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arXiv 2024年

作者： Szydlo, Tomasz Szabala, Amadeusz Kordiumov, Nazar Siuzdak, Konrad Wolski, Lukasz Alwasel, Khaled Habeeb, Fawzy Ranjan, Rajiv Institute of Computer Science AGH University of Science and Technology Al. Mickiewicza 30 Krakow30-059 Poland College of Computing and Informatics Saudi Electronic University Riyadh Saudi Arabia College of Computer Science University of Jeddah Jeddah Saudi Arabia The School of Computing Newcastle University Newcastle upon Tyne United Kingdom

Internet of Things systems exists in various areas of our everyday life. For example, sensors installed in smart cities and homes are processed in edge and cloud computing centres providing several benefits that improve our lives. The place of data processing is related to the required system response times - processing data closer to its source results in a shorter system response time. The Osmotic computing concept enables flexible deployment of data processing services and their possible movement, just like particles in the osmosis phenomenon move between regions of different densities. At the same time, the impact of complex computer architecture on the environment is increasingly being compensated by the use of renewable and low-carbon energy sources. However, the uncertainty of supplying green energy makes the management of Osmotic computing demanding, and therefore their autonomy is desirable. In the paper, we present a framework enabling osmotic computing simulation based on renewable energy sources and autonomic osmotic agents, allowing the analysis of distributed management algorithms. We discuss the challenges posed to the framework and analyze various management algorithms for cooperating osmotic agents. In the evaluation we show that changing the adaptation logic of the osmotic agents, it is possible to increase the self-consumption of renewable energy sources or increase the usage of low emission ones. © 2024, CC BY.

关键词： Computer architecture

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SCENEHGN: Hierarchical Graph Networks for 3D Indoor Scene Generation with Fine-Grained Geometry

arXiv

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arXiv 2023年

作者： Gao, Lin Sun, Jia-Mu Mo, Kaichun Lai, Yu-Kun Guibas, Leonidas J. Yang, Jie The Beijing Key Laboratory of Mobile Computing and Pervasive Device Institute of Computing Technology Chinese Academy of Sciences Beijing China The University of Chinese Academy of Sciences Beijing China Stanford University United States The School of Computer Science & Informatics Cardiff University United Kingdom

3D indoor scenes are widely used in computer graphics, with applications ranging from interior design to gaming to virtual and augmented reality. They also contain rich information, including room layout, as well as furniture type, geometry, and placement. High-quality 3D indoor scenes are highly demanded while it requires expertise and is time-consuming to design high-quality 3D indoor scenes manually. Existing research only addresses partial problems: some works learn to generate room layout, and other works focus on generating detailed structure and geometry of individual furniture objects. However, these partial steps are related and should be addressed together for optimal synthesis. We propose SCENEHGN, a hierarchical graph network for 3D indoor scenes that takes into account the full hierarchy from the room level to the object level, then finally to the object part level. Therefore for the first time, our method is able to directly generate plausible 3D room content, including furniture objects with fine-grained geometry, and their layout. To address the challenge, we introduce functional regions as intermediate proxies between the room and object levels to make learning more manageable. To ensure plausibility, our graph-based representation incorporates both vertical edges connecting child nodes with parent nodes from different levels, and horizontal edges encoding relationships between nodes at the same level. Our generation network is a conditional recursive neural network (RvNN) based variational autoencoder (VAE) that learns to generate detailed content with fine-grained geometry for a room, given the room boundary as the condition. Extensive experiments demonstrate that our method produces superior generation results, even when comparing results of partial steps with alternative methods that can only achieve these. We also demonstrate that our method is effective for various applications such as part-level room editing, room interpolation, and room gene

关键词： Graph neural networks

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28–38 GHz Phased Array 5G Antenna Design for Future Smartphone Applications

28–38 GHz Phased Array 5G Antenna Design for Future Smartph...

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Antennas and Propagation Society International Symposium

作者： Atta Ullah Naser Ojaroudi Parchin Isah Musa Danjuma Raed A. Abd-Alhameed Faculty of Engineering and Informatics University of Bradford Bradford UK School of Computing Engineering and the Built Environment Edinburgh Napier University Edinburgh UK Faculty of Engineering and Technology Nigerian Defence Academy Kaduna Nigeria

Broadband phased array antennas with wide-scan and smart beam-steering are desirable to meet the requirements of future cellular networks. This paper discusses the characteristics of a new beam-steerable phased array design having broad bandwidth for 5G communications. The discussion is focused on smartphones, due to their small size and complexity. The design procedure is straightforward and accomplished on a mainboard of future smart handheld devices. The introduced phased array design involves eight circular-dipole resonators with a $1\times 8$ linear form. The resonators have small sizes with microstrip-line feedings. For -10 dB, the design represents 28–38 GHz covering multiple bands in the 5G spectra.

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Energy Generation from Plastic Composites: A Systematic Review of Sustainable Practices and Technologies

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Circular Economy and Sustainability 2025年第2期5卷 1307-1343页

作者： Ametefe, Divine Senanu Ametefe, George Dzorgbenya John, Dah Aliu, Abdulmalik Adozuka Owen, Macaulay M. Shuib, Solehuddin Hamid, Aisha Wireless Communication Technology Group (WiCOT) College of Engineering School of Electrical Engineering Universiti Teknologi MARA (UiTM) Selangor Shah Alam 40450 Malaysia Department of Biotechnology College of Science Engineering and Technology Osun State University Osogbo Nigeria College of Computing Informatics and Mathematics Universiti Teknologi MARA (UiTM) Selangor Puncak Perdana 40150 Malaysia College of Built Environment Universiti Teknologi MARA (UiTM) Selangor Shah Alam 40450 Malaysia Institute of Energy Infrastructure IEI Universiti Tenaga Nasional UNITEN Jalan IKRAM-UNITEN Selangor Kajang 43000 Malaysia School of Mechanical Engineering College of Engineering Universiti Teknologi MARA UiTM Shah Alam 40450 Malaysia School of Chemistry and Environment Faculty of Applied Sciences Universiti Teknologi MARA Selangor Shah Alam 40450 Malaysia

Energy generation from plastic composites offers a viable solution to the dual challenges of plastic waste management and renewable energy production. This study explores the potential of plastic composites for energy generation through key waste-to-energy technologies, including incineration, pyrolysis, gasification, and anaerobic digestion. The study employs a Systematic Literature Review (SLR) methodology, following the PRISMA guidelines, and draws from two primary databases: ScienceDirect and Web of Science. Each method is assessed in terms of energy efficiency, environmental impact, economic feasibility, and scalability, based on studies published between 2020 and the second quarter of 2024. Pyrolysis and gasification emerge as particularly promising technologies due to their flexibility and higher energy recovery potential. Incineration, although widely used and well-established, presents challenges related to emissions, despite improvements in emissions control technologies. Anaerobic digestion, though limited in its application to conventional plastics, provides sustainability benefits when used with biodegradable materials. The analysis reveals regional disparities in research focus, the influence of policy frameworks, and the need for technological innovation to optimize these processes. Ultimately, the findings highlight the importance of integrating energy recovery from plastic waste within circular economy models to achieve sustainable waste management and renewable energy goals. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： Circular Economy Plastic Recycling Renewable Energy Production Sustainable Waste Management Waste-to-Energy

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Resource Allocation-Aware Efficient Interference Management Technique for Ultra-Dense Femto Environment

SSRN

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SSRN 2024年

作者： Guo, Wanying Wang, Bojun Zhao, Lian Siddiqui, Isma Farah School of Information and Communication Engineering Nanjing Institute of Technology Nanjing China College of Computing and Informatics Sungkyunkwan University Suwon Korea Republic of Cyberspace Institute Institute of Dataspace Hefei Comprehensive NationalScience Center Hefei China Department of Software Engineering Mehran University of Engineering & Technology Jamshoro Pakistan

Addressing the challenge of severe inter-layer and intra-layer interference in densely deployed Femtocells, we introduce an efficient resource allocation strategy centered on clustering. Initially, we employ the Fractional Frequency Reuse (FFR) technique to mitigate interference by segmenting cells into distinct ***, leveraging graph theory and convex optimization, we cluster the Femto Base Stations (FBS) to enhance efficiency. An algorithm prioritizing user fairness governs sub-channel allocation among FBSs. Additionally, a distributed power control algorithm dynamically adjusts FBS power levels, further enhancing system throughput. Comparative analysis reveals that our approach surpasses traditional non-clustered methods and three other comparison methods, exhibiting superior system throughput and Signal-to-Interference Ratio (SINR). Notably, our method significantly enhances user fairness, promoting greater satisfaction among Femto User Equipment (FUE) users. © 2024, The Authors. All rights reserved.

关键词： Femtocell

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Reducing the Gap Between Pretrained Speech Enhancement and Recognition Models Using a Real Speech-Trained Bridging Module

Reducing the Gap Between Pretrained Speech Enhancement and R...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Zhongjian Cui Chenrui Cui Tianrui Wang Mengnan He Hao Shi Meng Ge Caixia Gong Longbiao Wang Jianwu Dang Tianjin Key Laboratory of Cognitive Computing and Application Tianjin University Tianjin China DiDi Chuxing Beijing China Graduate School of Informatics Kyoto University Kyoto Japan Huiyan Technology (Tianjin) Co. Ltd Tianjin China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

The information loss or distortion caused by single-channel speech enhancement (SE) harms the performance of automatic speech recognition (ASR). Observation addition (OA) is an effective post-processing method to improve ASR performance by balancing noisy and enhanced speech. Determining the OA coefficient is crucial. However, the currently supervised OA coefficient module, called the bridging module, only utilizes simulated noisy speech for training, which has a severe mismatch with real noisy speech. In this paper, we propose training strategies to train the bridging module with real noisy speech. First, DNSMOS is selected to evaluate the perceptual quality of real noisy speech with no need for the corresponding clean label to train the bridging module. Additional constraints during training are introduced to enhance the robustness of the bridging module further. Each utterance is evaluated by the ASR back-end using various OA coefficients to obtain the word error rates (WERs). The WERs are used to construct a multidimensional vector. This vector is introduced into the bridging module with multi-task learning and is used to determine the optimal OA coefficients. The experimental results on the CHiME-4 dataset show that the proposed methods all had significant improvement compared with the simulated data trained bridging module, especially under real evaluation sets.

关键词： Training Refining Speech recognition Speech enhancement Multitasking Vectors Robustness Noise robustness Noise measurement Optimization

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Enhancing the Performance of Semi-supervised Electricity Theft Detection in Smart Grids with Feature Engineering and Ensemble Learning

Enhancing the Performance of Semi-supervised Electricity The...

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IEEE Kansas Power and Energy Conference

作者： Ruobin Qi Wynter Japp Stephen Pan Jun Zheng Sihua Shao Department of Computer Science and Engineering New Mexico Institute of Mining and Technology Socorro NM School of Computing and Informatics University of Louisiana Lafayett Lafayette LA Department of Computer Science University of Arizona Tucson AZ Department of Electrical Engineering New Mexico Institute of Mining and Technology Socorro NM

ISBN: (数字)9798350372403

ISBN: (纸本)9798350372410

Electricity theft is a type of cyberattack posing significant risks to the security of smart grids. Semi-supervised outlier detection (SSOD) algorithms utilize normal power usage data to build detection models, enabling them to detect unknown electricity theft attacks. In this paper, we applied feature engineering and ensemble learning to improve the detection performance of SSOD algorithms. Specifically, we extracted 22 time-series and wavelet features from load profiles, which served as inputs for the seven popular SSOD algorithms investigated in this study. Experimental results demonstrate that the proposed feature engineering greatly enhances the performance of SSOD algorithms to detect various false data injection (FDI) attacks. Furthermore, we constructed bagged ensemble models using the best-performing SSOD algorithm as the base model, with results indicating further improvements in detection performance compared to the base model alone.

关键词： Wavelet domain Electricity Feature extraction Data models Smart meters Smart grids Ensemble learning

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Evaluating the Effectiveness of E-Learning Website Using Electroencephalogram 8th

Evaluating the Effectiveness of E-Learning Website Using Ele...

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8th International Visual informatics Conference, IVIC 2023

作者： Aning, Alberto Baharum, Aslina Mohd Naim, Nur Faraha Mohd Yusop, Nurhafizah Moziyana Darius, Dian Darina Indah Mat Noor, Noorsidi Aizuddin Deris, Farhana Diana Faculty of Computing and Informatics Universiti Malaysia Sabah Kota Kinabalu Sabah Malaysia Computing and Information System School of Engineering and Technology Sunway University 5 Jalan Universiti Selangor Sunway City Malaysia Faculty of Defence Science and Technology National Defence University of Malaysia Kuala Lumpur Malaysia Faculty of Engineering Universiti Pertahanan Nasional Malaysia Kem Sungai Besi Kuala Lumpur57000 Malaysia Mass Appraisal Housing and Planning Research Group Centre for Real Estate Studies Real Estate Department Faculty of Built Environment and Surveying Universiti Teknologi Malaysia Johor Johor Bahru Malaysia Faculty of Social Sciences and Humanities Universiti Teknologi Malaysia Johor Johor Bahru Malaysia

ISBN: (纸本)9789819973385

Although e-learning technology provides numerous benefits for educators, enticing students to use e-learning services is a challenge, particularly for the e-learning websites of higher education institutions in Malaysia. E-learning websites of Malaysian higher education institutions have few guidelines for user interface design that foster emotional engagement. Due to this problem, there is a significant percentage of student disengagement on e-learning platforms. A visualization pattern as a guideline has been proposed for designing an e-learning GUI website for HEIs in Malaysia. The proposed guideline has been implemented on the prototype website’s graphical user interface (GUI). The effectiveness of the GUI was evaluated using an electroencephalogram (EEG) device and resulted in 65% of the participants being in the ‘Most Effective’ category, with the highest average of most effectiveness standing at 32.6%. The research has demonstrated that the developed guideline increased student engagement with the GUI of the e-learning website prototype. The guideline is intended to assist higher education institutions (HEIs) and website developers and designers in creating e-learning websites that can sustain students’ interest in e-learning over time. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Graphical user interfaces

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Transformative effects of ChatGPT on modern education: Emerging Era of AI Chatbots

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Internet of Things and Cyber-Physical Systems 2024年第1期4卷 19-23页

作者： Gill, Sukhpal Singh Xu, Minxian Patros, Panos Wu, Huaming Kaur, Rupinder Kaur, Kamalpreet Fuller, Stephanie Singh, Manmeet Arora, Priyansh Parlikad, Ajith Kumar Stankovski, Vlado Abraham, Ajith Ghosh, Soumya K. Lutfiyya, Hanan Kanhere, Salil S. Bahsoon, Rami Rana, Omer Dustdar, Schahram Sakellariou, Rizos Uhlig, Steve Buyya, Rajkumar School of Electronic Engineering and Computer Science Queen Mary University of London London United Kingdom Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China Raygun Performance Monitoring Wellington New Zealand Center for Applied Mathematics Tianjin University Tianjin China Department of Science Kings Education London United Kingdom Cymax Group Technologies BC Canada QM Academy Queen Mary University of London London United Kingdom Jackson School of Geosciences University of Texas at Austin AustinTX United States Centre for Climate Change Research Indian Institute of Tropical Meteorology Pune India Microsoft Hyderabad India Institute for Manufacturing Department of Engineering University of Cambridge Cambridge United Kingdom Faculty of Computer and Information Science University of Ljubljana Ljubljana Slovenia Machine Intelligence Research Labs AuburnWA United States Faculty of Computing and Data Science FLAME University Maharashtra Pune India Department of Computer Science and Engineering Indian Institute of Technology Kharagpur India Department of Computer Science University of Western Ontario London Canada Sydney Australia School of Computer Science University of Birmingham United Kingdom School of Computer Science and Informatics Cardiff University Cardiff United Kingdom Distributed Systems Group Vienna University of Technology Vienna Austria Department of Computer Science University of Manchester Oxford Road Manchester United Kingdom Laboratory School of Computing and Information Systems The University of Melbourne Australia

ChatGPT, an AI-based chatbot, offers coherent and useful replies based on analysis of large volumes of data. In this article, leading academics, scientists, distinguish researchers and engineers discuss the transformative effects of ChatGPT on modern education. This research discusses ChatGPT capabilities and its use in the education sector, identifies potential concerns and challenges. Our preliminary evaluation shows that ChatGPT perform differently in different subject areas including finance, coding, maths, and general public queries. While ChatGPT has the ability to help educators by creating instructional content, offering suggestions and acting as an online educator to learners by answering questions, transforming education through smartphones and IoT gadgets, and promoting group work, there are clear drawbacks in its use, such as the possibility of producing inaccurate or false data and circumventing duplicate content (plagiarism) detectors where originality is essential. The often reported "hallucinations" within GenerativeAI in general, and also relevant for ChatGPT, can render its use of limited benefit where accuracy is essential. What ChatGPT lacks is a stochastic measure to help provide sincere and sensitive communication with its users. Academic regulations and evaluation practices used in educational institutions need to be updated, should ChatGPT be used as a tool in education. To address the transformative effects of ChatGPT on the learning environment, educating teachers and students alike about its capabilities and limitations will be crucial. © 2023 The Authors

关键词： Machine learning

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An Improved Dictionary Cracking Scheme Based on Multiple GPUs for Wi-Fi Network

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Computers, Materials & Continua 2021年第3期66卷 2957-2972页

作者： Majdi K.Qabalin Zaid A.Arida Omar A.Saraereh Falin Wu Imran Khan Peerapong Uthansakul Moath Alsafasfeh Department of Computer Science Princess Sumaya University for TechnologyAmman13133Jordan School of Computing and Informatics Al Hussein Technical UniversityAmman11831Jordan Department of Electrical Engineering Hashemite UniversityZarqa13133Jordan School of Instrumentation and Optoelectronic Engineering Beihang UniversityBeijing100191China Department of Electrical Engineering University of Engineering and TechnologyPeshawarPakistan School of Telecommunication Engineering Suranaree University of TechnologyNakhon Ratchasima30000Thailand Department of Computer Engineering Al-Hussein Bin Talal UniversityMa’anJordan

The Internet has penetrated all aspects of human society and has promoted social ***-crimes in many forms are commonplace and are dangerous to society and national *** has become a major concern for citizens and *** Internet functions and software applications play a vital role in cybersecurity research and *** of the cyber-attacks are based on exploits in system or application *** is of utmost urgency to investigate software security *** demand for Wi-Fi applications is proliferating but the security problem is growing,requiring an optimal solution from *** overcome the shortcomings of the wired equivalent privacy(WEP)algorithm,the existing literature proposed security schemes forWi-Fi protected access(WPA)/***,in practical applications,the WPA/WPA2 scheme still has some weaknesses that attackers *** destroy a WPA/WPA2 security,it is necessary to get a PSK pre-shared key in pre-shared key mode,or an MSK master session key in the authentication ***-force cracking attacks can get a phase-shift keying(PSK)or a minimum shift keying(MSK).In real-world applications,many wireless local area networks(LANs)use the pre-shared key ***,brute-force cracking of WPA/WPA2-PSK is important in that *** article proposes a new mechanism to crack theWi-Fi password using a graphical processing unit(GPU)and enhances the efficiency through parallel computing of multiple GPU *** results show that the proposed algorithm is effective and provides a procedure to enhance the security of Wi-Fi networks.

关键词： Networks password cybersecurity password cracking mechanism

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