-
Analysis and Compensation of Lorentz Force Magnetic Bearing Magnetic Flux Density Uniformity Error Sensors (IF 3.9) Pub Date : 2024-04-24 Chunmiao Yu, Yuanwen Cai, Weijie Wang, Wenjing Han, Zengyuan Yin, Wenting Han
Aiming at the influence of the magnetic flux density uniformity error (MFDUE) of the Lorentz force magnetic bearing (LFMB) on the sensitivity accuracy of magnetically suspended control and sensing gyroscopes (MSCSGs) on the angular rate of a spacecraft, a high precision measurement method of the angular rate of a spacecraft based on the MFDUE compensation of LFMB is proposed. Firstly, the structure
-
A Degraded Finger Vein Image Recovery and Enhancement Algorithm Based on Atmospheric Scattering Theory Sensors (IF 3.9) Pub Date : 2024-04-24 Dingzhong Feng, Peng Feng, Yongbo Mao, Yang Zhou, Yuqing Zeng, Ye Zhang
With the development of biometric identification technology, finger vein identification has received more and more widespread attention for its security, efficiency, and stability. However, because of the performance of the current standard finger vein image acquisition device and the complex internal organization of the finger, the acquired images are often heavily degraded and have lost their texture
-
Study on the Improvement of Droplet Penetration Effect by Nozzle Tilt Angle under the Influence of Orthogonal Side Wind Sensors (IF 3.9) Pub Date : 2024-04-24 Daozong Sun, Junyutai Hu, Xinghan Huang, Wenhao Luo, Shuran Song, Xiuyun Xue
This study investigates the impact of varying side wind velocities and nozzle inclination angles on droplet penetration during plant protection spraying operations, focusing on citrus trees. Experiments were conducted across four wind speed levels (0, 1, 2, 3 m/s) perpendicular to the nozzle direction and seven nozzle inclination levels (0°, 8°, 15°, 23°, 30°, 38°, 45°) to evaluate droplet distribution
-
Characterization of Anisotropic Salt Weathering through Nondestructive Techniques Mapping Using a GIS Environment Sensors (IF 3.9) Pub Date : 2024-04-24 Miguel Gomez-Heras, Laura López-González, María Teresa Gil-Muñoz, Cristina Cabello-Briones, David Benavente, Javier Martínez-Martínez
Doctrinal texts on architectural heritage conservation emphasize the importance of fully understanding the structural and material characteristics and utilizing information systems. Photogrammetry allows for the generation of detailed, geo-referenced Digital Elevation Models of architectural elements at a low cost, while GIS software enables the addition of layers of material characteristic data to
-
Reliability Analysis and Optimization of a Reconfigurable Matching Network for Communication and Sensing Antennas in Dynamic Environments through Gaussian Process Regression Sensors (IF 3.9) Pub Date : 2024-04-24 Seppe Van Brandt, Kamil Yavuz Kapusuz, Joryan Sennesael, Sam Lemey, Patrick Van Torre, Jo Verhaevert, Tanja Van Hecke, Hendrik Rogier
During the implementation of the Internet of Things (IoT), the performance of communication and sensing antennas that are embedded in smart surfaces or smart devices can be affected by objects in their reactive near field due to detuning and antenna mismatch. Matching networks have been proposed to re-establish impedance matching when antennas become detuned due to environmental factors. In this work
-
Improving Eye-Tracking Data Quality: A Framework for Reproducible Evaluation of Detection Algorithms Sensors (IF 3.9) Pub Date : 2024-04-24 Christopher Gundler, Matthias Temmen, Alessandro Gulberti, Monika Pötter-Nerger, Frank Ückert
High-quality eye-tracking data are crucial in behavioral sciences and medicine. Even with a solid understanding of the literature, selecting the most suitable algorithm for a specific research project poses a challenge. Empowering applied researchers to choose the best-fitting detector for their research needs is the primary contribution of this paper. We developed a framework to systematically assess
-
Reducing DNS Traffic to Enhance Home IoT Device Privacy Sensors (IF 3.9) Pub Date : 2024-04-24 Marta Moure-Garrido, Carlos Garcia-Rubio, Celeste Campo
The deployment of Internet of Things (IoT) devices is widespread in different environments, including homes. Although security is incorporated, homes can become targets for cyberattacks because of their vulnerabilities. IoT devices generate Domain Name Server (DNS) traffic primarily for communication with Internet servers. In this paper, we present a detailed analysis of DNS traffic from IoT devices
-
The Impact of Dual-Tasks and Disease Severity on Posture, Gait, and Functional Mobility among People Living with Dementia in Residential Care Facilities: A Pilot Study Sensors (IF 3.9) Pub Date : 2024-04-24 Deborah A Jehu, Ryan Langston, Richard Sams, Lufei Young, Mark Hamrick, Haidong Zhu, Yanbin Dong
Gait speed and timed-up-and-go (TUG) predict cognitive decline, falls, and mortality. Dual-tasks may be useful in cognitive screening among people living with dementia (PWD), but more evidence is needed. This cross-sectional study aimed to compare single- and dual-task performance and determine the influence of dementia severity on dual-task performance and interference. Thirty PWD in two residential
-
Batch Specular Plane Flatness Measurements Based on Phase Measuring Deflectometry Sensors (IF 3.9) Pub Date : 2024-04-24 Zhuotong Li, Dongxue Wang, Lei Liu, Xiaodong Zhang
Flatness is a critical parameter in the manufacturing industry, directly impacting the fit and overall product performance. As the efficiency of manufacturing continues to advance, there is an increasing demand for more accurate and efficient measurement techniques. Existing methods often struggle to strike a balance between precision and efficiency. In response, this article introduces a novel approach
-
Evaluating Vascular Depth-Dependent Changes in Multi-Wavelength PPG Signals Due to Contact Force Sensors (IF 3.9) Pub Date : 2024-04-24 Joan Lambert Cause, Ángel Solé Morillo, Bruno da Silva, Juan C. García-Naranjo, Johan Stiens
Photoplethysmography (PPG) is a non-invasive method used for cardiovascular monitoring, with multi-wavelength PPG (MW-PPG) enhancing its efficacy by using multiple wavelengths for improved assessment. This study explores how contact force (CF) variations impact MW-PPG signals. Data from 11 healthy subjects are analyzed to investigate the still understudied specific effects of CF on PPG signals. The
-
Polymer Nanocomposite Sensors with Improved Piezoelectric Properties through Additive Manufacturing Sensors (IF 3.9) Pub Date : 2024-04-24 Rishikesh Srinivasaraghavan Govindarajan, Zefu Ren, Isabel Melendez, Sandra K. S. Boetcher, Foram Madiyar, Daewon Kim
Additive manufacturing (AM) technology has recently seen increased utilization due to its versatility in using functional materials, offering a new pathway for next-generation conformal electronics in the smart sensor field. However, the limited availability of polymer-based ultraviolet (UV)-curable materials with enhanced piezoelectric properties necessitates the development of a tailorable process
-
R-Cut: Enhancing Explainability in Vision Transformers with Relationship Weighted Out and Cut Sensors (IF 3.9) Pub Date : 2024-04-24 Yingjie Niu, Ming Ding, Maoning Ge, Robin Karlsson, Yuxiao Zhang, Alexander Carballo, Kazuya Takeda
Transformer-based models have gained popularity in the field of natural language processing (NLP) and are extensively utilized in computer vision tasks and multi-modal models such as GPT4. This paper presents a novel method to enhance the explainability of transformer-based image classification models. Our method aims to improve trust in classification results and empower users to gain a deeper understanding
-
On the Influence of Humidity on a Thermal Conductivity Sensor for the Detection of Hydrogen Sensors (IF 3.9) Pub Date : 2024-04-24 Sophie Emperhoff, Matthias Eberl, Tim Dwertmann, Jürgen Wöllenstein
Thermal conductivity sensors face an omnipresent cross-influence through varying humidity levels in real-life applications. We present the results of investigations on the influence of humidity on a hydrogen thermal conductivity sensor and approaches for predicting the behavior of thermal conductivity towards humidity. A literature search and comparison of different mixing equations for binary gas
-
The Uncertainty Assessment by the Monte Carlo Analysis of NDVI Measurements Based on Multispectral UAV Imagery Sensors (IF 3.9) Pub Date : 2024-04-24 Fatemeh Khalesi, Imran Ahmed, Pasquale Daponte, Francesco Picariello, Luca De Vito, Ioan Tudosa
This paper proposes a workflow to assess the uncertainty of the Normalized Difference Vegetation Index (NDVI), a critical index used in precision agriculture to determine plant health. From a metrological perspective, it is crucial to evaluate the quality of vegetation indices, which are usually obtained by processing multispectral images for measuring vegetation, soil, and environmental parameters
-
Research on Decoupling Model of Six-Component Force Sensor Based on Artificial Neural Network and Polynomial Regression Sensors (IF 3.9) Pub Date : 2024-04-24 Shuyu Wang, Hongyue Liu
A two-stage decoupling model based on an artificial neural network with polynomial regression is proposed for the six-component force sensor load decoupling problem in the case of multidimensional mixed loading. The six-dimensional load categorization stage model constructed in the first stage combines 63 load category label sets with a deep BP neural network. The six-dimensional load regression stage
-
Compound Acoustic Radiation Force Impulse Imaging of Bovine Eye by Using Phase-Inverted Ultrasound Transducer Sensors (IF 3.9) Pub Date : 2024-04-24 Gil Su Kim, Hak Hyun Moon, Hee Su Lee, Jong Seob Jeong
In general, it is difficult to visualize internal ocular structure and detect a lesion such as a cataract or glaucoma using the current ultrasound brightness-mode (B-mode) imaging. This is because the internal structure of the eye is rich in moisture, resulting in a lack of contrast between tissues in the B-mode image, and the penetration depth is low due to the attenuation of the ultrasound wave.
-
Systematic Evaluation of Ultrasonic In-Line Inspection Techniques for Oil and Gas Pipeline Defects Based on Bibliometric Analysis Sensors (IF 3.9) Pub Date : 2024-04-24 Jie Huang, Pengchao Chen, Rui Li, Kuan Fu, Yanan Wang, Jinyao Duan, Zhenlin Li
The global reliance on oil and gas pipelines for energy transportation is increasing. As the pioneering review in the field of ultrasonic defect detection for oil and gas pipelines based on bibliometric methods, this study employs visual analysis to identify the most influential countries, academic institutions, and journals in this domain. Through cluster analysis, it determines the primary trends
-
Determination of Self-Heating in Silicon Photomultipliers Sensors (IF 3.9) Pub Date : 2024-04-24 Erika Garutti, Stephan Martens, Joern Schwandt, Carmen Villalba-Pedro
The main consequence of radiation damage on a silicon photomultiplier (SiPM) is a significant increase in the dark current. If the SiPM is not adequately cooled, the power dissipation causes it to heat up, which alters its performance parameters. To investigate this heating effect, a measurement cycle was developed and performed with a KETEK SiPM glued to an Al2O3 substrate and with HPK SiPMs glued
-
Research on a Sound Source Localization Method for UAV Detection Based on Improved Empirical Mode Decomposition Sensors (IF 3.9) Pub Date : 2024-04-24 Tao Chen, Jiyan Yu, Zhengpeng Yang
To address the challenge of accurately locating unmanned aerial vehicles (UAVs) in situations where radar tracking is not feasible and visual observation is difficult, this paper proposes an innovative acoustic source localization method based on improved Empirical Mode Decomposition (EMD) within an adaptive frequency window. In this study, the collected flight signals of UAVs undergo smoothing filtering
-
Study on Gesture Recognition Method with Two-Stream Residual Network Fusing sEMG Signals and Acceleration Signals Sensors (IF 3.9) Pub Date : 2024-04-24 Zhigang Hu, Shen Wang, Cuisi Ou, Aoru Ge, Xiangpan Li
Currently, surface EMG signals have a wide range of applications in human–computer interaction systems. However, selecting features for gesture recognition models based on traditional machine learning can be challenging and may not yield satisfactory results. Considering the strong nonlinear generalization ability of neural networks, this paper proposes a two-stream residual network model with an attention
-
Image Reconstruction Requirements for Short-Range Inductive Sensors Used in Single-Coil MIT Sensors (IF 3.9) Pub Date : 2024-04-24 Joe R. Feldkamp
MIT (magnetic induction tomography) image reconstruction from data acquired with a single, small inductive sensor has unique requirements not found in other imaging modalities. During the course of scanning over a target, measured inductive loss decreases rapidly with distance from the target boundary. Since inductive loss exists even at infinite separation due to losses internal to the sensor, all
-
High-Precision Visual Servoing for the Neutron Diffractometer STRESS-SPEC at MLZ Sensors (IF 3.9) Pub Date : 2024-04-24 Martin Landesberger , Oguz Kedilioglu , Lijiu Wang , Weimin Gan , Joana Rebelo Kornmeier , Sebastian Reitelshöfer , Jörg Franke , Michael Hofmann
With neutron diffraction, the local stress and texture of metallic components can be analyzed non-destructively. For both, highly accurate positioning of the sample is essential, requiring the measurement at the same sample location from different directions. Current sample-positioning systems in neutron diffraction instruments combine XYZ tables and Eulerian cradles to enable the accurate six-degree-of-freedom
-
Estimation of Ground Reaction Forces during Sports Movements by Sensor Fusion from Inertial Measurement Units with 3D Forward Dynamics Model Sensors (IF 3.9) Pub Date : 2024-04-24 Tatsuki Koshio, Naoto Haraguchi, Takayoshi Takahashi, Yuse Hara, Kazunori Hase
Rotational jumps are crucial techniques in sports competitions. Estimating ground reaction forces (GRFs), a constituting component of jumps, through a biomechanical model-based approach allows for analysis, even in environments where force plates or machine learning training data would be impossible. In this study, rotational jump movements involving twists on land were measured using inertial measurement
-
Temporal Relationship-Aware Treadmill Exercise Test Analysis Network for Coronary Artery Disease Diagnosis Sensors (IF 3.9) Pub Date : 2024-04-24 Jianze Wei, Bocheng Pan, Yu Gan, Xuedi Li, Deping Liu, Botao Sang, Xingyu Gao
The treadmill exercise test (TET) serves as a non-invasive method for the diagnosis of coronary artery disease (CAD). Despite its widespread use, TET reports are susceptible to external influences, heightening the risk of misdiagnosis and underdiagnosis. In this paper, we propose a novel automatic CAD diagnosis approach. The proposed approach introduces a customized preprocessing method to obtain clear
-
Coupling of Modes in Step-Index Plastic Optical Fibers by Using D-Shape Technique Sensors (IF 3.9) Pub Date : 2024-04-24 Cláudio Márcio F. Silva, Gefeson M. Pacheco, Jognes Panasiewicz, Luis A. Rabanal Ramirez
This article presents a technique for reducing the stabilization length of steady-state modes in step-index plastic optical fibers (POFs) that is important for sensor networks, Internet of Things, and signal processing and data fusion in sensor systems. The results obtained with the computational tool developed suggest that the D-shape created in the POF effectively reduces the stabilization length
-
A Multiple Attention Convolutional Neural Networks for Diesel Engine Fault Diagnosis Sensors (IF 3.9) Pub Date : 2024-04-24 Xiao Yang, Fengrong Bi, Jiangang Cheng, Daijie Tang, Pengfei Shen, Xiaoyang Bi
Fault diagnosis can improve the safety and reliability of diesel engines. An end-to-end method based on a multi-attention convolutional neural network (MACNN) is proposed for accurate and efficient diesel engine fault diagnosis. By optimizing the arrangement and kernel size of the channel and spatial attention modules, the feature extraction capability is improved, and an improved convolutional block
-
The Influence of Nonlinear High-Intensity Dynamic Processes on the Standing Wave Precession of a Non-Ideal Hemispherical Resonator Sensors (IF 3.9) Pub Date : 2024-04-24 Wei Cheng, Shunqing Ren, Boqi Xi, Zhen Tian, Youhuan Ning, Yan Huo
The properties of small size, low noise, high performance and no wear-out have made the hemispherical resonator gyroscope a good choice for high-value space missions. To enhance the precision of the hemispherical resonator gyroscope for use in tasks with large angular velocities and angular accelerations, this paper investigates the standing wave precession of a non-ideal hemispherical resonator under
-
Enhanced Lightweight YOLOX for Small Object Wildfire Detection in UAV Imagery Sensors (IF 3.9) Pub Date : 2024-04-24 Tian Luan, Shixiong Zhou, Guokang Zhang, Zechun Song, Jiahui Wu, Weijun Pan
Target detection technology based on unmanned aerial vehicle (UAV)-derived aerial imagery has been widely applied in the field of forest fire patrol and rescue. However, due to the specificity of UAV platforms, there are still significant issues to be resolved such as severe omission, low detection accuracy, and poor early warning effectiveness. In light of these issues, this paper proposes an improved
-
Color and Luminance Separated Enhancement for Low-Light Images with Brightness Guidance Sensors (IF 3.9) Pub Date : 2024-04-24 Feng Zhang, Xinran Liu, Changxin Gao, Nong Sang
Existing retinex-based low-light image enhancement strategies focus heavily on crafting complex networks for Retinex decomposition but often result in imprecise estimations. To overcome the limitations of previous methods, we introduce a straightforward yet effective strategy for Retinex decomposition, dividing images into colormaps and graymaps as new estimations for reflectance and illumination maps
-
Impact of Rainfall on the Detection Performance of Non-Contact Safety Sensors for UAVs/UGVs Sensors (IF 3.9) Pub Date : 2024-04-24 Yasushi Sumi, Bong Keun Kim, Takuya Ogure, Masato Kodama, Naoki Sakai, Masami Kobayashi
This study comprehensively investigates how rain and drizzle affect the object-detection performance of non-contact safety sensors, which are essential for the operation of unmanned aerial vehicles and ground vehicles in adverse weather conditions. In contrast to conventional sensor-performance evaluation based on the amount of precipitation, this paper proposes spatial transmittance and particle density
-
Curved and Annular Diaphragm Coupled Piezoelectric Micromachined Ultrasonic Transducers for High Transmit Biomedical Applications Sensors (IF 3.9) Pub Date : 2024-04-24 Yun Zhang, Tong Jin, Zijie Zhao, Chenfang Yan, Xinchao Lu, Hang Gao, Chengjun Huang
In this paper, we present a novel three-dimensional (3D) coupled configuration of piezoelectric micromachined ultrasound transducers (pMUTs) by combing a curved and an annular diaphragm for transmit performance optimization in biomedical applications. An analytical equivalent circuit model (EQC) is developed with varied excitation methods to incorporate the acoustic–structure coupling of the curved
-
Design and Experiment of an Unoccupied Control System for a Tracked Grain Vehicle Sensors (IF 3.9) Pub Date : 2024-04-24 Jiahui Pan, Lizhang Xu, En Lu, Buwang Dai, Tiaotiao Chen, Weiming Sun, Zhihong Cui, Jinpeng Hu
In order to enhance crop harvesting efficiency, an automatic-driving tracked grain vehicle system was designed. Based on the harvester chassis, we designed the mechanical structure of a tracked grain vehicle with a loading capacity of 4.5 m3 and a grain unloading hydraulic system. Using the BODAS hydraulic controller, we implemented the design of an electronic control system that combines the manual
-
Modified RTK-GNSS for Challenging Environments Sensors (IF 3.9) Pub Date : 2024-04-24 Ellarizza Fredeluces, Tomohiro Ozeki, Nobuaki Kubo, Ahmed El-Mowafy
Real-Time Kinematic Global Navigation Satellite System (RTK-GNSS) is currently the premier technique for achieving centimeter-level accuracy quickly and easily. However, the robustness of RTK-GNSS diminishes in challenging environments due to severe multipath effects and a limited number of available GNSS signals. This is a pressing issue, especially for GNSS users in the navigation industry. This
-
Hardware and Software Setup for Quantitative 23Na Magnetic Resonance Imaging at 3T: A Phantom Study Sensors (IF 3.9) Pub Date : 2024-04-24 Giulio Giovannetti, Alessandra Flori, Nicola Martini, Filippo Cademartiri, Giovanni Donato Aquaro, Alessandro Pingitore, Francesca Frijia
Magnetic resonance (MR) with sodium (23Na) is a noninvasive tool providing quantitative biochemical information regarding physiology, cellular metabolism, and viability, with the potential to extend MR beyond anatomical proton imaging. However, when using clinical scanners, the low detectable 23Na signal and the low 23Na gyromagnetic ratio require the design of dedicated radiofrequency (RF) coils tuned
-
The Role of Interdigitated Electrodes in Printed and Flexible Electronics Sensors (IF 3.9) Pub Date : 2024-04-24 Shayma Habboush, Sara Rojas, Noel Rodríguez, Almudena Rivadeneyra
Flexible electronics, also referred to as printable electronics, represent an interesting technology for implementing electronic circuits via depositing electronic devices onto flexible substrates, boosting their possible applications. Among all flexible electronics, interdigitated electrodes (IDEs) are currently being used for different sensor applications since they offer significant benefits beyond
-
Signal Processing Using a Circular Sensor Array to Measure the Torsional Angle of a Bolted Joint Sensors (IF 3.9) Pub Date : 2024-04-24 Thorben Schüthe, Karl-Ragmar Riemschneider, Andreas Meyer-Eschenbach
This study presents a new approach to determining the preload force of bolted joints. The concept involves measuring the torsional angle without contact. For this purpose, we present a circular magnetic sensor array integrated into the torque wrench. The torsional angle in bolted joints depends on the dimensions of the screw and the materials used and is typically less than four degrees. For this reason
-
Adaptation of Postural Sway in a Standing Position during Tilted Video Viewing Using Virtual Reality: A Comparison between Younger and Older Adults Sensors (IF 3.9) Pub Date : 2024-04-24 Tsubasa Tashiro, Noriaki Maeda, Takeru Abekura, Rami Mizuta, Yui Terao, Satoshi Arima, Satoshi Onoue, Yukio Urabe
This study aimed to investigate the effects of wearing virtual reality (VR) with a head-mounted display (HMD) on body sway in younger and older adults. A standing posture with eyes open without an HMD constituted the control condition. Wearing an HMD and viewing a 30°-tilt image and a 60°-tilt image in a resting standing position were the experimental conditions. Measurements were made using a force
-
A Robust Interacting Multi-Model Multi-Bernoulli Mixture Filter for Maneuvering Multitarget Tracking under Glint Noise Sensors (IF 3.9) Pub Date : 2024-04-24 Benru Yu, Hong Gu, Weimin Su
In practical radar systems, changes in the target aspect toward the radar will result in glint noise disturbances in the measurement data. The glint noise has heavy-tailed characteristics and cannot be perfectly modeled by the Gaussian distribution widely used in conventional tracking algorithms. In this article, we investigate the challenging problem of tracking a time-varying number of maneuvering
-
A Continuous Non-Invasive Blood Pressure Prediction Method Based on Deep Sparse Residual U-Net Combined with Improved Squeeze and Excitation Skip Connections Sensors (IF 3.9) Pub Date : 2024-04-24 Kaixuan Lai, Xusheng Wang, Congjun Cao
Arterial blood pressure (ABP) serves as a pivotal clinical metric in cardiovascular health assessments, with the precise forecasting of continuous blood pressure assuming a critical role in both preventing and treating cardiovascular diseases. This study proposes a novel continuous non-invasive blood pressure prediction model, DSRUnet, based on deep sparse residual U-net combined with improved SE skip
-
Design of A Transformer Oil Viscosity, Density, and Dielectric Constant Simultaneous Measurement System Based on A Quartz Tuning Fork Sensors (IF 3.9) Pub Date : 2024-04-24 Hao Yang, Shijie Chen, Jiafeng Ding
Transformer oil, crucial for transformer and power system safety, demands effective monitoring. Aiming to address the problems of expensive and bulky equipment, poor real-time performance, and single parameter detection of traditional measurement methods, this study proposes a quartz tuning fork-based simultaneous measurement system for online monitoring of the density, viscosity, and dielectric constant
-
Improving the Signal-to-Noise Ratio of Axial Displacement Measurements of Microspheres Based on Compound Digital Holography Microscopy Combined with the Reconstruction Centering Method Sensors (IF 3.9) Pub Date : 2024-04-24 Yanan Zeng, Qihang Guo, Xiaodong Hu, Junsheng Lu, Xiaopan Fan, Haiyun Wu, Xiao Xu, Jun Xie, Rui Ma
In 3D microsphere tracking, unlike in-plane motion that can be measured directly by a microscope, axial displacements are resolved by optical interference or a diffraction model. As a result, the axial results are affected by the environmental noise. The immunity to environmental noise increases with measurement accuracy and the signal-to-noise ratio (SNR). In compound digital holography microscopy
-
Tunable High-Sensitivity Four-Frequency Refractive Index Sensor Based on Graphene Metamaterial Sensors (IF 3.9) Pub Date : 2024-04-22 Xu Bao, Shujun Yu, Wenqiang Lu, Zhiqiang Hao, Zao Yi, Shubo Cheng, Bin Tang, Jianguo Zhang, Chaojun Tang, Yougen Yi
As graphene-related technology advances, the benefits of graphene metamaterials become more apparent. In this study, a surface-isolated exciton-based absorber is built by running relevant simulations on graphene, which can achieve more than 98% perfect absorption at multiple frequencies in the MWIR (MediumWavelength Infra-Red (MWIR) band as compared to the typical absorber. The absorber consists of
-
Transfer Learning-Based Hyperspectral Image Classification Using Residual Dense Connection Networks Sensors (IF 3.9) Pub Date : 2024-04-23 Hao Zhou, Xianwang Wang, Kunming Xia, Yi Ma, Guowu Yuan
The extraction of effective classification features from high-dimensional hyperspectral images, impeded by the scarcity of labeled samples and uneven sample distribution, represents a formidable challenge within hyperspectral image classification. Traditional few-shot learning methods confront the dual dilemma of limited annotated samples and the necessity for deeper, more effective features from complex
-
Human Activity Recognition in a Free-Living Environment Using an Ear-Worn Motion Sensor Sensors (IF 3.9) Pub Date : 2024-04-23 Lukas Boborzi, Julian Decker, Razieh Rezaei, Roman Schniepp, Max Wuehr
Human activity recognition (HAR) technology enables continuous behavior monitoring, which is particularly valuable in healthcare. This study investigates the viability of using an ear-worn motion sensor for classifying daily activities, including lying, sitting/standing, walking, ascending stairs, descending stairs, and running. Fifty healthy participants (between 20 and 47 years old) engaged in these
-
MYFix: Automated Fixation Annotation of Eye-Tracking Videos Sensors (IF 3.9) Pub Date : 2024-04-23 Negar Alinaghi, Samuel Hollendonner, Ioannis Giannopoulos
In mobile eye-tracking research, the automatic annotation of fixation points is an important yet difficult task, especially in varied and dynamic environments such as outdoor urban landscapes. This complexity is increased by the constant movement and dynamic nature of both the observer and their environment in urban spaces. This paper presents a novel approach that integrates the capabilities of two
-
Research on Surface Defect Detection of Strip Steel Based on Improved YOLOv7 Sensors (IF 3.9) Pub Date : 2024-04-23 Baozhan Lv, Beiyang Duan, Yeming Zhang, Shuping Li, Feng Wei, Sanpeng Gong, Qiji Ma, Maolin Cai
Surface defect detection of strip steel is an important guarantee for improving the production quality of strip steel. However, due to the diverse types, scales, and texture structures of surface defects on strip steel, as well as the irregular distribution of defects, it is difficult to achieve rapid and accurate detection of strip steel surface defects with existing methods. This article proposes
-
A Novel Approach to Raman Distributed Temperature-Sensing System for Short-Range Applications Sensors (IF 3.9) Pub Date : 2024-04-23 Augusto Pieracci, Jacopo Nanni, Giovanni Tartarini, Massimo Lanzoni
A novel approach to the development of Distributed Temperature-Sensing (DTS) systems based on Raman Scattering in Multimode optical fibers operating at around 800 nm is presented, focusing on applications requiring temperature profile measurement in the range of a few hundreds of meters. In contrast to the standard Raman DTS systems, which aim to shorten the pulse space width as much as possible to
-
Compressed Sensing for Biomedical Photoacoustic Imaging: A Review Sensors (IF 3.9) Pub Date : 2024-04-23 Yuanmao Wang, Yang Chen, Yongjian Zhao, Siyu Liu
Photoacoustic imaging (PAI) is a rapidly developing emerging non-invasive biomedical imaging technique that combines the strong contrast from optical absorption imaging and the high resolution from acoustic imaging. Abnormal biological tissues (such as tumors and inflammation) generate different levels of thermal expansion after absorbing optical energy, producing distinct acoustic signals from normal
-
Additive Manufacturing: A Comprehensive Review Sensors (IF 3.9) Pub Date : 2024-04-23 Longfei Zhou, Jenna Miller, Jeremiah Vezza, Maksim Mayster, Muhammad Raffay, Quentin Justice, Zainab Al Tamimi, Gavyn Hansotte, Lavanya Devi Sunkara, Jessica Bernat
Additive manufacturing has revolutionized manufacturing across a spectrum of industries by enabling the production of complex geometries with unparalleled customization and reduced waste. Beginning as a rapid prototyping tool, additive manufacturing has matured into a comprehensive manufacturing solution, embracing a wide range of materials, such as polymers, metals, ceramics, and composites. This
-
DEMA: A Deep Learning-Enabled Model for Non-Invasive Human Vital Signs Monitoring Based on Optical Fiber Sensing Sensors (IF 3.9) Pub Date : 2024-04-23 Qichang Zhang, Qing Wang, Weimin Lyu, Changyuan Yu
Optical fiber sensors are extensively employed for their unique merits, such as small size, being lightweight, and having strong robustness to electronic interference. The above-mentioned sensors apply to more applications, especially the detection and monitoring of vital signs in medical or clinical. However, it is inconvenient for daily long-term human vital sign monitoring with conventional monitoring
-
Multi-Sensor Image and Range-Based Techniques for the Geometric Documentation and the Photorealistic 3D Modeling of Complex Architectural Monuments Sensors (IF 3.9) Pub Date : 2024-04-23 Alexandra Tsiachta, Panagiotis Argyrou, Ioannis Tsougas, Maria Kladou, Panagiotis Ravanidis, Dimitris Kaimaris, Charalampos Georgiadis, Olga Georgoula, Petros Patias
The selection of the optimal methodology for the 3D geometric documentation of cultural heritage is a subject of high concern in contemporary scientific research. As a matter of fact, it requires a multi-source data acquisition process and the fusion of datasets from different sensors. This paper aims to demonstrate the workflow for the proper implementation and integration of geodetic, photogrammetric
-
A New Method for Bearing Fault Diagnosis across Machines Based on Envelope Spectrum and Conditional Metric Learning Sensors (IF 3.9) Pub Date : 2024-04-23 Xu Yang, Junfeng Yang, Yupeng Jin, Zhongchao Liu
In recent years, most research on bearing fault diagnosis has assumed that the source domain and target domain data come from the same machine. The differences in equipment lead to a decrease in diagnostic accuracy. To address this issue, unsupervised domain adaptation techniques have been introduced. However, most cross-device fault diagnosis models overlook the discriminative information under the
-
Enhanced Tracer Particle Detection in Dynamic Bulk Systems Based on Polarimetric Radar Signature Correlation Sensors (IF 3.9) Pub Date : 2024-04-23 Birk Hattenhorst, Nicholas Karsch, Thomas Musch
This contribution focuses on the detection of tracer particles within non-homogeneous bulk media, aiming to enhance insights into particulate systems. Polarimetric radar measurements are employed, utilizing cross-polarizing channels in order to mitigate interference from bulk media reflections. To distinguish the tracer particle in the measurements, a resonant cross-polarizing structure is constructed
-
A Multi-Faceted Digital Health Solution for Monitoring and Managing Diabetic Foot Ulcer Risk: A Case Series Sensors (IF 3.9) Pub Date : 2024-04-23 Emily Matijevich, Evan Minty, Emily Bray, Courtney Bachus, Maryam Hajizadeh, Brock Liden
Introduction: Diabetic foot ulcers (DFU) are a devastating complication of diabetes. There are numerous challenges with preventing diabetic foot complications and barriers to achieving the care processes suggested in established foot care guidelines. Multi-faceted digital health solutions, which combine multimodal sensing, patient-facing biofeedback, and remote patient monitoring (RPM), show promise
-
A Lightweight and Affordable Wearable Haptic Controller for Robot-Assisted Microsurgery Sensors (IF 3.9) Pub Date : 2024-04-23 Xiaoqing Guo, Finn McFall, Peiyang Jiang, Jindong Liu, Nathan Lepora, Dandan Zhang
In robot-assisted microsurgery (RAMS), surgeons often face the challenge of operating with minimal feedback, particularly lacking in haptic feedback. However, most traditional desktop haptic devices have restricted operational areas and limited dexterity. This report describes a novel, lightweight, and low-budget wearable haptic controller for teleoperated microsurgical robotic systems. We designed
-
Resilient Event-Based Fuzzy Fault Detection for DC Microgrids in Finite-Frequency Domain against DoS Attacks Sensors (IF 3.9) Pub Date : 2024-04-23 Bowen Ma, Qing Lu, Zhou Gu
This paper addresses the problem of fault detection in DC microgrids in the presence of denial-of-service (DoS) attacks. To deal with the nonlinear term in DC microgrids, a Takagi-Sugeno (T-S) model is employed. In contrast to the conventional approach of utilizing current sampling data in the traditional event-triggered mechanism (ETM), a novel integrated ETM employs historical information from measured
-
Optimizing Image Enhancement: Feature Engineering for Improved Classification in AI-Assisted Artificial Retinas Sensors (IF 3.9) Pub Date : 2024-04-23 Asif Mehmood, Jungbeom Ko, Hyunchul Kim, Jungsuk Kim
Artificial retinas have revolutionized the lives of many blind people by enabling their ability to perceive vision via an implanted chip. Despite significant advancements, there are some limitations that cannot be ignored. Presenting all objects captured in a scene makes their identification difficult. Addressing this limitation is necessary because the artificial retina can utilize a very limited
-
Lightweight Crypto-Ransomware Detection in Android Based on Reactive Honeyfile Monitoring Sensors (IF 3.9) Pub Date : 2024-04-23 José A. Gómez-Hernández, Pedro García-Teodoro
Given the high relevance and impact of ransomware in companies, organizations, and individuals around the world, coupled with the widespread adoption of mobile and IoT-related devices for both personal and professional use, the development of effective and efficient ransomware mitigation schemes is a necessity nowadays. Although a number of proposals are available in the literature in this line, most
-
Evaluation of Low-Cost CO2 Sensors Using Reference Instruments and Standard Gases for Indoor Use Sensors (IF 3.9) Pub Date : 2024-04-23 Qixiang Cai, Pengfei Han, Guang Pan, Chi Xu, Xiaoyu Yang, Honghui Xu, Dongde Ruan, Ning Zeng
CO2 monitoring is important for carbon emission evaluation. Low-cost and medium-precision sensors (LCSs) have become an exploratory direction for CO2 observation under complex emission conditions in cities. Here, we used a calibration method that improved the accuracy of SenseAir K30 CO2 sensors from ±30 ppm to 0.7–4.0 ppm for a CO2-monitoring instrument named the SENSE-IAP, which has been used in
-
Intelligent Tire Prototype in Longitudinal Slip Operating Conditions Sensors (IF 3.9) Pub Date : 2024-04-23 Jennifer Bastiaan, Abhishek Chawan, Wookjin Eum, Khalil Alipour, Foroogh Rouhollahi, Mohammad Behroozi, Javad Baqersad
With the recent advances in autonomous vehicles, there is an increasing need for sensors that can help monitor tire–road conditions and the forces that are applied to the tire. The footprint area of a tire that makes direct contact with the road surface, known as the contact patch, is a key parameter for determining a vehicle’s effectiveness in accelerating, braking, and steering at various velocities