bluuebunny/crossref_metadata_2025 huggingface dataset:
Parallel Spectral–Spatial Attention Network with Feature Redistribution Loss for Hyperspectral Change Detection
Authors: Huang Yixiang , Zhang Lifu , Huang Changping , Qi Wenchao , Song Ruoxi
Published: January 2023

Change detection methods using hyperspectral remote sensing can precisely identify differences of the same area at different observing times. However, due to massive spectral bands, current change detection methods are vulnerable to unrelatedspectral and spatial information in hyperspectral images with the stagewise calculation of attention maps. Besides, current change methods arrange hidden change features in a random distribution form, which cannot express a class-oriented discrimination in advance. Moreover, existent deep change methods have not fully considered the hierarchical features’ reuse and the fusion of the encoder–decoder framework. To better handle the mentioned existent problems, the parallel spectral–spatial attention network with feature redistribution loss (TFR-PS2ANet) is proposed. The contributions of this article are summarized as follows: (1) a parallel spectral–spatial attention module (PS2A) is introduced to enhance relevant information and suppress irrelevant information in parallel using spectral and spatial attention maps extracted from the original hyperspectral image patches; (2) the feature redistribution loss function (FRL) is introduced to construct the class-oriented feature distribution, which organizes the change features in advance and improves the discriminative abilities; (3) a two-branch encoder–decoder framework is developed to optimize the hierarchical transfer and change features’ fusion; Extensive experiments were carried out on several real datasets. The results show that the proposed PS2A can enhance significant information effectively and the FRL can optimize the class-oriented feature distribution. The proposed method outperforms most existent change detection methods.
Effect of Urban Built-Up Area Expansion on the Urban Heat Islands in Different Seasons in 34 Metropolitan Regions across China
Authors: Han Wenchao , Tao Zhuolin , Li Zhanqing , Cheng Miaomiao , Fan Hao , Cribb Maureen , Wang Qi
Published: January 2023

The urban heat island (UHI) refers to the land surface temperature (LST) difference between urban areas and their undeveloped or underdeveloped surroundings. It is a measure of the thermal influence of the urban built-up area expansion (UBAE), a topic that has been extensively studied. However, the impact of UBAE on the LST differences between urban areas and rural areas (UHIU−R) and between urban areas and emerging urban areas (UHIU−S) in different seasons has seldom been investigated. Here, the UHIU−S and UHIU−R in 34 major metropolitan regions across China, and their spatiotemporal variations based on long-term space-borne observations during the period 2001–2020 were analyzed. The UBAE quantified by the difference in landscape metrics of built-up areas between 2020 and 2000 and their impact on UHI was further analyzed. The UBAE is impacted by the level of economic development and topography. The UBAE of cities located in more developed regions was more significant than that in less developed regions. Coastal cities experienced the most obvious UBAE, followed by plain and hilly cities. The UBAE in mountainous regions was the weakest. On an annual basis, UHIU−R was larger than UHIU−S, decreasing more slowly with UBAE than UHIU−S. In different seasons, the UHIU−S and UHIU−R were larger, more clearly varying temporally with UBAE in summer than in winter, and their temporal variations were significantly correlated with UBAE in summer but not in winter. The seasonal difference in UHIU−R was larger than that of UHIU−S. Both the UHIU−S and UHIU−R in coastal cities were the lowest in summer, decreasing the fastest with UBAE, while those in mountain cities decreased the slowest. The change in the density of built-up lands was the primary driver affecting the temporal variations in UHIU−S and UHIU−R during UBAE, followed by changes in proportion and shape, while the impact of the speed of expansion was the smallest, all of which were more obvious in summer than in winter. The decreased density of built-up lands can reduce UHI. These findings provide a new perspective for a deeper understanding of the effect of urban expansion on LST in different seasons.
Evaluating the Impact of Soil Enthalpy upon the Thawing Process of the Active Layer in Permafrost Regions of the Qinghai–Tibet Plateau Using CLM5.0
Authors: Wang Shenning , Li Ren , Wu Tonghua , Zhao Lin , Wu Xiaodong , Hu Guojie , Yao Jimin , Ma Junjie , Liu Wenhao , Jiao Yongliang , Xiao Yao , Yang Shuhua , Shi Jianzong , Qiao Yongping
Published: January 2023

The hydrothermal dynamics of the active layer is a key issue in the study of surface processes in permafrost regions. Even though the soil energy budget is controlled by thermal conduction and latent heat transfer, few studies have focused on their effects upon the active layer thickness (ALT). In the present study, the community land model (CLM) version 5.0 is used to simulate the soil temperature and moisture of the active layers at the Tanggula (TGL) and Beiluhe (BLH) stations in permafrost regions of the Qinghai–Tibet Plateau based on the theory of soil enthalpy in order to estimate the soil energy state and analyze the energy changes in the active layer during freezing and thawing. The results indicate that the soil enthalpy has significant seasonal variation characteristics, which accurately reflected the freezing and thawing processes of the active layer. The change in soil enthalpy is significantly related to the thawing depth of the active layer in TGL and BLH, and its changing process can be expressed as an exponential relationship. Near the surface, the variation of the energy due to temperature gradient and actual evaporation can also be expressed as an exponential relationship. The promoting effect of heat conduction on the ALT is greater than the inhibiting effect of latent heat transfer, with the energy contribution from the phase change accounting for about 20–40% of the energy due to the temperature gradient. The thawing depth increases by 14.16–18.62 cm as the energy due to the temperature gradient increases by 1 MJ/m2 and decreases by 2.75–7.16 cm as the energy due to the phase change increases by 1 MJ/m2. Thus, the present study quantifies the effects of soil energy upon the ALT and facilitates an understanding of the hydrothermal processes in soils in permafrost regions.
Comparison of GRACE/GRACE-FO Spherical Harmonic and Mascon Products in Interpreting GNSS Vertical Loading Deformations over the Amazon Basin
Authors: Wang Pengfei , Wang Song-Yun , Li Jin , Chen Jianli , Qi Zhaoxiang
Published: January 2023

We compute the vertical displacements in the Amazon Basin using the Gravity Recovery and Climate Experiment (GRACE) and GRACE Follow-On (GRACE-FO) observations, including both the gravity spherical harmonic (SH) solutions from the Center for Space Research (CSR), GeoForschungsZentrum (GFZ) and Jet Propulsion Laboratory (JPL) and mascons from CSR, JPL and Goddard Space Flight Center (GSFC). The correlation coefficients, annual amplitude and root mean squares (RMS) reductions are calculated to assess the agreements between the GRACE/GRACE-FO and Global Navigation Satellite System (GNSS) vertical displacements at 22 selected GNSS stations. For the six GRACE/GRACE-FO products (i.e., CSR SH, GFZ SH, JPL SH, CSR mascon, GSFC mascon and JPL mascon), the mean annual amplitude reductions are 77.6%, 76.4%, 76.3%, 78.6%, 78.5% and 76.6%, respectively, the corresponding mean RMS reductions are 63.2%, 61.7%, 62.3%, 64.9%, 65.3% and 63.8%, respectively, and the mean correlation coefficients are all over 0.93. On the whole, mascon solutions agree slightly better with GNSS solutions than SH solutions do. The CSR SH and the GSFC mascon solutions show the best agreements with the GNSS solution among the 3 SH and 3 mascon products, respectively. We estimate GRACE/GRACE-FO noises using the three-cornered hat (TCH) method and find that the CSR SH and GSFC mascons also have the smallest noise variances among the SH and mascon products, respectively. By analyzing the GNSS stations from the central and southern Amazon Basin, we find that: (1) the RMS reductions when the mascon solutions are removed from GNSS height series are slightly larger than those using the SH solutions in the center, while in south all the RMS reductions are fairly close; (2) for both SH solutions and mascon solutions, the correlation coefficients in the center are slightly larger than those in the south, but conversely, the mean annual amplitude reductions in the center are much smaller than those in the south.
An Overview of Shoreline Mapping by Using Airborne LiDAR
Authors: Wang Junbo , Wang Lanying , Feng Shufang , Peng Benrong , Huang Lingfeng , Fatholahi Sarah N. , Tang Lisa , Li Jonathan
Published: January 2023

Since the shorelines are important geographical boundaries, monitoring shoreline change plays an important role in integrated coastal management. With the evolution of remote sensing technology, many studies have used optical images to measure and to extract shoreline. However, some factors limit the use of optical imaging on shoreline mapping. Considering that the airborne LiDAR data can provide more accurate topographical information, there are some studies that have been investigated using airborne LiDAR to map shorelines. However, a literature review that combines airborne LiDAR with shoreline measurement and extracting methods has not yet been conducted. The motivation of this paper is to present a narrative review of shoreline mapping by using airborne LiDAR, including a laser scanning system, data availability, and current extraction techniques over the past two decades. Therefore, we conducted a broad search and finally summarized more than 130 articles on airborne LiDAR technology for shoreline measurement and shoreline extraction. We find that shoreline mapping by using airborne LiDAR still meets the challenge, such as objective condition limitations, data availability limitations, and self-characteristic limitations. The current method of shoreline extraction has a great potential to be improved; particularly when combined with the emerging current state-of-the-art LiDAR point cloud processing techniques (e.g., deep-learning algorithms), they will have a brighter future. This review paper provides an overview and the current trend of shoreline mapping using airborne LiDAR, and points out the limitations, challenges, and future opportunities. Moreover, it also can serve as a starting point for novices and experts to study the shoreline mapping by using airborne LiDAR, which provides a scientific support for studying shoreline changes.
Imaging the Fault Zone Structure of the Pearl River Estuary Fault in Guangzhou, China, from Waveform Inversion with an Active Source and Dense Linear Array
Authors: Ma Xiaona , Wang Weitao , Xu Shanhui , Yang Wei , Zhang Yunpeng , Dong Chuanjie
Published: January 2023

Since high-resolution structure imaging of active faults within urban areas is vital for earthquake hazard mitigation, we perform a seismic survey line crossing the Pearl River Estuary Fault (PREF) in Guangzhou, China. First, ten shots of a new and environmentally friendly gas explosion source are excited with about 1 km spacing and recorded by 241 nodal short-period seismometers with an average spacing of 60 m. Then, based on these acquisition data, we adopt waveform inversion to explore the kinematic and dynamic information of early arrival wavefields to recover the subsurface structures. The inversion results indicate that while the low-velocity zone (LVZ) in depth surrounding the PREF is 2.5 km in width and extended to 0.7 km, another LVZ of 1.5 km in width and extended to 0.7 km in depth is surrounded by the Beiting–Nancun fault. We observe that the analysis of evolution and activities of the fault systems reveal no historical earthquakes in our study area; we interpret that the two LVZs controlled by the faults are probably attributed to the fluid dynamics, sediment source, and fault motion at different geological times, rather than fault-related damage zones. The results can provide significant basis for earthquake prevention and hazard assessment in Guangzhou. The finding also shows that the waveform inversion can effectively explore the fine structure of active faults in urban area with dense linear array and spare active source excitations.
Application of Geomatic Techniques for the Assessment of Anthropogenic Changes in the Urban Beaches of “La Magdalena” (Santander, Spain)
Authors: Flor Germán , Sánchez-Fernández Manuel , Flor-Blanco Germán , de Sanjosé Blasco José Juan
Published: January 2023

Since the 1970s, dredging sands have been poured onto the embayed beaches of La Magdalena in the western mouth of the estuarine Bay of Santander (N Spain) in order to increase beach width. Up until the year 2000, the sands were systematically fed by a trailing suction dredge, which was later replaced by truck sand transfers from the surplus sands of the western beach to the eastern ones and by mechanical redistribution to create artificial berms. A recent project aimed to solve sand losses after each storm by building two perpendicular breakwaters about 620 m apart. The eastern breakwater was built in the early summer of 2018, and wave storms in November 2018, February 2019, October 2020 and the last days of 2021 progressively dismantled the reconstructed upper beach areas and eroded other segments. The western breakwater, however, designed to retain the E–W sandy beach drift, was never built. Four photogrammetric restitutions from 2005, 2010, 2014 and 2017 and an aerial LiDAR in 2012 were obtained to better understand the previous topographic distribution of the back and foreshore. Numerous field observations were made, and six field surveys have been performed since 2018 using laser TLS and GNSS, which occurred in November 2018, March 2019, October 2019, March 2020, October 2020 and April 2021. The definitive results of the evolution of the sand loss are presented, a hypothesis is proposed to explain the dynamo-sedimentary trend, in which longitudinal transport dominates promoting the formation in the progress of a new sand beach, and some sustainable solutions are proposed. The results show that the constructive solution has failed to stabilize the beach and that the predictive models that justified it have not coincided with the real dynamic and sedimentary evolution.
Pre-Seismic Anomaly Detection from Multichannel Infrared Images of FY-4A Satellite
Authors: Yue Yingbo , Chen Fuchun , Chen Guilin
Published: January 2023

Research of seismic infrared remote sensing has been undertaken for several decades, but there is no stable and effective earthquake prediction method. A new algorithm combining the long short-term memory and the density-based spatial clustering of applications with noise models is proposed to extract the anomalies from the multichannel infrared remote sensing images of the Fengyun-4 satellites. A statistical analysis is used to validate the correlation between the anomalies and earthquakes. The results show that the correlation rate is 64.29%, the hit rate is 68.75%, and the probability gain is about 1.91. In the Madoi and YangBi earthquake cases, the infrared anomaly detected in this paper is correlated with the TEC anomaly found in the previous research. This indicates that it is feasible to combine multi-source data to improve the accuracy of earthquake prediction in future studies.
On the Choice of the Most Suitable Period to Map Hill Lakes via Spectral Separability and Object-Based Image Analyses
Authors: Maltese Antonino
Published: January 2023

Technological advances in Earth observation made images characterized by high spatial and temporal resolutions available, nevertheless bringing with them the radiometric heterogeneity of small geographical entities, often also changing in time. Among small geographical entities, hill lakes exhibit a widespread distribution, and their census is sometimes partial or shows unreliable data. High resolution and heterogeneity have boosted the development of geographic object-based image analysis algorithms. This research analyzes which is the most suitable period for acquiring satellite images to identify and delimitate hill lakes. This is achieved by analyzing the spectral separability of the surface reflectance of hill lakes from surrounding bare or vegetated soils and by implementing a semiautomatic procedure to enhance the segmentation phase of a GEOBIA algorithm. The proposed procedure was applied to high spatial resolution satellite images acquired in two different climate periods (arid and temperate), corresponding to dry and vegetative seasons. The segmentation parameters were tuned by minimizing an under- and oversegmentation metric on surfaces and perimeters of hill lakes selected as the reference. The separability of hill lakes from their surrounding was evaluated using Euclidean and divergence metrics both in the arid and temperate periods. The classification accuracy was evaluated by calculating the error matrix and normalized error matrix. Classes’ reflectances in the image acquired in the arid period show the highest average separability (3–4 higher than in the temperate one). The segmentation based on the reference areas performs more than that based on the reference perimeters (metric ≈ 20% lower). Both separability metrics and classification accuracies indicate that images acquired in the arid period are more suitable than temperate ones to map hill lakes.
Generation of Multiple Frames for High Resolution Video SAR Based on Time Frequency Sub-Aperture Technique
Authors: Yang Congrui , Chen Zhen , Deng Yunkai , Wang Wei , Wang Pei , Zhao Fengjun
Published: January 2023

Video Synthetic Aperture Radar (ViSAR) operating in spotlight mode has received widespread attention in recent years because of its ability to form a sequence of SAR images for a region of interest (ROI). However, due to the heavy computational burden of data processing, the application of ViSAR is limited in practice. Although back projection (BP) can avoid unnecessary repetitive processing of overlapping parts between consecutive video frames, it is still time-consuming for high-resolution video-SAR data processing. In this article, in order to achieve the same or a similar effect to BP and reduce the computational burden as much as possible, a novel time-frequency sub-aperture technology (TFST) is proposed. Firstly, based on azimuth resampling and full aperture azimuth scaling, a time domain sub-aperture (TDS) processing algorithm is proposed to process ViSAR data with large coherent integration angles to ensure the continuity of ViSAR monitoring. Furthermore, through frequency domain sub-aperture (FDS) processing, multiple high-resolution video frames can be generated efficiently without sub-aperture reconstruction. In addition, TFST is based on the range migration algorithm (RMA), which can take into account the accuracy while ensuring efficiency. The results of simulation and X-band airborne SAR experimental data verify the effectiveness of the proposed method.
Comparison of Lake Extraction and Classification Methods for the Tibetan Plateau Based on Topographic-Spectral Information
Authors: Wang Xiaoliang , Zhou Guangsheng , Lv Xiaomin , Zhou Li , Hu Mingcheng , He Xiaohui , Tian Zhihui
Published: January 2023

Accurate identification and extraction of lake boundaries are the basis of the accurate assessment of lake changes and their responses to climate change. To reduce the effects of lake ice and snow cover, mountain shadows, cloud and fog shielding, alluvial and proluvial deposits, and shoals on the extraction of lake boundaries on the Tibetan Plateau, this study developed an RNSS water index to increase the contrast between the lake and similar surface objects of the spectral curve, and constructed a new method flow for lake extraction on the Tibetan Plateau based on image synthesis, topographic-spectral feature indexes, and machine learning algorithms. The lake extraction effects of three common machine learning classification algorithms were compared: the Cart decision tree, random forest (RF), and gradient boosting decision tree (GBDT). The results show that the new lake extraction method based on topographic-spectral characteristics and the GBDT classification method had the highest extraction accuracy for Tibetan Plateau lakes in 2016 and 2021. Its overall accuracy, Kappa coefficient, user’s accuracy, and producer’s accuracy for 2016 and 2021 were 99.81%, 0.887, 83.55%, 94.67% and 99.88%, 0.933, 89.18%, 98.24%, respectively, and the total area of lake extraction was the most consistent with the validation datasets. The three classification methods can effectively extract lakes covered by ice and snow, and the extraction effect was ranked as GBDT > RF > Cart. The lake extraction effect under mountain shadow was ranked as Cart > GBDT > RF, and the lake extraction effect under alluvial deposits and shoals was ranked as GBDT > RF > Cart. The results may provide technical support for extracting lakes from long time series and reveal the impact of climate change on Tibetan Plateau lakes.
IoT-Based Systems for Soil Nutrients Assessment in Horticulture
Authors: Postolache Stefan , Sebastião Pedro , Viegas Vitor , Postolache Octavian , Cercas Francisco
Published: January 2023

Soil nutrients assessment has great importance in horticulture. Implementation of an information system for horticulture faces many challenges: (i) great spatial variability within farms (e.g., hilly topography); (ii) different soil properties (e.g., different water holding capacity, different content in sand, sit, clay, and soil organic matter, different pH, and different permeability) for different cultivated plants; (iii) different soil nutrient uptake by different cultivated plants; (iv) small size of monoculture; and (v) great variety of farm components, agroecological zone, and socio-economic factors. Advances in information and communication technologies enable creation of low cost, efficient information systems that would improve resources management and increase productivity and sustainability of horticultural farms. We present an information system based on different sensing capability, Internet of Things, and mobile application for horticultural farms. An overview on different techniques and technologies for soil fertility evaluation is also presented. The results obtained in a botanical garden that simulates the diversity of environment and plant diversity of a horticultural farm are discussed considering the challenges identified in the literature and field research. The study provides a theoretical basis and technical support for the development of technologies that enable horticultural farmers to improve resources management.
Submillimeter Sized 2D Electrothermal Optical Fiber Scanner
Authors: Kaur Mandeep , Menon Carlo
Published: January 2023

Optical scanners are used frequently in medical imaging units to examine and diagnose cancers, assist with surgeries, and detect lesions and malignancies. The continuous growth in optics along with the use of optical fibers enables fabrication of imaging devices as small as a few millimeters in diameter. Most forward viewing endoscopic scanners contain an optical fiber acting as cantilever which is vibrated at resonance. In many cases, more than one actuating element is used to vibrate the optical fiber in two directions giving a 2D scan. In this paper, it is proposed to excite the cantilever fiber using a single actuator and scan a 2D region from its vibrating tip. An electrothermal actuator is optimized to provide a bidirectional (horizontal and vertical) displacement to the cantilever fiber placed on it. A periodic current, having a frequency equal to the resonant frequency of cantilever fiber, was passed through the actuator. The continuous expansion and contraction of the actuator enabled the free end of fiber to vibrate in a circle like pattern. A small change in the actuation frequency permitted the scanning of the area inside the circle.
Optimization of the Polarization Profile of Conical-Shaped Shells Piezoelectric Sensors
Authors: Horta Muñoz Sergio , Ruiz David
Published: January 2023

Conical shell structures are frequently submitted to severe static and dynamic mechanical loads that can result in situations that affect the service of the systems that are part of, or even cause catastrophic failures. For this reason, a common solution is to design an active deformation control system, usually using piezoelectric patches strategically distributed along the surface of the shell structure. Moreover, these elements may be part of an energy recovery system. This paper details the methodology to topologically optimize the placement of piezoelectric elements through a characteristic function, analysing static and free vibration loading cases by means of the finite element method. Then, the optimal arrangement of the electrode with different polarization profiles is distributed throughout the entire structure. The nature of the loading cases studied corresponds to a general situation where static loads and dynamics vibration are considered. The objective function of the problem only depends linearly on the displacement fields, and therefore, the optimal electrode profile can be obtained for any combination of loads. As a consequence, this technique allows for maximising the electric charge obtained, which results in a greater capacity for monitoring, actuation and/or energy harvesting.
A Study on Dynamic Motion Planning for Autonomous Vehicles Based on Nonlinear Vehicle Model
Authors: Tang Xin , Li Boyuan , Du Haiping
Published: January 2023

Autonomous driving technology, especially motion planning and the trajectory tracking method, is the foundation of an intelligent interconnected vehicle, which needs to be improved urgently. Currently, research on path planning methods has improved, but few of the current studies consider the vehicle’s nonlinear characteristics in the reference model, due to the heavy computational effort. At present, most of the algorithms are designed by a linear vehicle model in order to achieve the real-time performance at the cost of lost accuracy. To achieve a better performance, the dynamics and kinematics characteristics of the vehicle must be simulated, and real-time computing ensured at the same time. In this article, a Takagi–Sugeno fuzzy-model-based closed-loop rapidly exploring random tree algorithm with on-line re-planning process is applied to build the motion planner, which effectively improves the vehicle performance of dynamic obstacle avoidance, and plans the local obstacle avoidance path in line with the dynamic characteristics of the vehicle. A nonlinear vehicle model is integrated into the motion planner design directly. For fast local path planning mission, the Takagi–Sugeno fuzzy modelling method is applied to the modeling process in the planner design, so that the vehicle state can be directly utilized into the path planner to create a feasible path in real-time. The performance of the planner was evaluated by numerical simulation. The results demonstrate that the proposed motion planner can effectively generate a reference trajectory that guarantees driving efficiency with a lower re-planning rate.
Plasmonic Biosensors with Nanostructure for Healthcare Monitoring and Diseases Diagnosis
Authors: An Tongge , Wen Jiahong , Dong Zhichao , Zhang Yongjun , Zhang Jian , Qin Faxiang , Wang Yaxin , Zhao Xiaoyu
Published: January 2023

Nanophotonics has been widely utilized in enhanced molecularspectroscopy or mediated chemical reaction, which has major applications in the field of enhancing sensing and enables opportunities in developing healthcare monitoring. This review presents an updated overview of the recent exciting advances of plasmonic biosensors in the healthcare area. Manufacturing, enhancements and applications of plasmonic biosensors are discussed, with particular focus on nanolisted main preparation methods of various nanostructures, such as chemical synthesis, lithography, nanosphere lithography, nanoimprint lithography, etc., and describing their respective advances and challenges from practical applications of plasmon biosensors. Based on these sensing structures, different types of plasmonic biosensors are summarized regarding detecting cancer biomarkers, body fluid, temperature, gas and COVID-19. Last, the existing challenges and prospects of plasmonic biosensors combined with machine learning, mega data analysis and prediction are surveyed.
Preliminary Results of a Structural Health Monitoring System Application for Real-Time Debonding Detection on a Full-Scale Composite Spar
Authors: Ciminello Monica , Sikorski Bogdan , Galasso Bernardino , Pellone Lorenzo , Mercurio Umberto , Concilio Antonio , Apuleo Gianvito , Cozzolino Aniello , Kressel Iddo , Shoham Shay , Tur Moshe
Published: January 2023

The present paper reports the outcomes of activities concerning a real-time SHM system for debonding flaw detection based on ground testing of an aircraft structural component as a basis for condition-based maintenance. In this application, a damage detection method unrelated to structural or load models is investigated. In the reported application, the system is applied for real-time detection of two flaws, kissing bond type, artificially deployed over a full-scale composite spar under the action of external bending loads. The proposed algorithm, local high-edge onset (LHEO), detects damage as an edge onset in both the space and time domains, correlating current strain levels to next strain levels within a sliding inner product proportional to the sensor step and the acquisition time interval, respectively. Real-time implementation can run on a consumer-grade computer. The SHM algorithm was written in Matlab and compiled as a Python module, then called from a multiprocess wrapper code with separate operations for data reception and data elaboration. The proposed SHM system is made of FBG arrays, an interrogator, an in-house SHM code, an original decoding software (SW) for real-time implementation of multiple SHM algorithms and a continuous interface with an external operator.
Graph Learning-Based Blockchain Phishing Account Detection with a Heterogeneous Transaction Graph
Authors: Kim Jaehyeon , Lee Sejong , Kim Yushin , Ahn Seyoung , Cho Sunghyun
Published: January 2023

Recently, cybercrimes that exploit the anonymity of blockchain are increasing. They steal blockchain users’ assets, threaten the network’s reliability, and destabilize the blockchain network. Therefore, it is necessary to detect blockchain cybercriminal accounts to protect users’ assets and sustain the blockchain ecosystem. Many studies have been conducted to detect cybercriminal accounts in the blockchain network. They represented blockchain transaction records as homogeneous transaction graphs that have a multi-edge. They also adopted graph learning algorithms to analyze transaction graphs. However, most graph learning algorithms are not efficient in multi-edge graphs, and homogeneous graphs ignore the heterogeneity of the blockchain network. In this paper, we propose a novel heterogeneous graph structure called an account-transaction graph, ATGraph. ATGraph represents a multi-edge as single edges by considering transactions as nodes. It allows graph learning more efficiently by eliminating multi-edges. Moreover, we compare the performance of ATGraph with homogeneous transaction graphs in various graph learning algorithms. The experimental results demonstrate that the detection performance using ATGraph as input outperforms that using homogeneous graphs as the input by up to 0.2 AUROC.
A Near InfraRed Emissive Chemosensor for Zn2+ and Phosphate Derivatives Based on a Di-(2-picolyl)amine-styrylflavylium Push-Pull Fluorophore
Authors: Gomes Liliana J. , Carrilho João P. , Pereira Pedro M. , Moro Artur J.
Published: January 2023

A new Near InfraRed (NIR) fluorescent chemosensor for metal ions and anions is herein presented. The fluorophore is based on a styrylflavylium dye, a synthetic analogue of the natural anthocyanin family, with a di-(2-picolyl)amine (DPA) moiety as the metal chelating unit. The substitution pattern of the styrylflavylium core (with tertiary amines on positions 7 and 4′) shifts the optical properties of the dye towards the NIR region of the electronic spectra, due to a strong push-pull character over the π-conjugated system. The NIR chemosensor is highly sensitive to the presence of Zn2+, which induces a strong CHelation Enhanced Fluorescence (CHEF) effect upon binding to the DPA unit (2.7 fold increase). The strongest competing ion is Cu2+, with a complete fluorescence quenching, while other metals induce lower responses on the optical properties of the chemosensor. Subsequent anion screening of the Zn2+-chemosensor coordination compound has demonstrated a distinct selectivity towards adenosine 5′-triphosphate (ATP) and adenosine 5′-diphosphate (ADP), with high association constants (K ~ 106 M−1) and a strong CHEF effect (2.4 and 2.9 fold fluorescence increase for ATP and ADP, respectively). Intracellular studies with the Zn2+-complexed sensor showed strong luminescence in the cellular membrane of Gram– bacteria (E. coli) and mitochondrial membrane of mammalian cells (A659), which highlights its possible application for intracellular labelling.
A Method of Noise Reduction for Radio Communication Signal Based on RaGAN
Authors: Peng Liang , Fang Shengliang , Fan Youchen , Wang Mengtao , Ma Zhao
Published: January 2023

Radio signals are polluted by noise in the process of channel transmission, which will lead to signal distortion. Noise reduction of radio signals is an effective means to eliminate the impact of noise. Using deep learning (DL) to denoise signals can reduce the dependence on artificial domain knowledge, while traditional signal-processing-based denoising methods often require knowledge of the artificial domain. Aiming at the problem of noise reduction of radio communication signals, a radio communication signal denoising method based on the relativistic average generative adversarial networks (RaGAN) is proposed in this paper. This method combines the bidirectional long short-term memory (Bi-LSTM) model, which is good at processing time-series data with RaGAN, and uses the weighted loss function to construct a noise reduction model suitable for radio communication signals, which realizes the end-to-end denoising of radio signals. The experimental results show that, compared with the existing methods, the proposed algorithm has significantly improved the noise reduction effect. In the case of a low signal-to-noise ratio (SNR), the signal modulation recognition accuracy is improved by about 10% after noise reduction.
Three-Dimensional Printing Quality Inspection Based on Transfer Learning with Convolutional Neural Networks
Authors: Yang Cheng-Jung , Huang Wei-Kai , Lin Keng-Pei
Published: January 2023

Fused deposition modeling (FDM) is a form of additive manufacturing where three-dimensional (3D) models are created by depositing melted thermoplastic polymer filaments in layers. Although FDM is a mature process, defects can occur during printing. Therefore, an image-based quality inspection method for 3D-printed objects of varying geometries was developed in this study. Transfer learning with pretrained models, which were used as feature extractors, was combined with ensemble learning, and the resulting model combinations were used to inspect the quality of FDM-printed objects. Model combinations with VGG16 and VGG19 had the highest accuracy in most situations. Furthermore, the classification accuracies of these model combinations were not significantly affected by differences in color. In summary, the combination of transfer learning with ensemble learning is an effective method for inspecting the quality of 3D-printed objects. It reduces time and material wastage and improves 3D printing quality.
Assessment of Motor Evoked Potentials in Multiple Sclerosis
Authors: Šoda Joško , Pavelin Sanda , Vujović Igor , Rogić Vidaković Maja
Published: January 2023

Transcranial magnetic stimulation (TMS) is a noninvasive technique mainly used for the assessment of corticospinal tract integrity and excitability of the primary motor cortices. Motor evoked potentials (MEPs) play a pivotal role in TMS studies. TMS clinical guidelines, concerning the use and interpretation of MEPs in diagnosing and monitoring corticospinal tract integrity in people with multiple sclerosis (pwMS), were established almost ten years ago and refer mainly to the use of TMS implementation; this comprises the magnetic stimulator connected to a standard EMG unit, with the positioning of the coil performed by using the external landmarks on the head. The aim of the present work was to conduct a narrative literature review on the MEP assessment and outcome measures in clinical and research settings, assessed by TMS Methodological characteristics of different TMS system implementations (TMS without navigation, line-navigated TMS and e-field-navigated TMS); these were discussed in the context of mapping the corticospinal tract integrity in MS. An MEP assessment of two case reports, by using an e-field-navigated TMS, was presented; the results of the correspondence between the e-field-navigated TMS with MRI, and the EDSS classifications were presented. Practical and technical guiding principles for the improvement of TMS studies in MEP assessment for MS are discussed, suggesting the use of e-field TMS assessment in the sense that it can improve the accuracy of corticospinal tract integrity testing by providing a more objective correspondence of the neurophysiological (e-field-navigated TMS) and clinical (Expanded Disability Status Scale—EDSS) classifications.
Assessment of Water Flow Glazing as Building-Integrated Solar Thermal Collector
Authors: del Ama Gonzalo Fernando , Moreno Santamaría Belén , Hernández Ramos Juan A.
Published: January 2023

In buildings with ambitious energy goals or limited roof areas for on-site energy generation, building-integrated solar thermal collectors are one of the main strategies to provide on-site renewable energy to the built environment. In addition, designing large glazing facades is a challenge to achieving the goal of zero-energy buildings due to the thermal load produced by standard double or triple glazing. This research shows that Water Flow Glazing (WFG) can produce domestic hot water as a building-integrated solar thermal collector by flowing water through the chamber between glass panes and can help reduce thermal loads through facades. In this article, the solar collector’s efficiency was defined according to the UNE-EN 12975-2 standard and then applied to the Water Flow Glazing. As a result, the transparent Water Flow Glazing’s optical efficiency η0 varies from 0.648 to 0.742, whereas the thermal loss coefficient a1 ranges from 9.51 to 4.16. Those values are like those of commercial plate collectors. Afterward, the model to predict the efficiency of WFG was tested in an existing facility by calculating the Normalized Root Mean Square Error (NRMSE) to assess the deviations between the simulation and measured values. Using building-integrated solar collectors can improve the integration of renewable energies in facades and roofs but also increase the uncertainties that affect their efficiencies, such as internal heat loads and heating, cooling, and ventilation systems. Therefore, testing existing facilities can help understand the impact of these technologies in the Zero Energy Building paradigm.
Sustainability Factors of Self-Help Groups in Disaster-Affected Communities
Authors: Ghosh Sameek , Ray Sougata , Nair Rajiv
Published: January 2023

Self-help groups are informal associations that use social capital to overcome resource constraints and act as a catalyst for rural development, women, and social empowerment. This study tries to identify the factors that affect the sustainability of self-help groups in natural disaster-affected communities. Natural calamities in the form of droughts, floods, or cyclones pose major challenges to livelihood in disaster-prone regions. The study is based on survey data from two different disaster-prone locations: the cyclone- and flood-prone Sundarbans, and drought-prone Bankura in West Bengal, India. Applying principal component analysis to the responses of 143 self-help group members, the study identifies four factors responsible for the sustainability of these self-help groups. This study shows that managerial functions, trust, fund utilization, and easy financing are the factors that matter the most. The findings suggest that policymakers and local governments can focus on these aspects to ensure the effectiveness of self-help groups in meeting their social objectives.
Cost Analysis of Implementing In-Pipe Hydro Turbine in the United Arab Emirates Water Network
Authors: Alawadhi Ghaya , Almehiri Meera , Sakhrieh Ahmad , Alshwawra Ahmad , Al Asfar Jamil
Published: January 2023

Water transmission lines have potential reserved energy, which is usually lost. Therefore, targeting this clean energy to produce electricity to power up the auxiliaries and utilities of water plants or consumers is financially and environmentally beneficial. This paper aims to investigate the feasibility of installing an inline hydropower system in an existing transmission water pipe. It analyzes the feasibility of implementing a mini-hydropower plant in the transmission line of Liwa’s reservoir in the UAE. The maximum possible power harvested is 218.175 kW at the given water flow rate and net head. The payback period and the return on investment are analyzed based on different scenarios related to capital investment, operation, maintenance cost, and plant capacity factor. It is found that the payback period ranges between one to six years, where the return on investment can be as high as 85%. Furthermore, the expected CO2 emissions saving for this project is calculated to be between 395 and 1939 tons per year.
Thermal Transfer Analysis for Sports Footwear, for Performance Athletes, during Volleyball Training
Authors: Dragoș Paul Florian , Șuteu Marius Darius , Pancu Rareș , Buhaș Sorin Dacian
Published: January 2023

The purpose of this paper is a social one, to present various experimental thermal analyses of sports footwear to identify the areas that ensure the best foot ventilation for comfort in movement. The mechanical properties of the analyzed footwear were determined on the Nano Indenter Agilent G200, with the help of which Young’s modulus was determined according to ISO 14577. Thermography measurements were performed at the Oradea University Sports Club. The FLIR SC 640 thermal imaging camera was used, which is a portable thermographic scanning equipment. The measurements were performed on eight athletes (subjects) in a volleyball training session, wearing sports footwear (Asics and Mizuno). Thermographic recordings were made during training at five different times: moment zero (before the start of training), moment one (2 min of training), moment two (5 min of training), moment three (15 min of training), and moment four (at the end of the volleyball training session). For the other three subjects, although having different models of the same sports footwear, the analysis of the thermal distribution values shows they are within the minimum and maximum limits of the five subjects analyzed in the paper. Based on the thermographic recording values obtained, a mathematical model was determined using polynomial regression to predict temperature values outside the range of the experimental data. In the present paper, research was carried out in order to identify the thermal variations of indoor sports shoes used in volleyball training so as to detect the heat exchange between the foot and the outdoor environment. Whether we are talking about winter sports or sports that take place in other atmospheric conditions, the comfort given by the optimal temperature at the level of each body segment is certainly reflected in the level of performance achieved.
How Does Personality Affect COVID-19 Pandemic Travel Risk Perceptions and Behaviors? Evidence from Segment Analysis in Taiwan
Authors: Lee Tsung-Hung , Jan Fen-Hauh
Published: January 2023

This study aims to assess the risk perceptions and travel intentions of travelers who were segmented into groups based on their personality traits. In total, 684 useful questionnaires were obtained from Taiwan. A multivariate statistical analysis was performed for data analysis. Five clusters of travelers were identified via cluster analysis: sensitive travelers, cogitative travelers, temperate travelers, introverted travelers, and moderate travelers. These clusters exhibited significant differences in the personality traits, risk perceptions, and behavioral intentions of travelers. By introducing strategies for market segmentation that destination managers can use to develop better marketing strategies that target tourist personality traits during pandemic outbreaks, this study potentially contributes to the literature on travel risk, satisfaction, and behavioral intention, and applies marketing strategies from researchers in tourism studies.
Risk Assessment of Potentially Toxic Elements in Agricultural Soils of Al-Ahsa Oasis, Saudi Arabia
Authors: Alharbi Talal , El-Sorogy Abdelbaset S.
Published: January 2023

Contamination of soil with potentially toxic elements (PTEs) is receiving great attention worldwide due to its apparent toxicity and hazards to local residents. The assessments of soil PTE distribution, sources, and environmental risks are, therefore, the first steps of high-efficiency pollutant degradation and sustainable utilization. The current study used a variety of contamination indicators and multivariate methods to evaluate the environmental risk of As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn in Al-Ahsa soils in eastern Saudi Arabia. For analysis, 30 surface soil samples were collected from palm fields irrigated with groundwater and treated sewage water. Landsat images of Al-Ahsa indicated an increase in the total vegetative area and the residential area, and a decrease in the bare land area from 1985 to 2021. The average concentrations of PTEs (mg/kg−1) were lower than the maximum admissible concentrations and had the following decreasing order: Zn (54.43) > Cr (28.67) > Ni (14.53) > Cu (10.83) > Pb (5.23) > As (2.27) > Hg (0.35) > Cd (0.26). The enrichment factor (EF) findings confirmed that the Al-Ahsa soil is significantly enriched with Hg, moderately to severely enriched with As, and moderately enriched with Cd. The potential ecological risk index (RI) demonstrates a moderate ecological risk, with only certain parts presenting a high risk. The different PTE levels in agricultural soils may be caused partly by the various qualities of groundwater that originate from various aquifers and sewage-treated water. The results of a multivariate analysis showed that most of the anthropogenic sources of Hg, As, and Cd may come from using a lot of fertilizers and insecticides. Levels of the remaining PTEs indicated natural sources from earth crust materials.