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4th IEEE International Conference on Electronic Technology, Communication and Information, ICETCI 2024

作者： Wu, Tong Evlyukhin, Andrey B. Tuz, Vladimir R. Leibniz University Cluster of Excellence PhoenixD Institute of Quantum Optics Hannover Germany Jilin University State Key Laboratory on Integrated Optoelectronics College of Electronic Science and Engineering International Center of Future Science Changchun China V. N. Karazin Kharkiv National University School of Radiophysics Biomedical Electronics and Computer Systems Kharkiv Ukraine

ISBN: (纸本)9798350361643

In this study, we design a structure consisting of the radial arrangement of several vertically standing dielectric disks (resonators) so that such a ring cluster supports exotic toroidal dipole mode excitation. Subsequently, the characteristics of a system composed of two identical rings with a change in the distance are studied to reveal how to affect the peculiarities of the coupling between two toroidal dipole modes. The manifestation of toroidal dipole coupling is confirmed by checking the extinction cross-section, near-field distributions, and induced toroidal moments obtained from both full-wave numerical simulation and microwave experiments. To experiment, particles are made from commercially available ceramics. During the measurements, standard microwave equipment is used to characterize the toroidal dipole coupling within the frequency band of 1-10 GHz. Since the structure comprises simple dielectric disks without any metallic elements, the proposed designs are hopefully scalable down to the micrometer or nanometer scale considering their practical applications as building blocks in metamaterials operated on the radiation-less exotic toroidal and anapole states. © 2024 IEEE.

关键词： Microwave resonators

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A Novel Machine Learning-Enhanced Swarm Intelligence Algorithm for Cost-Effective Cloud Load Balancing

A Novel Machine Learning-Enhanced Swarm Intelligence Algorit...

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Innovative Computing, Intelligent Communication and Smart Electrical systems (ICSES), International Conference on

作者： Nimmati Satheesh K Sakthivel Department of Computer Applications PSNA College of Engineering and Technology Dindigul Tamil Nadu India Department of Computer Science and Business Systems K.S Rangasamy College of Technology Tiruchengode Tamil Nadu India

ISBN: (数字)9798331543624

ISBN: (纸本)9798331543631

Cloud computing refers to the instant accessibility of shared computer resources over the internet on-demand, thereby revolutionizing the way organizations deploy and manage their IT infrastructure. Efficient load balancing in a cloud environment scales up, utilizing resources with optimized cost-effectiveness. This paper introduces a new Machine Learning-guided Improved Swarm Intelligence Algorithm for reliable load balancing in cloud computing. Methodology It spans on three main elements. The first is the data center controller for the management of tasks. VM allocation uses an Improved Beetle Swarm Optimization Algorithm and one-dimensional convolutional probabilistic neural network is used for host load prediction. To propose an approach that looks to optimize the key metrics such as make span, average cost of VM, resource utilization, and value response time through iterative optimization process. The results of the experiments reflect the success of the proposed algorithm, because an improved performance of load balancing is obtained in comparison with those achieved using PSO, Grey Wolf Optimization, and Genetic Algorithm. The convergence diagram displays the iterative optimization process achieved by the proposed algorithm in obtaining a balance among various performance metrics. Overall, the methodology proposed in this work will provide promising facilitation in the increased efficiency, scalability, and cost-effectiveness of environments based on cloud computing with a reliable load balancing.

关键词： Measurement Cloud computing Machine learning algorithms Load management Prediction algorithms Virtual machines Resource management Particle swarm optimization Optimization Genetic algorithms

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Fiber Optic Devices for High-Resolution Refractive Index Sensing

Fiber Optic Devices for High-Resolution Refractive Index Sen...

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Progress in Electromagnetic Research Symposium (PIERS)

作者： S. Pevec M. Njegovec J. Javornik D. Donlagic Laboratory for Electro Optics and Sensor Systems Faculty of Electrical Engineering and Computer Science University of Maribor Maribor Slovenia

The paper describes a fiber optic Fabry-Perot (FP) refractive index (RI) sensors that provide performances required in gas sensing applications. Presented high-resolution FabryPerot Interferometer (FPI) sensors are based on open-path cells that can be integrated with the optical fiber in different ways. They can be fabricated as microcells on the fiber tip or along the optical fiber, or as external/extrinsic gas cells connected to the fiber. All presented configurations are based on low-finesse FPI as they allow for a simple and cost-efficient designs.

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Creep response of fiber-reinforced composites: a review

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Discover Mechanical engineering 2022年第1期1卷 1-31页

作者： Katouzian, Mostafa Vlase, Sorin Marin, Marin Öchsner, Andreas Department of Mechanical Engineering Transilvania University of Brasov Brasov 500036 Romania Romanian Academy of Technical Science Bucharest Romania Department of Mathematics and Computer Science Transylvania University of Brasov Brasov 500036 Romania Faculty of Mechanical and Systems Engineering Esslingen University Esslingen 73728 Germany

The paper presents the results obtained in modeling the creep phenomenon of unidirectional composites reinforced with fibers. Thus, several models that have proven their validity and results obtained with their help are discussed. Analyzing a multitude of models described in the paper presented in references the authors describe the most used by the researchers. The micromechanical model, the homogenization method, the finite element method and the Mori–Tanaka formalism are described. These methods are most used in engineering applications studies in the last time. Following the analysis of each method, the advantages and disadvantages are presented and discussed. The results obtained are compared with experimental determinations. The application of the methods is done to composite materials reinforced with aligned carbon fiber. The methods are, sure, valid for every type of composite reinforced with fibers. Since the creep of materials is a frequently encountered phenomenon in practice, the knowledge of material properties and the existence of convenient calculation models become important for designers, which is why the paper presents the most used calculation methods to model this behavior. © The Author(s) 2022.

关键词： Carbon fiber Constitutive low Creep behavior Fiber reinforced composite Mechanical constants Viscoelastic model

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Component-Based Message Passing for Java: Developments, Achievements, and Impact

Component-Based Message Passing for Java: Developments, Achi...

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Software Services engineering (SSE) IEEE International Conference on

作者： Vladimir Getov Distributed and Intelligent Systems Research Group School of Computer Science and Engineering University of Westminster London United Kingdom

The pioneering research on message passing for Java (MPJ) which started after 1995 provided a crucially important framework and programming environment for parallel and distributed computing with Java. This framework resulted in an industry standard specification and a novel MPJ-based hierarchical development methodology for a new generation of large-scale distributed systems. The invention of a novel component-based model and methodology for rapid distributed software development and execution based on the MPJ work and achievements are the core contributions presented in this paper. Based on the high-performance Java component-based model, concepts and research results, grid, cloud, and extreme-scale computing represent a fundamental shift in the delivery of information technology services that has permanently changed the computing landscape.

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Hybrid System with Modified Cuckoo Search to Design Airfoil

Hybrid System with Modified Cuckoo Search to Design Airfoil

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Data science, Agents & Artificial Intelligence (ICDSAAI), International Conference on

作者： K. Thinakaran M. Anand T.Rajesh Kumar Saira Banu Atham K.M. Subramanian Department of Computer Science Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Data Science and Business Systems School of Computing SRM Institute of Science and Technology Kattankulathur Chennai Saveetha School of Engineering Saveetha Institute of Medical and Technical Science Department of Computer Science and Engineering School of CSE & IS Presidency University Bangaluru Department of Computer Science Engineering Shadan College of Engineering and Technology Hyderabad

The proposed models can design the airfoil by Cuckoo search with Levenberg-Marquardt. The Neural Network framework has impediments due to over-fitting. This paper proposed a modified cuckoo search. here the aerodynamic coefficient as an input to produce output the airfoil coordinates. The generated airfoil is compared to know its performance metrics. The Cuckoo search with the Feedforward Neural Network model yields the lowest prediction error.

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A Space-Efficient Digital Wallet Service in Blockchain systems

A Space-Efficient Digital Wallet Service in Blockchain Syste...

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IEEE International Conference on Big Data and Cloud Computing (BdCloud)

作者： Jingyu Zhang Jin Yang Chenghao Wu Lailong Luo School of Computer and Communication Engineering Changsha University of Science and Technology Changsha China Science and Technology on Information Systems Engineering Laboratory School of Systems Engineering National University of Defense Technology Changsha China

As an indispensable key network service in blockchain systems, digital wallet service is crucial for promoting the widespread application of blockchain technology and the development of the digital economy. However, with the increasing popularity of blockchain technology, the scale of the Unspent Transaction Output (UTXO) dataset continues to increase. A significant number of low-value UTXOs occupied the main dataset space, leading to blockchain dataset expansion. This has affected the performance of digital wallet service and the overall system performance. To address this issue, this paper proposes a Space-Efficient Digital Wallet (SEDW) service in blockchain systems. This strategy employs a Multidimensional Space Simulated Annealing (MSA) algorithm to obtain transaction input UTXOs. MSA can be combined with the UTXO dynamic adjustment mechanism, achieving the rapid consumption of low-value UTXOs without increasing the transaction fees. Experimental results demonstrate that the proposed SEDW strategy effectively optimized the selection of UTXOs in blockchain systems. It alleviated the expansion issue of the UTXO dataset, and controlled the generation of transaction fees, thereby achieving performance enhancement of digital wallet service.

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Machine Learning for Mesothelioma: Early Detection and Treatment

Machine Learning for Mesothelioma: Early Detection and Treat...

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Smart Generation Computing, Communication and Networking (SMART GENCON), International Conference on

作者： Bhavika Garg Tarun Jain Vijay Shankar Sharma Department of Computer Science and Engineering Manipal University Jaipur Department of IOT & Intelligent Systems Manipal University Jaipur

Mesothelioma is an extremely severe cancer that can easily transform into lung cancer. Mesothelioma diagnosis takes several months and treatment, including surgery, is expensive. Given the risk, early detection of Mesothelioma is essential for patient health, as it is connected to asbestos exposure. Various machine learning algorithms has been used in this research paper to compare with accurate results for mesothelioma detection. Support Vector Machine (SVM), Random Forest (RF), Decision Tree (DT), k Nearest Neighbourhood (k-NN), and Linear Regression (LR) are some of the machine learning methods being used. For this research paper, dataset is available on UCI, called the University of California Irvine [1]. The test dataset contains 264 instances, 35 characteristics and 8 performance measures, which is used to evaluate the classifiers accuracy. The average accuracy of XGB, RF, DT, SGD, LR and Voting Classifier are 100% each. Combing all the classifiers, helps us to break through the Mesothelioma data and the creation of data driven insights to improve patient care.

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A Method for Image De-Hazing for Vision Based Applications

A Method for Image De-Hazing for Vision Based Applications

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Computational Intelligence for Green and Sustainable Technologies (ICCIGST), International Conference on

作者： B V Santhosh Krishna A Senthil Anandhi G. Sharmila D Ramya L Balaji Baburao Pasupulati Computer Science and Engineering New Horizon College of Engineering Bangalore Karnataka India Computer Science and Engineering Karpagam College of Engineering Anna University Coimbatore Tamilnadu India Computer Science and Business Systems Sri Eshwar College of Engineering Coimbatore Tamilnadu India Electronics and Communication Engineering Veltech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Chennai Tamilnadu India Electrical & Electronics Engineering Veltech Rangarajan Dr.Sagunthala R&D Institute of Science and Technology Chennai Tamilnadu India

ISBN: (数字)9798350381887

ISBN: (纸本)9798350381894

The acquired images deteriorate in hazy or foggy circumstances, reducing the fidelity of the color, contrast, and visibility records. The atmospheric particles attenuate, scatter the source radiations are to be blame for this picture degradation. The corruption force relies upon assorted situations having a variable density of environmental particles, their frequency and distance from obtaining gadget. Existing picture dehazing strategies for apparent band pictures are either founded on earlier suspicion to reproduce the transmission map or utilized a learning system to straightforwardly gauge the dehazed picture. As of late, execution examination of existing well known picture dehazing techniques utilizing ghostly dim pictures are acted in which chose frequency groups from various for thickness levels are to be utilized for correlations. The correlation results are shown execution debasement of existing strategies with frequency groups determination and haze thickness levels. In this review, we plan a compelling ghastly and earlier based picture dehazing and upgrade network showing better execution when contrasted with existing strategies while utilizing phantom. Dim pictures from variable frequency groups and haze thickness levels. Our SPIDE-NET comprises of two organizations: 1) otherworldly Picture De-hazing Organization, which is prepared on multi-ghastly murky pictures between 450 nm and 720 nm, and exploits fluctuating constrictions in various frequency groups. 2) Multiscale Earlier based picture De-hazing Organization utilizes multi-scale dull channel and variety lessening priors on picture trios chose from a multiotherworldly foggy picture data set. The suggested approach is a CNN network in the encoder-decoder manner that combines data from both SID-Net and MPDNet by sharing a typical decoder stage. The SHIA dataset was used to create the suggested network, which was then assessed at various haze thickness levels. In comparison to well-known prior learning

关键词： Learning systems Correlation Image color analysis Reviews Force Phantoms Organizations Attenuation Decoding Image restoration

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AI-Based Detection and Analysis of Phishing Domains: Leveraging Machine Learning for Enhanced Cybersecurity

AI-Based Detection and Analysis of Phishing Domains: Leverag...

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IEEE International Conference on System, Computation, Automation and Networking (ICSCAN)

作者： R. Dhanalakshmi N. Vijayaraghavan Akhil Kumar B. Sahaya Beni Prathiba Center for Cyber Physical Systems School of Computer Science and Engineering Vellore Institute of Technology - Chennai Chennai India Department of Mathematics KCG College of Technology Chennai India SCSET Bennett University Greater Noida India Center for Cyber Physical Systems School of Computer Science and Engineering Vellore Institute of Technology Chennai India

ISBN: (数字)9798331510022

ISBN: (纸本)9798331510039

In the ever-evolving landscape of cyber security, the prevalence of phishing attacks poses a formidable threat to information security systems worldwide, compromising data integrity and eroding user trust. This paper introduces an innovative solution harnessing artificial intelligence to identify and analyze phishing domains, particularly focusing on newly registered domains from public databases like WHOIS. This approach is crucial as traditional security measures often prove insufficient against the sophistication of phishing tactics. Our proposed AI-driven system employs an analysis strategy. It utilizes machine learning to conduct an in-depth backend code and content analysis. This involves comparing suspect and legitimate sites for structural and syntactical disparities, utilizing deep learning models trained on extensive datasets of known phishing and authentic domains. These methodologies offer a nuanced evaluation, crucial for distinguishing sophisticated phishing attempts from genuine domains. Additionally, the system excels at identifying malicious links within these domains, enhancing its overall protective capabilities. The efficiency of our solution lies in its capacity for real-time, accurate threat detection. We introduce a probabilistic scoring mechanism that assesses the likelihood of a domain being a phishing site, facilitating informed decision-making for cyber security personnel. Furthermore, our system is designed for seamless integration into existing cyber security frameworks, providing versatility and ease of use.

关键词： Deep learning Content management Codes Phishing Focusing Probabilistic logic Threat assessment Real-time systems computer crime Long short term memory

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