSNs is saving the energy consumed during communication and extending the network lifetime. Multicriteria Decision Analysis (MCDA) methods have been exploited for saving network energy. However, the majority of researches focus on the Cluster Head (CH) selection. In this paper, we aim to enhance the process of forwarder selection using an efficient combined multicriteria model. The proposed scheme improved the intercluster communication by controlling the distance separating CHs from the sink node. To minimize the cluster density, this work consists of activating only sensor nodes that detect enough strong signals. The activation phase presents a fault-tolerant technique to succeed in the communication process. Moreover, the proposed work is aimed at selecting the most efficient hops, which are responsible for routing data to the sink using the Analytic Hierarchy Process (AHP) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methods. Simulation results proved that our new protocol maximized the residual energy by 15% and 25% and the network lifetime by 35% and 47% compared to the Distributed Clustering Protocol using Voting and Priority (DCPVP) and Low-Energy Adaptive Clustering Hierarchy (LEACH), respectively.

Description: This study explores the use of a hybrid Autoregressive Integrated Moving Average (ARIMA) and Neural Network modelling for estimates of the electric field along vertical paths (buildings) close to Digital Television (DTV) transmitters. The work was carried out in Belém city, one of the most urbanized cities in the Brazilian Amazon and includes a case study of the application of this modelling within the subscenarios found in Belém. Its results were compared with the ITU recommendations P. 1546-5 and proved to be better in every subscenario analysed. In the worst case, the estimate of the model was approximately 65% better than that of the ITU. We also compared this modelling with a classic modelling technique: the Least Squares (LS) method. In most situations, the hybrid model achieved better results than the LS.

Description: The cold accumulation problem can lead to performance degradation of heat pumps. This paper presents the design and optimization of a solar-assisted storage system to solve this issue. A ground source heat pump (GSHP) project was established using the transient system simulation program (TRNSYS) based on a ground heat exchange theoretical model, which was validated by a previously established experiment in Beijing. The Beijing, Harbin, and Zhengzhou regions were used in numerical simulations to represent three typical cities where buildings require space heating (a cold region, a severe cold region, and a hot summer and cold winter region, respectively). System performance was simulated over periods of ten years. The simulation results showed that the imbalance efficiencies in the Beijing, Harbin, and Zhengzhou regions are 55%, 79%, and 38%, respectively. The annual average soil temperature decreases 7.3°C, 11.0°C, and 5.3°C during ten years of conventional GSHP operation in the Beijing, Harbin, and Zhengzhou regions, respectively. Because of the soil temperature decrease, the minimum heating coefficient of performance (COP) values decrease by 23%, 46%, and 11% over the ten years for GSHP operation in these three regions, respectively. Moreover, the simulation data show that the soil temperature would still be decreasing if based on the previous solar energy area calculation method. Design parameters such as the solar collector size are optimized for the building load and average soil temperature in various cold regions. Long-term operation will test the matching rate of the compensation system with the conventional GSHP system. After the system is optimized, the solar collector area increases of 20% in the Beijing region, 25% in the Harbin region, and 15% in the Zhengzhou region could help to maintain the annual average soil temperature balance. The optimized system could maintain a higher annual average COP because of the steady soil temperature. It provides a method for the design of a solar collector area which needs to be determined in the seasonal heat storage solar ground source heat pump system.

Description: This research proposes a compact elliptical ring antenna excited by a circular disc monopole (CDM) for ultra-wideband (UWB) communications. In the study, time- and frequency-domain pulse distortions of the antenna in the transmission mode were characterized by magnitude and phase of the antenna transfer function (Hrad). The results showed that the gain and magnitude of Hrad in the boresight direction are sufficiently flat with linear phase response. The average antenna gain is 3.9 dBi over the UWB spectrum. The antenna also exhibits low pulse distortion with the correlation factors (ρ) of 0.98 and 0.93 for the fifth-order derivative Gaussian pulse and modulated Gaussian pulse with 6 GHz band rejection. The CDM-excited elliptical ring antenna possesses several attractive features, including wide bandwidth, flat gain, compactness, low cost, and low distortion.

Description: With the advent of IR (Industrial Revolution) 4.0, the spread of sensors in IoT (Internet of Things) may generate massive data, which will challenge the limited sensor storage and network bandwidth. Hence, the study of big data compression is valuable in the field of sensors. A problem is how to compress the long-stream data efficiently with the finite memory of a sensor. To maintain the performance, traditional techniques of compression have to treat the data streams on a small and incompetent scale, which will reduce the compression ratio. To solve this problem, this paper proposes a block-split coding algorithm named “CZ-Array algorithm,” and implements it in the shareware named “ComZip.” CZ-Array can use a relatively small data window to cover a configurable large scale, which benefits the compression ratio. It is fast with the time complexity O() and fits the big data compression. The experiment results indicate that ComZip with CZ-Array can obtain a better compression ratio than gzip, lz4, bzip2, and p7zip in the multiple stream data compression, and it also has a competent speed among these general data compression software. Besides, CZ-Array is concise and fits the hardware parallel implementation of sensors.

Description: The aim of this paper is to investigate the feasibility of using the Dynamic Time Warping (DTW) method to measure motor states in advanced Parkinson’s disease (PD). Data were collected from 19 PD patients who experimented leg agility motor tests with motion sensors on their ankles once before and multiple times after an administration of 150% of their normal daily dose of medication. Experiments of 22 healthy controls were included. Three movement disorder specialists rated the motor states of the patients according to Treatment Response Scale (TRS) using recorded videos of the experiments. A DTW-based motor state distance score (DDS) was constructed using the acceleration and gyroscope signals collected during leg agility motor tests. Mean DDS showed similar trends to mean TRS scores across the test occasions. Mean DDS was able to differentiate between PD patients at Off and On motor states. DDS was able to classify the motor state changes with good accuracy (82%). The PD patients who showed more response to medication were selected using the TRS scale, and the most related DTW-based features to their TRS scores were investigated. There were individual DTW-based features identified for each patient. In conclusion, the DTW method can provide information about motor states of advanced PD patients which can be used in the development of methods for automatic motor scoring of PD.

Description: Pulse waves of a radial artery under different pressures applied through a cuff play an important role in disease diagnosis, especially in traditional chinese medicine (TCM). Pulse waves could be collected by a pressure sensor array affixed to an inflatable cuff. During a process of collecting pulse waves, one sensor of a sensor array moves up and down when the sensor is shocked by a pulse wave. Movement of the sensor leads to the passive displacement of other nearby sensors because of a connecting structure between them. Then, vibration signals will be generated by the nearby sensors although these sensors do not receive radial artery pulse waves. These vibration signals considered an interference are usually superimposed on real signals obtained from these nearby sensors and degrade signal quality. The problem mentioned above does not only generally exist in a pressure sensor array attached to a wristband but also is easy to ignore. This paper proposes a novel interference suppression algorithm based on Welch’s method for estimating and weakening adjacent sensor channel interference to overcome the problem. At first, a sensor array attached to an inflatable cuff and a vibration generator is proposed to establish an experimental platform for simplifying the pulse wave collection process. Then, the interference suppression algorithm is proposed according to mechanical analysis and Welch’s method based on the proposed sensor array and vibration generator. Next anti-interference abilities of the algorithm based on a simplified process are evaluated by different vibration frequencies and applied pressures. The anti-interference abilities of the algorithm based on pulse waves of the radial artery are evaluated indirectly. The results show that the novel interference suppression algorithm could weaken adjacent sensor channel interference and upgrade the signal quality.

Description: In wastewater treatment plants, the degradation of complex substances that contaminate water is carried out by microorganisms, which are fixed by a network formed by filamentous bacteria, creating large flocs that settle easily. However, the excessive growth of said bacteria causes a series of drawbacks such as the reduction of settling velocity, leakage of activated sludge with the effluent, and formation of supernatant, a phenomenon known as bulking. This research work seeks to develop and evaluate a procedure for the physical characterization of the flocs to determine the parameters that affect the settling velocity and thereby detect and control bulking. For this purpose, sedimentation and image analysis tests were carried out from wastewater from the Aguas Antofagasta treatment plant (Chile). The image analysis was performed with images captured from an optical microscope in two magnifications (100x and 50x), which were analyzed by marking each floc individually and characterized by an image processing software. Additionally, sedimentation tests were performed on columns (area of 74 (cm2) and height of 70 (cm)). As a result, an inversely proportional dependence was found on the settling velocity evaluated by the Vesilind equation in the zone of constant fall velocity with respect to the number of flocs connected per cluster, giving an estimate of the settling velocity depending on the number of flocs connected. This would allow predicting settling velocity with image analysis, taking into account that the problem of bulking is determined by the type of filamentous bacteria that causes it and the sedimentation process is affected in large part by local factors. It can be concluded through this study that as the number of flocs connected per cluster increases, the settling velocity decreases. This study provides wastewater treatment plants with a practical tool to determine sedimentation times and thus improve the quality of the treated water, avoiding problems of flocs leaking with the effluent. In addition, the image analysis itself allows rapid detection of the phenomenon of bulking and its severity.

Description: In recent years, methods based on neural network have achieved excellent performance for image segmentation. However, segmentation around the edge area is still unsatisfactory when dealing with complex boundaries. This paper proposes an edge prior semantic segmentation architecture based on Bayesian framework. The entire framework is composed of three network structures, a likelihood network and an edge prior network at the front, followed by a constraint network. The likelihood network produces a rough segmentation result, which is later optimized by edge prior information, including the edge map and the edge distance. For the constraint network, the modified domain transform method is proposed, in which the diffusion direction is revised through the newly defined distance map and some added constraint conditions. Experiments about the proposed approach and several contrastive methods show that our proposed method had good performance and outperformed FCN in terms of average accuracy for 0.0209 on ESAR data set.

Description: The increasing cohabitation between telecommunication antennas generating electromagnetic waves and solar panels poses the problem of interaction between these radio waves and solar cells. In order to study the effect of radio waves on the performance of a polycrystalline silicon solar cell in a three-dimensional approach, it is necessary to assess the attenuation of the radio wave in the illuminated polysilicon grain and also to find the expressions of its components. This work investigated the attenuation of radio waves into a polycrystalline silicon grain by analyzing, firstly, the behaviour of the penetration length of the radio waves into the polysilicon grain and secondly, the behaviour of the attenuation factor. The propagation of the radio waves into the polycrystalline silicon grain can be considered without attenuation that can be neglected.

Description: In this work, a SiO2-TiO2 coating, composed of different numbers of TiO2 and SiO2 layers, was fabricated by a spray-coating technique. The films were deposited onto ignimbrite rock and divided into two groups according to the number of SiO2 layers applied, 10 and 15 layers of SiO2 and 5 layers of TiO2 for each group. The morphology and chemical composition of the synthesized samples were characterized by field emission scanning electron microscopy (FE-SEM) and energy dispersive X-ray spectrometer (EDS), which reveal the successful SiO2-TiO2 coating on ignimbrite. The photocatalytic activities of samples obtained were evaluated toward the decomposition of 3 ppm of methyl orange (MO). Finally, NOx gas degradation was studied. The obtained results evidenced that the SiO2 and TiO2 coating improved the photocatalytic activity of ignimbrite.

Description: Antenna arrays with high directivity, low side-lobe level, and null control in desired direction and whip antenna with wider bandwidth both need to be optimized to meet different needs of communication systems. A new natural heuristic algorithm simulating social behavior of grasshoppers, grasshopper optimization algorithm (GOA), is applied to electromagnetic field as a new effective technology to solve the antenna optimization problem for the first time. Its algorithm is simple and has no gradient mechanism, can effectively avoid falling into local optimum, and is suitable for single-objective and multiobjective optimization problems. GOA is used to optimize the side lobe suppression, null depth, and notch control of arbitrary linear array and then used to optimize the loading and matching network of 10-meter HF broadband whip antenna compared with other algorithms. The results show that GOA has more advantages in side-lobe suppression, null depth, and notch control of linear array than other algorithms and has better broadband optimization performance for HF whip antenna. The pattern synthesis and antenna broadband optimization based on GOA provide a new and effective method for antenna performance optimization.

Description: The aim of the research is to propose a new optimization method for the multiconstrained optimization of sparse linear arrays (including the constraints of the number of elements, the aperture of arrays, and the minimum distance between adjacent elements). The new method is a modified wolf pack optimization algorithm based on the quantum theory. In the new method, wolves are coded by Bloch spherical coordinates of quantum bits, updated by quantum revolving gates, and selectively adaptively mutated when performing poorly. Because of the three-coordinate characteristics of the sphere, the number of global optimum solutions is greatly expanded and ultimately can be searched with a higher probability. Selective mutation enhances the robustness of the algorithm and improves the search speed. Furthermore, because the size of each dimension of Bloch spherical coordinates is always [−1, 1], the variables transformed by solution space must satisfy the constraints of the aperture of arrays and the minimum distance between adjacent elements, which effectively avoids infallible solutions in the process of updating and mutating the position of the wolf group, reduces the judgment steps, and improves the efficiency of optimization. The validity and robustness of the proposed method are verified by the simulation of two typical examples, and the optimization efficiency of the proposed method is higher than the existing methods.

Description: The material parameters of a metamaterial (MTM) are determined by the transformation function used in the optical transformation. Some previously reported MTMs, such as the invisibility cloak, the field rotator, and the field concentrator, were designed by a linear transformation. Their impedance was matched to the background so that no reflection was found; however, the material parameters were mismatched to the background due to the linear transformation function. In the present work, the parameters were matched by using high-order polynomial functions as the transformation function. Since similar materials are filled in boundary cells of the finite-difference time-domain (FDTD) algorithm, the stair-casing error was reduced and the tolerance against boundary abrasion was increased. The frequency response of the proposed method was analyzed. The proposed method is applicable to MTM structures that have complex boundary shapes. In this work, circular and elliptic boundary shapes were considered as examples.

Description: Electric fields radiated by cloud flashes that occurred over the rugged terrain of mountainous country Nepal were recorded, analysed, and compared with those from different geographical regions. The total duration of the flash varies from 80 to 469.5 ms. The majority of the cloud flashes were of two stages: the first stage of the majority of the flashes was found to consist of large microsecond scale bipolar pulses having negative initial polarity and the late stage consists of submicrosecond scale pulses having both positive and negative initial polarities. The average durations of the first and second stages are 11.23 and 66.79 ms, respectively, and the time gap between them is 53.57 ms. The cloud pulses led by the negative initial polarity pulses are more compactly distributed and are higher in mountainous countries as compared to those of flashes lead by positive initial polarity pulses, with the average values of interpulse interval being 211.42 and 309.79 μs, respectively.

Description: A novel two-iteration binary tree fractal bionic structure antenna is proposed for the third generation (3G), fourth generation (4G), WLAN, and Bluetooth wireless applications in the paper, which is based on the principles of conventional microstrip monopole antenna and resonant coupling technique, combined with the advantages of fractal geometry. A new fractal structure was presented for antenna radiator, similar to the tree in nature. The proposed antenna adapted two iterations on a fractal structure radiator, which covers mobile applications in two broad frequency bands with a bandwidth of 44.2% (1.85–2.9 GHz) for TD-SCDMA, WCDMA, CDMA2000, LTE33-41, and Bluetooth frequency bands, and 11.5% (4.9–5.5 GHz) for WLAN frequency band. The proposed antenna was fabricated on a G10/FR4 substrate with a dielectric constant of 4.4 and a size of 50 × 40 mm2. The good agreement between the measurement results and the simulation results validate that the proposed design approach meet the requirements for various wireless applications.

Description: A novel low-profile dual-polarization frequency-selective rasorber (FSR) with a transmissive window in the absorption band is proposed in this paper. Based on the equivalent circuit model (ECM), the principles of the impedance design are theoretically derived. Then, a two-layer structure model is constructed. The top layer is composed of a lossy three-legged loaded element (TLLE), and the bottom layer is composed of a square ring bandpass frequency-selective surface (FSS). Furthermore, the strips are folded to reduce the unit cell size to stabilize the angular response. The maximum stable response angle increases from 20 to 40° due to the miniaturized design under both TE and TM polarization. The experimental results of the prototype are in good agreement with the simulation results, which validates the rationality of our design.

Description: Directional modulation (DM) has become a new research hotspot of physical layer security (PLS) communication at the transmitter side. In this paper, we propose a robust synthesis algorithm for DM signal under the condition of the array manifold vectors perturbation. This algorithm optimizes the constraints of sidelobe level and Euclidean distance of constellation points by considering the worst case performance of array manifold vectors. Furthermore, we also design an active constellation extension (ACE) method to relax the equality constraint of desired modulation symbols into a robust inequality constraint at the desired direction. These constraints can be reformulated in a convex form with and regularization, which are computationally tractable. Simulation results show better performance of the proposed robust algorithm compared with the benchmark synthesis algorithms in the presence of array manifold vectors uncertainty.

Description: In this paper, global position system high-resolution sounding data from 1998 to 2008 were used to statistically analyze the spatiotemporal distribution and determine the probability, thickness, and intensity of atmospheric ducts at 12 stations in Alaska. In addition, the singular value decomposition (SVD) was used to examine the relationship between the Arctic vortex and atmospheric ducts. The annual average probability of atmospheric ducts, primarily surface and elevation ducts, was approximately 30% in Alaska. The probability of elevation ducts was greater than that of surface ducts. The Arctic vortex area and intensity index of each subarea were significantly negatively correlated with the occurrence of atmospheric ducts. Thus, when the area of the Arctic vortex increased and the intensity index of each subarea strengthened, the probability of atmospheric ducts decreased and their characteristics weakened.

Description: The Direction-of-Arrival (DoA) and bandwidth (BW) estimation strategy impinging on a linear array using multiple snapshots data is addressed within the multitask Bayesian Compressive Sensing (MT-BCS). The DoA estimation is used as the reconstruction of sparse signal constrained by the Laplace prior through multitask Bayesian Compressive Sensing. Receiving wideband signal data through linear array, the space is divided into I parts according to the equal interval. The data of interest are assumed to be represented as I-dimensional vector, and the wideband signal can be reconstructed accurately using only a small number M. The receiving antenna operates in the frequency range . Starting from the voltages measured at the output of the array elements at a multiple time instants at , the retrieval of the DoAs is addressed by means of a customized strategy based on MT-BCS in order to correlate the solutions obtained over different frequency samples. The bandwidth of the signals is obtained as a byproduct by identifying at which frequencies the MT-BCS estimations include a signal along the ith (i = 1,…, I) sampling direction. From the outputs of different frequencies, we can know the DoA and BW of signals. A preliminary numerical result is reported to show the behavior of the proposed approach in multiple snapshots data.

Description: Chad is like many African countries with no meteorological station at the moment to measure solar radiation throughout the country. Thus, theoretical models are used to estimate incident solar radiation. These models are established in correlation form. Our objective was to present a model, which allows the determination of the solar component on two surfaces (horizontal and inclined). This model allowed us to determine, over time, the component of global, direct, and diffuse solar radiation over a period that will cover the different seasons of the year. The calculation is done according to Klein’s days over all the months of the year. The hourly results of the global, direct, and diffuse radiation obtained for all the planes going from January to December are satisfactory compared to the results of the other authors quoted in the literature, which give the maximum and minimum values very close to theirs. These results allowed us to validate the applicability of this model in a climate other than the desert climate.

Description: Bifacial solar cells based on organic-inorganic perovskite are fabricated with a laminating process. The structure of the devices is ITO/SnO2/CH3NH3PbI3/NiO/ITO, in which both electrodes are the transparent ITO layer. Therefore, the device can receive light from both sides. By laminating the two half-devices, ITO/SnO2/CH3NH3PbI3 and CH3NH3PbI3/NiO/ITO, at high temperature with pressure, the merging of the middle perovskite layers is enhanced. The optimized bifacial PSCs show a Voc of 0.85 V, FF of 0.58, Jsc of 17.53 mA/cm2, and PCE of 8.47%. The photovoltaic performance varies when the light is illuminated from different sides of the bifacial PSCs. With illumination from the SnO2 side, the Voc and Jsc of the PSCs are apparently higher than those from the NiO side, suggesting more severe electron-hole recombination at the NiO/perovskite interface than at the SnO2/perovskite interface.

Description: Residential and commercial buildings consume approximately 60% of the world’s electricity. It is almost impossible to provide a general definition of thermal comfort, because the feeling of thermal comfort is affected by varying preferences and specific traits of the population living in different climate zones. Considering that no studies have been conducted on thermal satisfaction of net-zero energy buildings prior to this date, one of the objectives of the present study is to draw a comparison between the thermal parameters for evaluation of thermal comfort of a net-zero energy building occupants. In so doing, the given building for this study is first optimized for the target parameters of thermal comfort and energy consumption, and, hence, a net-zero energy building is formed. Subsequent to obtaining the acceptable thermal comfort range, the computational analyses required to determine the temperature for thermal comfort are carried out using the Computational Fluid Dynamics (CFD) model. The findings of this study demonstrate that to reach net-zero energy buildings, solar energy alone is not able to supply the energy consumption of buildings and other types of energy should also be used. Furthermore, it is observed that optimum thermal comfort is achieved in moderate seasons.

Description: The aim of this study is to investigate the flocculation capacity of activated sludge flocculant in chromium ion and nitrobenzene solutions. Besides comparing with activated carbon, we changed some potential factors which may influence the flocculation, such as solution pH value, reaction time, flocculant dosage, and solution initial concentration, and tested the flocculation capacity of this bioflocculant for both chromium and nitrobenzene. In addition, the flocculation of activated sludge after acidic or alkali modification for double solutions was also estimated. Compared with activated carbon, the activated sludge flocculant showed a good flocculation capacity for nitrobenzene, but poor flocculation for chromium following the initial concentration increase. The flocculation for nitrobenzene or chromium increased at initial stage and decreased gradually following the primary dosage of flocculant increase. The flocculation for nitrobenzene increased at the primary stage and decreased after peak, while the flocculation for chromium increased following the pH increase of both solutions. Although the flocculation for nitrobenzene decreased, the flocculation for chromium increased obviously, when we prolonged the reaction time. The flocculant showed a gradual increasing trend in double kinds of solution when they were heating. The flocculation for both nitrobenzene and chromium decreased after acid modification of activated sludge flocculant, while the flocculation increased after basic modification. The present research provided further theoretical basis of the biosorption of heavy metal waste water and nitrobenzene organic toxicants.

Description: We have demonstrated the ability of thin nanocrystalline SiC films with various types of conductivity to detect oxidative (O2), reducing gases (CO, CH4) with the maximum allowable concentrations for human safety. It was shown that n-nc-SiC films with electronic conductivity had a higher gas sensitivity Sn than p-nc-SiC films with hole conductivity sensivity Sp to the action of gases in a wide concentration range. So, for the maximum permissible concentrations of O2 (3%), CO (0.1%), CH4 (10%) the sensitivity ratio of the films Sn/Sp was 2.9; 4.8 and 10, respectively. For research, we used a simple resistor geometry optimizing which it is possible to significantly increase the sensitivity of films to gases in order to detect extremely low gas concentrations. Thus, based on nc-SiC films, it is possible to develop high-temperature gas sensors to detect reactive gases in a wide range of concentrations, including threshold allowable values.

Description: The increasing use of photovoltaic systems entails the use of new technologies to improve the efficiency and power quality of the grid. System performance is constantly increasing, but its reliability decreases due to factors such as the uncontrolled operation, the quality of the design and quantity of components, and the use of nonlinear loads that may lead to distortion in the signal, which directly affects the life of the system globally. This article presents an analysis of the reliability of a single-phase full-bridge inverter for active power injection into the grid, which considers the inverter stage with its coupling stage. A comparison between an L filter and an LCL filter, which comprise the coupling stage, is made. Reliability prediction is based on metrics, failure rate, mean time between failures, and total harmonic distortion. The analysis and numerical simulation are performed. Finally, filter considerations are suggested to extend the reliability of the inverter in a photovoltaic system.

Description: A platinum-reduced graphene oxide thin film composite (Pt@rGO, 100 nm) was prepared on a fluorine-doped tin oxide- (FTO-) coated glass substrate by a screen printing method using a Pt@rGO screen printing paste (0.12% Pt; ). The as-prepared electrode (denoted as Pt@rGO/FTO) was used as the cathode for the assembly of dye-sensitized solar cells (DSSCs). It showed a well-dispersed and high loading of Pt on rGO surface with a particle size distributed around 10 nm. The redox behavior of ferrocene was performed at Pt/FTO, Pt@rGO/FTO, and rGO/FTO electrodes by a cyclic voltammetry (CV) method. The kinetic parameters, in particular, the standard reduction potential (, V), the transfer coefficient (), the heterogeneous rate constant (, cm·s-1), and the diffusion coefficient (, cm2 s-1), were determined by CV data treatment using convolution-deconvolution and fitting methods. The values of ,,, and at Pt@rGO/FTO electrode were, respectively, 326 mV, 0.471, 3.33 cm·s-1, and 4.19 cm2·s-1, equivalent to those of Pt/FTO electrode (340 mV, 0.474, 3.18 cm·s-1, and 4.19 cm2·s-1). The Pt@rGO/FTO electrode exhibited excellent electrocatalytic activity compared to that of Pt thin film (Pt/FTO electrode) prepared from Pt commercial paste. The heterogeneous electron transfer rate constant (cm·s-1) for I3-/I- at Pt@rGO/FTO is 1.3 times faster than that at Pt/FTO. The energy conversion efficiency of the DSSCs assembled from Pt@rGO-DSSC cathode reached 7.0%, an increase of 20.7% over the commercial Pt-based cathode (Pt-DSSC, 5.8%). The rGO component in the Pt@rGO composite plays two important roles: (i) facilitating the electron transfer between Pt NPs catalyst and the FTO substrate via the bandgap effect and (ii) the enlargement catalytic surface area of Pt NPs via the loading effect. The rGO material has, therefore, potential to replace the Pt content and improve the performance of the DSSC device.

Description: Electric discharges seriously threat the safety of high-voltage switchgear. In this paper, a spectrum-based optical method is proposed for hazardous discharge monitoring. A SiPM-based trinal spectral sensor is developed with good performances in terms of sensitivity, defect resolution, and risk evaluation. Experiments carried out on two types of artificial discharges (i.e., partial discharge and arc discharge) demonstrate that the light intensities coupled in the three spectral bands account for different proportions and the ratio among the three components generally experiences a regular change with increase in severity of discharge. The typical spectral ratio values are then acquired for hazard rating of discharge and recognition of discharge types with high confidence.

Description: With the development of urbanization, land surface temperature (LST), as a vital variable for the urban environment, is highly demanded by urban-related studies, especially the LST with both fine temporal and spatial resolutions. Thermal sharpening methods have been developed just under this demand. Until now, there are some thermal sharpening methods proposed especially for urban surface. However, the evaluation of their accuracy still stopped at the level that only considers the statistical aspect, but no spatial information has been included. It is widely acknowledged that the spatial pattern of the thermal environment in an urban area is relatively critical for urban-related studies (e.g., urban heat island studies). Thus, this paper chose three typical methods from the limited number of thermal sharpening methods designed for the urban area and made a comparison between them, together with a newly proposed thermal sharpening method, superresolution-based thermal sharpener (SRTS). These four methods are analyzed by data from different seasons to explore the seasoning impact. Also, the accuracy for different land covers is explored as well. Furthermore, accuracy evaluation was not only taken by statistical variables which are commonly used in other studies; evaluation of the spatial pattern, which is equally important for urban-related studies, was also carried out. This time, the spatial pattern not only was analyzed qualitatively but also has been quantified by some variables for the comparison of accuracy. It is found that all methods obtained lower accuracies for data in winter than for data in other seasons. Linear water features and areas along it are difficult to be detected correctly for most methods.

Description: The most important aspect of virtual reality (VR) is the degree by which a user can feel and experience virtual space as though it is reality. Until recently, the experience of VR had to be satisfied with operations using a separate controller along with the visual and auditory elements. However, for a far more realistic VR environment, users should be able to experience the delicacy of tactile materials. This study proposes tactile technology, which is inexpensive and easy to use. To achieve this, we analyzed the unique patterns of materials through image filtering and designed a computing model to deliver realistic vibrations to the user. In addition, we developed and tested a haptic glove so that the texture of the material can be sensed in a VR environment.