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6th International Conference on Intelligent Computing and Optimization, ICO 2023

作者： Alam, Md Janay Choudhury, Ashiquzzaman Al Maksud, Kazi Sifat Reza, Ahmed Wasif Arefin, Mohammad Shamsul Department of Computer Science and Engineering East West University Dhaka Bangladesh Department of Computer Science and Engineering Chittagong University of Engineering and Technology Chittagong Bangladesh

ISBN: (纸本)9783031503269

The adaptation of IoT-based technology in agriculture is increasing rapidly in recent times. IoT devices are of great assistance to farmers in monitoring dairy farms, greenhouses, and other agricultural facilities. The most crucial component of an IoT device is ensuring data security and privacy. Data leakage can have significant negative consequences as it may result in financial loss for farmers. It is important to prioritize data security to protect the interests of farmers and ensure the success of their agricultural endeavors. Blockchain technology can be a solution to secure data transactions in the network layer. With the concept of private and public key pairs, data hashing, and decentralized systems;important and sensitive data will be secured. In this study, we discuss the structure of a three-layer architecture for green IoT technology and identify the privacy issues presented in each layer. Then we propose a solution by implementing a secure Ethereum-based blockchain system for data transactions at the network layer. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Losses

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Butterfly Optimized Feature Selection with Fuzzy C-Means Classifier for Thyroid Prediction

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Intelligent Automation & Soft Computing 2023年第3期35卷 2909-2924页

作者： S.J.K.Jagadeesh Kumar P.Parthasarathi Mehedi Masud Jehad F.Al-Amri Mohamed Abouhawwash Department of Computer Science and Engineering Kathir College of EngineeringCoimbatore641062India Department of Computer science and Engineering Bannari Amman Institute of TechnologySathyamangalam638401TamilnaduIndia Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityP.O.BOX 11099Taif21944Saudi Arabia Department of Mathematics Faculty of ScienceMansoura UniversityMansoura 35516Egypt Department of Computational Mathematics Scienceand Engineering(CMSE)Michigan State UniversityEast LansingMI48824USA

The main task of thyroid hormones is controlling the metabolism rate of humans,the development of neurons,and the signiﬁcant growth of reproductive *** medical science,thyroid disorder will lead to creating thyroiditis and thyroid *** two main thyroid disorders are hyperthyroidism and *** research works focus on the prediction of thyroid *** improve the accuracy in the classiﬁcation of thyroid disorder this paper pro-poses optimization-based feature selection by using differential evolution with the Butterﬂy optimization algorithm(DE-BOA).For the classiﬁer fuzzy C-means algorithm(FCM)is *** proposed DEBOA-FCM is evaluated with para-metric metric measures of sensitivity,speciﬁcity,and *** this work,the thyroid disease dataset collected from the machine learning University of Cali-fornia Irvine(UCI)database was *** accuracy rate for the Differential Evo-lutionary algorithm got 0.884,the Butterﬂy optimization algorithm got 0.906,Fuzzy C-Means algorithm got 0.899 and DEBOA+Focused Concept Miner(FCM)proposed work 0.943.

关键词： Fuzzy butterﬂy differential evolution thyroid hyperthyroid

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NCFS:new chaotic fuzzy system as a general function approximator

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Journal of Control and Decision 2023年第4期10卷 514-528页

作者： Hamid Abbasi Mahdi Yaghoobi Arash Sharifi Mohammad Teshnehlab Department of Computer Engineering Science and Research BranchIslamic Azad UniversityTehranIran Department of Electrical and Computer Engineering Mashhad BranchIslamic Azad UniversityMashhadIran Department of Electrical and Computer Engineering K.N.T University of TechnologyTehranIran

Conventional fuzzy systems(type-1 and type 2)are universal *** goal of this paper is to design and implement a new chaotic fuzzy system(NCFS)based on the Lee oscil-lator for function approximation and chaotic *** incorporates fuzzy reasoning of the fuzzy systems,self-adaptation of the neural networks,and chaotic signal generation in a unique *** features enable the structure to handle uncertainties by generating new information or by chaotic search among prior *** fusion of chaotic structure into the neurons of the membership layer of a conventional fuzzy system makes the NCFS more capable of confronting nonlinear *** on the GFA and Stone-Weierstrass theorems,we show that the proposed model has the function approximation *** NCFS perfor-mance is investigated by applying it to the problem of chaotic *** results are demonstrated to ilustrate the concept of function approximation.

关键词： Chaotic fuzzy system function approximation chaotic neural network oscillatory neuron

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Relative Power Loss Analysis of Poly-Si PV Panels: An Overview in Eastern Indian Climatic Condition

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Journal of The Institution of Engineers (India): Series B 2022年第5期103卷 1775-1780页

作者： Pal, Sudipta Basu Das Bhattacharya, Konika Mukherjee, Dipankar Department of Computer Science Technology University of Engineering Management Kolkata India Department of Electrical Engineering Indian Institute of Engineering Science and Technology Shibpur India Department of Electronics and Telecommunication Engineering Indian Institute of Engineering Science and Technology Shibpur India

Renewable energies are generated from natural processes that are continuously renewed. Therefore, it is required to combine the PV modules either in series combinations or parallel combinations for developing the appropriate Photovoltaic (PV) panel/PV arrays. Several PV modules are connected in a series–parallel combination to constitute PV arrays. These PV arrays currently act as a decentralized source of D.C power for onward transmission. When identical wattages PV modules are coupled in a parallel or series connection, there must be a probability to the PV module's manufacturing process that gives rise to power loss. Mainly these types of losses are called Mismatch losses. Mismatch losses (power losses) in PV panels principally occur in terms of Relative Power Loss (RPL). Therefore, the authors carried out I–V characterizations of different technology of PV modules under varying insolation and temperatures. The main aim of the work is to develop the right kind of photovoltaic (PV) panel/PV arrays in a particular Eastern Indian climatic zone. From the authors' characterization of RPL, analysis was conducted to judge which technology is most suitable to build a large size array/BIPV. The experimental results reveal lower mismatch losses of poly-Si PV modules for crystalline silicon and amorphous silicon counterparts. © 2022, The Institution of Engineers (India).

关键词： Solar panels

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User Feedback Severity Level Identification and Classification through Deeper Analysis of Text 4

User Feedback Severity Level Identification and Classificati...

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4th International Conference on Computing, Mathematics and engineering Technologies, iCoMET 2023

作者： Umair, Muhammad Aun Irtaza, Syed Salim, Shahid University of Engineering and Technology Department of Computer Science Taxila Pakistan

ISBN: (纸本)9798350335316

Now a days world is look right on digitalized. Social media is captivating in this digital age through the accessibility of consumer's feedback. The recent work in the field of classification based on comments on social media is gaining appeal on a global scale. Unfortunately, the study does not offer better accuracy in terms of toxic comments. On social media platforms, hateful and abusive language has a detrimental effect on users' mental health and involvement from people from all diverse backgrounds. Automatic methods is most commonly used datasets with categorical labels to detect foul language. The level of offensiveness of comments varies. In NLP we use binary classification like either a comment is offensive or not and leave continues classification. In continues classification one can identify the severity level of comments, can set a threshold, and by using Deep Learning and modeling techniques can directly identify the severity level of comments by considering context. The review of related literature shows that identification of toxicity of user comments can be improved by pre-processing methods, such as deleting null values and anomies from the dataset, to refine the dataset and increase its accuracy by applying different algorithm techniques to make feature more valuables. This research provides analysis of user comments datasets and study's user comments toxicity with different machine learning approaches. First, we need to do pre-processing steps including punctuations, stop words, null entries, and duplicate removal to remove anomalies. After that we need to apply different methods like count vectorizer and bag of words to extract features. After that, we MCPL algorithm applied on these datasets to predicts results. By applying MCPL model on user comments dataset 88.5% accuracy were founded. © 2023 IEEE.

关键词： Social networking (online)

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Energy Efficient Distributed Cloud Load Balancing Using Virtual Machines 6th

Energy Efficient Distributed Cloud Load Balancing Using Virt...

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6th International Conference on Intelligent Computing and Optimization, ICO 2023

作者： Afridi, Sabbir Mahmud Hossain, Akmal Rafsan, Md Mehdi Ahsan Reza, Ahmed Wasif Arefin, Mohammad Shamsul Department of Computer Science and Engineering East West University Dhaka Bangladesh Department of Computer Science and Engineering Chittagong University of Engineering and Technology Chittagong Bangladesh

ISBN: (纸本)9783031501500

Load balancing is a crucial element of any distributed system because it serves to spread workloads equally throughout numerous computing resources aiming to optimize speed and efficiency. However, traditional load-balancing techniques often consume a significant amount of energy, which can lead to increased operating costs and negative environmental impacts. We propose a dynamic round-robin approach for cloud load balancing in this paper to alleviate the strain on wireless networks. Our algorithm achieves 8% more efficiency compared to the traditional round-robin model. Additionally, our load-balancing virtual machine architecture exhibits an improvement in resource usage efficiency ranging from 15 to 42% compared to the current model. Overall, our model significantly increases the efficiency of the current load-balancing method. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Virtualization

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OntoDSO: an ontological-based dolphin swarm optimization (DSO) approach to perform energy efficient routing in Wireless Sensor Networks (WSNs)

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International Journal of Information technology (Singapore) 2024年第3期16卷 1551-1557页

作者： Boopathi, Mythili Parikh, Swapnil Awasthi, Aishwary Malviya, Ashwini Nachappa, M.N. Mishra, Awakash Shyam, Gopal Krishna Narula, Gagandeep Singh Department of Information Technology Vellore Institute of Technology Tamil Nadu Vellore India Department of Computer Science and Engineering Faculty of Engineering and Technology Parul University Gujarat Vadodara India Department of Mechanical Engineering Sanskriti University UP Mathura India Department of UGDX ATLAS SkillTech University Mumbai India Department of Computer Science and Information Technology Jain (Deemed to be University) Bengaluru India Maharishi School of Engineering and Technology Maharishi University of Information Technology Noida India Department of Computer Science Engineering Presidency University Bengaluru India Guru Gobind Singh Indraprastha University Delhi Dwarka India

The aim of the paper is to perform an energy-efficient routing for moving nodes in Wireless Sensor Networks (WSNs) by using an ontological-based dolphin swarm optimization (DSO) approach. It makes use of echolocation and ontology to locate and represent cluster nodes close to the sink thereby maintaining optimal energy consumption during simulation. A comparative analysis for 20 samples (N = 10 each) is performed between OntoDSO, Ad-hoc On-demand Distance Vector (AODV) algorithm and existing literature review studies by taking several parameters namely mean delay, mean packet delivery ratio and mean energy consumption into consideration. The simulation of results is performed using MATLAB Simulink with implementation parameters such as number of nodes (n) and initial battery life. As a result, it is found that the OntoDSO approach identifies a set of optimized routes that can satisfy delay constraints and consume less energy, thereby achieving higher performance than AODV and existing studies in the context of WSNs. © 2024, The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of computer Applications and Management.

关键词： Ad-hoc On-demand Distance Vector (AODV) algorithm Dolphin Swarm Optimization (DSO) algorithm Packet delivery ratio and energy consumption Wireless Sensor Network (WSN)

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Density-Aware and Semantic-Guided Fusion for 3-D Object Detection Using LiDAR-Camera Sensors

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IEEE Sensors Journal 2023年第18期23卷 22051-22063页

作者： Jhong, Sin-Ye Chen, Yung-Yao Hsia, Chih-Hsien Wang, Yu-Quan Lai, Chin-Feng Department of Engineering Science National Cheng Kung University Tainan701 Taiwan Department of Electronic and Computer Engineering National Taiwan University of Science and Technology Taipei106 Taiwan Department of Computer Science and Information Engineering National Ilan University Yilan260 Taiwan

Three-dimensional object detection plays a key role in autonomous driving systems. The performance of light detection and ranging (LiDAR)-based models is limited because of the sparsity and inhomogeneity of point clouds. Researchers have developed numerous camera-LiDAR-based fusion methods to address the limitations of LiDAR-based models. Still, because of the major differences in representations between pixel and point cloud, these fusion methods cannot appropriately leverage the benefits of both types of sensors. In this study, we developed a 3-D object detection model based on LiDAR-camera fusion. The model first augments raw points with possibility features extracted from a camera stream and subsequently uses possibility-guided farthest point sampling (P-FPS) for high-quality feature extraction in the 3-D backbone. In addition, we designed a detection head for density-aware artificial point sampling and fusion that can aggregate geometric and semantic features by using high-resolution artificial points and shift the position of an artificial point according to the density of points in a region of interest (ROI) to obtain more representative point features. We conducted massive experiments by using the public KITTI dataset. Our method outperforms previously developed state-of-the-art 3-D object detection methods, especially in detecting small and distant objects. © 2023 IEEE.

关键词： Semantics

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Secure and Efficient Data Synchronization Techniques for Digital Twins in Fog-Edge Cloud Environments 7

Secure and Efficient Data Synchronization Techniques for Dig...

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7th International Conference on Inventive Computation Technologies, ICICT 2024

作者： Jegadeesan, S. Hayvita, R.K. Nishath, A.G. Ramalakshmi, S. Krishnan, R. Santhana Essaki Muthu, A. Velammal College of Engineering And Technology Department of Information Technology Madurai India Scad College of Engineering And Technology Department of Computer Science And Engineering Cheranmahadevi India Scad College of Engineering And Technology Department of Electronics And Communication Engineering Cheranmahadevi India

ISBN: (纸本)9798350359299

Data synchronization is a critical aspect in the deployment of Digital Twins within Fog-Edge Cloud environments, ensuring consistency and reliability across distributed systems. However, the security and efficiency of synchronization techniques remain significant challenges. The paper presents a novel algorithm named TwinCrypt, which is designed based on the combination of appropriate encryption algorithm called as Homomorphic Encryption and suitable computing mechanism scheme called as Secure Multi-Party Computation. The algorithm is aimed to achieve secure and efficient data synchronization for Digital Twins in Fog-Edge Cloud environments. The proposed algorithm aims to address vulnerabilities associated with data transmission and storage, offering robust protection against unauthorized access and data breaches. The performance effectiveness of TwinCrypt is analysed by conducting suitable simulations and the simulation results are compared with are conducted comparing it with the existing algorithms used for data synchronization viz. RSA Encryption, AES Encryption, and Zero-Knowledge Proofs in similar environments. Simulation metrics such as latency, throughput, and security overhead are employed to assess the performance of TwinCrypt against its counterparts. The results establish that TwinCrypt outperforms existing algorithms in both security and efficiency, showcasing its suitability for real- world deployment scenarios. © 2024 IEEE.

关键词： Fog computing

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Hybrid Arithmetic-Rider Optimization algorithm as new intelligent model for travelling salesman problem

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International Journal of Information technology (Singapore) 2024年 1-18页

作者： Krishna, Madugula Murali Majhi, Santosh Kumar Panda, Nibedan Department of Computer Science and Engineering Veer Surendra Sai University of Technology Odisha Burla 768018 India Department of Computer Science and Information Technology Guru Ghasidas Viswavidyalaya C.G. Bilaspur India School of Computer Engineering KIIT Deemed to Be University Odisha Bhubaneswar 751024 India

Travelling Salesman Problem (TSP) is one of the significant NP-hard benchmark problems for performing discrete optimization. In recent times, determining the optimal route mechanism has been implemented and ensured as an important mechanism for solving practical applications. In real-time applications, energy-saving, reaching the destination at the assigned time, and identifying the shortest route is very essential. Route determination is researched by different scientists and engineers. Numerous research is done on this problem, and it is still challenging. Therefore, meta-heuristics are involved in this problem as it is inspired by the biological species. This article constitutes the continuation of the work on adapting the TSP using the hybridized algorithm named Arithmetic-ROA (A-ROA). The ultimate aim of the proposed TSP is to reduce the distance travelled by the salesman while focusing on the entire city. To attain this optimal solution, the novel hybrid A-ROA optimizes the number of the city to be travelled. The results acquired by the new hybrid heuristic are compared with other heuristic algorithms. The computational results confirm that the developed algorithm obtained better results when compared with existing algorithms. The developed optimization algorithm also provides enhanced performance within a realistic amount of computational time. © The Author(s), under exclusive licence to Bharati Vidyapeeth's Institute of computer Applications and Management 2024.

关键词： Arithmetic Optimization Algorithm Arithmetic-Rider Optimization Algorithm Benchmark Datasets Meta-heuristic Algorithms Rider Optimization Algorithm Travelling Salesman Problem

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