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Exploring Deep Learning Methods for computer Vision Applications across Multiple Sectors:Challenges and Future Trends

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computer Modeling in engineering & Sciences 2024年第4期139卷 103-141页

作者： Narayanan Ganesh Rajendran Shankar Miroslav Mahdal Janakiraman SenthilMurugan Jasgurpreet Singh Chohan Kanak Kalita School of Computer Science and Engineering Vellore Institute of TechnologyChennai600127India Department of Computer Science and Engineering Koneru Lakshmaiah Education FoundationVaddeswaram522502India Department of Control Systems and Instrumentation Faculty of Mechanical EngineeringVSB-Technical University of OstravaOstrava70800Czech Republic Department of Computer Science and Engineering Vel Tech High Tech Dr.Rangarajan Dr.Sakunthala Engineering CollegeChennai600062India Department of Mechanical Engineering and University Centre for Research&Development Chandigarh UniversityMohali140413India Department of Mechanical Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and TechnologyAvadi600062India

computer vision(CV)was developed for computers and other systems to act or make recommendations based on visual inputs,such as digital photos,movies,and other *** learning(DL)methods are more successful than other traditional machine learning(ML)methods *** techniques can produce state-of-the-art results for difficult CV problems like picture categorization,object detection,and face *** this review,a structured discussion on the history,methods,and applications of DL methods to CV problems is *** sector-wise presentation of applications in this papermay be particularly useful for researchers in niche fields who have limited or introductory knowledge of DL methods and *** review will provide readers with context and examples of how these techniques can be applied to specific areas.A curated list of popular datasets and a brief description of them are also included for the benefit of readers.

关键词： Neural network machine vision classification object detection deep learning

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A Survey of Cyber Attacks on Cyber Physical systems:Recent Advances and Challenges

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IEEE/CAA Journal of Automatica Sinica 2022年第5期9卷 784-800页

作者： Wenli Duo MengChu Zhou Abdullah Abusorrah Macao Institute of Systems Engineering Macao University of Science and TechnologyMacao 999078China IEEE Department of Electrical and Computer Engineering K.A.CARE Energy Research and Innovation Center Department of Electrical and Computer Engineering K.A.CARE Energy Research and Innovation Center and Center of Research Excellence in Renewable Energy and Power SystemsKing Abdulaziz University

A cyber physical system(CPS)is a complex system that integrates sensing,computation,control and networking into physical processes and objects over *** plays a key role in modern industry since it connects physical and cyber *** order to meet ever-changing industrial requirements,its structures and functions are constantly ***,new security issues have arisen.A ubiquitous problem is the fact that cyber attacks can cause significant damage to industrial systems,and thus has gained increasing attention from researchers and *** paper presents a survey of state-of-the-art results of cyber attacks on cyber physical ***,as typical system models are employed to study these systems,time-driven and event-driven systems are ***,recent advances on three types of attacks,i.e.,those on availability,integrity,and confidentiality are *** particular,the detailed studies on availability and integrity attacks are introduced from the perspective of attackers and ***,both attack and defense strategies are discussed based on different system *** challenges and open issues are indicated to guide future research and inspire the further exploration of this increasingly important area.

关键词： Attack detection attack strategy cyber attack cyber physical system(CPS) secure control

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On convergence of covariance matrix of empirical Bayes hyper-parameter estimator

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Control Theory and Technology 2024年第2期22卷 149-162页

作者： Yue Ju Biqiang Mu Tianshi Chen School of Data Science and Shenzhen Research Institute of Big Data The Chinese University of Hong KongShenzhenShenzhen518172GuangdongChina Division of Decision and Control Systems School of Electrical Engineering and Computer ScienceKTH Royal Institute of Technology10044StockholmSweden Key Laboratory of Systems and Control Institute of Systems ScienceAcademy of Mathematics and System ScienceChinese Academy of SciencesBeijing100190China

Regularized system identification has become the research frontier of system identification in the past *** related core subject is to study the convergence properties of various hyper-parameter estimators as the sample size goes to *** this paper,we consider one commonly used hyper-parameter estimator,the empirical Bayes(EB).Its convergence in distribution has been studied,and the explicit expression of the covariance matrix of its limiting distribution has been ***,what we are truly interested in are factors contained in the covariance matrix of the EB hyper-parameter estimator,and then,the convergence of its covariance matrix to that of its limiting distribution is *** general,the convergence in distribution of a sequence of random variables does not necessarily guarantee the convergence of its covariance ***,the derivation of such convergence is a necessary complement to our theoretical analysis about factors that influence the convergence properties of the EB hyper-parameter *** this paper,we consider the regularized finite impulse response(FIR)model estimation with deterministic inputs,and show that the covariance matrix of the EB hyper-parameter estimator converges to that of its limiting ***,we run numerical simulations to demonstrate the efficacy of ourtheoretical results.

关键词： Regularized system identification Hyper-parameter estimator Empirical Bayes Convergence of covariance matrix

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Average Current Control Design of Active Power Decoupling Converter with Low Filter Inductance Based on Double Sampling Techniques for PV Microinverter

Average Current Control Design of Active Power Decoupling Co...

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2024 International Conference on Sustainable Energy: Energy Transition and Net-Zero Climate Future, ICUE 2024

作者： Shen, Yidi Hasnain, Arafat Zakzewski, Daniel Resalayyan, Rakesh Khaligh, Alireza University of Maryland College Park Department of Electrical and Computer Engineering The Institute for Systems Research College ParkMD United States

ISBN: (纸本)9798331517076

Active power decoupling (APD) converter is a power dense and reliable solution in dc-ac power conversion systems to balance the fluctuating ac-side power and constant dc-side power. In boost type APD converter, filter inductor with low inductance can be beneficial in achieving efficient and compact designs or allows the implementation of zero voltage switching (ZVS) based modulation. On the other hand, the reduced inductance increases the difficulty of controller design due to reduction of the average current control loop phase margin and higher requirement in low-pass-filter (LPF). This paper proposes an average current control based on double sampling techniques to reduce the phase delay of LPF and improve the current tracking performance under low inductance. The implementation of double sampling in the digital signal processor (DSP) and the design of control loops are discussed. The proposed approach is experimentally verified using a 40 V, 400 W APD converter prototype. © 2024 IEEE.

关键词： Low pass filters

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An integrated strategy of AEF attribute evaluation for reliable thunderstorm detection

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Digital Communications and Networks 2025年第1期11卷 234-245页

作者： Xu Yang Hongyan Xing Xinyuan Ji Xin Su Witold Pedrycz School of Electronics and Information Engineering Nanjing University of Information Science and TechnologyNanjing 210044China Department of Electrical and Computer Engineering University of AlbertaEdmonton AB T6G 2R3Canada College of Internet of Things Engineering Hohai UniversityChangzhou 213022China Systems Research Institute Polish Academy of Sciences00-901 WarsawPoland Department of Computer Engineering Faculty of Engineering and Natural SciencesIstinye UniversitySariyer/IstanbulTurkey

Thunderstorm detection based on the Atmospheric Electric Field(AEF)has evolved from time-domain models to space-domain *** is especially important to evaluate and determine the particularly Weather Attribute(WA),which is directly related to the detection reliability and *** this paper,a strategy is proposed to integrate three currently competitive WA's evaluation ***,a conventional evaluation method based on AEF statistical indicators is *** evaluation approaches include competing AEF-based predicted value intervals,and AEF classification based on fuzzy *** AEF attributes contribute to a more accurate AEF classification to different *** resulting dynamic weighting applied to these attributes improves the classification *** evaluation method is applied to evaluate the WA of a particular AEF,to obtain the corresponding evaluation *** integration in the proposed strategy takes the form of a score *** cumulative score levels correspond to different final WA *** imaging is performed to visualize thunderstorm activities using those AEFs already evaluated to exhibit thunderstorm *** results confirm that the proposed strategy effectively and reliably images thunderstorms,with a 100%accuracy of WA *** is the first study to design an integrated thunderstorm detection strategy from a new perspective of WA evaluation,which provides promising solutions for a more reliable and flexible thunderstorm detection.

关键词： Atmospheric electric field(AEF) Thunderstorm Attribute Fuzzy c-means Imaging

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The Truncated Cone Effect in AFM Nanoindentation on Soft Materials

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Micro and Nanosystems 2023年第2期15卷 153-158页

作者： Kontomaris, Stylianos-Vasileios Malamou, Anna Department of Research and Development BioNanoTec LTD Nicosia Cyprus Faculty of Engineering and Architecture Metropolitan College Athens Greece Radar Systems and Remote Sensing Lab of the School of Electrical & Computer Engineering of National Technical University of Athens Athens Greece

Background: Atomic Force Microscopy (AFM) nanoindentation is the principal method for the characterization of soft materials at the nanoscale. In most cases, pyramidal tips are used and approximated to perfect cones. However, the extended use of the AFM tip may alter its sharp-ness. Objective: In many cases, a truncated cone shape is appropriate for tip modeling. In this technical note, the equation that relates the force with the indentation depth when indenting an elastic half-space using a truncated cone is derived. Methods: The nanoindentation equation for a truncated cone tip is derived using the fundamental differential equation that relates the sample’s contact stiffness with Young’s modulus. Results: When fitting Sneddon’s equation (which is valid for a perfect cone) on data obtained using a truncated cone-shaped AFM tip, the results show a ‘pseudo-softening’ behavior. Conclusion: The AFM tip's sharpness in nanoindentation experiments is a crucial parameter for obtaining the correct mechanical patterns of unknown samples. © 2023 Bentham Science Publishers.

关键词： Biological materials

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A survey on hyperspectral image restoration: from the view of low-rank tensor approximation

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Science China(Information Sciences) 2023年第4期66卷 33-63页

作者： Na LIU Wei LI Yinjian WANG Ran TAO Qian DU Jocelyn CHANUSSOT School of Information and Electronics and Beijing Key Laboratory of Fractional Signals and Systems Beijing Institute of Technology Department of Electrical and Computer Engineering Mississippi State University GIPSA-Lab University of Grenoble Alpes Aerospace Information Research Institute Chinese Academy of Sciences

The ability to capture fine spectral discriminative information enables hyperspectral images(HSIs) to observe, detect and identify objects with subtle spectral discrepancy. However, the captured HSIs may not represent the true distribution of ground objects and the received reflectance at imaging instruments may be degraded, owing to environmental disturbances, atmospheric effects, and sensors' hardware limitations. These degradations include but are not limited to complex noise, heavy stripes, deadlines,cloud/shadow occlusion, blurring and spatial-resolution degradation, etc. These degradations dramatically reduce the quality and usefulness of HSIs. Low-rank tensor approximation(LRTA) is such an emerging technique, having gained much attention in the HSI restoration community, with an ever-growing theoretical foundation and pivotal technological innovation. Compared to low-rank matrix approximation(LRMA),LRTA characterizes more complex intrinsic structures of high-order data and owns more efficient learning abilities, being established to address convex and non-convex inverse optimization problems induced by HSI restoration. This survey mainly attempts to present a sophisticated, cutting-edge, and comprehensive technical survey of LRTA toward HSI restoration, specifically focusing on the following six topics: denoising, fusion,destriping, inpainting, deblurring, and super-resolution. For each topic, state-of-the-art restoration methods are introduced, with quantitative and visual performance assessments. Open issues and challenges are also presented, including model formulation, algorithm design, prior exploration, and application concerning the interpretation requirements.

关键词： hyperspectral image image restoration low-rank tensor approximation multisource fusion remote sensing

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Automatic extraction of lightweight and efficient neural network architecture of heavy convolutional architectures to predict microsatellite instability from hematoxylin and eosin histology in gastric cancer

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Neural Computing and Applications 2024年第25期36卷 15295-15321页

作者： Rostami, Habib Ashkpour, Maryam Behzadi-Khormouji, Hamed Mokhtari, Maral Khayati, Armin Keshavarz, Ahmad Talatian Azad, Saeed Tabesh, Yahya Computer Engineering Department Faculty of Intelligent Systems Engineering and Data Science Persian Gulf University Bushehr75168 Iran Artificial Intelligence and Intelligent Healthcare Lab Artificial Intelligence and Data Mining Research Group Faculty of Intelligent Systems Engineering and Data Science ICT Research Institute Persian Gulf University Bushehr75168 Iran Faculty of New Science and Technologies University of Tehran Tehran Iran Department of Computer Science Imec-IDLab University of Antwerp Sint-Pietersvliet 7 Antwerp2000 Belgium Shahid Faghihi Hospital Shiraz University of Medical Sciences Shiraz Iran Department of Computer Science Engineering and IT School of Electrical and Computer Engineering Shiraz University Shiraz Iran Electrical Engineering Department Faculty of Intelligent Systems Engineering and Data Science Persian Gulf University Bushehr75168 Iran IoT and Signal Processing Research Group Faculty of Intelligent Systems Engineering and Data Science ICT Research Institute Persian Gulf University Bushehr75168 Iran Department of Mathematical Sciences Sharif University of Technology Tehran Iran

Cancers have emerged as a significant concern due to their impact on public health and society. The examination and interpretation of tissue sections stained with Hematoxylin and Eosin (H&E) play a crucial role in disease assessment, particularly in cases like gastric cancer. Microsatellite instability (MSI) is suggested to contribute to the carcinogenesis of specific gastrointestinal tumors. However, due to the nonspecific morphology observed in H&E-stained tissue sections, MSI determination often requires costly evaluations through various molecular studies and immunohistochemistry methods in specialized molecular pathology laboratories. Despite the high cost, international guidelines recommend MSI testing for gastrointestinal cancers. Thus, there is a pressing need for a new diagnostic modality with lower costs and widespread applicability for MSI detection. This study aims to detect MSI directly from H&E histology slides in gastric cancer, providing a cost-effective alternative. The performance of well-known deep convolutional neural networks (DCNNs) and a proposed architecture are compared. Medical image datasets are typically smaller than benchmark datasets like ImageNet, necessitating the use of off-the-shelf DCNN architectures developed for large datasets through techniques such as transfer learning. Designing an architecture proportional to a custom dataset can be tedious and may not yield desirable results. In this work, we propose an automatic method to extract a lightweight and efficient architecture from a given heavy architecture (e.g., well-known off-the-shelf DCNNs) proportional to a specific dataset. To predict MSI instability, we extracted the MicroNet architecture from the Xception network using the proposed method and compared its performance with other well-known architectures. The models were trained using tiles extracted from whole-slide images, and two evaluation strategies, tile-based and whole-slide image (WSI)-based, were employed and comp

关键词： Network architecture

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Continuous flow pyrolysis of virgin and waste polyolefins:a comparative study,process optimization and product characterization

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Frontiers of Chemical Science and engineering 2024年第6期18卷 133-149页

作者： Ecrin Ekici Güray Yildiz Magdalena Joka Yildiz Monika Kalinowska ErolŞeker Jiawei Wang Karlsruhe Institute of Technology Institute of Catalysis Research and TechnologyEggenstein-Leopoldshafen 76344Germany Izmir Institute of Technology Faculty of EngineeringDepartment of Energy Systems EngineeringIzmir 35430Türkiye Department of Materials Engineering and Production Faculty of Mechanical EngineeringBialystok University of TechnologyBialystok 15-351Poland Department of Agricultural and Food Engineering and Environmental Development Institute of Civil Engineering and EnergeticsFaculty of Civil Engineering and Environmental SciencesBialystok University of Technology15-351 BialystokPoland Department of Chemistry Biology and BiotechnologyInstitute of Civil Engineering and EnergeticsFaculty of Civil Engineering and Environmental SciencesBialystok University of TechnologyBialystok 15-351Poland Izmir Institute of Technology Faculty of EngineeringDepartment of Chemical EngineeringIzmir 35430Türkiye Energy and Bioproducts Research Institute(EBRI) Aston UniversityBirmingham B47ETUnited Kingdom

Under optimal process conditions,pyrolysis of polyolefins can yield ca.90 wt%of liquid product,i.e.,combination of light oil fraction and heavier *** this work,the experimental findings reported in a selected group of publications concerning the non-catalytic pyrolysis of polyolefins were collected,reviewed,and compared with the ones obtained in a continuously operated bench-scale pyrolysis *** process parameters were used for the pyrolysis of waste and virgin counterparts of high-density polyethylene,low-density polyethylene,polypropylene and a defined mixture of those(i.e.,25:25:50 wt%,respectively).To mitigate temperature drops and enhance heat transfer,an increased feed intake is employed to create a hot melt plastic *** 1.5 g·min^(-1) feed intake,1.1 L·min^(-1) nitrogen flow rate,and a moderate pyrolysis temperature of 450℃,the formation of light hydrocarbons was favored,while wax formation was limited for polypropylene-rich *** of virgin plastics yielded more liquid(maximum 73.3 wt%)than that of waste plastics(maximum 66 wt%).Blending polyethylenes with polypropylene favored the production of liquids and increased the formation of gasoline-range *** products were mainly composed of C3 hydrocarbons,and no hydrogen production was detected due to moderate pyrolysis temperature.

关键词： waste plastics polyolefins chemical recycling pyrolysis alternative fuels waste-to-energy

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Bionic lightweight design of limb leg units for hydraulic quadruped robots by additive manufacturing and topology optimization

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Bio-Design and Manufacturing 2024年第1期7卷 1-13页

作者： Huaizhi Zong Junhui Zhang Lei Jiang Kun Zhang Jun Shen Zhenyu Lu Ke Wang Yanli Wang Bing Xu The State Key Laboratory of Fluid Power and Mechatronic Systems Zhejiang UniversityHangzhou 310058China Unmanned Vehicle Research and Development Center China North Vehicle Research InstituteBeijing 100072China School of Mechatronic Engineering Nanchang UniversityNanchang 330031China Auclean High-Tech Ltd. Wuxi 214108China

Galloping cheetahs,climbing mountain goats,and load hauling horses all show desirable locomotion capability,which motivates the development of quadruped *** various quadruped robots,hydraulically driven quadruped robots show great potential in unstructured environments due to their discrete landing positions and large *** the most critical movement unit of a quadruped robot,the limb leg unit(LLU)directly affects movement speed and reliability,and requires a compact and lightweight *** by the dexterous skeleton–muscle systems of cheetahs and humans,this paper proposes a highly integrated bionic actuator system for a better dynamic performance of an *** propose that a cylinder barrel with multiple element interfaces and internal smooth channels is realized using metal additive manufacturing,and hybrid lattice structures are introduced into the lightweight design of the piston *** addition,additive manufacturing and topology optimization are incorporated to reduce the redundant material of the structural parts of the *** mechanical properties of the actuator system are verified by numerical simulation and experiments,and the power density of the actuators is far greater than that of cheetah *** mass of the optimized LLU is reduced by 24.5%,and the optimized LLU shows better response time performance when given a step signal,and presents a good trajectory tracking ability with the increase in motion frequency.

关键词： Additive manufacturing Bionic lightweight design Limb leg unit Quadruped robot Trajectory tracking

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