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RSSI-Based 3D Wireless Sensor Node Localization Using Hybrid T Cell Immune and Lotus Optimization

computers, Materials & Continua 2024年第12期81卷 4833-4851页

作者： Weiwei Hu Kiran Sree Pokkuluri Rajesh Arunachalam Bander A.Jabr Yasser A.Ali Preethi Palanisamy School of Information Engineering Technology&MediaUniversity of HenanKaifeng475004China Department of Computer Science and Engineering Shri Vishnu Engineering College forWomenBhimavaram534202Andhra PradheshIndia Department of Electronics and Communication Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical SciencesThandalam602105ChennaiIndia Department of Computer Engineering College of Computer and Information SciencesKing Saud UniversityRiyadh11543Saudi Arabia Department of Computer Science and Engineering Saveetha School of EngineeringSaveetha Institute of Medical and Technical SciencesThandalam602105ChennaiIndia

Wireless Sensor Network(WSNs)consists of a group of nodes that analyze the information from surrounding *** sensor nodes are responsible for accumulating and exchanging ***,node local-ization is the process of identifying the target node’s *** this research work,a Received Signal Strength Indicator(RSSI)-based optimal node localization approach is proposed to solve the complexities in the conventional node localization ***,the RSSI value is identified using the Deep Neural Network(DNN).The RSSI is conceded as the range-based method and it does not require special hardware for the node localization process,also it consumes a very minimal amount of cost for localizing the nodes in 3D *** position of the anchor nodes is fixed for detecting the location of the ***,the optimal position of the target node is identified using Hybrid T cell Immune with Lotus Effect Optimization algorithm(HTCI-LEO).During the node localization process,the average localization error is minimized,which is the objective of the optimal node *** the regular and irregular surfaces,this hybrid algorithm effectively performs the localization *** suggested hybrid algorithm converges very fast in the three-dimensional(3D)*** accuracy of the proposed node localization process is 94.25%.

关键词： Sensor node localization received signal strength indicator 3D wireless sensor network deep neural network average localization error and hybrid T cell immune with lotus effect optimization algorithm

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Automated cybersecurity compliance and threat response using AI, blockchain and smart contracts

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International Journal of Information Technology (Singapore) 2025年第2期17卷 767-781页

作者： Alevizos, Lampis UCLan-School of Engineering and Computer Science Volvo Group Amsterdam Netherlands

To address the challenges of internal security policy compliance and dynamic threat response in organizations, we present a novel framework that integrates artificial intelligence (AI), blockchain, and smart contracts. We propose a system that automates the enforcement of security policies, reducing manual effort and potential human error. Utilizing AI, we can analyse cyber threat intelligence rapidly, identify non-compliances and automatically adjust cyber defence mechanisms. Blockchain technology provides an immutable ledger for transparent logging of compliance actions, while smart contracts ensure uniform application of security measures. The framework’s effectiveness is demonstrated through simulations, showing improvements in compliance enforcement rates and response times compared to traditional methods. Ultimately, our approach provides for a scalable solution for managing complex security policies, reducing costs and enhancing the efficiency while achieving compliance. Finally, we discuss practical implications and propose future research directions to further refine the system and address implementation challenges. © The Author(s) 2024.

关键词： Artificial intelligence Automation Blockchain Compliance Cyber threat intelligence Security Smart contracts

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Blockchain-Assisted Fine-Grained Deduplication and Integrity Auditing for Outsourced Large-Scale Data in Cloud Storage

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IEEE Internet of Things Journal 2025年第12期12卷 21662-21678页

作者： Liu, Bingyun Zhang, Xiaojun Yang, Xingchun Zhang, Yuan Xue, Jingting Zhou, Rang Southwest Petroleum University School of Computer Science and Software Engineering Engineering Research Center for Intelligent Oil and Gas Exploration Chengdu610500 China Sichuan Police College Intelligent Policing Key Laboratory of SichuanProvince Luzhou646000 China University of Electronic Science and Technology of China School of Computer Science and Engineering Chengdu610054 China Chengdu University of Technology School of Computer Science and Cyber Security Chengdu610059 China

Cloud computing has emerged as a promising mode for storaging vast quantities of big data, which is vulnerable to potential security threats, making it urgent to ensure data confidentiality and integrity auditing. In addition, as a large number of duplicate data files exist in cloud storage, data deduplication is significant to improve storage efficiency. In this article, we propose a blockchain-assisted fine-grained deduplication and integrity auditing scheme for outsourced large-scale data in cloud storage, achieving internal deduplication and cross-user external deduplication for ciphertexts and authentication tags. By constructing sparse summation ciphertext tree, the scheme implements Proofs of Ownership protocol through vector commitment, and guarantees the retrieval of distributed deduplication data blocks by designing the reconstruction matrix and bloom filter. The scheme exploits blockchain and smart contracts to ensure transparent integrity auditing without a third-party auditor (TPA), thereby avoiding malicious auditing biases. Security analysis and performance evaluation demonstrate the feasibility of the scheme for deploying in cloud storage systems. © 2014 IEEE.

关键词： Data integrity

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Spatial attention-based hybrid VGG-SVM and VGG-RF frameworks for improved cotton leaf disease detection

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Neural Computing and Applications 2025年第14期37卷 8309-8329页

作者： Pandiyaraju, V. Anusha, B. Senthil Kumar, A.M. Jaspin, K. Venkatraman, Shravan Kannan, A. School of Computer Science and Engineering Vellore Institute of Technology Tamil Nadu Chennai India Department of Computer Science and Engineering Marian Engineering College Trivandram Kerala Trivandrum India Department of Computer Science and Engineering St. Joseph’s Institute of Technology Tamil Nadu Chennai India Department of Information Science and Technology College of Engineering Guindy Anna University Tamil Nadu Chennai India

The agriculture industry's production and food quality have been impacted by plant leaf diseases in recent years. Hence, it is vital to have a system that can automatically identify and diagnose diseases at an initial stage for enhancing the quality of agricultural output and also for stopping the overall plant extinction. Most state-of-the-art methods do not provide appropriate accuracy of identification when the similarity among different diseases is higher and the input leaf images have complex background. In this work, a transfer learning-based automated crop disease recognition system is proposed to handle this problem. The cotton leaf disease detection framework being proposed here includes two key stages: (1) the feature extraction stage, where the convolutional neural network (CNN) model from the visual geometry group (VGG-16) is employed to obtain the deep features from cotton leaf images with complex background. (2) Cotton leaf disease detection stage: Here, the extracted optimal features are input to the machine learning classifiers, namely random forest (RF) and nonlinear support vector machine (SVM), for the initial classification of the diseases. For providing an optimal cotton crop disease detection performance, Kaggle’s four-class cotton disease dataset with complex background is chosen in this work. For the final decision making and analysis, two hybrid models named spatial attention-based hybrid VGG-RF and hybrid VGG-SVM have been proposed in this work for enhancing the decision accuracy. These hybrid models offered an average accuracy of approximately 98.29% and 99.31%, respectively, which is higher than the accuracy provided by the related work. This proved that the proposed hybrid model, namely spatial attention-based VGG-SVM and VGG-RF models, with spatial attention outperformed the state-of-the-art classifiers. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2025.

关键词： Convolutional neural networks

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An Effective Optimization Method for Integrated Scheduling of Multiple Automated Guided Vehicle Problems

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Tsinghua science and Technology 2024年第5期29卷 1355-1367页

作者： Hongyan Sang Zhongkai Li M.Fatih Tasgetiren School of Computer Science Liaocheng UniversityLiaocheng 252000China Industrial Engineering Department Baskent UniversityAnkara 06000Türkiye

Automated Guided Vehicle(AGV)scheduling problem is an emerging research topic in the recent *** paper studies an integrated scheduling problem comprising task assignment and path planning for *** reduce the transportation cost of AGVs,this work also proposes an optimization method consisting of the total running distance,total delay time,and machine loss cost of AGVs.A mathematical model is formulated for the problem at hand,along with an improved Discrete Invasive Weed Optimization algorithm(DIWO).In the proposed DIWO algorithm,an insertion-based local search operator is developed to improve the local search ability of the algorithm.A staggered time departure heuristic is also proposed to reduce the number of AGV collisions in path *** experiments are conducted,and 100 instances from actual factories have proven the effectiveness of the optimization method.

关键词： Automated Guided Vehicle(AGV) integrated scheduling staggered time departure heuristics

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IRS-enabled NOMA communication systems:A network architecture primer with future trends and challenges

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Digital Communications and Networks 2024年第5期10卷 1503-1528页

作者： Haleema Sadia Ahmad Kamal Hassan Ziaul Haq Abbas Ghulam Abbas Muhammad Waqas Zhu Han Faculty of Electrical Engineering and Telecommunications and Networking(TeleCoN)Research Center Ghulam Ishaq Khan Institute of Engineering and Technology(GIKI)Topi 23640Pakistan Faculty of Computer Science and Engineering GIKITopi 23640Pakistan Department of Computer Engineering College of Information TechnologyUniversity of Bahrain32028Bahrain School of Engineering Edith Cowan UniversityPerth WA6027Australia Department of Electrical and Computer Engineering University of HoustonHoustonTX 77004USA Department of Computer Science and Engineering Kyung Hee UniversitySeoul 446-701South Korea

Non-Orthogonal Multiple Access(NOMA)has already proven to be an effective multiple access scheme for5th Generation(5G)wireless *** provides improved performance in terms of system throughput,spectral efficiency,fairness,and energy efficiency(EE).However,in conventional NOMA networks,performance degradation still exists because of the stochastic behavior of wireless *** combat this challenge,the concept of Intelligent Reflecting Surface(IRS)has risen to prominence as a low-cost intelligent solution for Beyond 5G(B5G)*** this paper,a modeling primer based on the integration of these two cutting-edge technologies,i.e.,IRS and NOMA,for B5G wireless networks is *** in-depth comparative analysis of IRS-assisted Power Domain(PD)-NOMA networks is provided through 3-fold ***,a primer is presented on the system architecture of IRS-enabled multiple-configuration PD-NOMA systems,and parallels are drawn with conventional network configurations,i.e.,conventional NOMA,Orthogonal Multiple Access(OMA),and IRS-assisted OMA *** by this,a comparative analysis of these network configurations is showcased in terms of significant performance metrics,namely,individual users'achievable rate,sum rate,ergodic rate,EE,and outage ***,for multi-antenna IRS-enabled NOMA networks,we exploit the active Beamforming(BF)technique by employing a greedy algorithm using a state-of-the-art branch-reduceand-bound(BRB)*** optimality of the BRB algorithm is presented by comparing it with benchmark BF techniques,i.e.,minimum-mean-square-error,zero-forcing-BF,and ***,we present an outlook on future envisioned NOMA networks,aided by IRSs,i.e.,with a variety of potential applications for 6G wireless *** work presents a generic performance assessment toolkit for wireless networks,focusing on IRS-assisted NOMA *** comparative analysis provides a solid foundation for the dev

关键词： Intelligent reflecting surface Non-orthogonal multiple access 6G Beamforming Sum rate Energy efficiency

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Passive Ubiquitous Perception System Oriented to Aerospace-Ground Internet of Things Communication

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Journal of Communications and Information Networks 2024年第3期9卷 277-285页

作者： Hong Hong Wei Gong Qiwei Wang School of Electronic and Optical Engineering Nanjing University of Science and TechnologyNanjing 210094China School of Computer Science and Technology University of Science and Technology of ChinaHefei 230027China

Because the aerospace-ground Internet no longer relies on deploying infrastructure such as base stations,it has the advantage of all-weather full coverage services that traditional terrestrial networks do not ***,the traditional global navigation satellite system does not support communication *** newly developing aerospace network system is still in the construction stage,and there is no applicable solution *** communication technology is an important method to solve the contradiction between the low battery capacity of the Internet of things(IoT)node and the high energy consumption of *** is the development trend of the ***,the current passive technology based on Wi-Fi and other signals cannot achieve arbitrary communication due to the excitation signal acquisition *** solve the above two major problems,this paper proposes a passive system design for aerospace-ground IoT *** system can use the global navigation signal as excitation signal for backscatter *** the global navigation signal has the characteristics of all-weather and full coverage,this design solves the carrier acquisition problem in previous *** addition,this paper also proposes a low-power signal detection technology that can detect navigation signals with high precision on passive *** evaluate system performance through simulation *** experimental results show that the backscatter system based on global navigation satellite signals can realize efficient communication of IoT nodes.

关键词： backscatter passive IoT global navigation satellite system aerospace network

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Retrieval of Interactive Requirements of Data Intensive Applications using Random Forest Classifier

Informatica (Slovenia)

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Informatica (Slovenia) 2023年第9期47卷 35-50页

作者： Raymond, Renita Anouncia, S. Margret School of Computer Science and Engineering Vellore Institute of Technology Vellore India

Classifying requirements in data-intensive systems based on their interactions can assist the requirements engineering process in becoming more systematic and transparent, resulting in higher requirement compliance and software project completion. However, understanding the requirements centred on interactions with the system is particularly tough due to the increased complexity of big data. In most cases, awareness of interaction-based requirements is critical in moving forward with prediction and decision-making. As a result, the classification of interactive requirements plays a critical role in removing the difficulties from unclear requirements. Various approaches to effective requirement classification are being devised. However, due to inadequate requirement management reflecting the fast-changing organizational change, classification accuracy does not achieve its maximum potential. The best approach for reducing misclassification rate and retrieving interactive requirements for data-intensive systems would be to use Word Embedding and Random Forest Classifier retrieval mechanism, as none of the studies to date have emphasized it. It also assessed the impact by comparing the results to metrics derived from the Random Forest classifier's training on word count characteristics. The data set used to experiment with the classification, particularly for interaction-based needs, is unique to our work and has not been covered by any other studies to date. The researchers will benefit from this study as they will better understand the requirement classification process. With an F1 score of 0.91, precision of 0.89, and recall of 0.93, statistical analysis showed that Word Embedding followed by Random Forest Classifier produced a relatively high classification result to differentiate interactive requirements for data-intensive systems. © 2023 Slovene Society Informatika. All rights reserved.

关键词： Classification (of information)

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PEP: An Accurate and Efficient Pupil Detection Framework Based on Pupil Edge Points

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IEEE Sensors Journal 2025年第12期25卷 22385-22396页

作者： Zhang, Wei Liu, Yu Lv, Linfeng Wang, Xiang Li, Ziqiang Liu, Lei Li, Bin Department of Electronic Engineering and Information Science University of Science and Technology of China Hefei230026 China Carnegie Mellon University Department of Electrical and Computer Engineering Pittsburgh United States Nanjing University of Information Science and Technology School of Computer Science Nanjing China

With the rapid development of headmounted devices, eye tracking as an emerging human-computer interaction technology, has gained increasing importance. However, pupil detection, the core algorithm in eye tracking, suffered low accuracy in complex scenarios and long runtime, which limits the frame rate. This paper proposes PEP (neural network based on Pupil Edge Points), an efficient pupil detection framework that not only achieves high detection accuracy but also significantly reduces computational costs, thereby addressing the performance bottlenecks of existing methods in challenging environments. The core innovation of the PEP framework lies in its focus on detecting edge-representative points (the points at the edge of the pupil) along the pupil edge, a method more precise than traditional full-region segmentation and better suited for accurate pupil ellipse fitting. Additionally, PEP enhances the accuracy of pupil edge point predictions through two key features: (1) a loss function that includes natural ellipse prior regularization term and (2) a data augmentation strategy that randomly masks edges. We evaluated PEP against state-of-the-art (SOTA) model-based and learning-based methods across multiple datasets. The evaluation results show that PEP achieved superior overall performance regarding pupil detection rate and accuracy. Moreover, PEP’s parameter number and computational cost are 80% lower than other learning-based methods, making it highly efficient. The proposed framework is practical, scalable, and demonstrates exceptional potential for pupil detection and gaze-tracking applications. © 2001-2012 IEEE.

关键词： Virtual reality

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A Server Placement Algorithm for Reducing Risk and Improving Power Utilization in Data Centers

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Tsinghua science and Technology 2024年第1期29卷 158-173页

作者： Rui Chen Huikang Huang Xiaoxuan Luo Weiwei Lin School of Computer Science and Engineering South China University of TechnologyGuangzhou 510006China Peng Cheng Laboratory Shenzhen 518066China

As the power demand in data centers is increasing,the power capacity of the power supply system has become an essential resource to be *** many data centers use power oversubscription to make full use of the power capacity,there are unavoidable power supply risks associated with ***,how to improve the data center power capacity utilization while ensuring power supply security has become an important *** solve this problem,we first define it and propose a risk evaluation metric called Weighted Power Supply Risk(WPSRisk).Then,a method,named Hybrid Genetic Algorithm with Ant Colony System(HGAACS),is proposed to improve power capacity utilization and reduce power supply risks by optimizing the server placement in the power supply *** uses historical power data of each server to find a better placement solution by population *** possesses not only the remarkable local search ability of Ant Colony System(ACS),but also enhances the global search capability by incorporating genetic operators from Genetic Algorithm(GA).To verify the performance of HGAACS,we experimentally compare it with five other placement *** experimental results show that HGAACS can perform better than other algorithms in both improving power utilization and reducing the riskof powersupply system.

关键词： server placement power utilization power supply risk swarm intelligence algorithm

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