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International Symposium on INFOTEH-JAHORINA (INFOTEH)

作者： Ehlimana Krupalija Emir Cogo Šeila Bećirović Irfan Prazina Damir Pozderac Ingmar Bešić Department of Computer Science and Informatics Faculty of Electrical Engineering University of Sarajevo Sarajevo Bosnia and Herzegovina

Many different methods are used for generating blackbox test case suites. Test case minimization is used for reducing the feasible test case suite size in order to minimize the cost of testing while ensuring maximum fault detection. This paper presents an optimization of the existing test case minimization algorithm based on forward-propagation of the cause-effect graphing method. The algorithm performs test case prioritization based on test case strength, a newly introduced test case selection metric. The optimized version of the minimization algorithm was evaluated by using thirteen different examples from the available literature. In cases where the existing algorithm did not generate the minimum test case subsets, significant improvements of test effect coverage metric values were achieved. Test effect coverage metric values were not improved only in cases where maximum optimization was already achieved by using the existing algorithm.

关键词： Measurement Fault detection Software algorithms Closed box Software quality Minimization Real-time systems

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Computation Pre-Offloading for MEC-Enabled Vehicular Networks via Trajectory Prediction 10

Computation Pre-Offloading for MEC-Enabled Vehicular Network...

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10th IEEE Smart World Congress, SWC 2024

作者： Zhang, Ting Yang, Bo Yu, Zhiwen Cao, Xuelin Alexandropoulos, George C. Zhang, Yan Yuen, Chau Northwestern Polytechnical University School of Software Shaanxi Xi'an710129 China Northwestern Polytechnical University School of Computer Science Shaanxi Xi'an710129 China Xidian University School of Cyber Engineering Shaanxi Xi'an710071 China National and Kapodistrian University of Athens Department of Informatics and Telecommunications Athens15784 Greece University of Oslo Department of Informatics Oslo0316 Norway Nanyang Technological University School of Electrical and Electronics Engineering Singapore

ISBN: (纸本)9798331520861

Task offloading is of paramount importance to efficiently orchestrate vehicular wireless networks, necessitating the availability of information regarding the current network status and computational resources. However, due to the mobility of the vehicles and the limited computational resources for performing task offloading in near-real-time, such schemes may require high latency, thus, become even infeasible. To address this issue, in this paper, we present a Trajectory Prediction-based Pre-offloading Decision (TPPD) algorithm for analyzing the historical trajectories of vehicles to predict their future coordinates, thereby allowing for computational resource allocation in advance. We first utilize the Long Short-Term Memory (LSTM) network model to predict each vehicle's movement trajectory. Then, based on the task requirements and the predicted trajectories, we devise a dynamic resource allocation algorithm using a Double Deep Q-Network (DDQN) that enables the edge server to minimize task processing delay, while ensuring effective utilization of the available computational resources. Our simulation results verify the effectiveness of the proposed approach, showcasing that, as compared with traditional real-time task offloading strategies, the proposed TPPD algorithm significantly reduces task processing delay while improving resource utilization. © 2024 IEEE.

关键词： Vehicular ad hoc networks

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Empowering Software engineering Students: The Role of Gamification in Promoting Learning Independence 7

Empowering Software Engineering Students: The Role of Gamifi...

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7th International Conference on Vocational Education and electrical engineering, ICVEE 2024

作者： Hidayat, Wahyu Nur Hamdan, Achmad Ichwanto, Muhammad Aris Muslihati Cakir, Gulsun Kurubacak Sari, Rahajeng Kartika Afni, Nur Hisyam, Mochammad Raffi Fadhil Universitas Negeri Malang Faculty of Engineering Department of Electrical Engineering and Informatics Malang Indonesia Universitas Negeri Malang Faculty of Vocational Department of Electronic Systems Engineering Technology Malang Indonesia Universitas Negeri Malang Faculty of Engineering Department of Civil Engineering and Planning Malang Indonesia Universitas Negeri Malang Faculty of Education Science Department of Guidance and Counseling Malang Indonesia Ankara Haci Bayram Veli University College of Communication Department of Journalism Ankara Turkey Smk Negeri 10 Malang Department of Computer Network and Telecommunication Engineering Malang Indonesia

ISBN: (纸本)9798331505103

The role of learning media greatly supports the learning process, increasing motivation and interest in the process. Learning media can also be a place to improve competence optimally through bootcamp training menus and the like with more specific training objectives. The main objective of this study is to develop a gamification-based website to enhance students' preparedness for their Final Competency Test by tackling challenges in comprehending programming absent practical experience. The learning method implemented in this website is case-based learning that integrates dynamic coding activities. The research method uses the Plomp approach with 3 main stages, namely preliminary research, prototyping, and assessment stage. The trial of the gamification website began with media and content validation followed by small group testing and large group testing. Validation by media and material experts led to the execution of small group trials (95.7%) and large group trials (91.7%), producing exceptionally positive outcomes. The results of the small group test with 12 respondents produced a very suitable value with a score of 95.7 and the large group test with 27 respondents produced a score of 9 1. 7 % with very suitable criteria. This indicates that the web-based platform is highly viable for assisting vocational students in acquiring software development skills, enhancing their preparedness for practical IT positions such as software developers and system analysts. Subsequent study involved the incorporation of gamification, such as computer-supported collaborative learning. © 2024 IEEE.

关键词： Software testing

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A Secure Federated Learning Framework using Blockchain and Differential Privacy 9

A Secure Federated Learning Framework using Blockchain and D...

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9th IEEE International Conference on Cyber Security and Cloud Computing and 8th IEEE International Conference on Edge Computing and Scalable Cloud, CSCloud-EdgeCom 2022

作者： Firdaus, Muhammad Larasati, Harashta Tatimma Rhee, Kyung-Hyune Pukyong National University Department of Artificial Intelligence Convergence Korea Republic of Pusan National University Department of Computer Engineering Korea Republic of Institut Teknologi Bandung School of Electrical Engineering and Informatics Indonesia

ISBN: (数字)9781665480666

ISBN: (纸本)9781665480666

Federated learning (FL) has considerably emerged as a promising solution to enhance user privacy and data security by enabling collaboratively multi-party model learning without exchanging confidential data. Nevertheless, most existing FL approaches still rely on a central server to obtain a global model by collecting all uploaded models from participants, which may lead to several threats from malicious participants and even expose participant privacy. Therefore, to tackle these problems, we proposed a secure FL framework by empowering blockchain to replace the centralized aggregator sever and utilize Differential Privacy (DP) to address various attacks, e.g., membership inference attacks, during the collaborative FL model training process. The proposed framework has been implemented through two scenarios, i.e., blockchain-based FL to form a decentralized system and DP-based FL to construct the randomized privacy protection using the IBM DP Library. © 2022 IEEE.

关键词： Blockchain

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Topology Design for Robust IoT Data Gathering via Bayesian Networks

Topology Design for Robust IoT Data Gathering via Bayesian N...

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IEEE Conference on Global Communications (GLOBECOM)

作者： Haiyan Wei Zhenlong Xiao Xinghao Ding Xianbin Wang School of Informatics Xiamen University China Department of Electrical and Computer Engineering Western University Canada

Internet of Things (IoT) systems have become the critical platform to enable a wide variety of smart applications. During IoT data gathering over wireless network, data may be missing due to the constraints of sensors as well as the reliability of communications. From a graph signal processing perspective, recovery of missing data may be strongly affected by the IoT system topology, which can be characterized by a directed adjacency matrix. To guarantee a robust data gathering, we propose a novel method in this paper to design the optimal topology for IoT networks via Bayesian networks, where the designed directed adjacency matrix is with orthogonal graph frequency components. Moreover, the gathering of IoT data becomes sparser in the graph frequency domain using the designed adjacency matrix and may hence improve the recovery performance of missing data. Experimental results show that our proposed methods outperform several existing algorithms.

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CEGSet: Collection of standardized cause-effect graph specifications

CEGSet: Collection of standardized cause-effect graph specif...

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Mediterranean Conference on Embedded Computing (MECO)

Cause-effect graphs are a commonly used black-box testing method, and many different algorithms for converting system requirements to cause-effect graph specifications and deriving test case suites have been proposed. However, in order to test the efficiency of black-box testing algorithms on a variety of cause-effect graphs containing different numbers of nodes, logical relations and dependency constraints, a dataset containing a collection of cause-effect graph specifications created by authors of existing papers is necessary. This paper presents CEGSet, the first collection of existing cause-effect graph specifications. The dataset contains a total of 65 graphs collected from the available relevant literature. The specifications were created by using the ETF-RI-CEG graphical software tool and can be used by future authors of papers focusing on the cause-effect graphing technique. The collected graphs can be re-imported in the tool and used for the desired purposes. The collection also includes the specification of system requirements in the form of natural language from which the cause-effect graphs were derived where possible. This will encourage future work on automatizing the process of converting system requirements to cause-effect graph specifications.

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Curious Administrator's Misbehaviors in Message Layer Security (MLS)

Curious Administrator's Misbehaviors in Message Layer Securi...

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2025 International Conference on Computing, Networking and Communications, ICNC 2025

作者： Choi, Hyoung-Kee Kwon, Songhui Sungkyunkwan University College of Computing and Informatics Suwon Korea Republic of Sungkyunkwan University Department of Electrical and Computer Engineering Suwon Korea Republic of

ISBN: (纸本)9798331520960

A key factor of the MLS group protocol is that it provides asynchronously efficient group key establishment with forward secrecy and post-compromise security for many groups in a standardized way. End-to-end encryption (E2EE) is essential to fulfilling the correctness of security in a messenger application. The correctness heavily depends on the trustworthiness of a middleman server in the center where a curious administrator may break E2EE. If this happened the administrator as a nonmember could read messages and impersonate a member by intervening with group-key management. This paper presents an in-depth explanation of the MLS protocol and demonstrates a proof-of-concept of curious administrator's misbehaviors by analyzing the protocol. Our research outputs suggest that unconditionally trustworthy relationships on the central server in designing network protocols for security needs to prepare for any incidents caused by misbehaving administrator of the central server. © 2025 IEEE.

关键词： End-to-End Encryption Message Layer Security Secure Messaging Service

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Evolving Multi-Branch Attention Convolutional Neural Networks for Online RIS Configuration

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IEEE Transactions on Cognitive Communications and Networking 2025年

作者： Stamatelis, George Stylianopoulos, Kyriakos Alexandropoulos, George C. National and Kapodistrian University of Athens Department of Informatics and Telecommunications Panepistimiopolis Ilissia Athens15784 Greece University of Illinois Chicago Department of Electrical and Computer Engineering IL60601 United States

In this paper, we consider the problem of jointly controlling the configuration of a Reconfigurable Intelligent Surface (RIS) with unit elements of discrete responses and a codebook-based transmit precoder in RIS-empowered Multiple-Input Single-Output (MISO) communication systems. The adjustable elements of the RIS and the precoding vector need to be jointly modified in real time to account for rapid changes in the wireless channels, making the application of complicated discrete optimization algorithms impractical. We present a novel Multi-Branch Attention Convolutional Neural Network (MBACNN) architecture for this design objective which is optimized using NeuroEvolution (NE), leveraging its capability to effectively tackle the non-differentiable problem arising from the discrete phase states of the RIS elements. The channel matrices of all involved links are first passed to separate self-attention layers to obtain initial embeddings, which are then concatenated and passed to a convolutional network for spatial feature extraction, before being fed to a per-element multi-layered perceptron for the final RIS phase configuration calculation. Our MBACNN architecture is then extended to multi-RIS-empowered MISO communication systems, and a novel NE-based optimization approach for the online distributed configuration of multiple RISs is presented. The superiority of the proposed single-RIS approach over both learning-based and classical discrete optimization benchmarks is showcased via extensive numerical evaluations over both stochastic and geometrical channel models. It is also demonstrated that the proposed distributed multi-RIS approach outperforms both distributed controllers with feedforward neural networks and fully centralized ones. © 2015 IEEE.

关键词： Convolutional neural networks

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NDAS: Noise-Decomposed Abnormal Segmentation for Robust Medical Image Retrieval

NDAS: Noise-Decomposed Abnormal Segmentation for Robust Medi...

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International Conference on Ubiquitous Information Management and Communication (IMCOM)

作者： Ju-Chan Kim Pham Van Nguyen Duc-Tai Le Hyunseung Choo College of Computing and Informatics Sungkyunkwan University Suwon South Korea Department of Electrical and Computer Engineering Sungkyunkwan University Suwon South Korea

ISBN: (数字)9798331507817

ISBN: (纸本)9798331507824

This paper presents NDAS (Noise-Decomposed Ab-normal Segmentation), an innovative framework for robust med-ical image retrieval and segmentation. By explicitly decomposing noise and abnormal features, NDAS enhances retrieval accuracy and segmentation precision. Experimental results on the BraTS 2019 dataset validate NDAS's superiority over CBMIR and SBMIR methods, achieving the highest Top-5 accuracy and Dice coefficient. This demonstrates its effectiveness in handling noise, isolating pathological regions, and retrieving diagnostically relevant medical images. NDAS offers a significant advancement in medical imaging analysis, emphasizing its potential for clinical applications requiring precision and reliability.

关键词： Image segmentation Pathology Accuracy Noise Image retrieval Information management Reliability Medical diagnostic imaging

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On the Performance of RIS-aided OFDM-Based LEO Satellite Networks with Doppler Effects 24

On the Performance of RIS-aided OFDM-Based LEO Satellite Net...

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24th IEEE International Workshop on Signal Processing Advances in Wireless Communications, SPAWC 2023

作者： Toka, Mesut Kaushik, Aryan Armada, Ana Garcia Shin, Wonjae Ajou University Department of Electrical and Computer Engineering Korea Republic of University of Sussex School of Engineering and Informatics Brigthon BN1 9RH United Kingdom Universidad Carlos Iii de Madrid Department of Signal Theory and Communications Leganés28911 Spain

ISBN: (纸本)9781665496261

In this paper, we analyze the outage behavior of a reconfigurable intelligent surface (RIS)-aided low earth orbit (LEO) satellite network based on orthogonal frequency division multiplexing (OFDM). In the satellite network, a RIS node with multiple reflecting elements is deployed between the satellite and ground user since there are strong blockages in the line-of-sight link. Due to the very high velocity of the LEO satellite, the satellite-RIS link suffers from a severe Doppler shift. We propose deploying the RIS node between the satellite and ground user to overcome the performance degradation caused by the Doppler shift in the satellite link. To evaluate the system performance, we obtain an approximated closed-form outage probability (OP) expression corresponding to any sub-carrier. Also, an asymptotic expression for the obtained OP is provided to present further insights. The theoretical results validated by the Monte Carlo simulations demonstrate that the effects of the Doppler shift can be significantly decreased as the number of RIS elements and sub-carrier spacing are increased. © 2023 IEEE.

关键词： Orthogonal frequency division multiplexing

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