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Hyperspectral anomaly detection:a performance comparison of existing techniques

International Journal of Digital Earth 2022年第1期15卷 2078-2125页

作者： Noman Raza Shah Abdur Rahman M.Maud Farrukh Aziz Bhatti Muhammad Khizer Ali Khurram Khurshid Moazam Maqsood Muhammad Amin iVISION Lab Electrical Engineering DepartmentInstitute of Space TechnologyIslamabadPakistan AI Enabling Technologies Lab Center of Excellence in Artificial IntelligenceBahria UniversityIslamabadPakistan Department of Electrical and Computer Engineering Pak-Austria Fachhochschule:Institute of Applied Sciences and TechnologyHaripurPakistan Avionics Engineering Department Institute of Space TechnologyIslamabadPakistan

Anomaly detection in Hyperspectral Imagery(HSI)has received considerable attention because of its potential application in several *** anomaly detection algorithms for HSI have been proposed in the literature;however,due to the use of different datasets in previous studies,an extensive performance comparison of these algorithms is *** this paper,an overview of the current state of research in hyperspectral anomaly detection is presented by broadly dividing all the previously proposed algorithms into eight different *** addition,this paper presents the most comprehensive comparative analysis to-date in hyperspectral anomaly detection by evaluating 22 algorithms on 17 different publicly available *** indicate that attribute and edge-preserving filtering-based detection(AED),local summation anomaly detection based on collaborative representation and inverse distance weight(LSAD-CR-IDW)and local summation unsupervised nearest regularized subspace with an outlier removal anomaly detector(LSUNRSORAD)perform better as indicated by the mean and median values of area under the receiver operating characteristic(ROC)***,this paper studies the effect of various dimensionality reduction techniques on anomaly *** indicate that reducing the number of components to around 20 improves the performance;however,any further decrease deteriorates the performance.

关键词： Anomaly detection algorithms hyperspectral imagery deep learning dimensionality reduction

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A flexible capacitive photoreceptor for the biomimetic retina

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Light(Science & Applications) 2022年第1期11卷 38-49页

作者： Mani Teja Vijjapu Mohammed E.Fouda Agamyrat Agambayev Chun Hong Kang Chun-Ho Lin Boon S.Ooi Jr-Hau He Ahmed M.Eltawil Khaled N.Salama Sensors lab Advanced Membranes and Porous Materials CenterComputerElectrical and Mathematical Science and Engineering DivisionKing Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Kingdom of Saudi Arabia Communication and Computing Systems Lab ComputerElectrical and Mathematical Science and Engineering DivisionKing Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Kingdom of Saudi Arabia Department of Electrical Engineering and Computer Science University of California-IrvineIrvineCA 92612USA Department of Electrical Computer and Energy EngineeringArizona State UniversityTempeAZUSA Computer Electrical and Mathematical Science and Engineering DivisionKing Abdullah University of Science and Technology(KAUST)Thuwal 23955-6900Kingdom of Saudi Arabia Department of Materials Science and Engineering City University of Hong KongHong Kong SARChina

Neuromorphic vision sensors have been extremely beneficial in developing energy-efficient intelligent systems for robotics and privacy-preserving security *** is a dire need for devices to mimic the retina's photoreceptors that encode the light illumination into a sequence of spikes to develop such ***,we develop a hybrid perovskite-based flexible photoreceptor whose capacitance changes proportionally to the light intensity mimicking the retina's rod cells,paving the way for developing an efficient artificial retina *** proposed device constitutes a hybrid nanocomposite of perovskites(methyl-ammonium lead bromide)and the ferroelectric terpolymer(polyvinylidene fluoride trifluoroethylene-chlorofluoroethylene).A metal-insulator-metal type capacitor with the prepared composite exhibits the unique and photosensitive capacitive behavior at various light intensities in the visible light *** proposed photoreceptor mimics the spectral sensitivity curve of human photopic *** hybrid nanocomposite is stable in ambient air for 129 weeks,with no observable degradation of the composite due to the encapsulation of hybrid perovskites in the hydrophobic *** functionality of the proposed photoreceptor to recognize handwritten digits(MNIST)dataset using an unsupervised trained spiking neural network with 72.05%recognition accuracy is *** demonstration proves the potential of the proposed sensor for neuromorphic vision applications.

关键词： perovskite illumination preserving

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A Comparative Study of Machine Learning Models for Plant Disease Identification 19th

A Comparative Study of Machine Learning Models for Plant D...

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19th International Conference on Soft Computing Models in Industrial and Environmental Applications, SOCO 2024

作者： Mara, Măcelaru Pop, Petrică Barata, José Department of Mathematics and Computer Science North University Center at Baia Mare Technical University of Cluj-Napoca Cluj-Napoca Romania Electrical and Computer Engineering Department School of Sciences and Technology NOVA University of Lisbon Lisbon Portugal

ISBN: (纸本)9783031750090

Early identification of plant diseases plays an important role in reducing the financial losses for farmers and enhancing the productivity and quality of crops. The present work proposes five machine learning (ML) algorithms: K-Nearest Neighbors, Random Forest, Iterative Dichotomizer 3, Adaptive Boosting and Logistic Regression for plant disease identification. In order to test the proposed ML algorithms, we used a large data set containing 74798 images mainly from PlantVillage dataset. The achieved experimental results show that the proposed ML techniques can be used to reliably identify various plant diseases. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Adversarial machine learning

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MEC-IoT-Healthcare: Analysis and Prospects

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computers, Materials & Continua 2023年第6期75卷 6219-6250页

作者： Hongyuan Wang Mohammed Dauwed Imran Khan Nor Samsiah Sani Hasmila Amirah Omar Hirofumi Amano Samih M.Mostafa College of Computer Science Guangdong University of Science and TechnologyDongGuan523083China Department of Medical Instrumentation Techniques Engineering Dijlah University CollegeBaghdadIraq Department of Electrical Engineering University of Engineering&TechnologyPeshawar814Pakistan Center for Artificial Intelligence Technology Faculty of Information Science and TechnologyUniversiti Kebangsaan Malaysia43600BangiSelangorMalaysia Research Institute for Information Technology Kyushu UniversityFukuoka819-0395Japan Computer Science-Mathematics Department Faculty of ScienceSouth Valley UniversityQena83523Egypt

Physical sensors,intelligent sensors,and output recommenda-tions are all examples of smart health technology that can be used to monitor patients’health and change their *** health is an Internet-of-Things(IoT)-aware network and sensing infrastructure that provides real-time,intelligent,and ubiquitous healthcare *** of the rapid development of cloud computing,as well as related technologies such as fog computing,smart health research is progressively moving in the right ***,fog computing,IoT sensors,blockchain,privacy and security,and other related technologies have been the focus of smart health research in recent *** the moment,the focus in cloud and smart health research is on how to use the cloud to solve the problem of enormous health data and enhance service performance,including cloud storage,retrieval,and calculation of health big *** article reviews state-of-the-art edge computing methods that has shifted to the collection,transmission,and calculation of health data,which includes various sensors and wearable devices used to collect health data,various wireless sensor technologies,and how to process health data and improve edge performance,among other ***,the typical smart health application cases,blockchain’s application in smart health,and related privacy and security issues were reviewed,as well as future difficulties and potential for smart health *** comparative analysis provides a reference for the the mobile edge computing in healthcare systems.

关键词： IoT mobile-edge computing cloud computing e-health

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A Study on Reducing Skin Irritation in Multi-Channel TES for Painless Force Feedback 14

A Study on Reducing Skin Irritation in Multi-Channel TES for...

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14th International Conference on Ubiquitous and Future Networks, ICUFN 2023

作者： Yu, Jin-Woo Kim, Bomin Kim, Jinmo Kim, Han-Joon Choi, Ji-Woong Dgist Department of Electrical Engineering & Computer Science Daegu Korea Republic of Kumoh National Institute of Technology Department of Medical It Convergence Engineering Gumi Korea Republic of Brain Engineering Convergence Research Center Dgist Department of Electrical Engineering & Computer Science Daegu Korea Republic of

ISBN: (纸本)9798350335385

Reducing unwanted skin irritation during transcutaneous electrical stimulation (TES) is essential for providing clear virtual sensations in virtual reality (VR) systems, leading to a more immersive experience. We investigated general characteristics of parameters in the TES, including the number of channels and pulse width of the stimulation signal, which may affect reducing skin irritation with 3D electromagnetic computer simulation with numerical neuron models. The results showed that the increasing number of channels and the declining pulse width attenuated skin irritation to 44.5 %. © 2023 IEEE.

关键词： Electromagnetic simulation

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Efficient UAV Routing Strategies for Wireless Sensor Network Data Retrieval

Efficient UAV Routing Strategies for Wireless Sensor Network...

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2024 International Conference on Decision Aid Sciences and Applications, DASA 2024

作者： Ahmed, Amjed Abbas Al-Sharhanee, Kareem Ali Malalah Najim, Ali Hamza Alheeti, Khattab M. Ali Satar, Nurhizam Safie Mohd Hashim, Aisha Hassan Abdallah Universiti Kebangsaan Malaysia Center for Cyber Security Faculty of Information Science and Technology Bangi Malaysia Department of Computer Techniques Engineering Baghdad Iraq College of Engineering Techniques Department of Communication Technical Engineering Al-Farahidi University Baghdad10011 Iraq Department of Computer Technical Al-Diwaniyah Iraq College of Computer and Information Technology University of Anbar Computer Networking Systems Department Anbar Iraq Center for Cyber Security Faculty of Information Science and Technology Bangi43600 Malaysia International Islamic University Malaysia Faculty of Engineering Department of Electrical and Computer Engineering Selangor Malaysia

ISBN: (纸本)9798350369106

WSNs are applied in many disciplines where certain conditions require the ability to adapt to network sink mobility and changes in the dynamics of the area coverage. To meet these needs, it is necessary to develop integrated systems where the ''terrestrial' systems and the Unmanned Aerial Vehicles (UAVs)' collect data from sensors efficiently. Planning of UAV trajectories is another challenging issue if many WSN nodes are randomly deployed. This challenge has a big impact on the overall effectiveness of the system. This paper presents a novel approach for reducing the traveled distance of unscrewed aerial vehicles (UAVs) to improve the data collection efficiency in WSNs with poor node density. Yet the method that has been developed is aimed at increasing 'the efficiency and efficacy of data collection... with the assistance of Unmanned Aerial Vehicles (UAVs)' which means this work reveals practical application solutions. © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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A Composite Decomposition Method for Large-Scale Global Optimization

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第12期5卷 6304-6319页

作者： Tian, Maojiang Chen, Minyang Du, Wei Tang, Yang Jin, Yaochu Yen, Gary G. Southern University of Science and Technology Department of Computer Science and Engineering Shenzhen518055 China East China University of Science and Technology Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education Shanghai200237 China East China University of Science and Technology Engineering Research Center of Process System Engineering Ministry of Education Shanghai200237 China Westlake University School of Engineering Hangzhou310030 China Oklahoma State University School of Electrical and Computer Engineering StillwaterOK74048 United States

Cooperative coevolution (CC) algorithms, based on the divide-and-conquer strategy, have emerged as the predominant approach to solving large-scale global optimization (LSGO) problems. The efficiency and accuracy of the grouping stage significantly impact the performance of the optimization process. While the general separability grouping (GSG) method has overcome the limitation of previous differential grouping (DG) methods by enabling the decomposition of nonadditively separable functions, it suffers from high computational complexity. To address this challenge, this article proposes a composite separability grouping (CSG) method, seamlessly integrating DG and GSG into a problem decomposition framework to utilize the strengths of both approaches. CSG introduces a step-by-step decomposition framework that accurately decomposes various problem types using fewer computational resources. By sequentially identifying additively, multiplicatively and generally separable variables, CSG progressively groups nonseparable variables by recursively considering the interactions between each nonseparable variable and the formed nonseparable groups. Furthermore, to enhance the efficiency and accuracy of CSG, we introduce two innovative methods: a multiplicatively separable variable detection method and a nonseparable variable grouping method. These two methods are designed to effectively detect multiplicatively separable variables and efficiently group nonseparable variables, respectively. Extensive experimental results demonstrate that CSG achieves more accurate variable grouping with lower computational complexity compared to GSG and state-of-the-art DG-series designs. © 2024 IEEE.

关键词： computational efficiency

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Detection of Perfect Stealthy Attacks on Cyber-Physical Systems Subject to Measurement Quantizations: A Watermark-Based Strategy

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 114-125页

作者： Yu-Ang Wang Zidong Wang Lei Zou Bo Shen Hongli Dong the College of Information Science and Technology Donghua University the Engineering Research Center of Digitalized Textile and Fashion Technology Ministry of Education IEEE the College of Electrical Engineering and Automation Shandong University of Science and Technology the Department of Computer Science Brunel University London Uxbridge the Sanya Offshore Oil and Gas Research Institute Northeast Petroleum University the Artificial Intelligence Energy Research Institute Northeast Petroleum University Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control Northeast Petroleum University

In this paper, the attack detection problem is investigated for a class of closed-loop systems subjected to unknownbutbounded noises in the presence of stealthy attacks. The measurement outputs from the sensors are quantized before transmission.A specific type of perfect stealthy attack, which meets certain rather stringent conditions, is taken into account. Such attacks could be injected by adversaries into both the sensor-toestimator and controller-to-actuator channels, with the aim of disrupting the normal data flow. For the purpose of defending against these perfect stealthy attacks, a novel scheme based on watermarks is developed. This scheme includes the injection of watermarks(applied to data prior to quantization) and the recovery of data(implemented before the data reaches the estimator).The watermark-based scheme is designed to be both timevarying and hidden from adversaries through incorporating a time-varying and bounded watermark signal. Subsequently, a watermark-based attack detection strategy is proposed which thoroughly considers the characteristics of perfect stealthy attacks,thereby ensuring that an alarm is activated upon the occurrence of such attacks. An example is provided to demonstrate the efficacy of the proposed mechanism for detecting attacks.

关键词： Attack detection cyber-physical systems (CPSs) perfect stealthy attacks watermark-based strategy

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pFedCal: Lightweight Personalized Federated Learning with Adaptive Calibration Strategy

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IEEE Transactions on Services Computing 2025年第3期18卷 1627-1640页

作者： Deng, Dongshang Wu, Xuangou Zhang, Tao Xiang, Chaocan Zhao, Wei Xu, Minrui Kang, Jiawen Han, Zhu Niyato, Dusit Anhui University of Technology School of Computer Science and Technology Anhui Province Key Laboratory of Digital Twin Technology in Metallurgical Industry Anhui Engineering Research Center for Intelligent Applications and Security of Industrial Internet Ma'anshan243002 China Beijing Jiaotong University School of Cyberspace Science and Technology Beijing100044 China Anhui Provincial Key Laboratory of Digital Twin Technology in Metallurgical Industry Anhui243002 China Chongqing University College of Computer Science Chongqing400044 China Nanyang Technological University School of Computer Science and Engineering 639798 Singapore Guangdong University of Technology School of Automation Guangzhou510062 China University of Houston Department of Electrical and Computer Engineering HoustonTX77004 United States Kyung Hee University Department of Computer Science and Engineering Seoul446-701 Korea Republic of

Federated learning (FL) is a promising artificial intelligence framework that enables clients to collectively train models with data privacy. However, in real-world scenarios, to construct practical FL frameworks, several challenges have to be addressed, including statistical heterogeneity, constrained resources, and fairness. Therefore, we first investigate an aggregation gap caused by statistical heterogeneity during local model initialization, which not only causes additional computational overhead for clients but also leads to the degradation of fairness. To bridge this gap, we propose pFedCal, a novel personalized federated learning with lightweight adaptive calibration strategy that performs calibration compensation through the prior knowledge of clients. Specifically, we introduce compensation for each client at the model initialization, with the compensation derived from the global gradient and the latest gradient bias. To enhance the calibration effect, we introduce a smoothing-based calibration strategy, and we design an adaptive calibration strategy. A representative example demonstrates that the proposed calibration and smoothing strategies improve fairness for clients. The theoretical analysis indicates that with an appropriate learning rate, pFedCal converges to a first-order stationary point for non-convex loss functions. Comprehensive experimental results show that pFedCal achieves faster convergence, higher accuracy, and improved fairness than the state-of-the-art methods. © 2008-2012 IEEE.

关键词： Federated learning

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Guest Editorial Special Issue on Neuromorphic Devices and Circuits for Next-Generation Flexible Electronics in IEEE Journal on Flexible Electronics

IEEE Journal on Flexible Electronics

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IEEE Journal on Flexible Electronics 2024年第1期3卷 2-3页

作者： Liu, Fengyuan Goswami, Sreetosh Pan, Lijia Wang, Yanzhi Fondazione Bruno Kessler Microsystems Technology Unit Center for Sensors and Devices Trento38123 Italy Northeastern University Bendable Electronics and Sustainable Technologies Group Electrical and Computer Engineering Department BostonMA02120 United States Indian Institute of Science Centre for Nano Science and Engineering Bengaluru560012 India Nanjing University School of Electronic Engineering Nanjing210023 China Northeastern University Electrical and Computer Engineering Department BostonMA02120 United States

It is fascinating how our body receives an immense amount of sensory information through numerous receptors distributed throughout the body and efficiently integrates it to make decisions for daily activities, while maintaining extremely low energy consumption and cognitive load. This bioinspired sensory information processing paradigm offers unparalleled advantages over traditional von Neumann architectures due to its exceptional energy efficiency, fault tolerance, and adaptability. While previous efforts in this area have mainly focused on the development of biomimetic sensors, it is equally important to create a computing architecture that can process sensory data locally before transmitting it to a higher level. The strategy of offloading computation at the edge can significantly reduce data latency, saving transmission bandwidth and relieving the burden of computation at a higher level, just like the way our peripheral nervous system complements the central nervous system.

关键词： Special issues and sections Neuromorphic engineering Receptor (biochemistry) Flexible electronics

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