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IEEE International Conference on Communications (ICC)

作者： Minrui Xu Dusit Niyato Jiawen Kang Zehui Xiong Mingzhe Chen School of Computer Science and Engineering Nanyang Technological University Singapore School of Automation Guangdong University of Technology China Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore Singapore Department of Electrical and Computer Engineering Institute for Data Science and Computing University of Miami Coral Gables FL USA

In this paper, a novel paradigm of mobile edgequantum computing (MEQC) is proposed, which brings quantum computing capacities to mobile edge networks that are closer to mobile users (i.e., edge devices). First, we propose an MEQC system model where mobile users can offload computational tasks to scalable quantum computers via edge servers with cryogenic components and fault-tolerant schemes. Second, we show that it is NP-hard to obtain a centralized solution to the partial offloading problem in MEQC in terms of the optimal latency and energy cost of classical and quantum computing. Third, we propose a multi-agent hybrid discrete-continuous deep reinforcement learning using proximal policy optimization to learn the long-term sustainable offloading strategy without prior knowledge. Finally, experimental results demonstrate that the proposed algorithm can reduce at least 30% of the cost compared with the existing baseline solutions under different system settings.

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SENS+: A Co-Existing Fabrication System for a Smart DFA Environment Based on Energy Fusion Information

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Sensors 2023年第6期23卷 2890页

作者： Chang, Teng-Wen Huang, Hsin-Yi Hong, Cheng-Chun Datta, Sambit Nakapan, Walaiporn College of Design National Yunlin University of Science and Technology Yunlin Douliou640 Taiwan School of Electrical Engineering Computing and Mathematical Sciences Curtin University BentleyWA6102 Australia Parabolab Bangkok11000 Thailand

In factories, energy conservation is a crucial issue. The co-fabrication space is a modern-day equivalent of a new factory type, and it makes use of Internet of Things (IoT) devices, such as sensors, software, and online connectivity, to keep track of various building features, analyze data, and produce reports on usage patterns and trends that can be used to improve building operations and the environment. The co-fabrication user requires dynamic and flexible space, which is different from the conventional user’s usage. Because the user composition in a co-fabrication space is dynamic and unstable, we cannot use the conventional approach to assess their usage and rentals. Prototyping necessitates a specifically designed energy-saving strategy. The research uses a "seeing–moving–seeing" design thinking framework, which enables designers to more easily convey their ideas to others through direct observation of the outcomes of their intuitive designs and the representation of their works through design media. The three components of human behavior, physical manufacture, and digital interaction are primarily the focus of this work. The computing system that connects the physical machine is created through communication between the designer and the digital interface, giving the designer control over the physical machine. It is an interactive fabrication process formed by behavior. The Sensible Energy System+ is an interactive fabrication process of virtual and real coexistence created by combining the already-existing technology, the prototype fabrication machine, and SENS. This process analyzes each step of the fabrication process and energy, fits it into the computing system mode to control the prototype fabrication machine, and reduces the problem between virtual and physical fabrication and energy consumption. © 2023 by the authors.

关键词： Fabrication

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A Dynamic Recognition Method of Metamorphic Relation Identification 13

A Dynamic Recognition Method of Metamorphic Relation Identif...

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13th International Conference on Reliability, Maintainability, and Safety, ICRMS 2022

作者： Hong, Jie Zhang, Jie Qiu, Qi Ma, Angang Li, Meng Yan, Shiyu Gong, Helin School of Computing University of South China Hunan Hengyang China Engineering and Technology Research Center Software Evaluation and Testing for Intellectual Equipment of Hunan Province Hunan Hengyang China CNNC Key Laboratory on High Trusted Computing Hunan Hengyang China Nuclear Power Institute of China Science and Technology on Reactor System Design Technology Laboratory Chengdu China

ISBN: (数字)9781665486903

ISBN: (纸本)9781665486903

Metamorphic testing is one of the effective methods to alleviate the test oracle problem. Metamorphic relation is the core of metamorphic testing, and there is no effective automatic identification technology. This paper transforms the metamorphic relation recognition issue into a symbolic expression regression problem. The test input pairs are generated using the preset input pattern, and the output pattern is mined by gene expression programming. After reduction and verification, a valid metamorphic relation is obtained. Experiments show that this method can identify the relation obtained by static analysis and a more significant number. At the same time, compared with existing technologies, it has apparent advantages in effectiveness, reliability, and performance. © 2022 IEEE.

关键词： Static analysis

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Clustering digital mental health perceptions using transformer-based models

Franklin Open

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Franklin Open 2025年 11卷

作者： Ibitoye, Ayodeji O.J. Oladimeji, Oladosu O. Afe, Oluwaseyi F. School of Computing and Mathematical Sciences University of Greenwich London United Kingdom Faculty of Engineering and Design Atlantic Technological University Sligo Ireland Department of Computer Science Lead City University Ibadan Nigeria

The rise in online mental health discussions underscores the need to understand diverse perspectives to inform targeted interventions. Addressing the granularity of existing research on mapping such perspectives, this study proposes a model combining contextual and sentiment analysis, keyword scoring, and clustering techniques to identify themes in online comments. Using transformer-based models (BERT, ALBERT, ELECTRA), the study achieved high-quality clustering of seven distinct mental health perspectives: stigma, empowerment, treatment approaches, recovery, social/environmental factors, advocacy, and cultural dimensions. ELECTRA outperformed others in clustering quality (silhouette score: 0.73;Davies-Bouldin Index: 0.34). The findings reveal cohesive, well-separated clusters that enhance understanding of digital mental health discourse. These insights provide a foundation for data-driven advocacy, tailored interventions, and broader awareness, addressing the complex dynamics of mental health narratives in online spaces. This study bridges a critical research gap by offering a systematic approach to analysing and interpreting mental health perspectives in digital environments. © 2025

关键词： Decision support Digital mental health Mental health Mental health perspectives Text clustering Transformer-based architectures

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Detection of Knee Osteoarthritis from Magnetic Resonance Imaging Using a 3-D Independent Component Analysis Method in Machine Learning 1st

Detection of Knee Osteoarthritis from Magnetic Resonance Ima...

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1st International Conference on Advanced Network Technologies and Computational Intelligence, ICANTCI 2024

作者： Karve, Swagat Dhope, Tanuja Satish Kaushal, Rajesh Kumar, Naveen Chippalkatti, Pranav Jadhav, Akshay S. B. Patil College of Engineering Maharashtra Indapur India College of Engineering Maharashtra Pune India Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura India Department of Computer Science and Engineering School of Computing MIT Art Design and Technology University Pune India MIT College of Railway Engineering Maharashtra Barshi India

ISBN: (纸本)9783031860683

Osteoarthritis (OA) is a widespread condition without a currently available treatment, significantly affecting individuals’ quality of life as this is a progressive condition that deteriorates with time, frequently leading to persistent Joint pain and stiffness can become severe enough to make daily tasks difficult. Magnetic resonance (MR) images are commonly employed in OA diagnosis, where medical experts assess changes, especially within the tibio-femoral cartilage compartment for knee OA. This study presents a new diagnostic technique for knee OA that detects the illness from MR images using a Support Vector Machine (SVM) algorithm. Our suggested method employs the Independent Component Analysis (ICA) technique on 3-D MR imaging data from a real-world cohort. The experimental results show that our ICA-SVM machine learning model obtained 86% testing accuracy and 72% specificity. and sensitivity of 100%, having been trained on a limited MR image dataset. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Support vector machines

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(Un)designing AI for Mental and Spiritual Wellbeing 24

(Un)designing AI for Mental and Spiritual Wellbeing

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27th ACM Conference on Computer-Supported Cooperative Work and Social computing, CSCW Companion 2024

作者： Smith, C. Estelle Bezabih, Alemitu Freed, Diana Halperin, Brett A. Wolf, Sara Claisse, Caroline Li, Jingjin Hoefer, Michael Rifat, Mohammad Rashidujjaman Colorado School of Mines GoldenCO United States Brown University ProvidenceRI United States Human Centered Design & Engineering University of Washington SeattleWA United States Julius-Maximilians-Universität Würzburg Würzburg Germany Open Lab School of Computing Newcastle University Newcastle upon Tyne United Kingdom *** Mountain ViewCA United States University of St. Thomas St. PaulMN United States University of Toronto TorontoON Canada

ISBN: (纸本)9798400711145

With rapid advances in Artificial Intelligence (AI) impacting human health and wellbeing, scholarly discourse should focus equally on the prospective opportunities and harms of Human-AI Interaction (HAI) in Computer-Supported Collaborative Work and Social computing (CSCW). This panel invites critical interdisciplinary discussion around the (un)designing of AI by asking: how, when, where, and why should AI (not) be involved in sociotechnical systems for mental and spiritual health and wellbeing? Motivated by functional, technical, and ethical concerns, the panel aims to ensure that: (1) progress in HAI for mental and spiritual health is informed by expertise from the respective clinical disciplines;(2) ethical and responsible design principles lie at the core of research motivations and methodologies;and (3) AI hype can be tempered by caution given its impacts on marginalized and stigmatized groups. A panel of respected experts in mental health, spiritual care, and AI will discuss CSCW topics regarding HAI in contexts of clinical practice (e.g., electronic health records, patient portals, decision-making and referral systems, technology-supported interactions during bedside care or clinical appointments) as well as social contexts beyond the clinic (e.g., social apps, online health communities and social media, and computer-mediated communication in spiritual/religious groups). © 2024 Owner/Author.

关键词： Electronic health record

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SCPA-Net: Self-calibrated pyramid aggregation for image dehazing

SCPA-Net: Self-calibrated pyramid aggregation for image deha...

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作者： Chen, Zhihua Zhou, Yu Li, Ran Li, Ping Sheng, Bin Department of Computer Science and Engineering East China University of Science and Technology Shanghai China Department of Computing The Hong Kong Polytechnic University Hong Kong School of Design The Hong Kong Polytechnic University Hung Hom Hong Kong Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China

Dehazing as an important image processing field has developed for many years, there exist many excellent methods for exploring more complex networks to solve this problem. In this paper, instead of designing a complex network structure, we propose a novel dehazing network based on the consideration of enhancing feature aggregation and feature representation abilities of dehazing architecture. Specifically, we propose a self-calibrated pyramid aggregation network (SCPA-Net) for image dehazing, which is based on an encoder-decoder architecture. In the encoder, we build a self-attention block as a unit to aggregate information from a neighborhood to adapt to its content. In the decoder, we introduce a self-calibration block to capture long-range spatial and channel dependencies to produce more discriminative representations. Finally, to learn the scale information, the pyramid upsampling structure is applied to aggregate the multiscale self-calibrated attentive features. Experimental results show our SCPA-Net can achieve impressive dehazing performance. © 2022 John Wiley & Sons, Ltd.

关键词： Demulsification

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Verify All Traffic: Towards Zero-Trust In-Network Intrusion Detection against Multipath Routing

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IEEE Journal on Selected Areas in Communications 2025年第6期43卷 2155-2171页

作者： Zhao, Ziming Li, Zhaoxuan Xie, Xiaofei Liu, Zhipeng Li, Tingting Yu, Jiongchi Zhang, Fan Chen, Binbin School of Software Technology Zhejiang University Ningbo315100 China College of Computer Science and Technology Zhejiang University Hangzhou310027 China ZJU-Hangzhou Global Scientific and Technological Innovation Center 311200 China Key Laboratory of Blockchain and Cyberspace Governance of Zhejiang Province 310027 China Jiaxing Research Institute Zhejiang University 314000 China Zhengzhou Xinda Institute of Advanced Technology Zhengzhou450001 China Singapore State Key Laboratory of Information Security Institute of Information Engineering Chinese Academy of Sciences Beijing100093 China School of Cyber Security UCAS Beijing100049 China School of Computing and Information Systems Singapore Management University Singapore188065 Singapore Advanced Digital Sciences Center Singapore138632 Singapore Singapore University of Technology and Design SingaporeB96049 Singapore

With the popularity of encryption protocols, machine learning (ML)-based traffic analysis technologies have attracted widespread attention. To adapt to modern high-speed bandwidth, recent research is dedicated to advancing zero-trust intrusion detection by offloading feature extraction and model inference into the network dataplane. Especially, with the rise of programmable switches, achieving line-speed ML inference becomes promising. However, existing research only considers a single switch node as a relay to conduct evaluation. This is far from real-world deployments involving multiple switches (given that zero-trust security assumes that threats can originate from anywhere, including within the network), particularly the multi-path routing phenomenon that exists in practice. In this paper, we reveal practical challenges in the context of enabling line-speed model inference in the network dataplane. Furthermore, we propose FCPlane, the forwarding and computing integrated dataplane for zero-trust intrusion detection that aims to enable efficient load balancing while providing reliable traffic analysis results, even against multipath routing. The core idea is to reconcile forwarding and computation to the flowlet level, for which a tailor-made Markov chain model is designed. Based on two public traffic datasets, we evaluate seven state-of-the-art in-network traffic analysis models deployed in four types of topologies (three with multipath routing and one without) to explore performance impact and demonstrate the effectiveness of our proposal. © 1983-2012 IEEE.

关键词： Network intrusion

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Static Virus Spread Algorithm for DNA Sequence design

arXiv

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arXiv 2023年

作者： Yao, Yao Zhang, Xun Liu, Xin Liu, Yuan Zhang, Xiaokang Zhang, Qiang The School of Computer Science and Technology Dalian University of Technology Liaoning Dalian116024 China The Key Laboratory of Advanced Design and Intelligent Computing Ministry of Education School of Software Engineering Dalian University Dalian116622 China

DNA is not only the genetic material of life, but also a favorable material for a new computing model. Various research works based on DNA computing have been carried out in recent years. DNA sequence design is the foundation of such research. The sequence quality directly affects the universality, robustness, and stability of DNA computing. How to design DNA sequences depends on the biological properties and target requirements, which is a typical combinatorial optimization problem. In this paper, in order to design DNA sequences with high-quality, we propose a novel meta-heuristic evolutionary algorithm, termed the static virus spread algorithm (SVS). Through this algorithm, we focus on the constraints of universal DNA sequence design and produce a large number of DNA sequences with non-complementarity and small difference in melting temperature as the objectives, and fully considering the balanced proportion of the four bases. The computer simulation and polyacrylamide gel electrophoresis experiments show that the high-quality DNA sequences designed by this algorithm are effective, which is expected to provide a convenient tool for sequence preparation before DNA biochemical operations. Copyright © 2023, The Authors. All rights reserved.

关键词： DNA sequences

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Cognizant Resource Balancing in Montgomery Modular Multiplication Optimization for Dsp

SSRN

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SSRN 2024年

作者： Tao, Qiqi Li, Liying Zhou, Junlong Cao, Guitao Meng, Dan Shanghai Key Laboratory of Trustworthy Computing MoE Engineering Research Center of SW/HW Co-design Technology and Application East China Normal University Shanghai200062 China School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing210094 China

The performance of modular multiplication directly influences the efficiency of a majority of encryption ***, there are numerous FPGA-based acceleration techniques targeting modular ***, many of these implementations require substantial hardware resources or suffer from resource ***, we present a novel FPGA-based implementation of Montgomery Modular Multiplication aimed at addressing these *** design employs a suitable radix bit width and word size based on the digital signal processing (DSP) bit width rather than the conventional binary powers of *** aim to instantiate more modular multipliers using limited resources while minimizing *** also introduce a novel DSP cascade structure, called parallel grouping cascade DSP, which reduces the number of clock cycles of internal *** balance the ratio of lookup table (LUT) and DSP usage, we also use multipliers implemented in the LUT to replace some *** results, implemented on Xilinx Virtex-7 field-programmable gate array (FPGA), demonstrate more than 27\% improvement in throughput on 1024-bit modular multiplication and more than 70\% improvement on 2048-bit compared to the best previous state-of-the-art references. © 2024, The Authors. All rights reserved.

关键词： Digital signal processing

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