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A Sustainable WSN System with Heuristic Schemes in IIoT

computers, Materials & Continua 2022年第9期72卷 4215-4231页

作者： Wenjun Li Siyang Zhang Guangwei Wu Aldosary Saad Amr Tolba Gwang-jun Kim School of Computer and Communication Engineering Changsha University of Science and TechnologyChangsha410114China College of Computer and Information Engineering Central South University of Forestry and TechnologyChangsha410114China Computer Science Department Community CollegeKing Saud UniversityRiyadh11437Saudi Arabia Mathematics and Computer Science Department Faculty of ScienceMenoufia UniversityEgypt Department of Computer Engineering Chonnam National UniversityGwangju61186Korea

Recently, the development of Industrial Internet of Things hastaken the advantage of 5G network to be more powerful and more ***, the upgrading of 5G network will cause a variety of issues increase,one of them is the increased cost of coverage. In this paper, we proposea sustainable wireless sensor networks system, which avoids the problemsbrought by 5G network system to some extent. In this system, deployingrelays and selecting routing are for the sake of communication and *** main aim is to minimize the total energy-cost of communication underthe precondition, where each terminal with low-power should be charged byat least one relay. Furthermore, from the perspective of graph theory, weextract a combinatorial optimization problem from this system. After that,as to four different cases, there are corresponding different versions of theproblem. We give the proofs of computational complexity for these problems,and two heuristic algorithms for one of them are proposed. Finally, theextensive experiments compare and demonstrate the performances of thesetwo algorithms.

关键词： Industrial Internet of Things sustainable wireless sensor network system combinatorial optimization problem heuristic algorithms

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A-REA: Relation-Aware Graph Convolutional Network Entity Alignment Via a Differential Adjacency Matrix

A-REA: Relation-Aware Graph Convolutional Network Entity Ali...

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2023 Asia-Pacific Conference on Image Processing, Electronics and computers, IPEC 2023

作者： Dang, Yuemei Qiu, Chen Gao, Feng Gu, Jinguang Zhang, Lihua Arman, Ghazaleh School of Computer Science and Technology Wuhan University of Science and Technology Hubei Wuhan China Software College East China Jiaotong University Jiangxi Nanchang China Urmia University of Technology Faculty of Information Technology and Computer Engineering Urmia Iran

ISBN: (纸本)9781665457033

Entity Alignment is the task of seeking entities with the same semantics from distinct knowledge graphs (KGs). Researchers have recently proposed Graph Convolutional Network (GCN) based approaches to achieve this task. Most existing GCN-based methods embed all the relations into an identical value, making the underlying loss on the diversity of the relationship. Relation semantics of entities and relation structure have benefitted the entity alignment task in the monolingual scenarios. This paper proposes a Relation-Aware Graph Convolutional Network with a Differential Adjacency Matrix (A-REA), which exploits the relation-specific semantics and structural information of entities in the KGs to promote the entity representations. The experiments on DBP-15K and DWY-100K datasets, including three cross-lingual subsets and two cross-knowledge graph sub-datasets, reveal that our approach leads to advance in entity alignment task in both the cross-lingual and cross-knowledge KGs. Discriminating the relation shows the effective signal for entity alignment, especially for the schema heterogeneity of different KGs. © 2023 IEEE.

关键词： Knowledge graph

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Design and Simulation of Ring Network-on-Chip for Different Configured Nodes

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computers, Materials & Continua 2022年第5期71卷 4085-4100页

作者： Arpit Jain Rakesh Kumar Dwivedi Hammam Alshazly Adesh Kumar Sami Bourouis Manjit Kaur Faculty of Engineering&Computer Sciences Teerthanker Mahaveer UniversityMoradabadUttar Pradesh244001India Faculty of Computers and Information South Valley UniversityQena83523Egypt Department of Electrical and Electronics Engineering School of EngineeringUniversity of Petroleum and Energy StudiesDehradun248007India Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia School of Engineering and Applied Sciences Bennett UniversityGreater Noida201310India

The network-on-chip(NoC)technology is frequently referred to as a front-end solution to a back-end *** physical substructure that transfers data on the chip and ensures the quality of service begins to collapse when the size of semiconductor transistor dimensions shrinks and growing numbers of intellectual property(IP)blocks working together are integrated into a *** system on chip(SoC)architecture of today is so complex that not utilizing the crossbar and traditional hierarchical bus *** connectivity reduces the amount of hardware required for routing and functions,allowing SoCs with NoC interconnect fabrics to operate at higher ***(Octagons)is a direct NoC that is specifically used to solve the scalability problem by expanding each node in the shape of an *** paper discusses the ring NoC design concept and its simulation in Xilinx ISE 14.7,as well as the communication of functional *** the field-programmable gate array(FPGA)synthesis,the performance of NoC is evaluated in terms of hardware and timing *** design allows 64 to 256 node communication in a single chip with‘N’bit data transfer in the ring *** performance of the NoC is evaluated with variable nodes from 2 to 256 in Digilent manufactured Virtex-5 FPGA hardware.

关键词： Ring NoC FPGA synthesis nodes communication SoC design integrated synthesis environment

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Secure and Robust Optical Multi-Stage Medical Image Cryptosystem

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computers, Materials & Continua 2022年第1期70卷 895-913页

作者： Walid El-Shafai Moustafa H.Aly Abeer D.Algarni Fathi E.Abd El-Samie Naglaa F.Soliman Department Electronics and Electrical Communications Faculty of Electronic EngineeringMenoufia UniversityMenouf32952Egypt Department of Electronics and Communications Engineering College of Engineering and TechnologyArab Academy for ScienceTechnology and Maritime TransportAlexandria1029Egypt Department of Information Technology College of Computer and Information SciencesPrincess Nourah Bint Abdulrahman UniversityRiyadh84428Saudi Arabia Department of Electronics and Communications Faculty of EngineeringZagazig UniversityZagazig44519Egypt

Due to the rapid growth of telemedicine and healthcare services,color medical image security applications have been expanded *** this paper,an asymmetric PTFrFT(Phase Truncated Fractional Fourier Transform)-based color medical image cryptosystem is *** different phases in the fractional Fourier and output planes are provided as deciphering ***,the ciphering keys will not be employed for the deciphering ***,the introduced PTFrFT algorithm comprises asymmetric ciphering and deciphering processes in contrast to the traditional optical symmetric OSH(Optical Scanning Holography)and DRPE(Double Random Phase Encoding)*** of the principal impacts of the introduced asymmetric cryptosystem is that it eliminates the onedimensionality aspects of the related symmetric cryptosystems due to its remarkable feature of phase nonlinear truncation *** comparisons on various colormedical images are examined and analyzed to substantiate the cryptosystem *** achieved experimental outcomes ensure that the introduced cryptosystem is robust and *** has terrific cryptography performance compared to conventional cryptography algorithms,even in the presence of noise and severe channel attacks.

关键词： Optical encryption medical image security symmetric and asymmetric encryption OSH DRPE PTFrFT

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Genome-wide exploratory analysis for NARAC dataset with preparation for haplotype block partitioning through minor allele frequency quality control viewpoint

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Iran Journal of computer Science 2023年第4期6卷 387-396页

作者： Saad, Mohamed N. Zareef, Galena W. Ibrahim, Fatma S. Said, Ashraf M. Hamed, Hisham F. A. Biomedical Engineering Department Faculty of Engineering Minia University Minia Egypt Biomedical Engineering Department Misr University for Science and Technology 6th of October City Egypt Bioinformatics Department Faculty of Computer and Information Minia University Minia Egypt Computer and Software Engineering Department Misr University for Science and Technology 6th of October City Egypt Department of Electrical Engineering Faculty of Engineering Egyptian-Russian University Cairo Egypt Electrical and Electronics Engineering Department Faculty of Engineering Minia University Minia Egypt

This article provides a detailed description, analysis, and visualization of a case–control genome-wide genotypic dataset from the North American Rheumatoid Arthritis Consortium (NARAC). The data is presented in terms of the number of females and males in both cases and controls, as well as the percentage of missing data. The number of alleles and genotypes is also counted, and the minor allele frequency (MAF) is calculated for each single nucleotide polymorphism (SNP). The data is further classified into four categories based on the SNP's MAF, namely, very rare, rare, low frequency, and common SNPs. The regions of these categories in the chromosome are investigated to determine the proportion of SNPs in coding locations and other regions. It is observed that each category has a different proportion in each region of consequence annotation. The data composition in terms of alleles and genotypes is found to be greatly disproportionate. The results present clear insights into the data and its MAF, which can be compared with other datasets. These findings can aid researchers in gaining a comprehensive understanding of such case–control datasets and bring accurate insights into the data. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023.

关键词： Genome-wide association study Genome-wide exploratory analysis Minor allele frequency Single nucleotide polymorphism Variant annotation

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Medical Material Allocation using Multi-Queue Scheduling during Pandemics

Medical Material Allocation using Multi-Queue Scheduling dur...

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2024 International Conference on Science, technology, engineering and Management, ICSTEM 2024

作者： Divya Priya, D. Subramaniam, Suthashini Kumar, P. Vinoth Theam, Lim Jit Ayyasamy, Ramesh Kumar Krishnan, Kesavan Department of Computer Science Engineering MLR Institue of Technology Hyderabad India Perak Kampar Malaysia Department of Artificial Intelligence and Data Science St Joseph's Institute of Technology OMR CHENNAI India Faculty of Computer Science and Information Technology Universiti Malaya Kuala Lumpur Malaysia

ISBN: (纸本)9798350376913

In this study, we implemented a multi-level queue scheduling algorithm for a hospital with three wards: General, Pandemic, and Arogya Sree. The Pandemic ward uses priority scheduling, while the others use FCFS. It also calculates distances to nearby airports based on geolocation to identify oxygen airlift points. This work allows us to eliminate human interference in resource allocation by automating the process based on priority derived from the doctor’s diagnosis. This ensures that maximum efficiency is reached. The common people faced many problems during the pandemic, mainly related to costs incurred and resource availability. We want to solve this by removing the human factor from the equation. © 2024 IEEE.

关键词： Scheduling algorithms

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ML Based Intrusion Detection Scheme for various types of attacks in a WSN using C4.5 and CART classifiers

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Materials Today: Proceedings 2023年 80卷 3769-3776页

作者： Gite, Pratik Chouhan, Kuldeep Murali Krishna, K. Kumar Nayak, Chinmaya Soni, Mukesh Shrivastava, Amit Department of Computer Science and Engineering IPSA-IES Indore AB Road MP Indore India Department of Computer Science and Engineering I.T.S Engineering College Greater Noida India Department of Electronics and Communication Engineering Vignan's Institute of Information Technology Duvvada Andhra Pradesh Visakhapatnam India Faculty of Emerging Technology Sri Sri University Odisha751001 India Department of Computer Science & Engineering Jagran Lakecity University Bhopal India Department of Computer Science Engineering Swami Vivekanand College of Engineering Khandwa Road Near Tolnaka Vivekanand Knowledge City Indore India

A key component for preserving a WSN's integrity is designing an intrusion detection system (IDS). This article covers several sorts of security threats that may occur in a WSN. It proposes a detection of malicious nodes in a WSN. This system identifies four common assaults (i.e., black hole, wormhole, gray hole, and DDoS attacks) and is based on a Base Station machine learning (ML) algorithm (BS). The suggested ML algorithm continually analyzes data patterns from each node. Based on this technique, BS recognizes the network's harmful behavior and provides notifications to neighbor nodes to prevent attacker. First, the various assaults are examined and their characteristics are derived in terms of network parameters. Furthermore, the gathered pattern trains an ML algorithm. Then, the attacker node is effectively and properly classified within the BS. The NS2 simulator simulated the needed secure WSN. The experimental findings revealed excellent accuracy of the suggested method for attack detection. This precision can enhance network performance in terms of energy usage and packet delivery (PDR). © 2021

关键词： Base stations

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Fused Transformers: Fused information of Arabic long Article for Summarization 6

Fused Transformers: Fused Information of Arabic long Article...

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6th International Conference on AI in Computational Linguistics, ACLing 2024

作者： Ezzat, Zeyad Khalfallah, Ayman Khoriba, Ghadad Center for Informatics Science Information Technology and Computer Science School Nile University Giza Egypt Computer and Systems Department Faculty of Engineering Alexandria University Alexandria Egypt Applied Innovation Centre Egypt Faculty of Computers and Artificial Intelligence Helwan University Cairo Egypt

This paper introduces a novel approach for extending the applicability of pre-trained models to accommodate longer texts. Addressing the inherent limitation of quadratic performance in attention models within transformers, we propose the concept of fused transformers. By integrating new adaptor techniques, we enhance the encoding of lengthy text segments by breaking them into shorter spans. Subsequently, these segments are fused to increase the model's effectiveness in processing extended texts. This fusion mechanism serves to fortify the model's capacity for fine-tuning. Furthermore, we implement a length-based curriculum for expedited training Our experiments yielded 16 Rouge-2 points, representing a doubling of the score achieved by the vanilla fine-tuning method on the newly introduced "Mukhtasar" dataset for summarization. This highlights the effectiveness of managing complex relations among text segments and confirms that our method can outperform conventional training approaches. © 2024 Elsevier B.V.. All rights reserved.

关键词： Distribution transformers

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An Efficient Multi-modal Approach for Multi-label Urban Garbage Classification 15th

An Efficient Multi-modal Approach for Multi-label Urban Gar...

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15th International Conference on Soft Computing and Pattern Recognition, SoCPaR 2023 and 14th World Congress on Nature and Biologically Inspired Computing, NaBIC 2023

作者： Thien, Nguyen Thanh Faculty of Computer Engineering University of Information Technology Ho Chi Minh City Viet Nam Vietnam National University Ho Chi Minh City Viet Nam

ISBN: (纸本)9783031810824

Classifying garbage in urban scene using multi-modal approach is a challenging task due to the complexity of the environment and diversity of collected data. Existing works usually extract features from multi-modalities, then combine them together to form final feature, which is used for classification later. Although these methods have achieved noticeable results, the correlation between different types of data might be lost, which can limit their performance. To address this problem, this paper introduces a multi-modal method for urban garbage classification with efficient feature integration. By fusing image data and each type of meta-data separately, then associating them to get final output, the proposed model can effectively classify several types of garbage. Extensive experiments show that the proposed method outperforms baseline models by a large margin. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Modal analysis

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Predicting Customer Behavior Using Neural Network Optimized by Grasshopper Algorithm 2

Predicting Customer Behavior Using Neural Network Optimized ...

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2nd International engineering Conference on Electrical, Energy, and Artificial Intelligence, EICEEAI 2023

作者： Loaeibi, Zoheir Alqammaz, Abdullah Sara, Massar Boostani, Reza School of Engineering Shiraz University Electrical and Computer Engineering Faculty Cse and It Dept. Shiraz Iran Zarqa University Faculty of Information Technology Department of Cyber Security Zarqa Jordan College of Engineering University of Business and Technology Jeddah21448 Saudi Arabia

ISBN: (纸本)9798350373363

Digital marketing, as an essential branch of science, could provide value for commercial organizations and strengthen the interaction with customers via increasing the electronic services. In digital marketing, real-time analysis of customer behaviors is considered as a key program, which could encourage novel advertisement concentration. Each deal that is assigned to a costumer, is a part of individual behavior and is a sample of feature vectors based on a set of interactions is modelled for creating the customer behavior. In this research, using data mining techniques and metaheuristic algorithms, the patterns of customer behavior are identified and predicted. Neural network as a classifier with acceptable performance is used for complex tasks. In the train phase, neural network is usually worked with back propagation algorithm. This algorithm suffers from falling into the local optima and needs to adjust the weights and using proper initialization weights. To optimize both weights and structure of the neural network, we adopt grasshopper evolutionary algorithm to adjust the weight in an iterative manner along with the adjusting the number of neurons in the hidden layer. In the proposed method, the probability of falling in the local optima is reduced and also the suggested algorithm could provide acceptable performance compared to the other rivals in a rich benchmark of digital marketing. © 2023 IEEE.

关键词： Optimization

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