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Deep Learning-Based ECG Classification for Arterial Fibrillation Detection

Computers, Materials & Continua 2024年第6期79卷 4805-4824页

作者： Muhammad Sohail Irshad Tehreem Masood Arfan Jaffar Muhammad Rashid Sheeraz Akram Abeer Aljohani Faculty of Computer Science&Information Technology The Superior UniversityLahore54000Pakistan intelligent Data Visual computing research(IDVCR) Lahore54000Pakistan Department of Computer Science National University of TechnologyIslamabad45000Pakistan Information systems Department College of Computer and Information SciencesImam Mohammad Ibn Saud Islamic University(IMSIU)Riyadh11432Saudi Arabia Department of Computer Science Applied CollegeTaibah UniversityMedina42353Saudi Arabia

The application of deep learning techniques in the medical field,specifically for Atrial Fibrillation(AFib)detection through Electrocardiogram(ECG)signals,has witnessed significant *** and timely diagnosis increases the patient’s chances of ***,issues like overfitting and inconsistent accuracy across datasets remain *** a quest to address these challenges,a study presents two prominent deep learning architectures,ResNet-50 and DenseNet-121,to evaluate their effectiveness in AFib *** aim was to create a robust detection mechanism that consistently performs *** such as loss,accuracy,precision,sensitivity,and Area Under the Curve(AUC)were utilized for *** findings revealed that ResNet-50 surpassed DenseNet-121 in all evaluated *** demonstrated lower loss rate 0.0315 and 0.0305 superior accuracy of 98.77%and 98.88%,precision of 98.78%and 98.89%and sensitivity of 98.76%and 98.86%for training and validation,hinting at its advanced capability for AFib *** insights offer a substantial contribution to the existing literature on deep learning applications for AFib detection from ECG *** comparative performance data assists future researchers in selecting suitable deep-learning architectures for AFib ***,the outcomes of this study are anticipated to stimulate the development of more advanced and efficient ECG-based AFib detection methodologies,for more accurate and early detection of AFib,thereby fostering improved patient care and outcomes.

关键词： Convolution neural network atrial fibrillation area under curve ECG false positive rate deep learning classification

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An adaptive large neighborhood search for the multi-point dynamic aggregation problem

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Control Theory and Technology 2024年第3期22卷 360-378页

作者： Shengyu Lu Bin Xin Jie Chen Miao Guo School of Automation Beijing Institute of TechnologyBeijing 100081China national Key Lab of Autonomous intelligent Unmanned systems Beijing 100081China Department of Control Science and Engineering Tongji UniversityShanghai 201804China

The multi-point dynamic aggregation(MPDA)problem is a challenging real-world *** the MPDA problem,the demands of tasks keep changing with their inherent incremental rates,while a heterogeneous robot fleet is required to travel between these tasks to change the time-varying state of each *** robots are allowed to collaborate on the same task or work separately until all tasks are *** is challenging to generate an effective task execution plan due to the tight coupling between robots abilities and tasks'incremental rates,and the complexity of robot *** effectiveness consideration,we use the variable length encoding to avoid redundancy in the solution *** creatively use the adaptive large neighborhood search(ALNS)framework to solve the MPDA *** the proposed algorithm,high-quality initial solutions are generated through multiple problem-specific solution construction *** heuristics are also used to fix the broken solution in the novel integrated decoding-construction repair process of the ALNS *** results of statistical analysis by the Wilcoxon rank-sum test demonstrate that the proposed ALNS can obtain better task execution plans than some state-of-the-art algorithms in most MPDA instances.

关键词： Adaptive large neighborhood search(ALNS) Multi-point dynamic aggregation(MPDA) Heuristic solution construction Multi-robot collaboration

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A Lightweight Intrusion Detection System Using Convolutional Neural Network and Long Short-Term Memory in Fog computing

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Computers, Materials & Continua 2024年第9期80卷 4703-4728页

作者： Hawazen Alzahrani Tarek Sheltami Abdulaziz Barnawi Muhammad Imam Ansar Yaser Computer Engineering Department Interdisciplinary Research Center of Smart Mobility and LogisticsKing Fahd University of Petroleum and MineralsDhahran31261Saudi Arabia Computer Engineering Department Interdisciplinary Research Center for Intelligent Secure SystemsKing Fahd University of Petroleum and MineralsDhahran31261Saudi Arabia Transportation research Institute(IMOB) Hasselt UniversityHasselt3500Belgium

The Internet of Things(IoT)links various devices to digital services and significantly improves the quality of our ***,as IoT connectivity is growing rapidly,so do the risks of network vulnerabilities and *** interesting Intrusion Detection systems(IDSs)are presented based on machine learning(ML)techniques to overcome this *** the resource limitations of fog computing environments,a lightweight IDS is *** paper introduces a hybrid deep learning(DL)method that combines convolutional neural networks(CNN)and long short-term memory(LSTM)to build an energy-aware,anomaly-based *** test this system on a recent dataset,focusing on reducing overhead while maintaining high accuracy and a low false alarm *** compare CICIoT2023,KDD-99 and NSL-KDD datasets to evaluate the performance of the proposed IDS model based on key metrics,including latency,energy consumption,false alarm rate and detection rate *** findings show an accuracy rate over 92%and a false alarm rate below 0.38%.These results demonstrate that our system provides strong security without excessive resource *** practicality of deploying IDS with limited resources is demonstrated by the successful implementation of IDS functionality on a Raspberry Pi acting as a Fog *** proposed lightweight model,with a maximum power consumption of 6.12 W,demonstrates its potential to operate effectively on energy-limited devices such as low-power fog nodes or edge *** prioritize energy efficiency whilemaintaining high accuracy,distinguishing our scheme fromexisting *** experiments demonstrate a significant reduction in false positives,ensuring accurate identification of genuine security threats while minimizing unnecessary alerts.

关键词： Intrusion detection fog computing CNN LSTM energy consumption

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A LESO Based Backstepping Controller Considering Coal Seam Hardness for Rotary Speed in Coal Mine Tunnel Drilling Process

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Journal of systems Science & Complexity 2024年第5期37卷 1789-1808页

作者： CHEN Luefeng LIU Xiao WU Min LU Chengda PEDRYCZ Witold HIROTA Kaoru School of Automation China University of GeosciencesWuhan 430074China Hubei Key Laboratory of Advanced Control and intelligent Automation for Complex systems Wuhan 430074China Engineering research center of intelligent Technology for Geo-Exploration Ministry of EducationWuhan 430074China Department of Electrical and Computer Engineering University of AlbertaEdmontonAB T6R2G7Canada The Tokyo Institute of Technology Yokohama 226-8502Japan

In the process of coal mine drilling,controlling the rotary speed is important as it determines the efficiency and safety of *** this paper,a linear extended state observer(LESO)based backstepping controller for rotary speed is proposed,which can overcome the impact of changes in coal seam hardness on rotary ***,the influence of coal seam hardness on the drilling rig’s rotary system is considered for the first time,which is reflected in the numerical variation of load torque,and a dynamic model for the design of rotary speed controller is *** an LESO is designed to observe the load torque,and feedforward compensation is carried out to overcome the influence of coal seam *** on the model of the compensated system,a backstepping method is used to design a controller to achieve tracking control of the rotary ***,the effectiveness of the controller designed in this paper is demonstrated through simulation and field experiments,the steady-state error of the rotary speed in field is 1 r/min,and the overshoot is reduced to 5.8%.This greatly improves the stability and security,which is exactly what the drilling process requires.

关键词： Backstepping extended state observer hydraulic tunnel drilling machine rotary speed

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Room-temperature ferrimagnetism and size-modulated electronic structures in two-dimensional cluster-based metal-organic frameworks

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Science China Chemistry 2024年第4期67卷 1334-1340页

作者： Jing Cheng Xingxing Li Jinlong Yang Key Laboratory of Precision and intelligent Chemistry University of Science and Technology of ChinaHefei 230026China Department of Chemical Physics University of Science and Technology of ChinaHefei 230026China Hefei national research center for Physical Sciences at the Microscale University of Science and Technology of ChinaHefei 230026China Hefei national Laboratory University of Science and Technology of ChinaHefei 230088China

Cluster-assembled materials have attracted particular attention for their complex hierarchical structures and unique ***,the majority of cluster-based assemblies developed so far are either non-magnetic or only exhibit magnetic ordering with a relatively low Curie temperature,limiting their applications in ***,two-dimensional(2D)cluster-assembled materials with room-temperature magnetism remain highly *** this purpose,based on first principles calculations,we design a series of thermodynamically stable 2D cluster-based metal-organic frameworks(MOFs)Fe_(n)-(pyz)(n=1-6)by utilizing Fenmetal clusters as nodes and nitrogen-containing pyrazine ligands as organic *** 2D cluster-based MOFs exhibit robust ferrimagnetic ordering due to the strong d-p direct exchange interaction between d-electron spin of Fe_(n)(n=1-6)clusters and charge transfer-induced p-electron spin of pyrazine *** particular,the ferrimagnetic Curie temperatures are well above room temperature(up to 836 K).Additionally,altering the size of Fe_(n)clusters in Fe_(n)-(pyz)(n=1-6)MOFs results in diverse functional spintronic properties,including bipolar magnetic semiconductors,half semiconductors and Dirac half ***,these 2D assembled MOFs possess sizable magnetic anisotropy energies,up to 9.16 me V per formula.

关键词： metal-organic framework two-dimensional material half metal bipolar magnetic semiconductor magnet

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Storage dynamics of ions on graphene

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Interdisciplinary Materials 2024年第2期3卷 189-202页

作者： Minghao Guo Kun Ni Yanwu Zhu Key Laboratory of Precision and intelligent Chemistry Department of Materials Science and EngineeringSchool of Chemistry and Materials ScienceHefei National Research Center for Physical Sciences at the MicroscaleUniversity of Science and Technology of ChinaHefeiAnhuiChina

Carbon has been widely utilized as electrode in electrochemical energy storage,relying on the interaction between ions and *** performance of a carbon electrode is determined by a variety of factors including the structural features of carbon material and the behavior of ions adsorbed on the carbon surface in the specific *** the fundamental unit of graphitic carbons,graphene has been employed as a model to understand the energy storage mechanism of carbon materials through various experimental and computational methods,ex‐situ or in‐*** this article,we provide a succinct overview of the state‐of‐the‐art proceedings on the ion storage mechanism on *** include the structure engineering of carbons,electric gating effect of ions,ion dynamics on the interface or in the confined space,and specifically lithium‐ion storage/reaction on *** aim is to facilitate the understanding of electrochemistry on carbon electrodes.

关键词： graphene ion dynamics ion storage ionic gating nano-confinement

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Decoupled deep hough voting for point cloud registration

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Frontiers of Computer Science 2024年第2期18卷 147-155页

作者： Mingzhi YUAN Kexue FU Zhihao LI Manning WANG Digital Medical research center School of Basic Medical SciencesFudan UniversityShanghai 200032China Shanghai Key Laboratory of Medical Image computing and Computer Assisted Intervention Shanghai 200032China

Estimating rigid transformation using noisy correspondences is critical to feature-based point cloud ***,a series of studies have attempted to combine traditional robust model fitting with deep *** them,DHVR proposed a hough voting-based method,achieving new state-of-the-art ***,we find voting on rotation and translation simultaneously hinders achieving better ***,we proposed a new hough voting-based method,which decouples rotation and translation ***,we first utilize hough voting and a neural network to estimate *** based on good initialization on rotation,we can easily obtain accurate rigid *** experiments on 3DMatch and 3DLoMatch datasets show that our method achieves comparable performances over the state-of-the-art *** further demonstrate the generalization of our method by experimenting on KITTI dataset.

关键词： point cloud registration robust model fitting deep learning hough voting

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Resource Allocation for Channel Estimation in Reconfigurable intelligent Surface-Aided Multi-Cell Networks

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Journal of Communications and Information Networks 2024年第1期9卷 64-79页

作者： Yining Xu Sheng Zhou Department of Electronic Engineering Beijing National Research Center for Information Science and TechnologyTsinghua UniversityBeijing 100084China

Reconfigurable intelligent surface(RIS)is a promising solution to deal with the blockage-sensitivity of millimeter wave band and reduce the high energy consumption caused by network densification. However, deploying large scale RISs may not bring expected performance gain due to significant channel estimation overhead and non-negligible reflected *** this paper,we derive the analytical expressions of the coverage probability, area spectrum efficiency(ASE)and energy efficiency (EE)of a downlink RIS-aided multi-cell *** order to optimize the network performance, we investigate the conditions for the optimal number of training symbols of each antenna-to-antenna and antenna-to-element path (referred to as the optimal unit training overhead) in channel *** study shows that:1)RIS deployment is not“the more, the better”, only when blockage objects are dense should one deploy more RISs;2) the coverage probability is maximized when the unit training overhead is designed as large as possible;3)however,the ASE-and-EE-optimal unit training overhead exists. It is a monotonically increasing function of the frame length and a monotonically decreasing function of the average signal-to-noise-ratio (in the high signal-to-noise-ratio region). Additionally,the optimal unit training overhead is smaller when communication nodes deploy particularly few or many antennas.

关键词： reconfigurable intelligent surface multi-cell network directional transmissions channel estimation resource allocation stochastic geometry

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Stereoselective recognition of morphine enantiomers by μ-opioid receptor

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national Science Review 2024年第3期11卷 183-191页

作者： Yibo Wang Van A.Ngo Xiaohui Wang Laboratory of Chemical Biology Changchun Institute of Applied ChemistryChinese Academy of Sciences Advanced computing for Life Sciences and Engineering Group Science Engagement Section National Center for Computational Sciences Oak Ridge National Lab School of Applied Chemistry and Engineering University of Science and Technology of China Beijing national Laboratory for Molecular Sciences

Stereospecific recognition of chiral molecules plays a crucial role in biological systems. The μ-opioid receptor（MOR） exhibits binding affinity towards（-）-morphine, a well-established gold standard in pain management, while it shows minimal binding affinity for the（+）-morphine enantiomer, resulting in a lack of analgesic activity. Understanding how MOR stereoselectively recognizes morphine enantiomers has remained a puzzle in neuroscience and pharmacology for over half-a-century due to the lack of direct observation techniques. To unravel this mystery, we constructed the binding and unbinding processes of morphine enantiomers with MOR via molecular dynamics simulations to investigate the thermodynamics and kinetics governing MOR's stereoselective recognition of morphine enantiomers. Our findings reveal that the binding of（-）-morphine stabilizes MOR in its activated state, exhibiting a deep energy well and a prolonged residence time. In contrast,（+）-morphine fails to sustain the activation state of ***, the results suggest that specific residues, namely D1142.50and D1473.32, are deprotonated in the active state of MOR bound to（-）-morphine. This work highlights that the selectivity in molecular recognition goes beyond binding affinities, extending into the realm of residence time.

关键词： stereoselective recognition thermodynamics and kinetics residence time morphine enantiomers μ-opioid receptor

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Optimal confrontation position selecting games model and its application to one-on-one air combat

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Defence Technology（防务技术） 2024年第1期31卷 417-428页

作者： Zekun Duan Genjiu Xu Xin Liu Jiayuan Ma Liying Wang School of Mathematics and Statistics Northwestern Polytechnical UniversityXi'an 710072China International Joint research center on Operations research Optimization and Artificial IntelligenceXi'an 710129China AVIC Xi’an Aeronautics computing Technique research Institute Xi'an 710065China Unmanned System research Institute Northwestern Polytechnical UniversityXi'an 710072China

In the air combat process,confrontation position is the critical factor to determine the confrontation situation,attack effect and escape probability of ***,selecting the optimal confrontation position becomes the primary goal of maneuver *** taking the position as the UAV’s maneuver strategy,this paper constructs the optimal confrontation position selecting games(OCPSGs)*** the OCPSGs model,the payoff function of each UAV is defined by the difference between the comprehensive advantages of both sides,and the strategy space of each UAV at every step is defined by its accessible space determined by the *** we design the limit approximation of mixed strategy Nash equilibrium(LAMSNQ)algorithm,which provides a method to determine the optimal probability distribution of positions in the strategy *** the simulation phase,we assume the motions on three directions are independent and the strategy space is a cuboid to simplify the *** simulations are performed to verify the feasibility,effectiveness and stability of the algorithm.

关键词： Unmanned aerial vehicles(UAVs) Air combat Continuous strategy space Mixed strategy Nash equilibrium

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