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13th IEEE Congress on Evolutionary Computation, CEC 2024

作者： Li, Yongfeng Zhang, Yuze Ma, Lijia Ji, Junkai Liu, Dugang Leung, Victor C. M. Li, Jianqiang Shenzhen University National Engineering Laboratory for Big Data System Computing Technology Shenzhen518060 China Guangdong Laboratory of Artificial Intelligence and Digital Economy Shenzhen518123 China College of Computer Science and Software Engineering Shenzhen University Shenzhen518060 China Artificial Intelligence Research Institute Shenzhen MSU-BIT University Shenzhen518172 China The University of British Columbia Department of Electrical and Computer Engineering VancouverV6T 1Z4 Canada

ISBN: (纸本)9798350308365

Cooperative co-evolution (CC) is a promising direction in solving large-scale multiobjective optimization problems (LMOPs). However, most existing methods of grouping decision variables face some difficulties when searching in the huge search space. Specifically, the methods of grouping decision variables can be classified into two types, i.e., high-consumption grouping methods and non-consumption grouping methods. On the one hand, the former ones divide the decision variables into different groups based on the correlation analysis between variables, which consume much evaluation. This way may lead to premature convergence within limited computational resources. On the other hand, the later ones allocate the decision variables into sub-groups based on some metrics, e.g., order and size, which consume no evaluation while may cause the search fall into local optima. To alleviate the above issues, this paper proposes a CC-based algorithm with a variable-importance grouping (VIG) method, called VICCA. Firstly, the decision variables are classified into several subgroups according to their importance quantified by a meta-gene construction method. Secondly, a CC strategy is designed to simultaneously optimize all subgroups of decision variables formed by VIG using the differential evolution operator, which aims to accelerate the convergence speed. Thirdly, a global evolutionary strategy is proposed to optimize original decision variable space by the competitive swarm optimizer, aiming to maintain the diversity. Finally, the experiments demonstrate that our proposed VICCA has the significant advantage in solving LMOPs when compared with state-of-the-art evolutionary algorithms. © 2024 IEEE.

关键词： Optimization algorithms

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A Novel Approach to Grover's Quantum Algorithm Simulation: Cloud-Based Parallel computing Enhancements 4

A Novel Approach to Grover's Quantum Algorithm Simulation: C...

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4th International Conference on Smart Electronics and Communication, ICOSEC 2023

作者： Gejea, Adugna Mekonnen Mayakannan, S. Palacios, Rosana Marianela Hamad, Abdulsattar Abdullah Sundaram, Barani Alghamdi, Wajdi Bule Hora University Department of Computer Science Ethiopia Vidyaa Vikas College of Engineering and Technology Department of Mechanical Engineering Tamilnadu Namakkal India Department of Marketing Engineering Riobamba060155 Ecuador Dijlah University College Department of Medical Laboratory Techniques Baghdad Iraq King Abdulaziz University Faculty of Computing and Information Technology Department of Information Technology Jeddah21589 Saudi Arabia

ISBN: (纸本)9798350300888

A truly universal quantum computer is still on the small scale at the present. There has been no transition from the laboratory use of quantum computers to more widespread use of the technology. As a result, quantum simulation has emerged as the accepted norm for supporting the validation of quantum algorithms. Many conventional algorithms benefit from grover's quantum search method because it accelerates their usage of search heuristics. For better multi-core load balancing, memory utilization, and simulation efficiency, this research presented a high-performance grover method simulation that combines the benefits of grover's technique with the parallel of cloud computing. This study also suggests and experimentally compares five distinct cloud-based computing architectures that are well-suited to quantum simulation. Through research and testing, this study also verifies the optimization's efficiency. Depending on the size of the current configuration, the experimental results reveal that the simulation can reach 31 bits. © 2023 IEEE.

关键词： Cloud computing

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Automation 5.0: The Key to Systems Intelligence and Industry 5.0

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IEEE/CAA Journal of Automatica Sinica 2024年第8期11卷 1723-1727页

作者： Ljubo Vlacic Hailong Huang Mariagrazia Dotoli Yutong Wang Petros A.Ioannou Lili Fan Xingxia Wang Raffaele Carli Chen Lv Lingxi Li Xiaoxiang Na Qing-Long Han Fei-Yue Wang Institute of Intelligent and Integrated Systems and the School of Engineering and Built Environment Griffith UniversityNathanQLD 4111Australia Department of Aeronautical and Aviation Engineering The Hong Kong Polytechnic UniversityHong KongChina Department of Electrical and Information Engineering Polytechnic of Bari70126 BariItaly State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190and also with the Qingdao Academy of Intelligent IndustriesQingdao 266114China Department of Electrical Engineering-Systems University of Southern CaliforniaLos AngelesCA 90007 USA School of Automation Beijing Institute of TechnologyBeijing 100081China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049 Beijing Huairou Academy of Parallel Sensing Beijing 101499China School of Mechanical and Aerospace Engineering Nanyang Technological UniversitySingapore 639798Singapore Department of Electrical and Computer Engineering Purdue School of Engineering and TechnologyIndiana University-Purdue University IndianapolisIndianapolisIN 46202 USA Department of Engineering University of CambridgeCB21TN CambridgeU.K. School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourne VIC 3122Australia State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190 School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Dazhou Artificial Intelligence Institute Dazhouand the Faculty of Innovation EngineeringMacao University of Science and TechnologyMacao 999078China

AUTOMATION has come a long way since the early days of mechanization,i.e.,the process of working exclusively by hand or using animals to work with *** rise of steam engines and water wheels represented the first generation of industry,which is now called Industry Citation:***,***,***,***,***,***,***,***,***,***,***,Q.-***,and F.-***,“Automation 5.0:The key to systems intelligence and Industry 5.0,”IEEE/CAA ***,vol.11,no.8,pp.1723-1727,Aug.2024.

关键词： Automation machinery intelligence

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Understanding Cybercrime: A Study of Malware Analysis, Phishing Attacks, and Sentiment Trends

Understanding Cybercrime: A Study of Malware Analysis, Phish...

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Intelligent and Innovative Technologies in computing, electrical and Electronics (IITCEE), International Conference

作者： U. Kumaran Sreeraag G Advik Narendran V. P. Meena Sushil Kumar Gupta Abhishek Appaji Department of Computer Science and Engineering Amrita School of Computing Bangalore Amrita Vishwa Vidyapeetham India Department of Electrical Engineering National Institute of Technology Jamshedpur Jharkhand India Department of Medical Electronics Engineering BMS College of Engineering Bangalore India

ISBN: (数字)9798331515911

ISBN: (纸本)9798331515928

With the rapid evolution of computer systems and technologies, individuals face an increasing threat of cybercrime. This research explores the changing landscape of cybercrime by focusing on three key areas: malware analysis, phishing attack analysis, and sentiment analysis. The study aims to identify malware strategies for evading detection and analyze the prevalence of spyware by examining diverse malware samples. Additionally, trend analysis highlights the rising complexity and frequency of phishing attacks, with a notable shift toward targeting reputable platforms. Sentiment analysis of media headlines surrounding data breaches uncovers a paradox: while concerns about cybersecurity remain, there is a growing confidence in the ability to manage cybersecurity crises. These findings provide insights into emerging threats and evolving public perceptions, offering a comprehensive understanding of the current cyber- crime landscape.

关键词： Sentiment analysis Phishing Focusing Data breach Media Market research Malware Complexity theory computer crime Spyware

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Computational Model Based on CNN to Identify Masses from Liver Images 2

Computational Model Based on CNN to Identify Masses from Liv...

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2nd International Conference on Intelligent Data Communication Technologies and Internet of Things, IDCIoT 2024

作者： Jyothirmai, Ch. N. V. Hemalakshmi, G.R. Prakash, N.B. Upadhye, Vijay Jagdish Patil, Harshal Taqui, Syed Noeman Potti Sreeramulu Chalavadhi Mallikarjuna Rao College of Engineering and Technology Department of CSE Andhra Pradesh 521 225 India School of Computing Science and Engineering VIT Bhopal University Madhya Pradesh 466114 India National Engineering College Department of Electrical and Electronics Engineering Kovilpatti 628503 India Parul Institute of Applied Sciences Parul University Research and Development Cell Department of Microbiology Gujarat 391760 India Department of Computer Science and Engineering Maharashtra 412 115 India Saveetha Institute of Medical and Technical Sciences Department of VLSI Microelectronics Saveetha School of Engineering Chennai602105 India

ISBN: (纸本)9798350327533

Therefore, Convolutional Neural Networks (CNNs) are capable of predicting or extrapolating from identified patterns to unknown data, enabling the analysis and extraction of knowledge from large images, in order to produce consistent outputs for inputs not previously presented. On the downside, the training process takes a long time as it is computationally expensive. Aiming to reduce the computational time to perform the training of the neural network (NN), and the analysis of images during the testing process, as well as taking advantage of the natural distributed characteristic of ANN, it was decided to transfer the processing-intensive parts of the tool from CPU (Central Processing Unit) to a GPU (Graphics Processing Unit). Finally, simulator tests were carried out, with consequent verification of the effectiveness of diagnoses on ultrasound images of the liver. The accuracy and total processing time for carrying out the analyses proposed during this research were then evaluated, making a comparison between the network training and testing times obtained on the CPU and GPU. It can also be seen-in both Tr&Tt cases-that GPU had a higher gain than CPU (about 10.6 times faster), even when dealing with a small database, with 120 images of 202500 pixels each. © 2024 IEEE.

关键词： Central Processing Unit Convolutional Neural Networks Graphics Processing Unit Masses Ultrasound liver images

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Sparse-view CBCT reconstruction using meta-learned neural attenuation field and hash-encoding regularization

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computers in Biology and Medicine 2025年 189卷 109900-109900页

作者： Shin, Heejun Kim, Taehee Lee, Jongho Chun, Se Young Cho, Seungryong Shin, Dongmyung Artificial Intelligence Engineering Division Radisen Co. Ltd. Seoul Korea Republic of Laboratory for Imaging Science and Technology Department of Electrical and Computer Engineering Seoul National University Seoul Korea Republic of Intelligent Computational Imaging Laboratory Department of Electrical and Computer Engineering Seoul National University Seoul Korea Republic of Medical Imaging and Radiotherapy Laboratory Department of Nuclear and Quantum Engineering Korea Advanced Institute of Science and Technology Daejean Korea Republic of

Cone beam computed tomography (CBCT) is an emerging medical imaging technique to visualize the internal anatomical structures of patients. During a CBCT scan, several projection images of different angles or views are collectively utilized to reconstruct a tomographic image. However, reducing the number of projections in a CBCT scan while preserving the quality of a reconstructed image is challenging due to the nature of an ill-posed inverse problem. Recently, a neural attenuation field (NAF) method was proposed by adopting a neural radiance field algorithm as a new way for CBCT reconstruction, demonstrating fast and promising results using only 50 views. However, decreasing the number of projections is still preferable to reduce potential radiation exposure, and a faster reconstruction time is required considering a typical scan time. In this work, we propose a fast and accurate sparse-view CBCT reconstruction (FACT) method to provide better reconstruction quality and faster optimization speed in the minimal number of view acquisitions ( © 2025 Elsevier Ltd

关键词： Image reconstruction

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RE-POSE: Synergizing Reinforcement Learning-Based Partitioning and Offloading for Edge Object Detection

arXiv

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arXiv 2025年

作者： Shi, Jianrui Zhao, Yong Cui, Zeyang Shen, Xiaoming Zeng, Minhang Liu, Xiaojie Department of Electrical and Computer Engineering National University of Singapore Singapore Department of Computing The Hong Kong Polytechnic University Hong Kong School of Computing and Data Science The University of Hong Kong Hong Kong Pengcheng Laboratory Shenzhen China

Object detection plays a crucial role in smart video analysis, with applications ranging from autonomous driving and security to smart cities. However, achieving real-time object detection on edge devices presents significant challenges due to their limited computational resources and the high demands of deep neural network (DNN)-based detection models, particularly when processing high-resolution video. Conventional strategies, such as input down-sampling and network up-scaling, often compromise detection accuracy for faster performance or lead to higher inference latency. To address these issues, this paper introduces RE-POSE, a Reinforcement Learning (RL)Driven Partitioning and Edge Offloading framework designed to optimize the accuracy-latency trade-off in resource-constrained edge environments. Our approach features an RL-Based Dynamic Clustering Algorithm (RL-DCA) that partitions video frames into non-uniform blocks based on object distribution and the computational characteristics of DNNs. Furthermore, a parallel edge offloading scheme is implemented to distribute these blocks across multiple edge servers for concurrent processing. Experimental evaluations show that RE-POSE significantly enhances detection accuracy and reduces inference latency, surpassing existing methods. © 2025, CC BY.

关键词： Computation offloading

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Wi-Wheat+:Contact-free wheat moisture sensing with commodity WiFi based on entropy

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Digital Communications and Networks 2023年第3期9卷 698-709页

作者： Weidong Yang Erbo Shen Xuyu Wang Shiwen Mao Yuehong Gong Pengming Hu College of Information Science and Engineering Henan University of TechnologyZhengzhou450001China Henan Key Laboratory of Grain Photoelectric Detection and Control Zhengzhou450001China College of International Education Kaifeng UniversityKaifengHenan475004China Knight Foundation School of Computing&Information Sciences Florida International UniversityMiamiFL33199USA Department of Electrical and Computer Engineering Auburn UniversityAuburnAL36849-5201USA

In this paper,we propose a contact-free wheat moisture monitoring system,termed Wi-Wheatþ,to address the several limitations of the existing grain moisture detection technologies,such as time-consuming process,expensive equipment,low accuracy,and difficulty in real-time *** proposed system is based on Commodity WiFi and is easy to *** WiFi CSI data,this paper proposes a feature extraction method based on multi-scale and multi-channel *** feasibility and stability of the system are validated through experiments in both Line-Of-Sight(LOS)and Non-Line-Of-Sight(NLOS)scenarios,where ten types of wheat moisture content are tested using multi-class Support Vector Machine(SVM).Compared with the Wi-Wheat system proposed in our prior work,Wi-Wheatþhas higher efficiency,requiring only a simple training process,and can sense more wheat moisture content levels.

关键词： Channel state information(CSI) WiFi Multi-scale entropy Multi-class support vector machine(SVM) Radio frequency(RF)sensing

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Orchestrated desaturation reprogramming from stearoyl-CoA desaturase to fatty acid desaturase 2 in cancer epithelial-mesenchymal transition and metastasis

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Cancer Communications 2025年第3期45卷 245-280页

作者： Zhicong Chen Yanqing Gong Fukai Chen Hyeon Jeong Lee Jinqin Qian Jing Zhao Wenpeng Zhang Yamin Li Yihui Zhou Qiaobing Xu Yu Xia Liqun Zhou Ji-Xin Cheng Department of Obstetrics and Gynecology Center for Reproductive MedicineGuangdong Provincial Key Laboratory of Major Obstetric DiseasesGuangdong Provincial Clinical Research Center for Obstetrics and GynecologyGuangdong-Hong Kong-Macao Greater Bay Area Higher Education Joint Laboratory of Maternal-Fetal MedicineThe Third Affiliated HospitalGuangzhou Medical UniversityGuangzhouGuangdongP.R.China Department of Biomedical Engineering Department of Electrical and Computer EngineeringPhotonics CenterBoston UniversityBostonMassachusettsUSA Department of Urology Peking University First HospitalBeijingP.R.China College of Biomedical Engineering&Instrument Science Key Laboratory for Biomedical Engineering of Ministry of EducationZhejiang UniversityHangzhouZhejiangP.R.China MOE Key Laboratory of Bioorganic Phosphorus Chemistry&Chemical Biology Department of ChemistryTsinghua UniversityBeijingP.R.China State Key Laboratory of Precision Measurement Technology and Instruments Department of Precision InstrumentTsinghua UniversityBeijingP.R.China Department of Biomedical Engineering Tufts UniversityMedfordMassachusettsUSA

Background:Adaptative desaturation in fatty acid(FA)is an emerging hallmark of cancer metabolic *** such as stearoyl-CoA desaturase(SCD)and fatty acid desaturase 2(FADS2)have been implicated in multiple cancers,and their dominant and compensatory effects have recently been ***,how tumors initiate and sustain their self-sufficient FA desaturation to maintain phenotypic transition remains *** study aimed to explore the molecular orchestration of SCD and FADS2 and their specific reprogramming mechanisms in response to cancer ***:The potential interactions between SCD and FADS2 were explored by bioinformatics analyses across multiple cancer cohorts,which guided subsequent functional and mechanistic *** expression levels of desaturases were investigated with online datasets and validated in both cancer tissues and cell *** desaturation activities were characterized through various isomer-resolved lipidomics methods and sensitivity assays using desaturase ***-situ lipid profilingwas conducted using multiplex stimulated Raman scattering *** assays were performed both in vitro and in vivo,with RNA-sequencing employed for the mechanism ***:After integration of the RNA-protein-metabolite levels,the data revealed that a reprogramming fromSCD-dependent to FADS2-dependent desaturation was linked to cancer epithelial-mesenchymal transition(EMT)and progression in both patients and cell ***2 overexpression and SCD suppression concurrently maintained EMT plasticity.A FADS2/β-catenin selfreinforcing feedback loop facilitated the degree of lipid unsaturation,membrane fluidity,metastatic potential and EMT ***,SCD inhibition triggered a lethal apoptosis but boosted survival plasticity by inducing EMT and enhancing FA uptake via adenosine monophosphate-activated protein kinase ***,this desaturation reprogramming increased tra

关键词： metabolic reprogramming stearoyl-CoA desaturase fatty acid desaturase 2 epithelialmesenchymal transition cancer metastasis

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Developing a Series of AI Challenges for the United States department of the Air Force∗

Developing a Series of AI Challenges for the United States D...

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2022 IEEE High Performance Extreme computing Conference, HPEC 2022

作者： Gadepally, Vijay Angelides, Gregory Barbu, Andrei Bowne, Andrew Brattain, Laura J. Broderick, Tamara Cabrera, Armando Carl, Glenn Carter, Ronisha Cha, Miriam Cowen, Emilie Cummings, Jesse Freeman, Bill Glass, James Goldberg, Sam Hamilton, Mark Heldt, Thomas Huang, Kuan Wei Isola, Phillip Katz, Boris Koerner, Jamie Lin, Yen-Chen Mayo, David Mcalpin, Kyle Perron, Taylor Piou, Jean Rao, Hrishikesh M. Reynolds, Hayley Samuel, Kaira Samsi, Siddharth Schmidt, Morgan Shing, Leslie Simek, Olga Swenson, Brandon Sze, Vivienne Taylor, Jonathan Tylkin, Paul Veillette, Mark Weiss, Matthew L Wollaber, Allan Yuditskaya, Sophia Kepner, Jeremy MIT Lincoln Laboratory United States MIT Computer Science and Artificial Intelligence Laboratory United States United States Department of the Air Force United States MIT Electrical Engineering and Computer Science United States Atmospheric and Plenetary Science MIT Department of Earth United States MIT Institute for Medical Engineering & Science United States MIT Connection Science United States

ISBN: (数字)9781665497862

ISBN: (纸本)9781665497862

American leadership in AI. These broad strategy documents have influenced organizations such as the United States department of the Air Force (DAF). The DAF-MIT AI Accelerator is an initiative between the DAF and MIT to bridge the gap between AI researchers and DAF mission requirements. Several projects supported by the DAF-MIT AI Accelerator are developing public challenge problems that address numerous Federal AI research priorities. These challenges target priorities by making large, AI-ready datasets publicly available, incentivizing open-source solutions, and creating a demand signal for dual use technologies that can stimulate further research. In this article, we describe these public challenges being developed and how their application contributes to scientific advances. © 2022 IEEE.

关键词： Large dataset

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