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arXiv 2025年

作者： Ahmed, Aram M. Hassan, Bryar A. Rashid, Tarik A. Noori, Kaniaw A. Saeed, Soran Ab.M. Ahmed, Omed H. Umar, Shahla U. Computer Science and Engineering Department University of Kurdistan Hewlêr Erbil Iraq Department of Computer Science College of Science Charmo University Chamchamal Sulaimani Iraq Database Technology Department Technical College of Informatics Sulaimani Polytechnic University Sulaimani Iraq Department of Information Technology University of Human Development Sulaymaniyah Iraq Network Department College of Computer Science and Information Technology Kirkuk University Kirkuk Iraq

This paper presents a multi-objective version of the Cat Swarm Optimization Algorithm called the Grid-based Multiobjective Cat Swarm Optimization Algorithm (GMOCSO). Convergence and diversity preservation are the two main goals pursued by modern multi-objective algorithms to yield robust results. To achieve these goals, we first replace the roulette wheel method of the original CSO algorithm with a greedy method. Then, two key concepts from Pareto Archived Evolution Strategy Algorithm (PAES) are adopted: the grid system and double archive strategy. Several test functions and a real-world scenario called the Pressure vessel design problem are used to evaluate the proposed algorithm's performance. In the experiment, the proposed algorithm is compared with other well-known algorithms using different metrics such as Reversed Generational Distance, Spacing metric, and Spread metric. The optimization results show the robustness of the proposed algorithm, and the results are further confirmed using statistical methods and graphs. Finally, conclusions and future directions were presented.. © 2025, CC BY.

关键词： Pressure vessels

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"Two Means to an End Goal": Connecting Explainability and Contestability in the Regulation of Public Sector AI

arXiv

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arXiv 2025年

作者： Schmude, Timothée Yurrita, Mireia Alfrink, Kars Goff, Thomas L.E. Viard, Tiphaine University of Vienna Faculty of Computer Science Research Network Data Science Doctoral School Computer Science Austria Delft University of Technology Department of Sustainable Design Engineering Netherlands i3 Télécom Paris Institut Polytechnique de Paris France

Explainability and its emerging counterpart contestability have become important normative and design principles for the trustworthy use of AI as they enable users and subjects to understand and challenge AI decisions. However, the regulation of AI systems spans technical, legal, and organizational dimensions, producing a multiplicity in meaning that complicates the implementation of explainability and contestability due to the difficulty of defining them. Resolving this conceptual ambiguity requires specifying and comparing the meaning of both principles across regulation dimensions, disciplines, and actors. This process, here defined as translation, is essential to provide guidance on the principles’ realization. To this end, we present the findings of a semi-structured interview study with 14 interdisciplinary AI regulation experts. We report on the experts’ understanding of the intersection between explainability and contestability in public AI regulation, their advice for a decision subject and a public agency in a welfare allocation AI use case, and their perspectives on the connections and gaps within the research landscape. We provide differentiations between descriptive and normative explainability, judicial and non-judicial channels of contestation, and individual and collective contestation action. We further outline three main translation processes pertaining to the alignment of top-down and bottom-up regulation, the assignment of responsibility for interpreting regulations, and the establishment of interdisciplinary collaboration. Our contributions include an empirically grounded conceptualization of the intersection between explainability and contestability and recommendations on implementing these principles in public institutions. We believe our contributions can inform policy-making and regulation of these core principles and enable more effective and equitable design, development, and deployment of trustworthy public AI systems. Copyright © 2025, T

关键词： Energy policy

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A Smart and Privacy-Preserving Logistics System Based on IoT and Blockchain Technologies

A Smart and Privacy-Preserving Logistics System Based on IoT...

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Advanced Innovations in Smart Cities (ICAISC), International Conference on

作者： Mohammed Balfaqih Zain Balfagih Akram A. Almohammedi Khaled M. Alfawaz Department of Computer and Network Engineering University of Jeddah Jeddah Saudi Arabia Computer of Science Department Effat University Jeddah Saudi Arabia Management Information System Department King Abdulaziz University Jeddah Saudi Arabia Automobile Transportation Department Sotuh Ural State University Chelyabinsk Russia Electrical & Electronics Engineering Department Karabiik University Karabiik Turkey

ISBN: (数字)9781665472753

ISBN: (纸本)9781665472760

The smart city concept serves the well-being of the urban population in order to improve quality of life in different life aspects including logistic services. However, the continuous growth of logistics volume combined with information opaqueness and process complexity led to challenging issues related to managing the services and information of logistics. Hence, efficient management of logistics activities with traceability and condition monitoring capabilities is required to ensure quality and safe delivery. It is necessary also to ensure the accuracy and dependability of distribution data. In this context, this paper proposes a smart and privacy-preserving logistics system for high-price goods distribution. An intelligent parcel (iParcel) containing piezoresistive sensors is developed to pack delivered goods during shipping process for violation detection such as severe fall or theft. Moreover, smart contracts based on blockchain is also developed for automatic approval and payment with the consideration of distributing the shipping information between legitimate logistics parties only. A zero-knowledge proof is used to conceal blockchain address and prove the authentication. iParcels are automatically tracked and traced in which upon violation occurrence, the contract is cancelled, and the payment is refunded. The transaction fee per party is reasonable for high-price products in the pay of guarantee successful shipment.

关键词： Condition monitoring Technological innovation Smart cities Sociology Authentication Blockchains Statistics

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PrintListener: Uncovering the Vulnerability of Fingerprint Authentication via the Finger Friction Sound

arXiv

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arXiv 2024年

作者： Zhou, Man Su, Shuao Wang, Qian Li, Qi Zhou, Yuting Ma, Xiaojing Li, Zhengxiong School of Cyber Science and Engineering Huazhong University of Science and Technology China School of Cyber Science and Engineering Wuhan University China Institute for Network Sciences and Cyberspace Tsinghua University China Department of Computer Science and Engineering University of Colorado Denver United States Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology China

Fingerprint authentication has been extensively employed in contemporary identity verification systems owing to its rapidity and cost-effectiveness. Due to its widespread use, fingerprint leakage may cause sensitive information theft, enormous economic and personnel losses, and even a potential compromise of national security. As a fingerprint that can coincidentally match a specific proportion of the overall fingerprint population, MasterPrint rings the alarm bells for the security of fingerprint authentication. In this paper, we propose a new side-channel attack on the minutiae-based Automatic Fingerprint Identification System (AFIS), called PrintListener, which leverages users’ fingertip swiping actions on the screen to extract fingerprint pattern features (the first-level features) and synthesizes a stronger targeted PatternMasterPrint with potential second-level features. The attack scenario of PrintListener is extensive and covert. It only needs to record users’ fingertip friction sound and can be launched by leveraging a large number of social media platforms. Extensive experimental results in real-world scenarios show that Printlistener can significantly improve the attack potency of MasterPrint. © 2024, CC0.

关键词： Friction

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A Comparative Study of Machine Learning and Deep Learning for Disaster Prediction

A Comparative Study of Machine Learning and Deep Learning fo...

引用

Computational Intelligence Approaches and Applications (ICCIAA), International Conference on

作者： Waleed Amer Ola Nasir Ala Hamarsheh Ali Mahmoud Ali Amani Abu Zaid Walaa Shtayah Department of Cyber Secyrity Faculty of Information Technology Zarqa University Zarqa Jordan Department of Computer Science Faculty of Information Technology Zarqa University Zarqa Jordan Department of computer science Faculty of Information Technology Arab American University Department of Computer Network Faculty of Engineering Technology Al-Balqa Applied University Amman Jordan Department of Artificial Intelligence Faculty of Information Technology Zarqa University Zarqa Jordan

ISBN: (数字)9798331523657

ISBN: (纸本)9798331523664

The analytical procedure known as Disaster Prediction (DP) makes estimates regarding future incident and disaster events before they actually occur. The present research seeks to determine which method produces the best results for DP. The research finds that Deep Learning surpasses Machine Learning and Artificial Intelligence methods when predicting disaster occurrence including or excluding events. The results indicate Deep Learning stands as the top DP method. CNN turned out to be the DL model with the best performance results which produced Accuracy at 0.993 and Precision at 0.986 along with Recall at 0.978. Among the models tested the LSTM model performed as the runner-up with accuracy reaching (0.975), precision at (0.959), while recall obtained (0.992). The research shows how DL technologies prove advantageous for disaster risk assessment plus their capability for developing proactive disaster response strategies.

关键词： Deep learning Accuracy Disasters Risk management Long short term memory Computational intelligence

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Deep Reinforcement Learning-Based Grant-Free NOMA Optimization for mURLLC

Deep Reinforcement Learning-Based Grant-Free NOMA Optimizati...

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作者： Liu, Yan Deng, Yansha Zhou, Hui Elkashlan, Maged Nallanathan, Arumugam Key Laboratory of Ministry of Education in Broadband Wireless Communication and Sensor Network Technology Nanjing University of Posts and Telecommunications Nanjing210003 China School of Electronic Engineering and Computer Science Queen Mary University of London LondonE1 4NS United Kingdom College of Electronic and Information Engineering Tongji University Shanghai201804 China Department of Engineering King s College London LondonWC2R 2LS United Kingdom Huawei Technology Company Ltd. Shanghai200121 China

Grant-free non-orthogonal multiple access (GF-NOMA) is a potential technique to support massive Ultra-Reliable and Low-Latency Communication (mURLLC) service. However, the dynamic resource configuration in GF-NOMA systems is challenging due to random traffics and collisions, that are unknown at the base station (BS). Meanwhile, joint consideration of the latency and reliability requirements makes the resource configuration of GF-NOMA for mURLLC more complex. To address this problem, we develop a novel learning framework for signature-based GF-NOMA in mURLLC service taking into account the multiple access signature collision, the UE detection, as well as the data decoding procedures for the K-repetition GF and the Proactive GF schemes. The goal of our learning framework is to maximize the long-term average number of successfully served users (UEs) under the latency constraint. We first perform a real-time repetition value configuration based on a double deep Q-network (DDQN) and then propose a Cooperative Multi-Agent learning technique based DQN (CMA-DQN) to optimize the configuration of both the repetition values and the contention-transmission unit (CTU) numbers. Our results show the superior performance of CMA-DQN over the conventional load estimation-based uplink resource configuration approach (LE-URC) in heavy traffic and demonstrate its capability in dynamically configuring in long term for mURLLC service. In addition, with our learning optimization, the Proactive scheme always outperforms the K-repetition scheme in terms of the number of successfully served UEs, especially under the high backlog traffic scenario. © 1972-2012 IEEE.

关键词： Reliability

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Edge Information Hub: Orchestrating Satellites, UAVs, MEC, Sensing and Communications for 6G Closed-Loop Controls

arXiv

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arXiv 2024年

作者： Lei, Chengleyang Feng, Wei Wei, Peng Chen, Yunfei Ge, Ning Mao, Shiwen The Department of Electronic Engineering State Key Laboratory of Space Network and Communications Tsinghua University Beijing100084 China The National Key Laboratory of Wireless Communications University of Electronic Science and Technology of China Chengdu611731 China The Department of Engineering University of Durham DurhamDH1 3LE United Kingdom The Department of Electrical and Computer Engineering Auburn University AuburnAL36849 United States

An increasing number of field robots would be used for mission-critical tasks in remote or post-disaster areas. Due to the limited individual abilities, these robots usually require an edge information hub (EIH), with not only communication but also sensing and computing functions. Such EIH could be deployed on a flexibly-dispatched unmanned aerial vehicle (UAV). Different from traditional aerial base stations or mobile edge computing (MEC), the EIH would direct the operations of robots via sensing-communication-computing-control (SC3) closed-loop orchestration. This paper aims to optimize the closed-loop control performance of multiple SC3 loops, with constraints on satellite-backhaul rate, computing capability, and on-board energy. Specifically, the linear quadratic regulator (LQR) control cost is used to measure the closed-loop utility, and a sum LQR cost minimization problem is formulated to jointly optimize the splitting of sensor data and allocation of communication and computing resources. We first derive the optimal splitting ratio of sensor data, and then recast the problem to a more tractable form. An iterative algorithm is finally proposed to provide a suboptimal solution. Simulation results demonstrate the superiority of the proposed algorithm. We also uncover the influence of SC3 parameters on closed-loop controls, highlighting more systematic understanding. Copyright © 2024, The Authors. All rights reserved.

关键词： Unmanned aerial vehicles (UAV)

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Block Chain Technology Implementations for Secured Financial Transactions using Cloud Environment

Block Chain Technology Implementations for Secured Financial...

引用

Interdisciplinary Humanitarian Conference for Sustainability (IIHC), International

作者： T Vara Lakshmi Naveen S.M Raja Sudhir Ramadass Sreekumar Narayanan Velagapudi Sreenivas Balambigai Subramanian Department of MBA Institute of Aeronautical Engineering Hyderabad Department of Computer Science and Engineering KG Reddy College of Engineering and Technology (Autonomous) R R Dist Telangana Sterck Systems Chennai Network Infrastructure and Management Department Faculty of Engineering and Technology Botho University Gaborone Botswana Department of Computer Science and Engineering Dhanekula Institute of Engineering and Technology Krishna dt A.P Department of ECE Kongu Engineering College Perundurai

The advancement of technology has an influence on consumers' decision to switch from executing your financial information in a conventional way to doing so online. Contracts are encouraged by the use of cloud computers or its key feature of accessibility from everywhere. The enormous amount of data handled by the cloud platform used to facilitate money transfers necessitates maintaining a high degree of security for all those important passwords stored there. Although the conventional authentication methods continue to work well in protecting data in cloud, more sophisticated cyber attacks against cloud-based storage of information still exist. Additionally, using typical cryptographic primitives to secure cloud data requires a significant amount of operation time due to the need to execute verification checks for both valid and illegitimate access control.

关键词： Cloud computing Privacy Switches Passwords Organizations Blockchains Decoding

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Using Real-Time Integrated computer Vision and Deep Learning for Advanced Factory Safety

Using Real-Time Integrated Computer Vision and Deep Learning...

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Electronic Communications, Internet of Things and Big Data (ICEIB), International Conference on

作者： Shang-Te Tsai Yu-Cheng Chang Chao-Yi Huang Fang-Yuan Yang Wei Chien Zong-Rong Wu School Art and Design Sanming University Fujian China Department of Computer Science and Information Engineering National Taipei University of Technology Taipei Taiwan Department of Information Management National Yunlin University of Science and Technology Yunlin Taiwan Department of Computer Information and Network Engineering Lunghwa University of Science and Technology Taoyuan Taiwan Department of Technical and Vocational Program in Artificial Intelligence National Yunlin University of Science and Technology Yunlin Taiwan

ISBN: (数字)9798350360721

ISBN: (纸本)9798350360738

Innovative safety in the workplace is vital as the high safety risks associated with electrical engineering construction can lead to injuries or even fatalities. Using computer vision technology, we experimented with scenarios such as “normal operations” and “unexpected incidents” to enhance safety measures. We integrated an Internet of Things system into the setup, enabling the system to quickly detect and alert to unexpected events in real-time, thereby improving workplace safety.

关键词： computer vision Prevention and mitigation Employment Real-time systems Production facilities Safety Internet of Things

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An avoiding overlap method between acoustic shadow and organ for automated ultrasound diagnosis and treatment 11

An avoiding overlap method between acoustic shadow and organ...

引用

11th IEEE Global Conference on Consumer Electronics, GCCE 2022

作者： Matsuyama, Momoko Koizumi, Norihiro Nishiyama, Yu Tsumura, Ryosuke Tsukihara, Hiroyuki Numata, Kazushi The University of Electro-Communications Department of Mechanical and Intelligent Systems Engineering Chofu Japan The University of Electro-Communications Department of Computer and Network Engineering Chofu Japan Health and Medical Research Institute National Institute of Advanced Industrial Science and Technology Line 4 Tsukuba Japan The University of Tokyo Department of Cardiothoracic Surgery Bunnkyo-Ku Japan Yokohama City University Medical Center Gastroenterological Center Yokohama Japan

ISBN: (纸本)9781665492324

Ultrasound diagnosis and treatment have attracted attention because they are noninvasive and allow real-time observation of lesions. However, it is difficult to accurately estimate the location of the treatment area because of information loss due to acoustic shadows caused by the reflection of sound waves from hard tissues such as bone. In this study, we propose a probe manipulation method that uses deep learning to avoid overlap between organs and shadows for automated diagnosis. © 2022 IEEE.

关键词： Ultrasonics

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