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Discrete GWO Optimized Data Aggregation for Reducing Transmission Rate in IoT

computer Systems Science & engineering 2023年第3期44卷 1869-1880页

作者： S.Siamala Devi K.Venkatachalam Yunyoung Nam Mohamed Abouhawwash Department of Computer Science and Engineering Sri Krishna College of TechnologyCoimbatore641042India Department of Applied Cybernetics Faculty of ScienceUniversity of Hradec KrálovéHradec Králové50003Czech Republic Department of Computer Science and Engineering Soonchunhyang UniversityAsan31538Korea Department of Mathematics Faculty of ScienceMansoura UniversityMansoura35516Egypt Department of Computational Mathematics Scienceand Engineering(CMSE)Michigan State UniversityEast LansingMI48824USA

The conventional hospital environment is transformed into digital transformation that focuses on patient centric remote approach through advanced *** diagnosis of many diseases will improve the patient *** cost of health care systems is reduced due to the use of advanced technologies such as Internet of Things(IoT),Wireless Sensor Networks(WSN),Embedded systems,Deep learning approaches and Optimization and aggregation *** data generated through these technologies will demand the bandwidth,data rate,latency of the *** this proposed work,efficient discrete grey wolf optimization(DGWO)based data aggregation scheme using Elliptic curve Elgamal with Message Authentication code(ECEMAC)has been used to aggregate the parameters generated from the wearable sensor devices of the *** nodes that are far away from edge node will forward the data to its neighbor cluster head using *** scheme will reduce the number of transmissions over the *** aggregated data are preprocessed at edge node to remove the noise for better *** node will reduce the overhead of cloud *** aggregated data are forward to cloud server for central storage and *** proposed smart diagnosis will reduce the transmission cost through aggrega-tion scheme which will reduce the energy of the *** cost for proposed system for 300 nodes is 0.34μ*** energy cost of existing approaches such as secure privacy preserving data aggregation scheme(SPPDA),concealed data aggregation scheme for multiple application(CDAMA)and secure aggregation scheme(ASAS)are 1.3μJ,0.81μJ and 0.51μJ *** optimization approaches and encryption method will ensure the data privacy.

关键词： Discrete grey wolf optimization data aggregation cloud computing IoT WSN smart healthcare elliptic curve elgamal energy optimization

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mLBOA:A Modified Butterfly Optimization Algorithm with Lagrange Interpolation for Global Optimization

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Journal of Bionic engineering 2022年第4期19卷 1161-1176页

作者： Sushmita Sharma Sanjoy Chakraborty Apu Kumar Saha Sukanta Nama Saroj Kumar Sahoo Department of Mathematics National Institute of Technology AgartalaAgartalaTripura 799046India Department of Computer Science and Engineering Iswar Chandra Vidyasagar CollegeBeloniaTripura 799155India Department of Computer Science and Engineering National Institute of Technology AgartalaAgartalaTripura 799046India Department of Applied Mathematics Maharaja Bir Bikram UniversityAgartalaTripura 799004India

Though the Butterfly Bptimization Algorithm(BOA)has already proved its effectiveness as a robust optimization algorithm,it has certain ***,a new variant of BOA,namely mLBOA,is proposed here to improve its *** proposed algorithm employs a self-adaptive parameter setting,Lagrange interpolation formula,and a new local search strategy embedded with Levy flight search to enhance its searching ability to make a better trade-off between exploration and ***,the fragrance generation scheme of BOA is modified,which leads for exploring the domain effectively for better *** evaluate the performance,it has been applied to solve the IEEE CEC 2017 benchmark *** results have been compared to that of six state-of-the-art algorithms and five BOA ***,various statistical tests,such as the Friedman rank test,Wilcoxon rank test,convergence analysis,and complexity analysis,have been conducted to justify the rank,significance,and complexity of the proposed ***,the mLBOA has been applied to solve three real-world engineering design *** all the analyses,it has been found that the proposed mLBOA is a competitive algorithm compared to other popular state-of-the-art algorithms and BOA variants.

关键词： Butterfly optimization algorithm Lagrange interpolation Levy flight search IEEE CEC 2017 functions engineering design problems

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Extending the Common Greenhouse Ontology with Incident Reporting from Autonomous Systems

Extending the Common Greenhouse Ontology with Incident Repor...

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2024 Joint Ontology Workshops - Episode X: The Tukker Zomer of Ontology, and Satellite Events, JOWO 2024

作者： Eichhorn, Tim Chalan, Ghusen van Roozendaal, Simon Reil, Jens van Ee, Tim Moreira, João Rebelo Sales, Tiago Prince Faculty of Electrical Engineering Mathematics and Computer Science University of Twente Netherlands TNO Netherlands Organization for Applied Scientific Research Netherlands Semantics Cybersecurity and Services University of Twente Netherlands

This paper presents the development of an extension to the Common Greenhouse Ontology (CGO) to enhance greenhouse automation, specifically focusing on incident reporting from autonomous systems. This research addresses the evolving landscape of technology in greenhouse operations and the need to support semantic interoperability among various components within a greenhouse ecosystem. By extending the CGO to accommodate robot-based autonomous systems, such as autonomous systems to combat diseases in crops and horticultural indoor positioning systems, this study aims to improve data transfer, understanding, and communication in smart horticulture projects. By designing the CGO extension based on practical implementations within the smart horticulture initiative of TNO and Hortivation, we demonstrate the effectiveness of the extended CGO for autonomous systems in enabling collaboration and standardised communication. The paper concludes by discussing the significance of the ontology extension in driving innovation and efficiency in greenhouse automation, while also highlighting areas for future exploration and refinement. © 2024 Copyright for this paper by its authors.

关键词： Ontology

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Optimizing Service Placement in Edge-to-Cloud AR/VR Systems Using a Multi-Objective Genetic Algorithm 14

Optimizing Service Placement in Edge-to-Cloud AR/VR Systems ...

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14th International Conference on Cloud Computing and Services Science, CLOSER 2024

作者： Herabad, Mohammadsadeq G. Taheri, Javid Ahmed, Bestoun S. Curescu, Calin Department of Mathematics and Computer Science Karlstad University Karlstad Sweden School of Electronics Electrical Engineering and Computer Science Queen’s University Belfast Belfast United Kingdom Department of Computer Science Faculty of Electrical Engineering Czech Technical University Prague Czech Republic Ericsson AB Stockholm Sweden

ISBN: (纸本)9789897587016

Augmented Reality (AR) and Virtual Reality (VR) systems involve computationally intensive image processing algorithms that can burden end-devices with limited resources, leading to poor performance in providing low latency services. Edge-to-cloud computing overcomes the limitations of end-devices by offloading their computations to nearby edge devices or remote cloud servers. Although this proves to be sufficient for many applications, optimal placement of latency sensitive AR/VR services in edge-to-cloud infrastructures (to provide desirable service response times and reliability) remain a formidable challenging. To address this challenge, this paper develops a Multi-Objective Genetic Algorithm (MOGA) to optimize the placement of AR/VR-based services in multi-tier edge-to-cloud environments. The primary objective of the proposed MOGA is to minimize the response time of all running services, while maximizing the reliability of the underlying system from both software and hardware perspectives. To evaluate its performance, we mathematically modeled all components and developed a tailor-made simulator to assess its effectiveness on various scales. MOGA was compared with several heuristics to prove that intuitive solutions, which are usually assumed sufficient, are not efficient enough for the stated problem. The experimental results indicated that MOGA can significantly reduce the response time of deployed services by an average of 67% on different scales, compared to other heuristic methods. MOGA also ensures reliability of the 97% infrastructure (hardware) and 95% services (software). © 2024 by SCITEPRESS – Science and Technology Publications, Lda.

关键词： Augmented reality

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Automatic classification of normal/AD brain MRI slices using whale-algorithm optimized hybrid image features

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Journal of Ambient Intelligence and Humanized Computing 2023年第10期14卷 14237-14248页

作者： Kadry, Seifedine Jessy, V. Elizabeth Rajinikanth, Venkatesan Crespo, Rubén González Department of Applied Data Science Noroff University College Kristiansand4612 Norway College of Engineering and Information Technology Ajman University Ajman United Arab Emirates Department of Electrical and Computer Engineering Lebanese American University Byblos Lebanon Division of Research and Innovation Department of Computer Science and Engineering Saveetha School of Engineering SIMATS Tamil Nadu Chennai602105 India Department of Computer Science and Technology Universidad Internacional de La Rioja La Rioja Logroño Spain

In recent years, the prevalence of Age-Related Illnesses (ARL) has been increasing among older individuals, and early recognition and treatment will result in better living conditions. It is well known that Alzheimer's Disease (AD) is among the ARD, and severe cases may result in dementia as well. It is the purpose of this study to propose a technique for distinguishing normal/AD brain MRI slices with improved accuracy utilizing the T2-modality. This scheme consists following phases: (i) Brain MRI collection and preprocessing, (ii) Deep feature extraction with the chosen scheme, (iii) Handcrafted feature extraction, (iv) Whale Algorithm (WA) based feature reduction and serial integration, and (v) binary classification using five-fold cross-validation. A total of 2000 MRI slices (1000 normal and 1000 AD class) are examined during this task using images collected from Alzheimer’s Disease Neuroimaging Initiative (ADNI). This study confirms that the proposed scheme provides a classification accuracy of > 98% when applied with the K-Nearest Classifier. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Feature extraction

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Robust Controller Synthesis and Analysis in Inverter-Dominant Droop-Controlled Islanded Microgrids

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IEEE/CAA Journal of Automatica Sinica 2021年第8期8卷 1401-1415页

作者： S.Mohsen Azizi School of Applied Engineering and Technology and the Department of Electrical and Computer EngineeringNew Jersey Institute of TechnologyNJ 07102 USA

This work investigates the problem of controller design for the inverters in an islanded ***-synthesis controllers and local droop controllers are designed to regulate the output voltages of inverters and share power among them,*** designed controllers alleviate the need for additional sensors to measure the states of the system by relying only on output *** is shown that the designed-synthesis controller properly damps resonant oscillations,and its performance is robust to the control-loop time delay and parameter *** stability of a droop-controlled islanded microgrid including multiple distributed generation(DG)units is analyzed by linearizing the nonlinear power flow model around the nominal operating point and applying theorems from linear *** is indicated that the droop controller stabilizes the microgrid system with dominantly inductive tie-line impedances for all values of resistive-inductive loads,while for the case of resistive-capacitive loads the stability is conditioned on an upper bound on the load *** robust performance of the designed-synthesis controller is studied analytically,compared with the similar analysis in an control(benchmark)framework,and verified by simulations for a four DG benchmark ***,the robustness of the droop controllers is analyzed by Monte Carlo simulations in the presence of local voltage fluctuations and phase differences among neighboring DGs.

关键词： Droop control inverter microgrid Monte Carlo simulation robust control μ-synthesis

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Terahertz deep learning fusion computed tomography

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Optics Express 2024年第10期32卷 17763-17774页

作者： Hung, Yi-Chun Su, Weng-Tai Chao, Ta-Hsuan Lin, Chia-Wen Yang, Shang-Hua Department of Electrical Engineering National Tsing Hua University Hsinchu Taiwan Department of Computer Science McCormick School of Engineering and Applied Science Northwestern University EvanstonIL60208 United States Institute of Electronics Engineering National Tsing Hua University Hsinchu30013 Taiwan Terahertz Optics and Photonics Center National Tsing Hua University Hsinchu30013 Taiwan

Terahertz (THz) tomographic imaging based on time-resolved THz signals has raised significant attention due to its non-invasive, non-destructive, non-ionizing, material-classification, and ultrafast-frame-rate nature for object exploration and inspection. However, the material and geometric information of the tested objects is inherently embedded in the highly distorted THz time-domain signals, leading to substantial computational complexity and the necessity for intricate multi-physics models to extract the desired information. To address this challenge, we present a THz multi-dimensional tomographic framework and multi-scale spatio-spectral fusion Unet (MS3-Unet), capable of fusing and collaborating the THz signals across diverse signal domains. MS3-Unet employs multi-scale branches to extract spatio-spectral features, which are subsequently processed through element-wise adaptive filters and fused to achieve high-quality THz image restoration. Evaluated by geometry-variant objects, MS3-Unet outperforms other peer methods in PSNR and SSIM. In addition to the superior performance, the proposed framework additionally provides high scalable, adjustable, and accessible interface to collaborate with different user-defined models or methods. © 2024 Optica Publishing Group under the terms of the Optica Open Access Publishing Agreement.

关键词： Adaptive filters

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Integrated dominating and hit set-inspired unequal clusteringbased data aggregation in wireless sensor networks

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International Journal of Intelligent Computing and Cybernetics 2022年第4期15卷 642-655页

作者： G.Vennira Selvi V.Muthukumaran A.C.Kaladevi S.Satheesh Kumar B.Swapna Department of Computer Science and Engineering Global Institute of Engineering and TechnologyVelloreIndia Department of Mathematics School of Applied SciencesREVA UniversityBangaloreIndia Department of Computer Science and Engineering Sona College of TechnologySalemIndia Department of Computer Science School of Applied SciencesREVA UniversityBangaloreIndia Department of Electronics and Communication Engineering Dr MGR Educational and Research InstituteChennaiIndia

Purpose-In wireless sensor networks,improving the network lifetime is considered as the prime objective that needs to be significantly addressed during data *** the traditional data aggregation techniques,cluster-based dominating set algorithms are identified as more effective in aggregating data through cluster ***,the existing cluster-based dominating set algorithms suffer from a major drawback of energy deficiency when a large number of communicating nodes need to collaborate for transferring the aggregated ***,due to this reason,the energy of each communicating node is gradually decreased and the network lifetime is also *** increase the lifetime of the network,the proposed algorithm uses two sets:Dominating set and hit ***/methodology/approach-The proposed algorithm uses two sets:Dominating set and hit *** dominating set constructs an unequal clustering,and the hit set minimizes the number of communicating nodes by selecting the optimized cluster head for transferring the aggregated data to the base *** simulation results also infer that the proposed optimized unequal clustering algorithm(OUCA)is greater in improving the network lifetime to a maximum amount of 22%than the existing cluster head selection approach considered for ***-In this paper,lifetime of the network is prolonged by constructing an unequal cluster using the dominating set and electing an optimized cluster head using hit *** dominator set chooses the dominator based on the remaining energy and its node degree of each *** optimized cluster head is chosen by the hit set to minimize the number of communicating nodes in the *** proposed algorithm effectively constructs the clusters with a minimum number of communicating nodes using the dominating and hit *** simulation result confirms that the proposed algorithm prolonging the lifetime of the network efficiently when compared with the existing algorithms.

关键词： Unequal clustering Hit set Dominating set Network lifetime

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Coverage modeling of fault-tolerant system under copula and waiting repair policy

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Life Cycle Reliability and Safety engineering 2024年第1期13卷 1-14页

作者： Tyagi, Vaishali Ram, Mangey Arora, Ritu Department of Applied Science & amp Department of Mathematics Computer Science and Engineering Graphic Era Deemed to Be University Uttarakhand Dehradun India Department of Mathematics and Statistics Gurukul Kangri Deemed to be University Kanya Gurukul Campus (Haridwar) Uttarakhand Haridwar India

This paper is related to the reliability of a three-unit repairable system having the concept of two types of repairs with waiting repair time and imperfect coverage. The concept of imperfect coverage for switching failed components is taken into account. If any unit fails, it is immediately repaired with the coverage probability c but, if the repair facility is not available instantly, then it has to wait for repairs and when the system waits for repairs, it is repaired by two types of repair facility. The Markov process is used to model the system mathematically to get the transient probabilities related to the system states. Laplace transform is utilized to assess the transient probabilities, which are additionally used to assess some reliability qualities such as availability, mean time to failure (MTTF), expected profit, and sensitivity. The failure time of the units is assumed to follow an exponential distribution whereas, the time to repair follows the general and Gumbel–Hougaard family of copula distribution. Numerical simulations have been taken to explore the availability, MTTF, profit, and sensitivity associated with the system. Results and conclusions are made for the system based on the graphical study. © The Author(s), under exclusive licence to Society for Reliability and Safety (SRESA) 2024.

关键词： Gumbel–Hougaard copula distribution Imperfect coverage Markov process Waiting time to repair

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MediVision - Advanced Medical Imaging and Visualization through AR/VR

MediVision - Advanced Medical Imaging and Visualization thro...

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2024 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2024

作者： Yoosaf, Salih Ziyad, Naeema University of Twente Faculty of Electrical Engineering Mathematics and Computer Science AE Enschede7500 Netherlands Wright State University Bernard D. Researcheris with the Department of Electrical Engineering DaytonOH45435 United States

ISBN: (纸本)9781665410205

MediVision revolutionizes medical imaging by integrating Augmented Reality (AR) and Virtual Reality (VR) with traditional 2D data. This platform transforms standard DICOM images into immersive 3D models, enhancing diagnostic accuracy and anatomical exploration. Using Unity 3D and advanced image processing, MediVision enables in-teractive visualization of complex conditions through intuitive gestures and labeling. It supports clinical diagnostics, treatment planning, and medical education by simulating procedures and disease progression. MediVision also promotes global healthcare accessibility, reduces diagnostic errors, and supports remote consultations, setting a new benchmark for accuracy and education in medical imaging. © 2024 IEEE.

关键词： Medical education

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