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Efficient resource allocation for D2D-enabled social IoT networks:A tripartite and time-scale optimization approach

Intelligent and Converged Networks 2024年第4期5卷 380-401页

作者： Saurabh Chandra Rajeev Arya Maheshwari Prasad Singh Department of Electronics&Communication Engineering National Institute of Technology PatnaPatna 800005India Department of Computer Science and Engineering National Institute of Technology PatnaPatna 800005India

In the densification of Device-to-Device(D2D)-enabled Social Internet of Things(SIoT)networks,improper allocation of resources can lead to high interference,increased signaling overhead,latency,and disruption of Channel State information(CSI).In this paper,we formulate the problem of sum throughput maximization as a Mixed Integer Non-Linear Programming(MINLP)*** problem is solved in two stages:a tripartite graph-based resource allocation stage and a time-scale optimization *** proposed approach prioritizes maintaining Quality of Service(QoS)and resource allocation to minimize power consumption while maximizing sum *** results demonstrate the superiority of the proposed algorithm over standard benchmark *** of the proposed algorithm using performance parameters such as sum throughput shows improvements ranging from 17%to 93%.Additionally,the average time to deliver resources to CSI users is minimized by 60.83%through optimal power *** approach ensures QoS requirements are met,reduces system signaling overhead,and significantly increases D2D sum throughput compared to the state-of-the-art *** proposed methodology may be well-suited to address the challenges SIoT applications,such as home automation and higher education systems.

关键词： Device-to-Device(D2D)communication Social Internet of Things(SIoT) resource allocation Quality of Service(QoS) tripartite graph time scale

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Hybrid Deep Learning Approach for Automating App Review Classification:Advancing Usability Metrics Classification with an Aspect-Based Sentiment Analysis Framework

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computers, Materials & Continua 2025年第1期82卷 949-976页

作者： Nahed Alsaleh Reem Alnanih Nahed Alowidi Department of Computer Science Faculty of Computing and Information TechnologyKing Abdulaziz UniversityJeddah21589Saudi Arabia Department of Computer Science College of Computer Science and EngineeringUniversity of HailHail81451Saudi Arabia

App reviews are crucial in influencing user decisions and providing essential feedback for developers to improve their *** the analysis of these reviews is vital for efficient review *** traditional machine learning(ML)models rely on basic word-based feature extraction,deep learning(DL)methods,enhanced with advanced word embeddings,have shown superior *** research introduces a novel aspectbased sentiment analysis(ABSA)framework to classify app reviews based on key non-functional requirements,focusing on usability factors:effectiveness,efficiency,and *** propose a hybrid DL model,combining BERT(Bidirectional Encoder Representations from Transformers)with BiLSTM(Bidirectional Long Short-Term Memory)and CNN(Convolutional Neural Networks)layers,to enhance classification *** analysis against state-of-the-art models demonstrates that our BERT-BiLSTM-CNN model achieves exceptional performance,with precision,recall,F1-score,and accuracy of 96%,87%,91%,and 94%,*** contributions of this work include a refined ABSA-based relabeling framework,the development of a highperformance classifier,and the comprehensive relabeling of the Instagram App Reviews *** advancements provide valuable insights for software developers to enhance usability and drive user-centric application development.

关键词： Requirements engineering(RE) app review analysis usabilitymetrics hybrid deep learning BERT-BiLSTM-CNN

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An Integrated Framework with Enhanced Primitives for Post-Quantum Cryptography: HEDT and ECSIDH for Cloud Data Security and Key Exchange

Informatica (Slovenia)

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Informatica (Slovenia) 2025年第11期49卷 165-176页

作者： Ilias, Shaik Mohammad Sharmila, V. Ceronmani Durga, V. Sathya Dept. of Computer Science and Engineering Hindustan Institute of Technology and Science Chennai India Department of Information Technology Hindustan Institute of Technology and Science Chennai India Department of Computer Science&Engineering Hindustan Institute of Technology and Science Chennai India

If adversaries were to obtain quantum computers in the future, their massive computing power would likely break existing security schemes. Since security is a continuous process, more substantial security schemes must be developed. Current PQC schemes primarily focus on data security or key exchange, and further improvement towards enhanced PQC primitives is required. Our proposal in this research is an innovative paradigm for PQC-focused cloud data security. The proposed HEDT approach achieves encryption and decryption with significantly lower latency (20% improvement) and higher reliability than AES, DES, and RSA, as demonstrated through experimental results. Furthermore, ECSIDH, a hybrid key exchange mechanism combining SIDH and ECDH, improves security strength by 50% while maintaining computational costs within 1.13x of SIDH. Compared to individual key exchange schemes like SIDH, ECSIDH offers superior security as a PQC candidate. These results confirm the robustness and efficiency of the proposed framework in ensuring secure data outsourcing and key exchange in cloud environments. © 2025 Slovene Society Informatika. All rights reserved.

关键词： Quantum computers

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Acoustic modelling using deep learning for Quran recitation assistance

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International Journal of Speech technology 2023年第1期26卷 113-121页

作者： Ghori, Ammar Farid Waheed, Aisha Waqas, Maria Mehmood, Aqsa Ali, Syed Abbas Department of Computer and Information Systems Engineering NED University of Engineering and Technology Karachi Pakistan

Recent advancements in computer science and engineering have significantly boosted interest in and success rate of speech recognition systems. Sophisticated speech recognition systems are being developed for a variety of languages having wide-spread applications. Arabic being one of the most widely used languages in the world, augmented by religious importance, is a potential candidate in this domain, however rich vocabulary and multiple dialects open up new challenges for development of Arabic speech recognition processes. This paper focuses on development of an Arabic isolated speech recognition system for the vocabulary of Holy Quran using Mel frequency cepstral coefficients and deep neural networks. The proposed system is capable of identifying individual words from a recited verse with reasonable accuracy. It targets the 362 unique words of the first and the last 19 chapters of the Holy Quran and uses 14 hours of audio data to demonstrate the working prototype of the system. A user-friendly, web-based application has also been developed for transcription of recitations. The software is specified to make an effort in spreading the right way of recitation of the Holy Quran. The presented architecture can be extended to a complete automatic speech recognition system to help people practice recitations, mapping speech to transcription and then matching the transcribed utterance with standard templates of correct recitation to identify reciter’s short comings. © 2022, The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.

关键词： Deep neural networks

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Improving Prediction of Chronic Kidney Disease Using KNN Imputed SMOTE Features and TrioNet Model

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computer Modeling in engineering & Sciences 2024年第6期139卷 3513-3534页

作者： Nazik Alturki Abdulaziz Altamimi Muhammad Umer Oumaima Saidani Amal Alshardan Shtwai Alsubai Marwan Omar Imran Ashraf Department of Information Systems College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityP.O.Box 84428Riyadh11671Saudi Arabia Department College of Computer Science and Engineering University of Hafr Al-BatinHafarAl-Batin39524Saudi Arabia Department of Computer Science&Information Technology The Islamia University of BahawalpurP.O.Box 63100BahawalpurPakistan Department of Computer Science College of Computer Engineering and SciencesPrince Sattam bin Abdulaziz UniversityP.O.Box 151Al-Kharj11942Saudi Arabia Information Technology and Management Illinois Institute of TechnologyChicagoIL 60616-3793USA Information and Communication Engineering Yeungnam UniversityGyeongsan38541Korea

Chronic kidney disease(CKD)is a major health concern today,requiring early and accurate *** learning has emerged as a powerful tool for disease detection,and medical professionals are increasingly using ML classifier algorithms to identify CKD *** study explores the application of advanced machine learning techniques on a CKD dataset obtained from the University of California,UC Irvine Machine Learning *** research introduces TrioNet,an ensemble model combining extreme gradient boosting,random forest,and extra tree classifier,which excels in providing highly accurate predictions for ***,K nearest neighbor(KNN)imputer is utilized to deal withmissing values while synthetic minority oversampling(SMOTE)is used for class-imbalance *** ascertain the efficacy of the proposed model,a comprehensive comparative analysis is conducted with various machine learning *** proposed TrioNet using KNN imputer and SMOTE outperformed other models with 98.97%accuracy for *** in-depth analysis demonstrates the model’s capabilities and underscores its potential as a valuable tool in the diagnosis of CKD.

关键词： Precisionmedicine chronic kidney disease detection SMOTE missing values healthcare KNNimputer ensemble learning

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Securing Next-Generation Quantum IoT Applications using Quantum Key Distribution

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IEEE Internet of Things Magazine 2025年第1期8卷 50-56页

作者： Bera, Basudeb Das, Ashok Kumar Sikdar, Biplab The Department of Electrical and Computer Engineering National University of Singapore Singapore The International Institute of Information Technology Hyderabad India

The next generation of Quantum Internet of Things (QIoT) has the potential to revolutionize various sectors, including smart homes, healthcare, and smart cities, by enabling more sophisticated and interconnected systems. These applications incorporate advanced features, such as autonomous decision-making based on Quantum Artificial Intelligence and Machine Learning (QAI/ML) and context-aware functionality. The security of the data in these applications relies on traditional cryptographic techniques, which, however, face a growing threat due to the significant advancements in quantum computing, especially with the Shor’s algorithm. This algorithm poses a substantial risk of breaking conventional cryptographic methods within a feasible timeframe. To address these emerging security challenges in the quantum realm, we propose a Quantum Key Distribution (QKD) based on the BB84 protocol. This approach aims to provide robust authentication using certificates through a classical channel and secure quantum key exchange via a quantum channel in a public environment. The proposed QKD scheme is implemented using a client-server model in Python and Qiskit, demonstrating its practicality in real-world applications. The obtained results showcase the successful establishment of a secure session key between IoT smart (sensor) devices and gateway nodes, effectively mitigating potential threats such as eavesdropping. © 2018 IEEE.

关键词： Smart homes

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DNA Computing with Water Strider Based Vector Quantization for Data Storage Systems

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computers, Materials & Continua 2023年第3期74卷 6429-6444页

作者： A.Arokiaraj Jovith S.Rama Sree Gudikandhula Narasimha Rao K.Vijaya Kumar Woong Cho Gyanendra Prasad Joshi Sung Won Kim Department of Networking and Communications College of Engineering and TechnologySRM Institute of Science and TechnologyKattankulathur603203India Department of Computer Science Engineering Aditya Engineering CollegeSurampalemAndhra Pradesh533437India Department of Computer Science and Engineering Vignan’s Institute of Information TechnologyVisakhapatnam530049India Department of Computer Science and Engineering Vignan’s Institute of Engineering for WomenVisakhapatnam530049India Department of Software Convergence Daegu Catholic UniversityGyeongsan38430Korea Department of Computer Science and Engineering Sejong UniversitySeoul05006Korea Department of Information and Communication Engineering Yeungnam UniversityGyeongsan-siGyeongbuk-do38541Korea

The exponential growth of data necessitates an effective data storage scheme,which helps to effectively manage the large quantity of *** accomplish this,Deoxyribonucleic Acid(DNA)digital data storage process can be employed,which encodes and decodes binary data to and from synthesized strands of *** quantization(VQ)is a commonly employed scheme for image compression and the optimal codebook generation is an effective process to reach maximum compression *** article introduces a newDNAComputingwithWater StriderAlgorithm based Vector Quantization(DNAC-WSAVQ)technique for Data Storage *** proposed DNAC-WSAVQ technique enables encoding data using DNA computing and then compresses it for effective data ***,the DNAC-WSAVQ model initially performsDNA encoding on the input images to generate a binary encoded *** addition,aWater Strider algorithm with Linde-Buzo-Gray(WSA-LBG)model is applied for the compression process and thereby storage area can be considerably *** order to generate optimal codebook for LBG,the WSA is applied to *** performance validation of the DNAC-WSAVQ model is carried out and the results are inspected under several *** comparative study highlighted the improved outcomes of the DNAC-WSAVQ model over the existing methods.

关键词： DNA computing data storage image compression vector quantization ws algorithm space saving

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Securing Autonomous UAV Cluster With Blockchain-Based Threshold Key Management System Utilizing Crypto-Asset and Multisignature

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IEEE Transactions on Mobile Computing 2025年第7期24卷 5765-5778页

作者： Kharjana, Mebanjop Sahana, Subhas Chandra Saha, Goutam North-Eastern Hill University Department of Information Technology Shillong793022 India National Institute of Technology Department of Computer Science and Engineering Durgapur713209 India

Unmanned aerial vehicles deployed in remote locations rely on self-governed key management for their protection. However, conventional key management depends on a centralized ground-based station or single vehicle. Such a system is vulnerable to compromised certificate authority problems and single-points-of-failure. This paper proposed to resolve these vulnerabilities using a blockchain-based threshold key management system. The proposed system utilized blockchain’s concepts of crypto-asset and multisignature. Keys are defined as crypto-assets to improve their management in the blockchain network. Multisignature facilitates collaboration during key management based on a threshold value. The threshold value is also configurable to meet systems’ security and performance requirements. The proposed system secured the process of re-enforcement, sub-clustering, re-merging, and inter-cluster migration. Security analysis revealed that the proposed system complied with most key management security guidelines. The custom signature module used to authenticate intra-cluster communication was also verified as safe. Threats to the cluster were identified, assessed for risk, and mitigated accordingly. Performance analysis found that both AODV and DSDV routing protocols offer consistent performance but DSDV prevailed during the worst-case network scenario. The paper finally identified research gaps, including the requirement for an optimized mechanism for collecting consent signatures. © 2002-2012 IEEE.

关键词： Blockchains Autonomous Aerial Vehicles Security Authentication Drones Public Key Mobile Computing Smart Contracts Collaboration Global Positioning System Autonomous UAV Cluster Threshold Key Management System Blockchain Crypto Asset Multisignature Unmanned Aerial Vehicles Autonomous Unmanned Aerial Vehicles Key Management System Unmanned Aerial Vehicles Cluster Worst Case Scenario Performance Requirements Security Analysis Security Requirements Certificate Authority Energy Consumption Application Programming Interface Secret Key Directed Acyclic Graph Public Key Denial Of Service Elliptic Curve Best Case Scenario Secret Sharing Smart Contracts Public Key Infrastructure Key Operations Unmanned Aerial Vehicles Networks Distributed Ledger technology Signature Scheme Digital Signature Blockchain Platform Random Oracle Model Bitcoin

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A SLOTTED PENTAGON SHAPE QUAD-BAND TWO-ELEMENT MILLIMETER WAVE MULTIPLE-IN, MULTIPLE-OUT ANTENNA USING THEORY OF CHARACTERISTIC MODES

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Telecommunications and Radio engineering (English translation of Elektrosvyaz and Radiotekhnika) 2024年第7期83卷 45-57页

作者： Shariff, Parveez B.G. Pathan, Sameena Mane, Pallavi R. Ali, Tanweer Department of Electronics and Communication Engineering Manipal Institute of Technology Manipal Academy of Higher Education Manipal576104 India Department of Information and Communication Technology Manipal Institute of Technology Manipal Academy of Higher Education Manipal576104 India

This article proposes the millimeter wave two-element multiple-in, multiple-out (MIMO) for wireless applications. The designed antenna is closely packed with a dimension of 0.42 λ0 × 1.03 λ0. The antenna resonates at quad band with good gain and impedance matching. The single-element structure is a pentagon shape with two slits at the edges. Single-element structure performance is studied through characteristic mode analysis. The MIMO antenna decoupling structure has been effective, resulting in an isolation |S21| of 30 dB. The antenna has broadside radiation. The MIMO antenna also satisfies the diversity performance of envelope correlation coefficient, diversity gain, channel capacity loss, total active reflection coefficient, and mean effective gain. © 2024 by Begell House, Inc.

关键词： Millimeter waves

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Video forgery localization using inter-frame denoising and intra-frame segmentation

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Multimedia Tools and Applications 2025年 1-17页

作者： Banerjee, Debanik Chittaragi, Nagaratna B. Koolagudi, Shashidhar G. Department of Computer Science and Engineering National Institute of Technology Karnataka Karnataka Surathkal575025 India Department of Information Science and Engineering Siddaganaga Institute of Technology Karnataka Tumkur572103 India

Video forgery detection has been necessary with recent spurt in fake videos like Deepfakes and doctored videos from multiple video capturing devices. In this paper, we provide a novel technique of detecting fake videos by creating an ensemble network, based on statistical and deep learning methods to detect interframe forgery and intraframe forgery in forged videos separately. In this paper, Noise signature extraction of a particular image capturing sensor and an Autoencoder-based Convolutional Neural Network model (CNN) are used to localize the forged regions. We have trained the model to localize Deepfake video forgeries as well as copy-paste forgeries with effective results in the test data. The proposed fake video detector can be applied at the back-end of on-line video aggregating services and check their authenticity to verify the genuineness of videos. The results achieved have shown better performances in detecting fake videos compared to existing methods. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Convolutional neural networks

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