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19th International Conference on Computer Aided Systems Theory, EUROCAST 2024

作者： Praschl, Christoph Dalkilic, Mert Bauernfeind, Sophie Wakolbinger, Markus Zwettler, Gerald A. Research and Development Department University of Applied Sciences Upper Austria Hagenberg i. M. Austria WAKO 3D Ltd. Linz Austria Department of Software Engineering School of Informatics Communications and Media University of Applied Sciences Upper Austria Hagenberg i. M. Austria

ISBN: (纸本)9783031829598

The provision of customized orthopedic aids, such as prostheses and orthoses, is essential for treating congenital malformations, chronic diseases, and musculoskeletal injuries. Traditionally, these aids have been crafted manually by skilled technicians. However, the advent of adaptive manufacturing techniques and digital methodologies, in the context of Industry 4.0, is revolutionizing this field. This paper explores the automated customization of orthopedic aids using a novel two-step pipeline that leverages digital scans and structural analysis. The first step involves adapting orthopedic aids based on 3D scans of the patient’s body, ensuring a precise fit. The second step employs the Finite Element Method (FEM) to analyze the structural integrity of these customized aids, focusing on aspects such as pressure distribution and heat conduction. While FEM has been extensively used in medical contexts to study human body structures, its application to the analysis of digitally customized orthopedic aids remains limited. The proposed methodology utilizes registered 3D meshes and reference skeletons to create patient-specific aids through an as-rigid-as-possible approach. The effectiveness of this process is evaluated by adapting a forearm and a foot orthosis based on patient-specific 3D scans. FEM analysis confirms that the customized aids maintain structural integrity comparable to their templates. This research demonstrates the feasibility of automated customization of orthopedic aids, paving the way for future applications involving a broader range of prostheses and orthoses, thereby enhancing the efficiency and accuracy of orthopedic treatments. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Structural health monitoring

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Container Scheduling Strategy Based on Image Layer Reuse and Sequential Arrangement in Mobile Edge Computing

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IEEE Transactions on Mobile Computing 2025年

作者： Wu, Haijie Lin, Weiwei Zhang, Haotong Shi, Fang Shen, Wangbo Li, Keqin Zomaya, Albert Y. South China University of Technology School of Computer Science and Engineering Guangzhou510006 China Pengcheng Laboratory Shenzhen518066 China South China University of Technology School of Software Engineering Guangzhou510006 China South China Agricultural University College of Mathematics and Informatics Guangzhou510642 China State University of New York Department of Computer Science New PaltzNY12561 United States University of Sydney School of Computer Science SydneyNSW2006 Australia

In Mobile Edge Computing (MEC) scenarios, computational tasks are popularly deployed using containerization to isolate the runtime environment. To complete the execution of the task, the edge server first pulls the image, then instantiates and runs the container. Since it takes a lot of time for the edge server to download the image from the cloud, image reuse reduces the pulling latency significantly. However, the limited storage capacity of edge servers hinders image reuse. Recent works have enhanced reuse efficiency by leveraging the hierarchical structure of images and caching high-value layers. However, their efficiency remains limited due to the lack of multi-container collaboration. This paper proposes a novel container scheduling strategy based on image layer reuse and sequence arrangement (ILR-SA) for MEC scenarios, which achieves efficient scheduling by collaborating multiple containers. First, containers are greedily deployed into the edge cluster. Then, the execution sequence of containers is modeled as an optimal Hamiltonian path problem, efficiently solved by our proposed decomposition algorithm. Finally, an efficient image layer update strategy is used to achieve layer reuse. We conduct rigorous experiments to demonstrate that our proposed container scheduling strategy reduces the computational task completion time by up to 91.3% compared to existing approaches. © 2002-2012 IEEE.

关键词： Mobile edge computing

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Virtual sensors for smart farming: An IoT- and AI-enabled approach

Internet of Things (The Netherlands)

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Internet of Things (The Netherlands) 2025年 32卷

作者： Chourlias, Athanasios Violos, John Leivadeas, Aris Department of Informatics & Telematics Harokopio University of Athens Omirou 9 Tavros 177 78 Greece Department of Software and IT Engineering École de technologie supérieure 1100 Notre-Dame St W Montreal H3C 1K3 Canada

Smart farming relies on precise environmental data to optimize agricultural practices, with key metrics such as air temperature, humidity, rain, ambient light, ultraviolet (UV) radiation and soil moisture to play a crucial role in agricultural decision-making. However, the vast spatial coverage of agricultural fields and the high cost of deploying numerous physical sensors pose significant challenges, particularly for small and medium-sized farms. To address these issues, virtual sensors – machine learning models that predict sensor values based on data from relevant physical sensors – offer a cost-effective and scalable alternative. In this research, a number of Arduino-based IoT devices are designed and deployed equipped with various physical sensors, a lithium-polymer battery which recharges continuously using a 6 W waveshare solar panel, and a Real-Time Clock (RTC) module that synchronizes data logging. The IoT devices operated across two agricultural fields over a span of almost three months. The data collected form the basis for evaluating multiple machine learning models as virtual sensors. Furthermore, the use of open weather data to develop a hardware-free solution is explored. Experimental results show that virtual sensors provide a cost-effective and accurate method for replacing physical sensors. The Light Gradient Boosting Machine emerged as the most accurate model for virtual sensors, achieving prediction errors of less than 1% in most of the cases. This makes it a valuable tool for enabling cost-effective and data-driven farming in resource-constrained IoT devices. © 2025 The Author(s)

关键词： IoT Machine learning Physical sensors Smart agriculture Smart farming Virtual sensors

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UAVs Meet LLMs: Overviews and Perspectives Toward Agentic Low-Altitude Mobility

arXiv

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arXiv 2025年

作者： Tian, Yonglin Lin, Fei Li, Yiduo Zhang, Tengchao Zhang, Qiyao Fu, Xuan Huang, Jun Dai, Xingyuan Wang, Yutong Tian, Chunwei Li, Bai Lv, Yisheng Kovács, Levente Wang, Fei-Yue The State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Department of Engineering Science Faculty of Innovation Engineering Macau University of Science and Technology 999078 China School of Automation Beijing Institute of Technology Beijing100081 China School of Software Northwestern Polytechnical University Xi’an710129 China College of Mechanical and Vehicle Engineering Hunan University Changsha410082 China John von Neumann Faculty of Informatics Obuda University BudapestH-1034 Hungary

Low-altitude mobility, exemplified by unmanned aerial vehicles (UAVs), has introduced transformative advancements across various domains, like transportation, logistics, and agriculture. Leveraging flexible perspectives and rapid maneuverability, UAVs extend traditional systems’ perception and action capabilities, garnering widespread attention from academia and industry. However, current UAV operations primarily depend on human control, with only limited autonomy in simple scenarios, and lack the intelligence and adaptability needed for more complex environments and tasks. The emergence of large language models (LLMs) demonstrates remarkable problem-solving and generalization capabilities, offering a promising pathway for advancing UAV intelligence. This paper explores the integration of LLMs and UAVs, beginning with an overview of UAV systems’ fundamental components and functionalities, followed by an overview of the state-of-the-art LLM technology. Subsequently, it systematically highlights the multimodal data resources available for UAVs, which provide critical support for training and evaluation. Furthermore, key tasks and application scenarios where UAVs and LLMs converge are categorized and analyzed. Finally, a reference roadmap towards agentic UAVs is proposed to enable UAVs to achieve agentic intelligence through autonomous perception, memory, reasoning, and tool utilization. Related resources are available at https://***/Hub-Tian/UAVs Meet LLMs. Copyright © 2025, The Authors. All rights reserved.

关键词： Drones

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Uncovering Non-native Speakers' Experiences in Global software Development Teams——A Bourdieusian Perspective

arXiv

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arXiv 2025年

作者： Wang, Yi Yue, Yang Wang, Wei Zhang, Gaowei Department of Software Engineering Beijing University of Posts and Telecommunications 10# Xitucheng Road Beijing100876 China 10# Xitucheng Road Beijing100876 China Department of Informatics University of California-Irvine IrvineCA92612 United States School of Artificial Intelligence Beijing University of Posts and Telecommunications 10# Xitucheng Road Beijing100876 China

Globally distributed software development has been a mainstream paradigm in developing modern software systems. We have witnessed a fast-growing population of software developers from areas where English is not a native language in the last several decades. Given that English is still the de facto working language in most global software engineering teams, we need to gain more knowledge about the experiences of developers who are non-native English speakers. We conducted an empirical study to fill this research gap. In this study, we interviewed 27 Chinese developers in commercial software development and open source global software development teams and applied Bourdieu's capital-field-habitus framework in an abductive data analysis process. Our study reveals four types of capital (language, social, symbolic, and economic) involved in their experiences and examines the interrelations among them. We found that non-native speakers' insufficient language capital played an essential role in prohibiting them from accessing and accumulating other capital, thus reproducing the sustained and systematic disadvantaged positions of non-native English speakers in GSD teams. We further discussed the theoretical and practical implications of the study. © 2025, CC BY-NC-ND.

关键词： Open source software

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Foreword to the special section on Recent Advances in Graphics and Interaction (RAGI 2024)

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Computers & Graphics 2025年

作者： Anabela Marto José Creissac Campos Kyle Johnsen Department of Informatics Engineering Polytechnic of Leiria Leiria Portugal Department of Informatics The University of Minho Braga Portugal High-Assurance Software Laboratory (HASLab) INESC TEC Braga Portugal College of Engineering University of Georgia Georgia USA

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Feature-Oriented Nonfunctional Requirement Analysis for software Product Line

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Journal of Computer Science & Technology 2009年第2期24卷 319-338页

作者：彭鑫 Seok-Won Lee 赵文耘 School of Computer Science Fudan University Knowledge-Intensive Software Engineering Research Group Department of Software and Information Systems College of Computing and Informatics University of North Carolina at Charlotte

Domain analysis in software product line （SPL） development provides a basis for core assets design and imple- mentation by a systematic and comprehensive commonality/variability analysis. In feature-oriented SPL methods, products of the domain analysis are domain feature models and corresponding feature decision models to facilitate application-oriented customization. As in requirement analysis for a single system, the domain analysis in the SPL development should con- sider both flmctional and nonfunctional domain requirements. However, the nonfunctional requirements （NFRs） are often neglected in the existing domain analysis methods. In this paper, we propose a context-based method of the NFR analysis for the SPL development. In the method, NFRs are materialized by connecting nonfunctional goals with real-world context, thus NFR elicitation and variability analysis can be performed by context analysis for the whole domain with the assistance of NFR templates and NFR graphs. After the variability analysis, our method integrates both functional and nonfunc- tional perspectives by incorporating the nonfunctional goals and operationalizations into an initial functional feature model. NFR-related constraints are also elicited and integrated. Finally, a decision model with both functional and nonfunctional perspectives is constructed to facilitate application-oriented feature model customization. A computer-aided grading system （CAGS） product line is employed to demonstrate the method throughout the paper.

关键词： software product line nonfunctional requirement domain analysis feature-oriented method variability analysis

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Self-supervised representation learning for Bayesian quantum architecture search

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Physical Review A 2025年第3期111卷 032403-032403页

作者： Zhimin He Hongxiang Chen Yan Zhou Haozhen Situ Yongyao Li Lvzhou Li School of Electronic and Information Engineering Foshan University Foshan 528000 China School of Computer Science and Artificial Intelligence Foshan University Foshan 528000 China Guangdong Provincial Key Laboratory of Industrial Intelligent Inspection Technology Foshan University Foshan 528000 China College of Mathematics and Informatics South China Agricultural University Guangzhou 510642 China School of Physics and Optoelectronic Engineering Foshan University Foshan 528225 China Institute of Quantum Computing and Software School of Computer Science and Engineering Sun Yat-sen University Guangzhou 510006 China Quantum Science Center of Guangdong-Hong Kong-Macao Greater Bay Area (Guangdong) Shenzhen 518045 China

Quantum architecture search (QAS) has shown significant promise in automating quantum circuit design for variational quantum algorithms (VQAs). However, a central challenge remains in the high computational cost of evaluating the ground-truth performance of numerous circuit architectures during the search process. This challenge is further complicated by factors such as inefficient gradient computation, the barren plateau phenomenon, and frequent data exchange between classical and quantum systems within VQAs, all of which restrict the scalability of QAS for increasingly complex VQAs. In this study, we propose an enhanced QAS framework that integrates a performance predictor trained through self-supervised learning with Bayesian optimization to overcome these computational barriers. To address the challenges of circuit performance evaluation, we develop a graph-isomorphism-network-based predictor pretrained using expressibility prediction, an intrinsic measure of a circuit's capacity to explore the Hilbert space uniformly. This pretraining process creates a structured and smooth latent space, significantly improving the predictor's accuracy and generalizability with minimal labeled data. Furthermore, Bayesian optimization is integrated into the QAS framework to refine the predictor iteratively, concentrating the search on regions containing high-performance circuits and thus accelerating the search process. Simulation results for VQAs involving the variational quantum eigensolver and quantum approximate optimization algorithm demonstrate that the proposed framework achieves faster convergence to optimal circuits and substantially reduces computational costs compared to existing QAS methods.

关键词： Bayesian networks

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Weighted Density for The Win: Accurate Subspace Density Clustering

Weighted Density for The Win: Accurate Subspace Density Clus...

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

作者： Maixuan Peng Yuyang Wu Yang Lu Mengke Li Yiqun Zhang Yiu-Ming Cheung School of Computer Science and Technology Guangdong University of Technology Guangzhou China Faculty of Science Wilfrid Laurier University Brantford Canada Fujian Key Laboratory of Sensing and Computing for Smart City School of Informatics Xiamen University Xiamen China College of Computer Science and Software Engineering Shenzhen University Shenzhen China Department of Computer Science Hong Kong Baptist University China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

k-clustering typically struggles with the detection of irregular-distributed clusters due to the natural bias, while density clustering usually cannot well-adapt to different datasets and clustering tasks as it is not an oriented optimization process. This paper, therefore, proposes to perform density clustering in dynamically learned subspaces. To exploit the irregular-distributed clusters obtained by density clustering for the subspace determination, we design a new strategy to appropriately evaluate the importance of attributes. It turns out that the proposed Weighted Density-based Subspace Clustering (WDSC) algorithm inherits the unbiased merits of density clustering, and also upgrades the unlearning density clustering to be learnable under the subspace learning paradigm of k-clustering. A comprehensive evaluation including significance tests, ablation studies, qualitative comparisons, etc., shows the superiority of WDSC.

关键词： Accuracy Heuristic algorithms Signal processing algorithms Clustering algorithms Signal processing Acoustics Speech processing Optimization

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A Lightweight and Robust Access Control Protocol for IoT-based e-Healthcare Network

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IEEE Transactions on Mobile Computing 2025年

作者： Ghaffar, Zahid Kuo, Wen-Chung Mahmood, Khalid Tariq, Tayyaba Shamshad, Salman Das, Ashok Kumar Alenazi, Mohammed J.F. National Yunlin University of Science and Technology Graduate School of Engineering Science and Technology Douliu64002 Taiwan National Yunlin University of Science and Technology Department of Computer Science and Information Engineering Douliu64002 Taiwan National Yunlin University of Science and Technology Graduate School of Intelligent Data Science Douliu64002 Taiwan The University of Lahore Department of Software Engineering Lahore54590 Pakistan International Institute of Information Technology Center for Security Theory and Algorithmic Research Hyderabad500 032 India Korea University Department of Computer Science and Engineering College of Informatics 145 Anam-ro Seongbuk-gu Seoul02841 Korea Republic of King Saud University College of Computer and Information Sciences Department of Computer Engineering Riyadh Saudi Arabia

Internet of Things (IoT) devices are crucial components in e-healthcare networks. It enables remote patient health monitoring and facilitates seamless communication among medical sensors, wearable devices, and healthcare providers through public communication channels. Despite these advantages, the use of public communication among medical sensors in e-healthcare networks introduces critical challenges, such as vulnerability to impersonation, physical capture, and ephemeral secret leakage, particularly in resource-constrained environments. In recent years, various access control protocols have been developed to mitigate these risks. However, these protocols often fail to ensure robust security while incurring significant communication and computation overhead. To overcome these limitations, we propose a lightweight and robust access control protocol for IoT-based e-healthcare networks using chaotic maps. We propose a novel protocol that integrates a PUF-based mechanism to mitigate the challenges of physical tampering and cloning attacks in e-healthcare networks. It leverages the inherent uniqueness of PUF and enhances security through the high-entropy properties of chaotic maps. We analyze the proposed protocol informally, which confirms that it significantly bolsters efficiency and security. We also validate the security using the Random or Real (RoR) model. Moreover, we verify the security of the proposed protocol using Scyther. These analyses highlight that the proposed protocol offers robust resistance to numerous attacks, such as impersonation, physical capture, and ephemeral secret leakage. Moreover, we also compare it with existing and relevant protocols. The comparative analysis showcases its superior performance. Notably, the proposed authentication protocol significantly reduces 46.84% computational overhead and decreases 31.30% communication overhead, underscoring its enhanced performance and resource efficiency. © 2002-2012 IEEE.

关键词： Authentication

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