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24th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2024

作者： Xu, Yuwei Zeng, Junyu Cao, Jie Dai, Shengjiang Xiang, Qiao Cheng, Guang School of Cyber Science and Engineering Southeast University Nanjing China Purple Mountain Laboratories for Network and Communication Security Nanjing China Engineering Research Center of Blockchain Application Supervision and Management Nanjing China Department of Electrical and Computer Engineering Queen’s University Kingston Canada School of Informatics Xiamen University Xiamen China

ISBN: (纸本)9789819615414

Consortium blockchains, with their decentralized characteristics, have found widespread applications across various industries. However, this also forms isolated data islands. These data islands have become obstacles to data sharing between industries, and the issue of cross-chain data consistency verification remains unresolved. Current mainstream cross-chain technologies solve asset transfer issues through complex transaction steps, thus failing to meet the need for efficient data transmission. Existing research has proposed solutions for cross-chain data consistency verification, but two major issues remain. Firstly, these schemes do not consider data changes or support data dynamic operations. Secondly, these schemes involve a significant amount of complex computations, leading to slow efficiency. To address the above issues, we propose DataJudge, a cross-chain data consistency verification scheme based on an extended Merkle hash tree. This scheme not only verifies cross-chain data consistency but also effectively fills the gap in existing schemes regarding dynamic operations. Additionally, we modify the paillier homomorphic encryption. To improve efficiency, we do not introduce many complex computations. Furthermore, the extended Merkle hash tree structure enhances efficiency. Finally, we implement a prototype system and evaluate it. The results demonstrate that DataJudge can effectively verify cross-chain data consistency and outperform existing schemes such as DCIV and BeDCV. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Data consistency

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Lyapunov-Based Stochastic Resource Allocation for Integrated Satellite-Terrestrial Networks

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IEEE Transactions on Vehicular Technology 2025年

作者： Koutsioumpa, Vasiliki I. Mitsiou, Nikos A. Tegos, Sotiris A. Diamantoulakis, Panagiotis D. Sarigiannidis, Panagiotis G. Karagiannidis, George K. Aristotle University of Thessaloniki Department of Electrical and Computer Engineering Thessaloniki54124 Greece University of Western Macedonia Department of Informatics and Telecommunications Engineering Kozani50100 Greece

The integration of a satellite network with a terrestrial network, supporting optimized network selection and service continuity, is essential to meet the requirements of sixth-generation (6 G) wireless networks. In a typical scenario with both terrestrial and satellite services, a subset, referred to as terrestrial users (t-users), can communicate only with the terrestrial base station (BS), while dual users (d-users) can transmit information to both the BS and an available LEO satellite. Thus, we focus on an integrated satellite-terrestrial uplink network, assuming that non-orthogonal multiple access (NOMA) is used in the terrestrial sub-network, which is motivated by the existence of non-line-of-sight channels between the BS and the users. We also investigate the use of two communication protocols for the satellite sub-network, considering both orthogonal multiple access (OMA) and NOMA. We define a utility function based on the achievable rates of the users and formulate an optimization problem to maximize the long-term utility of the network, taking into account constraints on the maximum capacity of the BS and the LEO satellite, as well as short- and long-term power consumption. We apply Lyapunov theory to decompose it into multiple single-time slot sub-problems, and finally transform it into convex form and solve it effectively. The network selection by the d-users as well as the optimal resource allocation for all users are also investigated. The simulation results show that d-users prefer to communicate with the LEO satellite rather than the BS. The probability of this selection is strongly influenced by the chosen communication scheme and the trajectory of the LEO satellite. Furthermore, there is an improvement in utility when the LEO satellite is close to its zenith position, while users achieve higher utility when the NOMA protocol is used in the satellite sub-network compared to the OMA counterpart. © 1967-2012 IEEE.

关键词： Lyapunov functions

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A Contend Node-Restricted Receiver-Initiated MAC Protocol With Consecutive Packet Transmission

IEEE Transactions on Green Communications and Networking

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IEEE Transactions on Green Communications and Networking 2025年

作者： Liu, Yuxin Ota, Kaoru Dong, Mianxiong Wang, Ruoyu Changsha University College of Computer Science and Engineering Changsha410022 China Muroran Institute of Technology Department of Sciences and Informatics Japan Central South University School of Computer Science and Engineering Changsha410083 China

The medium access control (MAC) protocol plays a crucial role in wireless communications, influencing key performance metrics, such as energy consumption, delay, collision, and throughput. This paper introduces the Contend Node Restricted Joint Consecutive Packet Transmissions Receiver-Initiated (CNR-CPT-RI) protocol, specifically designed to minimize collisions and reduce energy consumption in wake-up radio-enabled wireless sensor networks (WSNs). The CNR-CPT-RI protocol is an effective communication protocol that is mainly applied with nodes in the one-hop range of the sink. Since the sink has the ability to control each node, it becomes feasible to manage the nodes in a way that effectively reduces collisions and enhances network lifetime as well as throughput. Moreover, the CNR-CPT-RI protocol can adaptively adjust the number of nodes participating in channel contention, maintaining it within an optimal range to balance reduced collisions, decreased energy consumption, and sustained high throughput. Furthermore, the winning node in channel contention employs Consecutive Packet Transmissions (CPTs) method to further diminish competition. Comprehensive theoretical and experimental results demonstrate that the number of collisions of the CNR-CPT-RI protocol is only 42.4%, 35.9%, and 32.5% of the baseline protocol when the number of nodes is 10, 20, and 30, respectively. The energy consumption of the CNR-CPT-RI protocol is reduced by 5.7%, 15%, and 22.6%, and the delay is decreased by 6.7%, 16%, and 32%, respectively, compared with that of the existing protocol. © 2017 IEEE.

关键词： Internet protocols

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A Mamdani Fuzzy Inference System for Comprehensive Diabetes Risk Evaluation

A Mamdani Fuzzy Inference System for Comprehensive Diabetes ...

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International Conference on Electrical, computer and Communication engineering (ECCE)

作者： Tanjina Ahmed Tuly Tanjid Ahammed Shafin Md. Zahid Hasan Md. Hasan Imam Bijoy Mohammad Shamsul Arefin Mohammad Shorif Uddin Department of Computer Science and Engineering Health Informatics Research Lab Daffodil International University Dhaka Bangladesh Department of Computer Science and Engineering Chittagong University of Engineering and Technology Chattogram Bangladesh Department of Computer Science and Engineering Jahangirnagar University Savar Bangladesh

ISBN: (数字)9798350357509

ISBN: (纸本)9798350357516

Diabetes mellitus is a chronic condition characterized by insufficient insulin production and the inability to effectively utilize the insulin hormone, leading to elevated blood glucose levels. As diabetes is incurable and persists throughout a patient's lifetime, effective management requires early identification of risk factors to ensure continuous and feasible treatment. This study proposes a unique decision support system based on the Mamdani Fuzzy Inference System (MFIS) to predict diabetes risk. This study utilizes a publicly available diabetes dataset containing 442 data that includes nine key health metrics such as BMI, blood glucose, cholesterol levels, and blood pressure to predict the risk of diabetes. The dataset aims to support early diagnosis and better diabetes management by providing insights into individual risk factors. This resource contributes to the development of more accurate decision-support systems in healthcare. We identify key variables and establish a membership function to assess individual risk. The Fuzzy Inference System (FIS) is well-suited for handling complex and uncertain conditions, making it an effective tool for this application. The advantages of the MFIS include its ability to incorporate expert knowledge through linguistic variables and fuzzy rules. This system demonstrates the practical benefits of MFIS in developing intelligent decision-making tools, particularly in the domain of diabetes risk prediction.

关键词： Fuzzy logic Decision support systems Accuracy Uncertainty Predictive models Blood pressure Diabetes Glucose Insulin Blood

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A unified approach to quasi-uniform completion: Bridging MacNeille, Dedekind and Doitchinov's theories with a new framework

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Topology and its Applications 2025年

作者： Andrikopoulos, Athanasios Gounaridis, Ioannis University of Patras Dept. of Computer Engineering and Informatics Patras 26504 Greece

In this paper, we present a comprehensive completion theory applicable to all quasi-uniform spaces, denoted as Λ-completion. An integral aspect of this completion theory lies in its incorporation of prerequisites articulated by Doitchinov, facilitating a natural extension of the classical theory of uniform completeness. Central to this approach is the concept of “cut of nets,” which emerges from the amalgamation of two fundamental notions: (1) The notion of a “Dedekind-MacNeille cut” within order theory, and (2) the concept of a D-“Cauchy net” as introduced by Doitchinov. Notably, in the realm of uniformity, the concept of cut of nets aligns with the well-established notion of an equivalence class of nets. This convergence enhances our understanding and provides a unifying framework for the completion theory, drawing from both order theory and the nuanced perspective of Doitchinov's D-Cauchy nets. © 2025 Elsevier B.V.

关键词： Cauchy net Completeness Dedekind-MacNeille completion Embedding Quasi-uniform space Quasi-uniformity

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Predicting Heat Stroke Risk: A Clinical Decision Support System using Fuzzy Association Mining Approach

Predicting Heat Stroke Risk: A Clinical Decision Support Sys...

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International Conference on Electrical, computer and Communication engineering (ECCE)

作者： Abdullah Al Noman Rinvi Jaman Riti Md. Zahid Hasan Md. Hasan Imam Bijoy Mohammad Shorif Uddin Mohammad Shamsul Arefin Department of Computer Science and Engineering Health Informatics Research Lab Daffodil International University Dhaka Bangladesh Department of Computer Science and Engineering Jahangirnagar University Savar Bangladesh Department of Computer Science and Engineering Chittagong University of Engineering and Technology Chattogram Bangladesh

ISBN: (数字)9798350357509

ISBN: (纸本)9798350357516

Heat stroke is a serious medical condition that requires immediate treatment and is exacerbated by intense heat and climate change. This paper introduces a Clinical Decision Support System (CDSS) for heat stroke risk assessment based on Fuzzy Association Rule Mining. The system evaluates key attributes extracted from the Stanford Bioengineering Senior Capstone Project dataset, including daily water intake, cardiovascular history, heat index, environmental and rectal temperatures, blood pressure, pulse rate, humidity, age, and sex. These attributes help identify detailed patterns associated with heat stroke risk. Using fuzzy logic, the CDSS addresses the inherent vagueness of medical information through a set of "if- then" rules designed for healthcare practitioners. The system is tested with historical data, demonstrating its effectiveness in recognizing critical parameters to provide personalized, timely attention to potential heat stroke cases. It aims to reduce heat- related illnesses and fatalities by enabling rapid data-driven decision-making in healthcare. Despite certain limitations, this study highlights the necessity of intelligent systems for proactive health management.

关键词： Decision support systems Climate change Fuzzy systems Risk management Predictive models Medical services Medical conditions

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A Deep Learning Approach to User Allocation in a 5th Generation Network 24

A Deep Learning Approach to User Allocation in a 5th Generat...

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Proceedings of the 28th Pan-Hellenic Conference on Progress in Computing and informatics

作者： Ioannis Konstantoulas Iliana Loi Kyriakos Sgarbas Apostolos Gkamas Christos Bouras Department of Electrical and Computer Engineering University of Patras Patras Greece Department of Chemistry University of Ioannina Ioannina Greece Computer Engineering and Informatics Department University of Patras Patras Greece

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An Enhanced Fuzzy Routing Protocol for Energy Optimization in the Underwater Wireless Sensor Networks

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computers, Materials & Continua 2025年第5期83卷 1791-1820页

作者： Mehran Tarif Mohammadhossein Homaei Amir Mosavi Department of Computer Science University of VeronaVerona37134Italy Department of Computer Systems Engineering and Telematics University of ExtremaduraCaceres10003ExtremaduraSpain Institute of the Information Society Ludovika University of Public ServiceBudapest1083Hungary John Von Neumann Faculty of Informatics Obuda UniversityBudapest1034Hungary Department of Information and Computing Systems Abylkas Saginov Karaganda Technical UniversityKaraganda100000Kazakhstan

Underwater Wireless Sensor Networks(UWSNs)are gaining popularity because of their potential uses in oceanography,seismic activity monitoring,environmental preservation,and underwater ***,these networks are faced with challenges such as self-interference,long propagation delays,limited bandwidth,and changing network *** challenges are coped with by designing advanced routing *** this work,we present Under Water Fuzzy-Routing Protocol for Low power and Lossy networks(UWF-RPL),an enhanced fuzzy-based protocol that improves decision-making during path selection and traffic distribution over different network *** method extends RPL with the aid of fuzzy logic to optimize depth,energy,Received Signal Strength Indicator(RSSI)to Expected Transmission Count(ETX)ratio,and *** protocol outperforms other techniques in that it offersmore energy efficiency,better packet delivery,lowdelay,and no queue *** also exhibits better scalability and reliability in dynamic underwater networks,which is of very high importance in maintaining the network operations efficiency and the lifetime of UWSNs *** to other recent methods,it offers improved network convergence time(10%–23%),energy efficiency(15%),packet delivery(17%),and delay(24%).

关键词： Underwater sensor networks(UWSNs) routing energy fuzzy logic multipath load balancing

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Exploring UAV Interfaces: An Eye-Tracking Study on Novice and Experienced Users 24

Exploring UAV Interfaces: An Eye-Tracking Study on Novice an...

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Proceedings of the 28th Pan-Hellenic Conference on Progress in Computing and informatics

作者： Andreas Kousoulos Angelos Fotopoulos Dimosthenis Minas Michalis Xenos Department of Computer Engineering & Informatics / Software Quality and Human-Computer Interaction Laboratory University of Patras Patras Greece University of Patras Patras Greece

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Cyber Risk Identification and Classification-Based Load Forecasting Tool for Pandemic Situations

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IET Cyber-Physical Systems: Theory and Applications 2025年第1期10卷

作者： Shivran, Kuldeep Singh Swire-Thompson, Kyle Saxena, Neetesh Das, Sarasij Department of Electrical Engineering Indian Institute of Science Bangalore India School of Computer Science and Informatics Cardiff University Cardiff United Kingdom

Smart grid operators use load forecasting algorithms to predict energy load for the reliable and economical operation of the electricity grid. COVID-19 pandemic-like situations (PLS) can significantly impact energy load demand due to uncertainties in factors such as regulatory orders, pandemic severity and human behavioural patterns. Additionally, in a smart grid, cyberattacks can manipulate forecasted load data, leading to suboptimal decisions, economic losses and potential blackouts. Forecasting load during these situations is challenging for traditional load forecasting tools, as they struggle to identify cyberattacks amidst uncertain load demand, where cyberattacks may mimic pandemic-like load patterns. Traditional forecasting methods do not incorporate factors related to pandemics and cyberattacks. Recent studies have focused on forecasting by considering factors such as COVID-19 cases, social distancing, weather, and temperature but fail to account for the impact of regulatory orders and pandemic severity. They also lack the ability to differentiate between normal and anomalous forecasts and classify the type of attack in anomalous data. This paper presents a tool for short-term load forecasting, anomaly detection and cyberattack classification for pandemic-like situations (PLS). The proposed short-term load forecasting algorithm uses a weighted moving average and an adjustment factor incorporating regulatory orders and pandemic severity, making it computationally efficient and deterministic. Additionally, the proposed anomaly detection and cyberattack classification algorithm provides robust options for detecting anomalies and classifying various types of cyberattacks. The proposed tool has been evaluated using K-Fold cross-validation to improve generalisability and reduce overfitting. The mean squared error (MSE) was used to measure prediction accuracy and detect discrepancies. It has been analysed and tested on real-load data from the State Load Dispatch Ce

关键词： Mean square error

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