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A Length-Adaptive Non-Dominated Sorting Genetic Algorithm for Bi-Objective High-Dimensional Feature Selection

IEEE/CAA Journal of Automatica Sinica 2023年第9期10卷 1834-1844页

作者： Yanlu Gong Junhai Zhou Quanwang Wu MengChu Zhou Junhao Wen College of Computer Science Chongqing UniversityChongqing 400044China IEEE Department of Electrical and Computer Engineering New Jersey Institute of TechnologyNewarkNJ 07102 USA College of Big Data and Software Engineering Chongqing UniversityChongqing 400044China

As a crucial data preprocessing method in data mining,feature selection(FS)can be regarded as a bi-objective optimization problem that aims to maximize classification accuracy and minimize the number of selected *** computing(EC)is promising for FS owing to its powerful search ***,in traditional EC-based methods,feature subsets are represented via a length-fixed individual *** is ineffective for high-dimensional data,because it results in a huge search space and prohibitive training *** work proposes a length-adaptive non-dominated sorting genetic algorithm(LA-NSGA)with a length-variable individual encoding and a length-adaptive evolution mechanism for bi-objective highdimensional *** LA-NSGA,an initialization method based on correlation and redundancy is devised to initialize individuals of diverse lengths,and a Pareto dominance-based length change operator is introduced to guide individuals to explore in promising search space ***,a dominance-based local search method is employed for further *** experimental results based on 12 high-dimensional gene datasets show that the Pareto front of feature subsets produced by LA-NSGA is superior to those of existing algorithms.

关键词： Bi-objective optimization feature selection(FS) genetic algorithm high-dimensional data length-adaptive

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Ferroelectrically gated two-dimensional bismuth oxyselenides for strain-invariant flexible synaptic thin-film transistors

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science China(Information sciences) 2025年第5期68卷 396-403页

作者： Jie WEN Fei XIAO Zheng-Dong LUO Dongxin TAN Xuetao GAN Dawei ZHANG Zhufei CHU Yinshui XIA Yan LIU Genquan HAN Hangzhou Institute of Technology Xidian University State Key Discipline Laboratory of Wide Band Gap Semiconductor Technology School of MicroelectronicsXidian University Key Laboratory of Light Field Manipulation and Information Acquisition Ministry of Industry and Information Technology Shaanxi Key Laboratory of Optical Information Technology School of Physical Science and Technology Northwestern Polytechnical University School of Materials Science and Engineering The University of New South Wales ARC Centre of Excellence in Future Low-Energy Electronics Technologies (FLEET) The University of New South Wales Faculty of Electrical Engineering Computer Science Ningbo University

Two-dimensional van der Waals（2D vdW） semiconductors have proven to be of great importance for flexible thinfilm transistors（TFTs） owing to their intrinsic mechanical flexibility and superior electronic *** particular,bismuth oxyselenide（Bi2O2Se）,featuring ultrahigh electron mobility along with facile scalable thin-film growth methods,could offer a new option to deliver massively enhanced potential for flexible ***,it has remained a challenge to achieve nonvolatile flexible memory devices based on Bi2O2Se TFTs,thereby hindering the extension of Bi2O2Se TFTs to storage and emerging neuromorphic computing ***,a flexible synaptic TFT is demonstrated through the creation of a Bi2O2Se-based ferroelectric field-effect transistor（FeFET） structure on the flexible mica *** proposed device exhibits excellent nonvolatile memory characteristics,including a large memory window,excellent current modulation ratio,great retention,and strong ***,the Bi2O2Se-based FeFET can be operated as a synaptic device with analog conductance-modulating *** to the superior mechanical flexibility of the component materials and the mica substrate,the Bi2O2Se-based FeFETs can retain their performance against various bending states,showing a straininvariant electrical *** study marks the advancement of Bi2O2Se-based TFTs toward flexible nonvolatile memories and synaptic devices.

关键词： Bi$_{2}$O$_{2}$Se FeFET nonvolatile memory flexible device synaptic transistor

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Deadline-aware and energy efficient IoT task scheduling using fuzzy logic in fog computing

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Multimedia Tools and Applications 2025年第15期84卷 14359-14386页

作者： Thakur, Rahul Sikka, Geeta Bansal, Urvashi Giri, Jayant Mallik, Saurav Department of Computer Science and Engineering Dr. B R Ambedkar National Institute of Technology Punjab Jalandhar144011 India Department of Computer Science and Engineering National Institute of Technology Delhi Delhi110036 India Department of Mechanical Engineering Yeshwantrao Chavan College of Engineering Nagpur India Department of Environmental Health Harvard T H Chan School of Public Health BostonMA United States Saveetha University TN Chennai602105 India

Fog computing is an emerging paradigm that extends cloud computing (CC) by providing computation, communication, and storage services at the edge of a network, closer to end devices. It has gained significance due to the rapid development of IoT devices, which generate various types of tasks. Processing these tasks in the cloud can strain its infrastructure and lead to delays in time-sensitive requests. To address this limitation, fog computing (FC) concepts were introduced in 2012 by Cisco. FC is not meant to replace CC but rather to complement and extend its capabilities. One of the challenges in FC is efficiently assigning tasks to appropriate resources to minimize makespan, energy consumption (EC), and increase the number of deadline-satisfied tasks. In this work, the improvement of semi-greedy algorithm has been done by incorporating fuzzy logic (FL). By leveraging FL, the aim is to enhance the algorithm's decision-making process and make it more adaptive to varying conditions and uncertainties in the fog environment. The use of FL allows more nuanced and flexible task scheduling (TS) decisions based on fuzzy sets and fuzzy rules. The simulation experiments demonstrate that the proposed algorithm outperforms PSG (Priority-aware Semi-Greedy) and PSG-M (PSG with multistart), which were identified as the best scheduling algorithms (Algos) in the literature review. The algorithm exhibits better performance in terms of reducing makespan, EC, and increasing the percentage of deadline-satisfied tasks compared to PSG and PSG-M. The inclusion of FL further enhances the algorithm's effectiveness in handling complex scheduling scenarios in a FC environment. To evaluate the performance of the proposed algorithm, different simulation experiments have been conducted using a selected simulator after a systematic review of existing simulators. The experiments involved 300 and 500 random and static tasks, as well as 60 fog nodes in the fog environment. All simulations were impl

关键词： Fog computing

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ReE3D: Boosting Novel View Synthesis for Monocular Images using Residual Encoders

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IEEE Transactions on Multimedia 2023年 1-11页

作者： Guo, KeHua Chen, Tianyu Ren, Sheng Hu, Bin Wu, Zheng Guo, Shaojun Fang, Hui School of Computer Science and Engineering Central South University Changsha China School of Computer and Electrical Engineering Hunan University of Arts and Science Changde China National Innovation of Defense Technology Academy of Military Sciences PLA China Beijing China Computer Science Department Loughborough University Loughborough U.K

In recent years, novel view synthesis from a monocular image has become a research hot-spot that attracts significant attention. Some recent work identifies latent vectors for high-quality view generation via iterative optimisation, which is a time-consuming process. In contrast, some others utilise an encoder learning a mapping function to approximately estimate optimal latent codes, which significantly reduces its processing time but sacrifices reconstruction quality. Consequently, how to balance synthesis quality and its generation efficiency still remains challenging. In this paper, we propose a residual-based encoder to incorporate with a 3D Generative Adversarial Networks (GAN), named ReE3D, for novel view synthesis. It applies an iterative prediction of latent codes to ensure much higher quality of novel view synthesis with an insignificant increase of processing time when compared to existing encoder-based 3D GAN inversion methods. Additionally, we enforce a novel geometric loss constraint on the encoder to predict view-invariant latent codes, thus effectively mitigating the trade-off between geometric and texture quality in 3D GAN inversion. Extensive experimental results demonstrate that our extended encoder-based method has achieved best trade-off performance in terms of novel view synthesis quality and its execution time. Our method has gained comparable synthesis quality with exponentially decreased processing time when compared to iterative optimisation methods, while improved synthesis performance of encoder-based methods significantly. IEEE

关键词： Generative adversarial networks

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Deep Learning Algorithms for EEG-Based Driver Drowsiness Detection: A Comparative Investigation 10

Deep Learning Algorithms for EEG-Based Driver Drowsiness Det...

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10th IEEE Information technology International Seminar, ITIS 2024

作者： Hasan, Md Mahmudul Mahfuj Hossain, Mirza Sulaiman, Norizam Islam, Md Nahidul Khandaker, Sayma Universiti Malaysia Pahang Al-Sultan Abdullah Faculty of Electrical and Electronics Engineering Technology Pahang Malaysia Jashore University of Science and Technology Department of Computer Science and Engineering Jashore Bangladesh

ISBN: (纸本)9798331521295

Due to the significant variability in electroencephalogram (EEG) signals across individuals and recording sessions, developing a calibration-free system for detecting driver drowsiness presents a considerable challenge. While numerous deep learning techniques have been employed to analyze EEG signals for this purpose, most existing studies rely on deep learning models with limited success in accurately detecting drowsiness. In this research, we explored the application of five deep learning algorithms such as Artificial Neural Networks (ANN), Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), Gated Recurrent Units (GRU), and Long Short-Term Memory (LSTM), to improve the detection of driver drowsiness. Our applied models achieve detection accuracies of 73.46% for ANN, 80.09% for CNN, 65.74% for RNN, 83.95% for GRU, and 77.62% for LSTM across 11 subjects, outperforming conventional baseline approaches and state-of-the-art deep learning methods. Notably, the GRU model demonstrated superior accuracy in recognizing drowsiness from EEG signals compared to other applied models. © 2024 IEEE.

关键词： Convolutional neural networks

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Differential Privacy Preserving Quantum Computing via Projection Operator Measurements 1

Differential Privacy Preserving Quantum Computing via Projec...

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1st International Conference on Quantum Communications, Networking, and Computing, QCNC 2024

作者： Li, Yuqing Zhao, Yusheng Zhang, Xinyue Zhong, Hui Pan, Miao Zhang, Chi School of Cyberspace Science and Technology University of Science and Technology of China Hefei China Kennesaw State University Department of Computer Science Marietta United States University of Houston Department of Electrical and Computer Engineering Houston United States

ISBN: (纸本)9798350366778

Quantum computing has been widely applied in various fields, such as quantum physics simulations, quantum machine learning, and big data analysis. However, in the domains of data-driven paradigms, ensuring databases privacy. For classical computing, we can incorporate the concept of differential privacy (DP) to meet the standard of privacy preservation by manually adding noise. In quantum computing scenario, researchers have extended classic DP to quantum differential privacy (QDP) by considering quantum noise. In this paper, we propose a novel approach to satisfy the QDP definition by considering the errors generated by the projection operator measurement, which is denoted as shot noise. Then, we discuss the amount of privacy budget that can be achieved with shot noise, which serves as a metric for the level of privacy protection. Furthermore, we provide the QDP of shot noise in quantum circuits with depolarizing noise. Through numerical simulations, we show that shot noise can effectively provide privacy protection in quantum computing. © 2024 IEEE.

关键词： Quantum noise

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Design and Development of a NLP-Based Assistive Platform to Facilitate Smooth Transition from Bengali Regional to Colloquial Language 3rd

Design and Development of a NLP-Based Assistive Platform to ...

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3rd International Conference on Trends in Electronics and health Informatics, TEHI 2023

作者： Arman, Alif Islam, Md. Jahurul Nowshin, Nadiya Islam, Mohammad Shahidul Department of Electrical and Electronic Engineering Ahsanullah University Of Science and Technology Dhaka Bangladesh Institute of Information Technology Jahangirnagar University Savar Bangladesh Department of Computer Science and Engineering Brac University Dhaka Bangladesh

ISBN: (纸本)9789819739363

Bengali is the State Language of Bangladesh and about 300 million people use this language around the world. The maximum number of Bengali speakers are from Bangladesh. Though there is a common or Colloquial Language to communicate with each other in this country. But there are many Regional Languages in this country. Among the regional speakers one may not or do not understand other regional languages, that’s why it’s a crucial problem to communicate one regional speaker with another regional speaker. In this research, we are trying to make a platform for detecting one’s language region from his given sentences/words and according to his/her region, we are translating his/her sentences/words to Colloquial Language and this platform will train up him/his for learning the Standard Bengali Language as well as. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Translation (languages)

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Investigating Labeled Cyberbullying Incidents on the Weibo Social Network 21

Investigating Labeled Cyberbullying Incidents on the Weibo S...

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21st International Conference on Networking, Sensing and Control, ICNSC 2024

作者： Xu, Jun Yu, Songnan Lu, Xiaoyu Sean Wu, Di Kang, Qi School of Cyber Science and Engineering Nanjing University of Science and Technology Nanjing210000 China New Jersey Institute of Technology Department of Electrical and Computer Engineering NewarkNJ United States

ISBN: (纸本)9798350365221

This study aims to investigate cyberbullying incidents on Weibo by constructing a comprehensive dataset of labeled conversations. We collect 89K social media sessions from 10K user profiles and manually annotated the data to identify instances of cyberbullying. We analyze cyberbullying based on three fundamental characteristics, examining its distribution across different topics and the relationship between posting times and cyberbullying incidents. Additionally, we explore the influence of user popularity on the similarity of receiving bullying comments. Our study provides valuable insights into the characteristics of cyberbullying on Chinese social media and highlights the need for culturally sensitive detection models. © 2024 IEEE.

关键词： Phishing

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An Insight Survey on Sensor Errors and Fault Detection Techniques in Smart Spaces

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computer Modeling in engineering & sciences 2024年第3期138卷 2029-2059页

作者： Sheetal Sharma Kamali Gupta DeepaliGupta Shalli Rani Gaurav Dhiman Chitkara University Institute of Engineering and Technology Chitkara UniversityPunjab140401India PG Department of Information Technology Goswami Ganesh Dutta Sanatan Dharma CollegeChandigarh160030India Department of Computer Science Government Bikram College of CommercePatialaIndia Department of Electrical and Computer Engineering Lebanese American UniversityByblosLebanon University Centre for Research and Development Department of Computer Science and EngineeringChandigarh UniversityMohali140413India Department of Computer Science and Engineering Graphic Era Deemed to be UniversityDehradun248002India Division of Research and Development Lovely Professional UniversityPunjab144001India

The widespread adoption of the Internet of Things (IoT) has transformed various sectors globally, making themmore intelligent and connected. However, this advancement comes with challenges related to the effectiveness ofIoT devices. These devices, present in offices, homes, industries, and more, need constant monitoring to ensuretheir proper functionality. The success of smart systems relies on their seamless operation and ability to handlefaults. Sensors, crucial components of these systems, gather data and contribute to their functionality. Therefore,sensor faults can compromise the system’s reliability and undermine the trustworthiness of smart *** address these concerns, various techniques and algorithms can be employed to enhance the performance ofIoT devices through effective fault detection. This paper conducted a thorough review of the existing literature andconducted a detailed *** analysis effectively links sensor errors with a prominent fault detection techniquecapable of addressing them. This study is innovative because it paves theway for future researchers to explore errorsthat have not yet been tackled by existing fault detection methods. Significant, the paper, also highlights essentialfactors for selecting and adopting fault detection techniques, as well as the characteristics of datasets and theircorresponding recommended techniques. Additionally, the paper presents amethodical overview of fault detectiontechniques employed in smart devices, including themetrics used for evaluation. Furthermore, the paper examinesthe body of academic work related to sensor faults and fault detection techniques within the domain. This reflectsthe growing inclination and scholarly attention of researchers and academicians toward strategies for fault detectionwithin the realm of the Internet of Things.

关键词： Error fault detection techniques sensor faults outliers Internet of Things

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An Integrated Representation & Compression Scheme Based on Convolutional Autoencoders with 4D-DCT Perceptual Encoding for High Dynamic Range Light Fields 8

An Integrated Representation & Compression Scheme Based on C...

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8th IEEE International Conference on Information and Communication technology, CICT 2024

作者： Khaidem, Sally Sharma, Mansi Indian Institute of Technology Madras Department of Electrical Engineering Chennai India Thapar Institute of Engineering and Technology Department of Computer Science and Engineering Patiala India

ISBN: (纸本)9798331531539

The emerging and existing light field displays are highly capable of realistic presentation of 3D scenes on auto-stereoscopic glasses-free platforms. However, the large size of light field data presents a significant drawback for 3D displays and streaming purposes. When a light field has a high dynamic range (HDR), its size increases drastically. This paper proposes a novel compression algorithm specifically designed for high dynamic range light fields that achieves perceptually lossless compression. The algorithm leverages inter-view and intra-view correlations within the HDR light field by treating it as a four-dimensional volume. This compression technique is based on the 4D-DCT Uniform Colour Space (4DDCT-UCS) algorithm. Further encoding of 4DDCT-UCS processed images using High-Efficiency Video Coding (HEVC) eliminates intra-frame, inter-frame, and intrinsic redundancies in HDR light field data. Our comparison with state-of-the-art coders like JPEG-XL and existing HDR video coding algorithms demonstrates the superior compression performance of the proposed scheme for real-world light fields. © 2024 IEEE.

关键词： Encoding (symbols)

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