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2021 IEEE Green Energy and Smart Systems Conference, IGESSC 2021

作者： Alotaibi, Saleh Omer, Siddig Aljarallah, Sulaiman Su, Yuehong University Of Nottingham Faculty Of Engineering Department Of Architecture And Built Environment Nottingham United Kingdom Zulfi College Of Technology Department Of Computer Science Riyadh Saudi Arabia

ISBN: (纸本)9781665434560

Sustainable transportation has become an important consideration for countries seeking to reduce carbon emissions. Electric vehicles (EVs) are seen as a cornerstone of the transformation toward sustainability within the transportation sector;however, research on large-scale EVs' implementation to aid carbon emission reduction is sparse. Doubts have been raised concerning the effectiveness of EVs in satisfying sustainability in all of its dimensions: economic, social and environmental. Since achieving balanced sustainability requires an understanding of end-users' requirements, a mixed-methods empirical study surveyed end-users' perceptions of the desirable characteristics of EVs, using Saudi Arabia as a case study. Data gathered from 1012 respondents were analyzed to examine and rank their preferences, allowing the identification of a set of key features likely to influence Saudi citizens' utilization of EVs. Quantitative findings indicate that the features perceived as most significant were availability of charging stations and EV travelling distance. Other features which are also found important include aesthetics, maintenance costs, and charging cost, whereas end-users had low concern for branding and resale value. Thematic analysis of qualitative data shows that the most significant themes were security, localization of the EVs industry, charging energy sources, and self-driving. These results may serve as a framework to replicate the study in other countries, taking relevant inherent factors into account. © 2021 IEEE.

关键词： Sustainable development

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A Many-Objective Evolutionary Algorithm Based on Indicator Selection and Adaptive Angle Estimation

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SSRN 2024年

作者： Wang, Qian Gu, Qinghua Zhou, Qing Xiong, Neal Naixue Liu, Di School of Management Xi’an University of Architecture and Technology Shaanxi Xi’an China School of Resources Engineering Xi’an University of Architecture and Technology Shaanxi Xi’an China Xi’an Key Laboratory for Intelligent Industrial Perception Calculation and Decision Xi’an University of Architecture and Technology Xi’an710055 China Department of Mathematics and Computer Science Northeastern State University TahlequahOK74464 United States

Currently, real-world complex engineering problems often have more than three objectives that need to be optimized simultaneously. Existing algorithms for solving them mostly rely on the shape of the Pareto front to maintain diversity, which makes it difficult to effectively balance the convergence and diversity of the solutions. To address the above problems, a many-objective evolutionary algorithm based on indicator selection and adaptive angle estimation (MaOEA-ISAE) is proposed in this paper. Firstly, a unit vector metric selection strategy is presented, which uses the favorable physical properties of the metric to identify dominant individuals, thus striking a balance between convergence and diversity. Then, to preserve the diversity of the population, an adaptive angle estimation strategy based on Pareto front curvature prediction is developed. The angular distances of individuals are adaptively measured according to the predicted curvature, thereby selecting individuals with good diversity in the dominant region. Besides, the algorithm has a simple evolutionary process, and no additional parameters are involved. Finally, the proposed MaOEA-ISAE is compared with five other representative many-objective evolutionary algorithms on test instances of 3-20 objectives with different Pareto front shapes. The experimental results show the strong competitiveness of the proposed algorithm on different Pareto front problems. © 2024, The Authors. All rights reserved.

关键词： Evolutionary algorithms

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AgileWatts: An Energy-Efficient CPU Core Idle-State architecture for Latency-Sensitive Server Applications 22

AgileWatts: An Energy-Efficient CPU Core Idle-State Architec...

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Proceedings of the 55th Annual IEEE/ACM International Symposium on Microarchitecture

作者： Jawad Haj Yahya Haris Volos Davide B. Bartolini Georgia Antoniou Jeremie S. Kim Zhe Wang Kleovoulos Kalaitzidis Tom Rollet Zhirui Chen Ye Geng Onur Mutlu Yiannakis Sazeides Rivos Inc Mountain View California United States Computer Architecture Laboratory Department of Computer Science University of Cyprus Computing Systems Lab Huawei Zurich Research Center Department of Information Technology and Electrical Engineering ETH Zurich Switzerland

ISBN: (纸本)9781665462723

User-facing applications running in modern datacenters exhibit irregular request patterns and are implemented using a multitude of services with tight latency requirements (30--250μs). These characteristics render existing energy-conserving techniques ineffective when processors are idle due to the long transition time (order of 100μs) from a deep CPU core idle power state (C-state). While prior works propose management techniques to mitigate this inefficiency, we tackle it at its root with AgileWatts (AW): a new deep CPU core C-state architecture optimized for datacenter server processors targeting latency-sensitive *** drastically reduces the transition latency from deep CPU core idle power states while retaining most of their power savings based on three key ideas. First, AW eliminates the latency (several microseconds) of saving/restoring the core context when powering-off/-on the core in a deep idle state by i) implementing medium-grained power-gates, carefully distributed across the CPU core, and ii) retaining context in the power-ungated domain. Second, AW eliminates the flush latency (several tens of microseconds) of the L1/L2 caches when entering a deep idle state by keeping L1/L2 content power-ungated. A small control logic also remains ungated to serve cache coherence traffic. AW implements cache sleep-mode and leakage reduction for the power-ungated domain by lowering a core's voltage to the minimum operational level. Third, using a state-of-the-art power efficient all-digital phase-locked loop (ADPLL) clock generator, AW keeps the PLL active and locked during the idle state, cutting microseconds of wake-up latency at negligible power *** evaluation with an accurate industrial-grade simulator calibrated against an Intel Skylake server shows that AW reduces the energy consumption of Memcached by up to 71% (35% on average) with <1% end-to-end performance degradation. We observe similar trends for other evaluated services (MySQL and Kafka).

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IoT-enabled smart cities: a hybrid systematic analysis of key research areas, challenges, and recommendations for future direction

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Discover Cities 2024年第1期1卷 1-34页

作者： Omrany, Hossein Al-Obaidi, Karam M. Hossain, Mohataz Alduais, Nayef A. M. Al-Duais, Husam S. Ghaffarianhoseini, Amirhosein School of Architecture and Built Environment The University of Adelaide Adelaide Australia Department of the Natural and Built Environment College of Social Sciences and Arts Sheffield Hallam University Sheffield UK Faculty of Computer Science and Information Technology Universiti Tun Hussein Onn Malaysia Parit Raja Malaysia Department of Architecture Faculty of Built Environment Universiti Malaya Kuala Lumpur Malaysia School of Future Environments Auckland University of Technology Auckland New Zealand

Cities are expected to face daunting challenges due to the increasing population in the near future, putting immense strain on urban resources and infrastructures. In recent years, numerous studies have been developed to investigate different aspects of implementing IoT in the context of smart cities. This has led the current body of literature to become fairly fragmented. Correspondingly, this study adopts a hybrid literature review technique consisting of bibliometric analysis, text-mining analysis, and content analysis to systematically analyse the literature connected to IoT-enabled smart cities (IESCs). As a result, 843 publications were selected for detailed examination between 2010 to 2022. The findings identified four research areas in IESCs that received the highest attention and constituted the conceptual structure of the field. These include (i) data analysis, (ii) network and communication management and technologies, (iii) security and privacy management, and (iv) data collection. Further, the current body of knowledge related to these areas was critically analysed. The review singled out seven major challenges associated with the implementation of IESCs that should be addressed by future studies, including energy consumption and environmental issues, data analysis, issues of privacy and security, interoperability, ethical issues, scalability and adaptability as well as the incorporation of IoT systems into future development plans of cities. Finally, the study revealed some recommendations for those interconnected challenges in implementing IESCs and effective integrations within policies to support net-zero futures.

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An improved end-to-end micro-expression recognition system for real-world videos via dual-input CNN architecture

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Expert Systems with Applications 2025年 286卷

作者： Gan, Y.S. Liu, Kun-Hong Wu, Min-Huan Liong, Gen-Bing Liong, Sze-Teng School of Architecture Feng Chia University Taichung40724 Taiwan Department of Digital Media Technology School of Film Xiamen University Xiamen China Bachelor of Science in Senior Wellness and Sport Science Tunghai University Taiwan Faculty of Computer Science & Information Technology University of Malaya Kuala Lumpur50603 Malaysia Department of Electronic Engineering Feng Chia University Taichung40724 Taiwan

Micro-expression (ME) recognition reveals nonverbal emotions through subtle, involuntary facial muscle movements. However, the development and commercialization of ME recognition systems have been hindered by the lack of databases that accurately reflect real-world conditions. This study addresses this challenge by proposing a robust end-to-end system designed to operate effectively in unconstrained environments. Existing methods typically rely on a single apex frame, which may be unreliable due to noise, occlusions, or lighting variations. To address these issues, a 3D facial reconstruction technique is applied as a pre-processing step to normalize pose and lighting. A novel dual-peak frame detection strategy is then introduced to extract two expressive optical flow frames, reducing the impact of noise from any single frame. Finally, a Shallow and Small-size Dual-input (SSD) CNN architecture is designed to jointly process the two frames for improved emotion classification. The proposed system achieves strong performance on the challenging in-the-wild MEVIEW dataset, with accuracy and F1-score of 75 % and 77.68 %, respectively. Comprehensive evaluations further validate the effectiveness of the pipeline, highlighting its potential for real-world ME recognition applications. © 2025 Elsevier Ltd

关键词： Optical character recognition

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Research on Practical Byzantine Fault Tolerant Algorithm Based on Trust Mechanism

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Journal of computers (Taiwan) 2022年第2期33卷 11-23页

作者： Pang, Hui Li, Yanan Wen, Xiumei Mu, Yingxue Department of Computer Science and Technology Hebei University of Architecture Big Data Technology Innovation Center of Zhangjiakou Hebei Zhangjiakou China

The consensus algorithm is one of the core technologies of the blockchain, which determines how the nodes in the blockchain network reach a consensus and enable them to jointly maintain a piece of data. This paper focuses on the Practical Byzantine Fault Tolerant Algorithm (PBFT Algorithm), and proposes a Practical Byzantine Fault Tolerant Algorithm based on Trust Mechanism (TM-PBFT Algorithm) to solve the problems of its low fault-tolerant rate and high communication cost. This algorithm supports voting for trusted nodes before the consensus cycle starts. In order to make nodes actively vote and vote for reliable nodes, this paper models the trust degree of nodes. In addition, the time factor is added to the Shapley value to design a new reward and punishment scheme, which makes the distribution of income of each node more reasonable and further encourages nodes to vote for reliable nodes. As the system runs for a long time, the probability of malicious nodes becoming master nodes decreases. Finally, a comparison experiment between the proposed algorithm and the PBFT algorithm shows that the fault tolerance and throughput of the TM-PBFT algorithm are higher than that of the PBFT algorithm, and the communication bandwidth overhead is lower than that of the PBFT algorithm. © 2022 computer Society of the Republic of China. All rights reserved.

关键词： Blockchain

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Energy-Efficient Stochastic Computing (SC) Neural Networks for Internet of Things Devices With Layer-Wise Adjustable Sequence Length (ASL)

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IEEE Internet of Things Journal 2025年

作者： Wang, Ziheng Reviriego, Pedro Niknia, Farzad Gao, Zhen Conde, Javier Liu, Shanshan Lombardi, Fabrizio Northeastern University Department of Electrical and Computer Engineering MA02115 United States Universidad Politécnica de Madrid ETSI de Telecomunicación Madrid28040 Spain Tianjin University School of Electrical and Information Engineering Tianjin300072 China University of Electronic Science and Technology of China School of Information and Communication Engineering Chengdu611731 China

Stochastic computing (SC) has emerged as an efficient low-power alternative for deploying neural networks (NNs) in resource-limited scenarios, such as the Internet of Things (IoT). By encoding values as serial bitstreams, SC significantly reduces energy dissipation compared to conventional floating-point (FP) designs;however, further improvement of layer-wise mixed-precision implementation for SC remains unexplored. This paper introduces Adjustable Sequence Length (ASL), a novel scheme that applies mixedprecision concepts specifically to SC NNs. By introducing an operator-norm – based theoretical model, this paper shows that truncation noise can cumulatively propagate through the layers by the estimated amplification factors. An extended sensitivity analysis is presented, using Random Forest (RF) regression to evaluate multi-layer truncation effects and validate the alignment of theoretical predictions with practical network behaviors. To accommodate different application scenarios, this paper proposes two truncation strategies (coarse-grained and fine-grained), which apply diverse sequence length configurations at each layer. Evaluations on a pipelined SC MLP synthesized at 32 nm demonstrate that ASL can reduce energy and latency overheads by up to over 60% with negligible accuracy loss. It confirms the feasibility of the ASL scheme for IoT applications and highlights the distinct advantages of mixed-precision truncation in SC designs. © 2014 IEEE.

关键词： Stochastic programming

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A Comprehensive Review on Big Data Challenges 2

A Comprehensive Review on Big Data Challenges

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2nd International Conference on Business Analytics for technology and Security, ICBATS 2023

作者： Bharany, Salil Taleb, Nasser Sadiq, M. Tariq Kanwal, Nayab Abdelhakim, Mohamed Ghazal, Taher M. Pradhan, Manas Rehman, Ateeq Ur Tech Amritsar India CET Department United Kingdom Canadian University Dubai Faculty of Management Dubai United Arab Emirates University of Brighton School of Architecture Engineering United Kingdom NCBA&E School of Computer Science Lahore Pakistan Applied Science Private University Applied Science Research Center Amman11937 Jordan University of Dubai College of Engineering and IT United Arab Emirates Skyline University College School of Information Technology Sharjah United Arab Emirates Department of Electrical Engineering GCU Lahore Pakistan

ISBN: (纸本)9798350335644

Increased hardware capability has allowed many businesses to store massive amounts of data in the previous few years. Streams of data may go on forever, so they are used in so many different applications. Analyzing and querying these streams is challenging for a stream of dynamic information. The term "big data"refers to a collection of methods and tools that must be combined in novel ways to unearth the vast amounts of previously unseen information buried within vast, diverse, and intricate databases. There are several ways to obtain, organize and analyze data in the big data world. In order to deal with streaming data, efficient data mining procedures must be in place. In this article, we examine a variety of Big Data-related concerns and challenges. This paper introduces the features, and challenges of managing big data. © 2023 IEEE.

关键词： Big data

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Development of Reflex technology of Action Identification in Project Planning Systems

Development of Reflex Technology of Action Identification in...

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2022 International Conference on Smart Information Systems and Technologies, SIST 2022

作者： Teslia, Iurii Yehorchenkova, Nataliia Khlevna, Iulia Yehorchenkov, Oleksii Kataieva, Yevheniia Klevanna, Ganna Cherkasy State Technological University Department Of Information Technology Project Cherkasy Ukraine Kyiv National University Of Construction And Architecture Department Of Project Management Kyiv Ukraine Taras Shevchenko National University Of Kyiv Department Of Technology Management Kyiv Ukraine Cherkasy State Technological University Department Of Automated Systems Software Cherkasy Ukraine Cherkasy State Technological University Department Of Computer Science And Systems Analysis Cherkasy Ukraine

ISBN: (数字)9781665467902

ISBN: (纸本)9781665467902

The need for intellectualization of project management processes is shown, in particular, the creation of intelligent systems capable of effectively plan projects in the process of natural-language interaction with the project team. The analysis of existing theoretical and practical developments in this field is carried out. It is shown that the issue of intellectualization of the project planning process is still open. It is proposed to use a reflex approach to building an intelligent project planning system. The technology of reflex identification of actions in project planning systems, based on the model of non-force (information) interaction, is proposed. Scenarios of actions have been developed and their distribution has been performed in accordance with the content of natural language requests to the project planning system. Experimental studies are shown a high probability of correct recognition of actions in project planning systems from natural language requests of project team members. The results of the conducted experiments unequivocally testify to the effectiveness of the developed information technology of reflex identification of action scenarios in project planning systems. © 2022 IEEE.

关键词： Intelligent systems

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Handwritten Digit Recognition using Deep Learning Networks

Handwritten Digit Recognition using Deep Learning Networks

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2022 IEEE Conference on Telecommunications, Optics and computer science, TOCS 2022

作者： Yu, Shiying Liu, Jinmei Shu, Hang Cheng, Zhiwei Wuhan University School of Geodesy and Geomatics Wuhan430000 China Rutgers University School of Arts and Sciences New Jersey NJ08854 United States South West University School of Computer and Information Science Chongqing400010 China Xi'an University of Science and Technology Department of Architecture and Civil Engineering Xi'an710600 China

ISBN: (纸本)9781665470537

Handwritten digit recognition has been widely researched. Numerous classification methods have been proposed. This article improves the recognition of handwritten numbers method based on CNN neural network. Recognition of handwritten digits has made great progress, but due to insufficient recognition accuracy, it will have a certain impact on work efficiency. In this paper, a two-layer CNN network with two fully connected layers can achieve a good prediction performance. In our framework, the activation function used is the ReLU function, to some extent, this avoids the difficulties of gradient disappearance and gradient saturation. At the same time, dropout is added to the full connection layer to discard the neurons in the network with a certain probability, which can avoid certain accidents, and the final trained network will be more robust and the generalization performance will be stronger. This method effectively improves the accuracy of recognition in the final experiment, which achieves 98.75% accuracy on theMNIST dataset and 99.25% on the CIFAR-100 dataset. © 2022 IEEE.

关键词： Deep neural networks

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