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Preparation of single atom catalysts for high sensitive gas sensing
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作者 Xinxin He Ping Guo +7 位作者 Xuyang An Yuyang Li Jiatai Chen Xingyu Zhang Lifeng Wang Mingjin Dai Chaoliang Tan Jia Zhang 《International Journal of Extreme Manufacturing》 SCIE EI CAS CSCD 2024年第3期216-248,共33页
Single atom catalysts(SACs)have garnered significant attention in the field of catalysis over the past decade due to their exceptional atom utilization efficiency and distinct physical and chemical properties.For the ... Single atom catalysts(SACs)have garnered significant attention in the field of catalysis over the past decade due to their exceptional atom utilization efficiency and distinct physical and chemical properties.For the semiconductor-based electrical gas sensor,the core is the catalysis process of target gas molecules on the sensitive materials.In this context,the SACs offer great potential for highly sensitive and selective gas sensing,however,only some of the bubbles come to the surface.To facilitate practical applications,we present a comprehensive review of the preparation strategies for SACs,with a focus on overcoming the challenges of aggregation and low loading.Extensive research efforts have been devoted to investigating the gas sensing mechanism,exploring sensitive materials,optimizing device structures,and refining signal post-processing techniques.Finally,the challenges and future perspectives on the SACs based gas sensing are presented. 展开更多
关键词 single atom catalysts PREPARATION sensing mechanism gas sensing
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CrossFormer Embedding DeepLabv3+ for Remote Sensing Images Semantic Segmentation
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作者 Qixiang Tong Zhipeng Zhu +2 位作者 Min Zhang Kerui Cao Haihua Xing 《Computers, Materials & Continua》 SCIE EI 2024年第4期1353-1375,共23页
High-resolution remote sensing image segmentation is a challenging task. In urban remote sensing, the presenceof occlusions and shadows often results in blurred or invisible object boundaries, thereby increasing the d... High-resolution remote sensing image segmentation is a challenging task. In urban remote sensing, the presenceof occlusions and shadows often results in blurred or invisible object boundaries, thereby increasing the difficultyof segmentation. In this paper, an improved network with a cross-region self-attention mechanism for multi-scalefeatures based onDeepLabv3+is designed to address the difficulties of small object segmentation and blurred targetedge segmentation. First,we use CrossFormer as the backbone feature extraction network to achieve the interactionbetween large- and small-scale features, and establish self-attention associations between features at both large andsmall scales to capture global contextual feature information. Next, an improved atrous spatial pyramid poolingmodule is introduced to establish multi-scale feature maps with large- and small-scale feature associations, andattention vectors are added in the channel direction to enable adaptive adjustment of multi-scale channel features.The proposed networkmodel is validated using the PotsdamandVaihingen datasets. The experimental results showthat, compared with existing techniques, the network model designed in this paper can extract and fuse multiscaleinformation, more clearly extract edge information and small-scale information, and segment boundariesmore smoothly. Experimental results on public datasets demonstrate the superiority of ourmethod compared withseveral state-of-the-art networks. 展开更多
关键词 Semantic segmentation remote sensing multiscale self-attention
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Chaotic CS Encryption:An Efficient Image Encryption Algorithm Based on Chebyshev Chaotic System and Compressive Sensing
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作者 Mingliang Sun Jie Yuan +1 位作者 Xiaoyong Li Dongxiao Liu 《Computers, Materials & Continua》 SCIE EI 2024年第5期2625-2646,共22页
Images are the most important carrier of human information. Moreover, how to safely transmit digital imagesthrough public channels has become an urgent problem. In this paper, we propose a novel image encryptionalgori... Images are the most important carrier of human information. Moreover, how to safely transmit digital imagesthrough public channels has become an urgent problem. In this paper, we propose a novel image encryptionalgorithm, called chaotic compressive sensing (CS) encryption (CCSE), which can not only improve the efficiencyof image transmission but also introduce the high security of the chaotic system. Specifically, the proposed CCSEcan fully leverage the advantages of the Chebyshev chaotic system and CS, enabling it to withstand various attacks,such as differential attacks, and exhibit robustness. First, we use a sparse trans-form to sparse the plaintext imageand then use theArnold transformto perturb the image pixels. After that,we elaborate aChebyshev Toeplitz chaoticsensing matrix for CCSE. By using this Toeplitz matrix, the perturbed image is compressed and sampled to reducethe transmission bandwidth and the amount of data. Finally, a bilateral diffusion operator and a chaotic encryptionoperator are used to perturb and expand the image pixels to change the pixel position and value of the compressedimage, and ultimately obtain an encrypted image. Experimental results show that our method can be resistant tovarious attacks, such as the statistical attack and noise attack, and can outperform its current competitors. 展开更多
关键词 Image encryption chaotic system compressive sensing arnold transform
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Remote sensing of quality traits in cereal and arable production systems:A review
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作者 Zhenhai Li Chengzhi Fan +8 位作者 Yu Zhao Xiuliang Jin Raffaele Casa Wenjiang Huang Xiaoyu Song Gerald Blasch Guijun Yang James Taylor Zhenhong Li 《The Crop Journal》 SCIE CSCD 2024年第1期45-57,共13页
Cereal is an essential source of calories and protein for the global population.Accurately predicting cereal quality before harvest is highly desirable in order to optimise management for farmers,grading harvest and c... Cereal is an essential source of calories and protein for the global population.Accurately predicting cereal quality before harvest is highly desirable in order to optimise management for farmers,grading harvest and categorised storage for enterprises,future trading prices,and policy planning.The use of remote sensing data with extensive spatial coverage demonstrates some potential in predicting crop quality traits.Many studies have also proposed models and methods for predicting such traits based on multiplatform remote sensing data.In this paper,the key quality traits that are of interest to producers and consumers are introduced.The literature related to grain quality prediction was analyzed in detail,and a review was conducted on remote sensing platforms,commonly used methods,potential gaps,and future trends in crop quality prediction.This review recommends new research directions that go beyond the traditional methods and discusses grain quality retrieval and the associated challenges from the perspective of remote sensing data. 展开更多
关键词 Remote sensing Quality traits Grain protein CEREAL
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Multidomain Correlation-Based Multidimensional CSI Tensor Generation for Device-FreeWi-Fi Sensing
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作者 Liufeng Du Shaoru Shang +3 位作者 Linghua Zhang Chong Li JianingYang Xiyan Tian 《Computer Modeling in Engineering & Sciences》 SCIE EI 2024年第2期1749-1767,共19页
Due to the fine-grained communication scenarios characterization and stability,Wi-Fi channel state information(CSI)has been increasingly applied to indoor sensing tasks recently.Although spatial variations are explici... Due to the fine-grained communication scenarios characterization and stability,Wi-Fi channel state information(CSI)has been increasingly applied to indoor sensing tasks recently.Although spatial variations are explicitlyreflected in CSI measurements,the representation differences caused by small contextual changes are easilysubmerged in the fluctuations of multipath effects,especially in device-free Wi-Fi sensing.Most existing datasolutions cannot fully exploit the temporal,spatial,and frequency information carried by CSI,which results ininsufficient sensing resolution for indoor scenario changes.As a result,the well-liked machine learning(ML)-based CSI sensing models still struggling with stable performance.This paper formulates a time-frequency matrixon the premise of demonstrating that the CSI has low-rank potential and then proposes a distributed factorizationalgorithm to effectively separate the stable structured information and context fluctuations in the CSI matrix.Finally,a multidimensional tensor is generated by combining the time-frequency gradients of CSI,which containsrich and fine-grained real-time contextual information.Extensive evaluations and case studies highlight thesuperiority of the proposal. 展开更多
关键词 Wi-Fi sensing device-free CSI low-rank matrix factorization
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Color Image Compression and Encryption Algorithm Based on 2D Compressed Sensing and Hyperchaotic System
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作者 Zhiqing Dong Zhao Zhang +1 位作者 Hongyan Zhou Xuebo Chen 《Computers, Materials & Continua》 SCIE EI 2024年第2期1977-1993,共17页
With the advent of the information security era,it is necessary to guarantee the privacy,accuracy,and dependable transfer of pictures.This study presents a new approach to the encryption and compression of color image... With the advent of the information security era,it is necessary to guarantee the privacy,accuracy,and dependable transfer of pictures.This study presents a new approach to the encryption and compression of color images.It is predicated on 2D compressed sensing(CS)and the hyperchaotic system.First,an optimized Arnold scrambling algorithm is applied to the initial color images to ensure strong security.Then,the processed images are con-currently encrypted and compressed using 2D CS.Among them,chaotic sequences replace traditional random measurement matrices to increase the system’s security.Third,the processed images are re-encrypted using a combination of permutation and diffusion algorithms.In addition,the 2D projected gradient with an embedding decryption(2DPG-ED)algorithm is used to reconstruct images.Compared with the traditional reconstruction algorithm,the 2DPG-ED algorithm can improve security and reduce computational complexity.Furthermore,it has better robustness.The experimental outcome and the performance analysis indicate that this algorithm can withstand malicious attacks and prove the method is effective. 展开更多
关键词 Image encryption image compression hyperchaotic system compressed sensing
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Gel-Based Triboelectric Nanogenerators for Flexible Sensing:Principles,Properties,and Applications
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作者 Peng Lu Xiaofang Liao +7 位作者 Xiaoyao Guo Chenchen Cai Yanhua Liu Mingchao Chi Guoli Du Zhiting Wei Xiangjiang Meng Shuangxi Nie 《Nano-Micro Letters》 SCIE EI CAS CSCD 2024年第10期257-303,共47页
The rapid development of the Internet of Things and artificial intelligence technologies has increased the need for wearable,portable,and self-powered flexible sensing devices.Triboelectric nanogenerators(TENGs)based ... The rapid development of the Internet of Things and artificial intelligence technologies has increased the need for wearable,portable,and self-powered flexible sensing devices.Triboelectric nanogenerators(TENGs)based on gel materials(with excellent conductivity,mechanical tunability,environmental adaptability,and biocompatibility)are considered an advanced approach for developing a new generation of flexible sensors.This review comprehensively summarizes the recent advances in gel-based TENGs for flexible sensors,covering their principles,properties,and applications.Based on the development requirements for flexible sensors,the working mechanism of gel-based TENGs and the characteristic advantages of gels are introduced.Design strategies for the performance optimization of hydrogel-,organogel-,and aerogel-based TENGs are systematically summarized.In addition,the applications of gel-based TENGs in human motion sensing,tactile sensing,health monitoring,environmental monitoring,human-machine interaction,and other related fields are summarized.Finally,the challenges of gel-based TENGs for flexible sensing are discussed,and feasible strategies are proposed to guide future research. 展开更多
关键词 Triboelectric nanogenerators Gel materials Triboelectric materials Flexible sensing
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Fast compressed sensing spectral measurement with adaptive gradient multiscale resolution
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作者 蓝若明 刘雪峰 +1 位作者 李天平 白成杰 《Chinese Physics B》 SCIE EI CAS CSCD 2024年第2期298-304,共7页
We propose a fast,adaptive multiscale resolution spectral measurement method based on compressed sensing.The method can apply variable measurement resolution over the entire spectral range to reduce the measurement ti... We propose a fast,adaptive multiscale resolution spectral measurement method based on compressed sensing.The method can apply variable measurement resolution over the entire spectral range to reduce the measurement time by over 75%compared to a global high-resolution measurement.Mimicking the characteristics of the human retina system,the resolution distribution follows the principle of gradually decreasing.The system allows the spectral peaks of interest to be captured dynamically or to be specified a priori by a user.The system was tested by measuring single and dual spectral peaks,and the results of spectral peaks are consistent with those of global high-resolution measurements. 展开更多
关键词 SPECTROMETER compressed sensing adaptive gradient multiscale resolution fast measurement
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Remote sensing of air pollution incorporating integrated-path differential-absorption and coherent-Doppler lidar
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作者 Ze-hou Yang Yong Chen +5 位作者 Chun-li Chen Yong-ke Zhang Ji-hui Dong Tao Peng Xiao-feng Li Ding-fu Zhou 《Defence Technology(防务技术)》 SCIE EI CAS CSCD 2024年第1期594-601,共8页
An innovative complex lidar system deployed on an airborne rotorcraft platform for remote sensing of atmospheric pollution is proposed and demonstrated.The system incorporates integrated-path differential absorption l... An innovative complex lidar system deployed on an airborne rotorcraft platform for remote sensing of atmospheric pollution is proposed and demonstrated.The system incorporates integrated-path differential absorption lidar(DIAL) and coherent-doppler lidar(CDL) techniques using a dual tunable TEA CO_(2)laser in the 9—11 μm band and a 1.55 μm fiber laser.By combining the principles of differential absorption detection and pulsed coherent detection,the system enables agile and remote sensing of atmospheric pollution.Extensive static tests validate the system’s real-time detection capabilities,including the measurement of concentration-path-length product(CL),front distance,and path wind speed of air pollution plumes over long distances exceeding 4 km.Flight experiments is conducted with the helicopter.Scanning of the pollutant concentration and the wind field is carried out in an approximately 1 km slant range over scanning angle ranges from 45°to 65°,with a radial resolution of 30 m and10 s.The test results demonstrate the system’s ability to spatially map atmospheric pollution plumes and predict their motion and dispersion patterns,thereby ensuring the protection of public safety. 展开更多
关键词 Differential absorption LIDAR COHERENT Doppler lidar Remoting sensing Atmospheric pollution
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Sensing-Assisted Accurate and Fast Beam Management for Cellular-Connected mmWave UAV Network
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作者 Cui Yanpeng Zhang Qixun +4 位作者 Feng Zhiyong Qin Wen Zhou Ying Wei Zhiqing Zhang Ping 《China Communications》 SCIE CSCD 2024年第6期271-289,共19页
Beam management,including initial access(IA)and beam tracking,is essential to the millimeter-wave Unmanned Aerial Vehicle(UAV)network.However,the conventional communicationonly and feedback-based schemes suffer a high... Beam management,including initial access(IA)and beam tracking,is essential to the millimeter-wave Unmanned Aerial Vehicle(UAV)network.However,the conventional communicationonly and feedback-based schemes suffer a high delay and low accuracy of beam alignment,since they only enable the receiver to passively“hear”the information of the transmitter from the radio domain.This paper presents a novel sensing-assisted beam management approach,the first solution that fully utilizes the information from the visual domain to improve communication performance.We employ both integrated sensing and communication and computer vision techniques and design an extended Kalman filtering method for beam tracking and prediction.Besides,we also propose a novel dual identity association solution to distinguish multiple UAVs in dynamic environments.Real-world experiments and numerical results show that the proposed solution outperforms the conventional methods in IA delay,association accuracy,tracking error,and communication performance. 展开更多
关键词 beam management integrated sensing and communication UAV communication
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ConvNeXt-UperNet-Based Deep Learning Model for Road Extraction from High-Resolution Remote Sensing Images
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作者 Jing Wang Chen Zhang Tianwen Lin 《Computers, Materials & Continua》 SCIE EI 2024年第8期1907-1925,共19页
When existing deep learning models are used for road extraction tasks from high-resolution images,they are easily affected by noise factors such as tree and building occlusion and complex backgrounds,resulting in inco... When existing deep learning models are used for road extraction tasks from high-resolution images,they are easily affected by noise factors such as tree and building occlusion and complex backgrounds,resulting in incomplete road extraction and low accuracy.We propose the introduction of spatial and channel attention modules to the convolutional neural network ConvNeXt.Then,ConvNeXt is used as the backbone network,which cooperates with the perceptual analysis network UPerNet,retains the detection head of the semantic segmentation,and builds a new model ConvNeXt-UPerNet to suppress noise interference.Training on the open-source DeepGlobe and CHN6-CUG datasets and introducing the DiceLoss on the basis of CrossEntropyLoss solves the problem of positive and negative sample imbalance.Experimental results show that the new network model can achieve the following performance on the DeepGlobe dataset:79.40%for precision(Pre),97.93% for accuracy(Acc),69.28% for intersection over union(IoU),and 83.56% for mean intersection over union(MIoU).On the CHN6-CUG dataset,the model achieves the respective values of 78.17%for Pre,97.63%for Acc,65.4% for IoU,and 81.46% for MIoU.Compared with other network models,the fused ConvNeXt-UPerNet model can extract road information better when faced with the influence of noise contained in high-resolution remote sensing images.It also achieves multiscale image feature information with unified perception,ultimately improving the generalization ability of deep learning technology in extracting complex roads from high-resolution remote sensing images. 展开更多
关键词 Deep learning semantic segmentation remote sensing imagery road extraction
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Enhancing visual security: An image encryption scheme based on parallel compressive sensing and edge detection embedding
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作者 王一铭 黄树锋 +2 位作者 陈煌 杨健 蔡述庭 《Chinese Physics B》 SCIE EI CAS CSCD 2024年第1期287-302,共16页
A novel image encryption scheme based on parallel compressive sensing and edge detection embedding technology is proposed to improve visual security. Firstly, the plain image is sparsely represented using the discrete... A novel image encryption scheme based on parallel compressive sensing and edge detection embedding technology is proposed to improve visual security. Firstly, the plain image is sparsely represented using the discrete wavelet transform.Then, the coefficient matrix is scrambled and compressed to obtain a size-reduced image using the Fisher–Yates shuffle and parallel compressive sensing. Subsequently, to increase the security of the proposed algorithm, the compressed image is re-encrypted through permutation and diffusion to obtain a noise-like secret image. Finally, an adaptive embedding method based on edge detection for different carrier images is proposed to generate a visually meaningful cipher image. To improve the plaintext sensitivity of the algorithm, the counter mode is combined with the hash function to generate keys for chaotic systems. Additionally, an effective permutation method is designed to scramble the pixels of the compressed image in the re-encryption stage. The simulation results and analyses demonstrate that the proposed algorithm performs well in terms of visual security and decryption quality. 展开更多
关键词 visual security image encryption parallel compressive sensing edge detection embedding
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Power equipment vibration visualization using intelligent sensing method based on event-sensing principle
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作者 Mingzhe Zhao Xiaojun Shen +1 位作者 Lei Su Zihang Dong 《Global Energy Interconnection》 EI CSCD 2024年第2期228-240,共13页
Vibration measurements can be used to evaluate the operation status of power equipment and are widely applied in equipment quality inspection and fault identification.Event-sensing technology can sense the change in s... Vibration measurements can be used to evaluate the operation status of power equipment and are widely applied in equipment quality inspection and fault identification.Event-sensing technology can sense the change in surface light intensity caused by object vibration and provide a visual description of vibration behavior.Based on the analysis of the principle underlying the transformation of vibration behavior into event flow data by an event sensor,this paper proposes an algorithm to reconstruct event flow data into a relationship correlating vibration displacement and time to extract the amplitude-frequency characteristics of the vibration signal.A vibration measurement test platform is constructed,and feasibility and effectiveness tests are performed for the vibration motor and other power equipment.The results show that event-sensing technology can effectively perceive the surface vibration behavior of power and provide a wide dynamic range.Furthermore,the vibration measurement and visualization algorithm for power equipment constructed using this technology offers high measurement accuracy and efficiency.The results of this study provide a new noncontact and visual method for locating vibrations and performing amplitude-frequency analysis on power equipment. 展开更多
关键词 Power equipment Event sensing Non contact measurement Graphic display FEASIBILITY
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Facile Semiconductor p-n Homojunction Nanowires with Strategic p-Type Doping Engineering Combined with Surface Reconstruction for Biosensing Applications
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作者 Liuan Li Shi Fang +12 位作者 Wei Chen Yueyue Li Mohammad Fazel Vafadar Danhao Wang Yang Kang Xin Liu Yuanmin Luo Kun Liang Yiping Dang Lei Zhao Songrui Zhao Zongzhi Yin Haiding Sun 《Nano-Micro Letters》 SCIE EI CAS CSCD 2024年第10期15-30,共16页
Photosensors with versatile functionalities have emerged as a cornerstone for breakthroughs in the future optoelectronic systems across a wide range of applications.In particular,emerging photoelectrochemical(PEC)-typ... Photosensors with versatile functionalities have emerged as a cornerstone for breakthroughs in the future optoelectronic systems across a wide range of applications.In particular,emerging photoelectrochemical(PEC)-type devices have recently attracted extensive interest in liquid-based biosensing applications due to their natural electrolyte-assisted operating characteristics.Herein,a PEC-type photosensor was carefully designed and constructed by employing gallium nitride(GaN)p-n homojunction semiconductor nanowires on silicon,with the p-GaN segment strategically doped and then decorated with cobalt-nickel oxide(CoNiO_(x)).Essentially,the p-n homojunction configuration with facile p-doping engineering improves carrier separation efficiency and facilitates carrier transfer to the nanowire surface,while CoNiO_(x)decoration further boosts PEC reaction activity and carrier dynamics at the nanowire/electrolyte interface.Consequently,the constructed photosensor achieves a high responsivity of 247.8 mA W^(-1)while simultaneously exhibiting excellent operating stability.Strikingly,based on the remarkable stability and high responsivity of the device,a glucose sensing system was established with a demonstration of glucose level determination in real human serum.This work offers a feasible and universal approach in the pursuit of high-performance bio-related sensing applications via a rational design of PEC devices in the form of nanostructured architecture with strategic doping engineering. 展开更多
关键词 p-n GaN nanowires Strategic p-doping Surface decoration Photoelectrochemical sensor Glucose sensing
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Modeling urban redevelopment:A novel approach using time-series remote sensing data and machine learning
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作者 Li Lin Liping Di +6 位作者 Chen Zhang Liying Guo Haoteng Zhao Didarul Islam Hui Li Ziao Liu Gavin Middleton 《Geography and Sustainability》 CSCD 2024年第2期211-219,共9页
Accurate mapping and timely monitoring of urban redevelopment are pivotal for urban studies and decisionmakers to foster sustainable urban development.Traditional mapping methods heavily depend on field surveys and su... Accurate mapping and timely monitoring of urban redevelopment are pivotal for urban studies and decisionmakers to foster sustainable urban development.Traditional mapping methods heavily depend on field surveys and subjective questionnaires,yielding less objective,reliable,and timely data.Recent advancements in Geographic Information Systems(GIS)and remote-sensing technologies have improved the identification and mapping of urban redevelopment through quantitative analysis using satellite-based observations.Nonetheless,challenges persist,particularly concerning accuracy and significant temporal delays.This study introduces a novel approach to modeling urban redevelopment,leveraging machine learning algorithms and remote-sensing data.This methodology can facilitate the accurate and timely identification of urban redevelopment activities.The study’s machine learning model can analyze time-series remote-sensing data to identify spatio-temporal and spectral patterns related to urban redevelopment.The model is thoroughly evaluated,and the results indicate that it can accurately capture the time-series patterns of urban redevelopment.This research’s findings are useful for evaluating urban demographic and economic changes,informing policymaking and urban planning,and contributing to sustainable urban development.The model can also serve as a foundation for future research on early-stage urban redevelopment detection and evaluation of the causes and impacts of urban redevelopment. 展开更多
关键词 Urban redevelopment Urban sustainability Remote sensing Time-series analysis Machine learning
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Untethered Micro/Nanorobots for Remote Sensing:Toward Intelligent Platform
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作者 Qianqian Wang Shihao Yang Li Zhang 《Nano-Micro Letters》 SCIE EI CAS CSCD 2024年第2期450-483,共34页
Untethered micro/nanorobots that can wirelessly control their motion and deformation state have gained enormous interest in remote sensing applications due to their unique motion characteristics in various media and d... Untethered micro/nanorobots that can wirelessly control their motion and deformation state have gained enormous interest in remote sensing applications due to their unique motion characteristics in various media and diverse functionalities.Researchers are developing micro/nanorobots as innovative tools to improve sensing performance and miniaturize sensing systems,enabling in situ detection of substances that traditional sensing methods struggle to achieve.Over the past decade of development,significant research progress has been made in designing sensing strategies based on micro/nanorobots,employing various coordinated control and sensing approaches.This review summarizes the latest developments on micro/nanorobots for remote sensing applications by utilizing the self-generated signals of the robots,robot behavior,microrobotic manipulation,and robot-environment interactions.Providing recent studies and relevant applications in remote sensing,we also discuss the challenges and future perspectives facing micro/nanorobots-based intelligent sensing platforms to achieve sensing in complex environments,translating lab research achievements into widespread real applications. 展开更多
关键词 Micro/nanorobot Remote sensing Wireless control SELF-PROPULSION Actuation at small scales
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Design and Implementation of a High-Sensitivity Magnetic Sensing System Based on GMI Effect
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作者 Wenzhu Wu Ming Xu +4 位作者 Changlin Han Junquan Tang Jia Xu Lin Xu Mingxin Qin 《Journal of Beijing Institute of Technology》 EI CAS 2024年第3期237-247,共11页
A high-sensitivity magnetic sensing system based on giant magneto-impedance(GMI)effect is designed and fabricated.The system comprises a GMI sensor equipped with a gradient probe and an signal acquisition and processi... A high-sensitivity magnetic sensing system based on giant magneto-impedance(GMI)effect is designed and fabricated.The system comprises a GMI sensor equipped with a gradient probe and an signal acquisition and processing module.A segmented superposition algorithm is used to increase target signal and reduce the random noise.The results show that under unshielded,room temperature conditions,the system achieves successful detection of weak magnetic fields down to 2 pT with a notable sensitivity of 1.84×10^(8)V/T(G=1000).By applying 17 overlays,the segmented superposition algorithm increases the power proportion of the target signal at 31 Hz from6.89%to 45.91%,surpassing the power proportion of the 2 Hz low-frequency interference signal.Simultaneously,it reduces the power proportion of the 20 Hz random noise.The segmented superposition process effectively cancels out certain random noise elements,leading to a reduction in their respective power proportions.This high-sensitivity magnetic sensing system features a simple structure,and is easy to operate,making it highly valuable for both practical applications and broader dissemination. 展开更多
关键词 HIGH-sensITIVITY magnetic field sensing system GMI effect segmented superposition algorithm
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Probability-Enhanced Anchor-Free Detector for Remote-Sensing Object Detection
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作者 Chengcheng Fan Zhiruo Fang 《Computers, Materials & Continua》 SCIE EI 2024年第6期4925-4943,共19页
Anchor-free object-detection methods achieve a significant advancement in field of computer vision,particularly in the realm of real-time inferences.However,in remote sensing object detection,anchor-free methods often... Anchor-free object-detection methods achieve a significant advancement in field of computer vision,particularly in the realm of real-time inferences.However,in remote sensing object detection,anchor-free methods often lack of capability in separating the foreground and background.This paper proposes an anchor-free method named probability-enhanced anchor-free detector(ProEnDet)for remote sensing object detection.First,a weighted bidirectional feature pyramid is used for feature extraction.Second,we introduce probability enhancement to strengthen the classification of the object’s foreground and background.The detector uses the logarithm likelihood as the final score to improve the classification of the foreground and background of the object.ProEnDet is verified using the DIOR and NWPU-VHR-10 datasets.The experiment achieved mean average precisions of 61.4 and 69.0 on the DIOR dataset and NWPU-VHR-10 dataset,respectively.ProEnDet achieves a speed of 32.4 FPS on the DIOR dataset,which satisfies the real-time requirements for remote-sensing object detection. 展开更多
关键词 Object detection anchor-free detector PROBABILISTIC fully convolutional neural network remote sensing
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Land Use Land Cover Analysis for Godavari Basin in Maharashtra Using Geographical Information System and Remote Sensing
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作者 Pallavi Saraf Dattatray G. Regulwar 《Journal of Geographic Information System》 2024年第1期21-31,共11页
The dynamic transformation of land use and land cover has emerged as a crucial aspect in the effective management of natural resources and the continual monitoring of environmental shifts. This study focused on the la... The dynamic transformation of land use and land cover has emerged as a crucial aspect in the effective management of natural resources and the continual monitoring of environmental shifts. This study focused on the land use and land cover (LULC) changes within the catchment area of the Godavari River, assessing the repercussions of land and water resource exploitation. Utilizing LANDSAT satellite images from 2009, 2014, and 2019, this research employed supervised classification through the Quantum Geographic Information System (QGIS) software’s SCP plugin. Maximum likelihood classification algorithm was used for the assessment of supervised land use classification. Seven distinct LULC classes—forest, irrigated cropland, agricultural land (fallow), barren land, shrub land, water, and urban land—are delineated for classification purposes. The study revealed substantial changes in the Godavari basin’s land use patterns over the ten-year period from 2009 to 2019. Spatial and temporal dynamics of land use/cover changes (2009-2019) were quantified using three Satellite/Landsat images, a supervised classification algorithm and the post classification change detection technique in GIS. The total study area of the Godavari basin in Maharashtra encompasses 5138175.48 hectares. Notably, the built-up area increased from 0.14% in 2009 to 1.94% in 2019. The proportion of irrigated cropland, which was 62.32% in 2009, declined to 41.52% in 2019. Shrub land witnessed a noteworthy increase from 0.05% to 2.05% over the last decade. The key findings underscored significant declines in barren land, agricultural land, and irrigated cropland, juxtaposed with an expansion in forest land, shrub land, and urban land. The classification methodology achieved an overall accuracy of 80%, with a Kappa Statistic of 71.9% for the satellite images. The overall classification accuracy along with the Kappa value for 2009, 2014 and 2019 supervised land use land cover classification was good enough to detect the changing scenarios of Godavari River basin under study. These findings provide valuable insights for discerning land utilization across various categories, facilitating the adoption of appropriate strategies for sustainable land use in the region. 展开更多
关键词 GIS Remote sensing Land Use Land Cover Change Change Detection Supervised Classification
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Wideband spectrum sensing using step-sampling based on the multipath nyquist folding receiver
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作者 Kai-lun Tian Kai-li Jiang +5 位作者 Sen Cao Jian Gao Ying Xiong Bin Tang Xu-ying Zhang Yan-fei Li 《Defence Technology(防务技术)》 SCIE EI CAS CSCD 2024年第1期523-536,共14页
Wideband spectrum sensing with a high-speed analog-digital converter(ADC) presents a challenge for practical systems.The Nyquist folding receiver(NYFR) is a promising scheme for achieving cost-effective real-time spec... Wideband spectrum sensing with a high-speed analog-digital converter(ADC) presents a challenge for practical systems.The Nyquist folding receiver(NYFR) is a promising scheme for achieving cost-effective real-time spectrum sensing,which is subject to the complexity of processing the modulated outputs.In this case,a multipath NYFR architecture with a step-sampling rate for the different paths is proposed.The different numbers of digital channels for each path are designed based on the Chinese remainder theorem(CRT).Then,the detectable frequency range is divided into multiple frequency grids,and the Nyquist zone(NZ) of the input can be obtained by sensing these grids.Thus,high-precision parameter estimation is performed by utilizing the NYFR characteristics.Compared with the existing methods,the scheme proposed in this paper overcomes the challenge of NZ estimation,information damage,many computations,low accuracy,and high false alarm probability.Comparative simulation experiments verify the effectiveness of the proposed architecture in this paper. 展开更多
关键词 Wideband spectrum sensing Sub-Nyquist sampling Step-sampling Nyquist folding receiver(NYFR) Multisignal processing
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