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A Deep Neural Network Approach for Fault Detection in Industrial Motors: Enhancing Reliability and Efficiency in Industry 4.0 21

A Deep Neural Network Approach for Fault Detection in Indust...

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21st IEEE International Conference on Smart Communities: Improving Quality of Life using AI, Robotics and IoT, HONET 2024

作者： Ali, Hassan Ahyen, Mostafa Yaqub, Raziq Badawi, Ahmed Shifa, Noora Khandakar, Amith University of Doha for Science and Technology Department of Electrical Engineering Doha Qatar Alabama A and M University Department of Electrical Engineering and Computer Science Huntsville United States Qatar University Department of Electrical Engineering Doha Qatar

ISBN: (纸本)9798350378078

In the era of Industry 4.0, the integration of sophisticated monitoring and control technologies is essential for the reliability and efficiency of industrial equipment. This paper presents a deep neural network (DNN)-based approach for fault detection and classification in industrial motors. The approach identifies common motor faults, including bent shaft, loose vibration, loosely mounted components, electrical faults, and bearing vibration. The proposed DNN model demonstrated robust performance, achieving an overall training accuracy of 83.49% ± 0.43% and a test accuracy of 81.91 % ± 0.82%. The model also achieved a mean precision of 82.05% ± 0.77%, mean recall of 81.91 % ± 0.82%, and mean F1-Score of81.86%± 0.78%. The 95% confidence intervals for accuracy, precision, recall, and F1-Score were (80.77%, 83.04%), (80.98%, 83.11 %), (80.77%, 83.04%), and (80.78%,82.95%), respectively. These results demonstrate the DNN model's ability to precisely classify various motor faults with minimal variability, as evidenced by its narrow confidence intervals and low standard deviations. The model's reliability and efficacy for real-world applications in proactive maintenance and fault detection are confirmed by the consistent performance that is observed across cross-validation folds. © 2024 IEEE.

关键词： Predictive maintenance

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COMPASS: Compiler Pass Selection For Improving Fidelity Of NISQ Applications 9

COMPASS: Compiler Pass Selection For Improving Fidelity Of N...

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9th Annual IEEE International Conference on Rebooting Computing, ICRC 2024

作者： Dangwal, Siddharth Ravi, Gokul Subramanian Seifert, Lennart Maximilian Das, Poulami Sud, James Chong, Frederic T. Department of Computer Science University of Chicago United States Department of Computer Science and Engineering University of Michigan United States Department of Electrical and Computer Engineering The University of Texas Austin United States

ISBN: (纸本)9798331541279

Noisy qubit devices limit the fidelity of programs executed on near-term or Noisy Intermediate Scale Quantum (NISQ) systems. The fidelity of NISQ applications can be improved by using various optimizations during program compilation (or transpilation). These optimizations or passes are designed to minimize circuit depth (or program duration), steer more computations on devices with lowest error rates, and reduce the communication overheads involved in performing two-qubit operations between non-adjacent qubits. Additionally, standalone optimizations have been proposed to reduce the impact of crosstalk, measurement, idling, and correlated errors. However, our experiments using real IBM quantum hardware show that using all optimizations simultaneously often leads to sub-optimal performance and the highest improvement in application fidelity is obtained when only a subset of passes are used. Unfortunately, identifying the optimal pass combination is non-trivial as it depends on the application and device specific properties. In this paper, we propose COMPASS, an automated software framework for optimal Compiler Pass Selection for quantum programs. COMPASS uses dummy circuits that resemble a given program but is composed of only Clifford gates and thus, can be efficiently simulated classically to obtain its correct output. The optimal pass set for the dummy circuit is identified by evaluating the efficacy of different pass combinations and this set is then used to compile the given program. Our experiments using real IBMQ machines show that COMPASS improves the application fidelity by 4.3x on average and by upto 248.8x compared to the baseline. However, the complexity of this search scales exponential in the number of compiler steps. To overcome this drawback, we propose Efficient COMPASS (E-COMPASS) that leverages a divide-and-conquer approach to split the passes into sub-groups and exhaustively searching within each sub-group. Our evaluations show that E-COMPASS impro

关键词： Qubits

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LSTM-Based Resource Prediction for Disaggregated RAN in 5G Non-Terrestrial Networks 2

LSTM-Based Resource Prediction for Disaggregated RAN in 5G N...

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2nd IEEE Virtual Conference on Communications, VCC 2024

作者： Tsegaye, Henok B. Tshakwanda, Petro M. Worku, Yonatan M. Sacchi, Claudio Christodoulou, Christos Devetsikiotis, Michael University of New Mexico Department of Electrical and Computer Engineering United States University of Trento Department of Information Engineering and Computer Science Italy

ISBN: (纸本)9798331530099

The growing demand for advanced beyond 5G connectivity solutions explores the deployment of end-to-end 5G Non- Terrestrial Networks (NTNs) in cloud-native environments. With the increasing reliance on mobile communications, leveraging next-generation radio access network (NG-RAN) architectures with functional splits has become essential. In the 5G NTN network, some split NG-RAN components can be moved to the satellite node to improve connectivity and resilience. This paper investigates advanced beyond 5G connectivity by deploying end-to-end 5G Non-Terrestrial Networks (NTNs) in cloud-native environments, focusing on Low Earth Orbit (LEO) satellites operating in regenerative mode. Specifically, it explores the implementation of F1 and E1 interface splits within such networks. The first architecture extends the F1 interface over the satellite radio interface (F1 over SRI), linking terrestrial central units (gNB-CU) with satellite-based distributed units (gNB-DU). The second architecture incorporates both F1 and E1 splits, facilitating connections between terrestrial control plane units (gNB-CUCP) and user plane units (gNB-CUUP) on the satellite via the E1 interface over SRI (F1-E1 over SRI). The study's primary goal is to predict the resource utilization-specifically CPU, memory, and bandwidth-of gNB-DU and gNB-CUUP functioning as satellite payloads. Employing Long-Short-Term Memory (LSTM) neural networks, this research aims to enhance network resilience by enabling proactive monitoring and resource allocation decisions, addressing the significant computational and bandwidth demands of payloading gNB-CUUP compared to gNB-DU. © 2024 IEEE.

关键词： 5G mobile communication systems

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MIMO performance enhancement of MIMO arrays using PCS-based near-field optimization technique

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science China(Information sciences) 2023年第6期66卷 170-185页

作者： Yipeng WANG Xiaoming CHEN Huiling PEI Wei E.I.SHA Yi HUANG Ahmed A.KISHK School of Information and Communications Engineering Xi'an Jiaotong University Key Laboratory of Micro-Nano Electronic Devices and Smart Systems of Zhejiang Province College of Information Science and Electronic EngineeringZhejiang University Department of Electrical Engineering and Electronics University of Liverpool Department of Electrical and Computer Engineering Concordia University

Extensive efforts have been made in designing large multiple-input multiple-output(MIMO)arrays. Nevertheless, improvements in conventional antenna characteristics cannot ensure significant MIMO performance improvement in realistic multipath environments. Array decorrelation techniques have been proposed, achieving correlation reductions by either tilting the antenna beams or shifting the phase centers away from each other. Hence, these methods are mainly limited to MIMO terminals with small arrays. To avoid such problems, this work proposes a decorrelation optimization technique based on phase correcting surface(PCS)that can be applied to large MIMO arrays, enhancing their MIMO performances in a realistic(non-isotropic)multipath environment. First, by using a near-field channel model and an optimization algorithm, a near-field phase distribution improving the MIMO capacity is obtained. Then the PCS(consisting of square elements)is used to cover the array's aperture, achieving the desired near-field phase *** examples demonstrate the effectiveness of this PCS-based near-field optimization technique. One is a1 × 4 dual-polarized patch array(working at 2.4 GHz)covered by a 2 × 4 PCS with 0.6λ center-to-center distance. The other is a 2 × 8 dual-polarized dipole array, for which a 4 × 8 PCS with 0.4λ center-to-center distance is designed. Their MIMO capacities can be effectively enhanced by 8% and 10% in single-cell and multi-cell scenarios, respectively. The PCS has insignificant effects on mutual coupling, matching, and the average radiation efficiency of the patch array, and increases the antenna gain by about 2.5 dB while keeping broadside radiations to ensure good cellular coverage, which benefits the MIMO performance of the *** proposed technique offers a new perspective for improving large MIMO arrays in realistic multipath in a statistical sense.

关键词： antenna correlation array antenna multiple-input multiple-output (MIMO) capacity

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LiDAR Technology for Human Activity Recognition: Outlooks and Challenges

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IEEE Internet of Things Magazine 2023年第2期6卷 143-150页

作者： Rinchi, Omar Ghazzai, Hakim Alsharoa, Ahmad Massoud, Yehia Missouri University of Science and Technology Electrical and Computer Engineering Department Rolla United States Thuwal Saudi Arabia

The smart and autonomous learning and recognition of human activities will certainly lead to an incredible progression for several applications and services in public healthcare, education, entertainment, safety and security, and more. With the recent advances in artificial intelligence, signal processing, and computational capabilities, light detection and ranging (LiDAR) technology can play an instrumental role to revamp current human activity recognition (HAR) systems. In this magazine, we investigate the potential of using LiDAR sensors as a novel technology enabling complex and real-time HAR applications. We first overview the HAR categories and the existing state-of-the-art technologies: video-based cameras, depth sensors, wearable devices, and WiFi. Afterward, we delve into the integration of LiDAR technology to perform HAR applications. Then, we discuss the advantages and drawbacks of utilizing LiDAR technology for HAR and compare it with the existing techniques. Finally, we discuss the challenges that need to be addressed to enable advanced LiDAR-based HAR applications. © 2018 IEEE.

关键词： Optical radar

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Crafting chirality in three dimensions via a novel fabrication technique for bound states in the continuum metasurfaces

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Light(science & Applications) 2024年第3期13卷 390-392页

作者： Zaid Haddadin Anna My Nguyen Lisa V.Poulikakos Department of Electrical&Computer Engineering University of California San DiegoLa JollaCAUSA Department of Mechanical&Aerospace Engineering University of California San DiegoLa JollaCAUSA Program of Materials Science&Engineering University of California San DiegoLa JollaCAUSA

An additional deposition step was added to a multi-step electron beam lithographic fabrication process to unlock the height dimension as an accessible parameter for resonators comprising unit cells of quasi-bound stat... 详细信息

关键词： dimensions dimension intrinsic

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Relationship of IQ with Causal Connections Between Brain Salient Network Regions 31

Relationship of IQ with Causal Connections Between Brain Sal...

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31st National and 9th International Iranian Conference on Biomedical engineering, ICBME 2024

作者： Ghoorchian, Mina Soltanian-Zadeh, Hamid Pedram, Mir Mohsen Sadeghi, Mohsen Mir Mohammad Institute for Cognitive Science Studies Department of Cognitive Science Tehran Iran University of Tehran School of Electrical and Computer Engineering Tehran Iran Kharazmi University Department of Electrical and Computer Engineering Faculty of Engineering Tehran Iran

ISBN: (纸本)9798331529710

IQ is one of the indicators that has always been of interest to psychiatrists, doctors and cognitive science researchers. Since this index plays a key role in people's lives and also in the occurrence of brain abnormalities, many studies have been conducted on it. In this paper, we used the resting state magnetic resonance imaging data available in the HCP database to classify people into three groups with low, medium, and high IQ and applied machine learning methods on the matrix of causal connections between related network regions. We applied brain highlights. We calculated the matrix of causal relationships in this network by the spDCM algorithm and then obtained the differences of the three groups using the ANOVA statistical test and 6 edges out of 169 edges with p-value © 2024 IEEE.

关键词： Support vector regression

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A Decentralized Communication Framework Based on Dual-Level Recurrence for Multiagent Reinforcement Learning

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IEEE Transactions on Cognitive and Developmental Systems 2024年第2期16卷 640-649页

作者： Li, Xuesi Li, Jingchen Shi, Haobin Hwang, Kao-Shing Northwestern Polytechnical University School of Computer Science and Engineering Xi'an710129 China National Sun Yat-sen University Department of Electrical Engineering Kaohsiung804 Taiwan

Designing communication channels for multiagent is a feasible method to conduct decentralized learning, especially in partially observable environments or large-scale multiagent systems. In this work, a communication model with dual-level recurrence is developed to provide a more efficient communication mechanism for the multiagent reinforcement learning field. The communications are conducted by a gated-attention-based recurrent network, in which the historical states are taken into account and regarded as the second-level recurrence. We separate communication messages from memories in the recurrent model so that the proposed communication flow can adapt changeable communication objects in the case of limited communication, and the communication results are fair to every agent. We provide a sufficient discussion about our method in both partially observable and fully observable environments. The results of several experiments suggest our method outperforms the existing decentralized communication frameworks and the corresponding centralized training method. © 2016 IEEE.

关键词： Decision making

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Heat Transfer Area Optimization for Heat Exchanger System

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computer Modeling in engineering & sciences 2025年第4期143卷 335-349页

作者： Yu-Cheng Liao Fu-I Chou Po-Yuan Yang Jyh-Horng Chou Department of Electrical Engineering National Kaohsiung University of Science and TechnologyKaohsiung807Taiwan Department of Intelligent Robotics National Pingtung UniversityPingtung900Taiwan Department of Mechanical and Computer-Aided Engineering Feng Chia UniversityTaichung407Taiwan

This paper presents an allowable-tolerance-based group search optimization(AT-GSO),which combines the robust GSO(R-GSO)and the external quality design planning of the Taguchi ***-GSO algorithm is used to optimize the heat transfer area of the heat exchanger *** R-GSO algorithm integrates the GSO algorithm with the Taguchi method,utilizing the Taguchi method to determine the optimal producer in each iteration of the GSO algorithm to strengthen the robustness of the search process and the ability to find the global *** conventional parameter design optimization,it is typically assumed that the designed parameters can be applied accurately and consistently throughout ***,for systems that are sensitive to changes in design parameters,even minor inaccuracies can substantially reduce overall system ***,the permissible variations of the design parameters are considered in the tolerance-optimized design to ensure the robustness of the *** optimized design of the heat exchanger system assumes that the system’s operating temperature parameters are ***,fixing the systemoperating temperature parameters at a constant value is *** paper assumes that the system operating temperature parameters have an uncertainty error when optimizing the heat transfer area of the heat exchanger *** results show that the AT-GSO algorithm optimizes the heat exchanger system and finds the optimal operating temperature in the absence of tolerance and under three tolerance conditions.

关键词： Heat exchanger system allowable tolerance-based group search optimization Taguchi method tolerance design

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PIDSNeRF: pose interpolation depth supervision neural radiance fields for view synthesis from challenging input

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Multimedia Tools and Applications 2024年 1-21页

作者： Wang, Jianxin Shao, Haijian Deng, Xing Jiang, Yingtao School of Computer Jiangsu University of Science and Technology Jiangsu Zhenjiang212003 China Department of Electrical and Computer Engineering University of Nevada Las VegasNV89154 United States

Recently, Neural Radiance Fields(NeRF) have shown remarkable performance in the task of novel view synthesis through multi-view. The present study introduces an advanced optimization framework, termed Pose Interpolation Depth Supervision Neural Radiance Fields (PIDSNeRF), designed to address the challenges encountered by NeRF in novel view synthesis. These challenges manifest as artifacts, texture details loss, and geometric inconsistencies, particularly in scenes characterized by different lighting conditions, Textureless regions, and sparse images as inputs. The principle of PIDSNeRF involves interpolating virtual camera positions in the 3D space domain based on known cameras, Subsequently, the sparse point clouds formed during camera pose estimation is re-projected onto these virtual poses, employing an inverse angle weighting strategy, thereby generating depth-supervised rays. Furthermore, we propose a depth diffusion method that spreads depth-supervised rays along the pixel plane, forming Gaussian functions with different variances based on the diffusion distances. Finally, depth supervision during volume rendering is achieved by optimizing the Kullback-Leibler(KL) divergence between the weight distribution of sampled points along each ray and the probability density function of the corresponding Gaussian function along that ray. The above process enables a more comprehensive optimization of multi-resolution grid features that align with the sampled points along the rays. The experiments on the DTU, LLFF, and DL3DV-10K datasets demonstrate, PIDSNeRF can synthesize complete novel views within minutes, and the various metrics of the synthesized images achieve the best performance. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Probability density function

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