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Evolutionary Optimization Methods for High-Dimensional Expensive Problems:A Survey

IEEE/CAA Journal of Automatica Sinica 2024年第5期11卷 1092-1105页

作者： MengChu Zhou Meiji Cui Dian Xu Shuwei Zhu Ziyan Zhao Abdullah Abusorrah Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewarkNJ 07102 USA School of Information and Electronic Engineering Zhejiang Gongshang UniversityHangzhou 310018China School of Intelligent Manufacturing Nanjing University of Science and TechnologyNanjing 210094China Institute of Systems Engineering Macao University of Science and TechnologyMacao 999078China School of Artificial Intelligence and Computer Jiangnan UniversityWuxi 214122China School of Information Science and Engineering Northeastern UniversityShenyang 110819China Center of Research Excellence in Renewable Energy and Power Systems Department of Electrical and Computer EngineeringFaculty of EngineeringKing Abdulaziz UniversityJeddah 21589Saudi Arabia K.A.CARE Energy Research and Innovation Center King Abdulaziz UniversityJeddah 21589Saudi Arabia

Evolutionary computation is a rapidly evolving field and the related algorithms have been successfully used to solve various real-world optimization *** past decade has also witnessed their fast progress to solve a class of challenging optimization problems called high-dimensional expensive problems(HEPs).The evaluation of their objective fitness requires expensive resource due to their use of time-consuming physical experiments or computer ***,it is hard to traverse the huge search space within reasonable resource as problem dimension *** evolutionary algorithms(EAs)tend to fail to solve HEPs competently because they need to conduct many such expensive evaluations before achieving satisfactory *** reduce such evaluations,many novel surrogate-assisted algorithms emerge to cope with HEPs in recent *** there lacks a thorough review of the state of the art in this specific and important *** paper provides a comprehensive survey of these evolutionary algorithms for *** start with a brief introduction to the research status and the basic concepts of ***,we present surrogate-assisted evolutionary algorithms for HEPs from four main *** also give comparative results of some representative algorithms and application ***,we indicate open challenges and several promising directions to advance the progress in evolutionary optimization algorithms for HEPs.

关键词： computer optimization evolutionary

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Looking Closer to the Transferability Between Natural and Medical Images in Deep Learning

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IEEE Access 2023年 11卷 79838-79850页

作者： Rufaida, Syahidah Izza Putra, Tryan Aditya Leu, Jenq-Shiou Song, Tian Katayama, Takafumi National Taiwan University of Science and Technology Department of Electronic and Computer Engineering Taipei10607 Taiwan Tokushima University Department of Electrical and Electrics Engineering Tokushima770-8506 Japan

Transfer-learning has rapidly become one of the most sophisticated and effective techniques in dealing with medical datasets. The most common transfer-learning method uses of a state-of-the-art model and its corresponding parameters as the starting point for new tasks. Recent studies have found that transfer-learning between medical and natural images has minimal advantages, attributed to their different characteristics, even with sufficient data and iterations. This study employs a meta-learning technique, building upon the traditional transfer learning approach, to explore the potential of natural tasks as a starting point for analyzing medical images. In addition, this study investigates the performance of transferring the searched augmentation from natural to medical images. Several studies proposing search algorithms for data augmentation argue that the augmentation techniques can be effectively transferred across different datasets. The results revealed that the transferability between natural and medical images leads to reduced performance owing to the characteristic difference between medical and natural searched augmentation. © 2013 IEEE.

关键词： Deep learning

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BIOMECHANICAL SIMULATION OF LATERAL ASYMMETRY IN TONGUE BRACING

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Canadian Acoustics - Acoustique Canadienne 2023年第3期51卷 196-197页

作者： Azreen, Jasia Mayer, Connor Liu, Yadong Shamei, Arian Stavness, Ian Gick, Bryan Department of Electrical and Computer Engineering University of British Columbia Canada Department of Language Science University of California Irvine United States Department of Linguistics University of British Columbia Canada Department of Computer Science University of Saskatchewan Canada

Tongue bracing occurs when the lateral edges of the tongue maintain contact with the palate or upper molars. Bracing is pervasive in speech: previous EPG data analysis shows lateral contact to be maintained for 97.5% of the total observation duration [Gick et al. (2017) JSLHR 60, 494]. This research has also indicated the presence of lateral bias or asymmetry in the tongue: a consistent tendency to release contact more on one side than the other, both in unilateral release and in sequential loss of contact during a bilateral release. However, in these cases of asymmetry, it remains unclear which side of the tongue should be considered dominant. The present study explores the question of dominance in lateral tongue bracing through biomechanical simulation of tongue muscle activation. Certain muscles have been identified as bracing agonists (GGP, GGM, MH, VERT, SL) and antagonists (GGA, STY, HG, TRANS, IL) [Liu et al. (2022) Phonetica 79, 523]. Agonists increase the likelihood of bilateral bracing and tend to raise or widen the tongue while antagonists decrease the likelihood of bilateral bracing and tend to lower or narrow the tongue. The current simulations explore whether a unilateral bracing outcome can be produced by asymmetric activation of agonists, antagonists or a combination thereof. Preliminary results from our simulation study show that reducing agonist activation or increasing antagonist activation on one side while keeping activations constant on the other side results in lower tongue-palate contact on the opposite side, due to the hydrostatic properties of the tongue, though the reduction is much greater in the former case. These results suggest that unilateral bracing may be instantiated primarily by contra-lateral muscle activation/deactivation from the side on which bracing contact is maintained, providing a starting point for further exploration of lateral tongue dominance. © 2023, Canadian Acoustical Association. All rights reserved.

关键词： Chemical activation

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HPC Application Parameter Autotuning on Edge Devices: A Bandit Learning Approach 31

HPC Application Parameter Autotuning on Edge Devices: A Band...

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31st Annual IEEE International Conference on High Performance Computing, Data, and Analytics, HiPC 2024

作者： Hossain, Abrar Badawy, Abdel-Hameed A. Islam, Mohammad A. Patki, Tapasya Ahmed, Kishwar Department of Electrical Engineering and Computer Science The University of Toledo United States Department of Electrical and Computer Engineering New Mexico State University United States Department of Computer Science and Engineering The University of Texas Arlington United States Center for Applied Scientific Computing Lawrence Livermore National Laboratory United States

ISBN: (纸本)9798331509095

The growing necessity for enhanced processing capabilities in edge devices with limited resources has led us to develop effective methods for improving high-performance computing (HPC) applications. In this paper, we introduce LASP (Lightweight Autotuning of Scientific Application Parameters), a novel strategy designed to address the parameter search space challenge in edge devices. Our strategy employs a multi-armed bandit (MAB) technique focused on online exploration and exploitation. Notably, LASP takes a dynamic approach, adapting seamlessly to changing environments. We tested LASP with four HPC applications: Lulesh, Kripke, Clomp, and Hypre. Its lightweight nature makes it particularly well-suited for resource-constrained edge devices. By employing the MAB framework to efficiently navigate the search space, we achieved significant performance improvements while adhering to the stringent computational limits of edge devices. Our experimental results demonstrate the effectiveness of LASP in optimizing parameter search on edge devices. © 2024 IEEE.

关键词： Edge computing

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Deep learning-based vehicle event identification

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Multimedia Tools and Applications 2024年第41期83卷 89439-89457页

作者： Chen, Yen-Yu Chen, Jui-Chi Lian, Zhen-You Chiang, Hsin-You Huang, Chung-Lin Chuang, Cheng-Hung Department of Artificial Intelligence and Computer Engineering National Chin-Yi University of Technology No.57 Sec. 2 Zhongshan Rd. Taichung411030 Taiwan Department of Computer Science and Information Engineering Asia University Taichung Japan Department of Electrical Engineering National Tsing Hua University Hsinchu Taiwan

In recent years, there has been a rapid development of intelligent driving assistance systems. Although most vehicles nowadays are equipped with driving assistance systems, the number of car accidents continues to rise. The main cause of car accidents is still largely attributed to human factors. Therefore, there has been an increasing focus on research related to vehicle event recognition and traffic video analysis. This study used deep learning methods to automatically recognize vehicle events from recorded driving videos. We expanded Inception-V3 to a 3D structure and replaced the bottom architecture of SlowFastNet with 3D-Inception-V3 to form a 3D-Inception-V3 + SlowFastNet model, making the network more suitable for video data recognition. In the experiment, we cut all videos into one-second clips and label each clip with vehicle event categories, including vehicle stopping, straight driving, turning, and collision. The experiment utilized training and testing procedures with eight distinct models, i.e., R3D, I3D, I3D + Kinetics-400, SlowFastNet(50), SlowFastNet(101), SlowFastNet(152), SlowFastNet(200), and the proposed 3D-Inception-V3 + SlowFastNet models. Comparative analysis through experiments revealed that our proposed network achieved the highest recognition accuracy of 93.3%. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Deep learning

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Dynamic Outcome Prediction of an NBA Match 18

Dynamic Outcome Prediction of an NBA Match

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18th International Conference on Ubiquitous Information Management and Communication, IMCOM 2024

作者： Kandhway, Kundan Indian Institute of Science Education and Research Department of Electrical Engineering and Computer Science Madhya Pradesh Bhopal462066 India

ISBN: (纸本)9798350331011

In this paper we formulate the problem of predicting the outcome (winner) of an ongoing National Basketball Association (NBA) match as a supervised machine learning problem. In this approach, as the match progresses, the outcome prediction dynamically adapts to the current match situation which does not happen in static prediction problems. Dynamic outcome prediction of the match seems to have received less attention in the literature than static predictions. We compute the features used in the classification problem based on the most up-to-date match situation till that point in time. A total of 32 features are used. We present results for all the regular season matches of the 2022-23 NBA season. Dynamic prediction accuracy varies from about 62% at the beginning of the match to about 78% at the beginning of the final quarter of the match. We also evaluate feature importance in this classification problem. © 2024 IEEE.

关键词： Forecasting

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HoloStream: a GPU-powered high-speed user interface for holographic microscopy imaging

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Optics Express 2025年第7期33卷 15648-15660页

作者： Morales, Johan Obando-Vásquez, Sofia Doblas, Ana Trujillo, Carlos Applied Optics Group School of Applied Science and Engineering EAFIT University Medellin Colombia Optical Imaging Research Lab Electrical and Computer Engineering Department University of Massachusetts Dartmouth DartmouthMA United States

This paper presents HoloStream, a GPU-powered high-speed user interface designed for holographic microscopy imaging. The platform reconstructs quantitative phase images rapidly for off-axis digital holographic microscopy (DHM) systems operating in the telecentric regime. By optimizing critical computational procedures, the HoloStream app reconstructs phase maps of 1280 × 960 pixels up to 11 frames per second (FPS) in live visualization and 90 fps for pre-recorded holographic videos. This real-time phase compensation is performed by upgrading the semi-heuristic phase compensation (SHPC) algorithm through GPU acceleration via PyCUDA. The interface also offers a user-friendly experience with flexible control over acquisition modes, visualization formats, and 3D tracking functionalities. Experimental validation demonstrates the platform’s capability to achieve fast and accurate phase imaging for live microscopy applications. The HoloStream app advances DHM technology by combining high-speed processing with ease of use, making it suitable for a wide range of DHM imaging applications. © 2025 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： computer graphics equipment

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STDG: Fast and Lightweight SNN Training Technique Using Spike Temporal Locality

STDG: Fast and Lightweight SNN Training Technique Using Spik...

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2023 IEEE Biomedical Circuits and Systems Conference, BioCAS 2023

作者： Cai, Zhengyu Kalatehbali, Hamid Rahimian Walters, Ben Azghadi, Mostafa Rahimi Amirsoleimani, Amirali Genov, Roman University of Toronto Department of Electrical and Computer Engineering Toronto Canada York University Department of Electrical Engineering and Computer Science Toronto Canada James Cook University College of Science and Engineering Townsville Australia

ISBN: (纸本)9798350300260

Spiking neural networks (SNNs) possess biological plausibility and energy efficiency as they communicate using asynchronous and mostly sparse spikes. These features make them an ideal choice for efficient neuromorphic computing. The non-differentiable, discrete binary spike events transmitted in SNNs pose a challenge for applying gradient-based optimization algorithms directly to these networks. Therefore, efficient techniques are necessary to enhance energy efficiency without sacrificing accuracy. In this work, we propose Spike Timing Dependent Gradient (STDG), a fast and lightweight learning scheme that uses temporal locality among spikes to avoid non-differentiable derivatives. Our experiments show that STDG reaches the state-of-the-art accuracy of 99.5% and 98.2% on the Caltech101 face/motorbike and the MNIST datasets, respectively. © 2023 IEEE.

关键词： Neuromorphic Computing Spike Timing Dependent Gradient Spike-timing-dependent Learning Spiking Neural Networks

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WLARS: Workload-Aware Recharge Scheduling Mechanism for Improving Surveillance Quality in Wireless Rechargeable Sensor Networks

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IEEE Sensors Journal 2023年第11期23卷 12237-12250页

作者： Dande, Bhargavi Chang, Chih-Yung Wu, Shih-Jung Roy, Diptendu Sinha National Taiwan University Department of Electrical Engineering Taipei10617 Taiwan Tamkang University Department of Computer Science and Information Engineering New Taipei25137 Taiwan National Institute of Technology Meghalaya Department of Computer Science and Engineering Shillong793003 India

With radio frequency (RF), the mobile charger (MC) can wirelessly transmit energy to the sensor nodes in the network. The wireless energy transfer enhances the lifetime of sensor nodes in wireless rechargeable sensor networks (WRSNs). Most of the studies improved the efficiency of MC or perpetuated the lifetime of WRSNs. At the same time, none of the studies focused on considering the spatial and temporal surveillance qualities (STSQs) of each sensor recharged. Therefore, this article proposed an efficient energy recharge scheduling for MC, aiming to maximize the STSQ of the given network. Initially, sensor routing load (RL) is considered to partition the network to distribute the charging load of the MCs evenly. Second, the busy level of the MC is considered to send the recharging requests to the MC. Based on the busy level of MC, the sensors adjust the sensing rate frequency to manage their energy. Finally, cooperation between the neighboring MCs is proposed to reduce the waiting time for recharging requested sensors. The simulation results present that the proposed work yields the literature in terms of STSQ, traveling distance, average waiting time (AWT), and energy usage efficiency. © 2001-2012 IEEE.

关键词： computer architecture

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Priority based k-coverage hole restoration and m-connectivity using whale optimization scheme for underwater wireless sensor networks

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International Journal of Intelligent Networks 2023年第1期4卷 240-252页

作者： Kumari, Sangeeta Mishra, Pavan Kumar Sangaiah, Arun Kumar Anand, Veena School of Computer Science Engineering and Technology Bennett University U.P Greater Noida India India Department of Electrical and Computer Engineering Lebanese American University Byblos Lebanon India

Coverage hole restoration and connectivity is a typical problem for underwater wireless sensor networks. In underwater applications like underwater oilfield reservoirs, undersea minerals and monitoring etc., where nodes face many hurdles and are unable to cover the required region during a natural disaster such as tsunami, flood, earthquakes, and environmental interference. It creates a coverage hole and consumes high energy with bad network quality. This problem considered as an NP-complete problem where a set of sensor nodes is required to identify the k-coverage hole and m-connectivity. In the literature, researchers have not focused on k-coverage hole restoration and m-connectivity issues during natural disasters and environmental interference. To mitigate this problem, we proposed priority-based coverage hole restoration and -connection using a whale optimization scheme to restore coverage holes and extract relevant information for the construction of undersea oilfield reservoirs, minerals, and mines. In this scheme, we identified the list of k-coverage holes and addressed autonomous underwater vehicles (AUVs) to place the additional mobile nodes in an appropriate coverage hole. A novel multi-objective function is formulated to obtain the optimal path for AUVs. Furthermore, while restoring coverage holes, we checked the connectivity of nodes. In the network, each node coordinated sleep scheduling with neighbor nodes to maintain energy efficiency. Performance evaluation of the proposed scheme shows better results than the existing schemes under different network scenarios which provide maximum coverage and connectivity, less energy consumption with a high convergence rate. © 2023 The Authors

关键词： Autonomous underwater vehicles

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