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Dynamic Weight Allocation–Based Network Security and Anomaly Detection Model for Intelligent VANETs

Transactions on Emerging Telecommunications Technologies 2025年第6期36卷

作者： Aadam Quraishi Rakeshnag Dasari Sushilkumar Dangiya Sateesh Kumar Nallamala Krishna Kanth Kondapaka Swaroop Reddy Gayam Isa Bayhan Uguloy Berdieva Rubal Jeet M.D. Research Cognitive and AI laboratory Interventional treatment institute Houston Texas USA Department of CSE Acharya Nagarjuna University Nagarjuna Nagar Guntur India Department of Electronics and Communication Engineering GTU – School of Engineering and Technology Ahmedabad India Independent Researcher USA Independent Researcher California USA Independent Researcher and Senior Software Engineer at TJMax USA Assistant Professor of Tourist Guiding Dept Bolu Abant Izzet Baysal University Golkoy Campus Bolu Turkey The Department of Tax and Taxation Tashkent State University of Economics Tashkent Uzbekistan Chandigarh Group of Colleges Jhanjeri Chandigarh Engineering College Department of Computer Science and Engineering Punjab India

Determining the weights of evaluation metrics is one of the key factors influencing the cybersecurity and anomaly detection of intelligent vehicular ad hoc networks (VANETs). To address the limitations of traditional weighting methods, which often overlook the impact of changes in metric attribute states on evaluation weights, this paper proposes a dynamic weight allocation–based network security and anomaly detection model. The model begins by decomposing and analyzing the security and anomaly detection objectives of VANETs, constructing a comprehensive evaluation metric system. The network security assessment model for VANETs presented in this research overcomes the drawbacks of conventional static models by utilizing a dynamic weight allocation technique. Based on current network conditions, a state variable weight method was created that dynamically computes security values by combining incentive and penalty mechanisms. A ranking-based weighting algorithm is employed to analyze the correlation between security and anomaly detection metrics. Subsequently, the proposed dynamic weight allocation algorithm calculates the dynamic weights of individual metrics within the system, enabling a robust assessment of network security and anomaly detection for intelligent VANETs. The evaluation results provide security level classifications and identify anomalies effectively. Experimental results demonstrate that the model significantly enhances the rationality and accuracy of intelligent VANET evaluations, contributing to improved cybersecurity and anomaly detection.

关键词： anomaly detection dynamic weight allocation intelligent vehicle network security VANETs

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TimeTubes: Visual Exploration of Observed Blazar Datasets

TimeTubes: Visual Exploration of Observed Blazar Datasets

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International Meeting on High-Dimensional Data-Driven science, HD3 2017

作者： Fujishiro, Issei Sawada, Naoko Nakayama, Masanori Wu, Hsiang-Yun Watanabe, Kazuho Takahashi, Shigeo Uemura, Makoto Center for Information and Computer Science Keio University 3-14-1 Hiyoshi Kohoku-ku Yokohama223-8522 Japan Institute of Computer Graphics and Algorithms TU Wien Favoritenstr. 9 / 5. Stock ViennaA-1040 Austria Department of Computer Science and Engineering Toyohashi University of Technology 1-1 Hibarigaoka Tempaku-cho Toyohashi441-8580 Japan School of Computer Science and Engineering University of Aizu Aizu Wakamatsu Fukushima965-8580 Japan Astrophysical Science Center Hiroshima University 1-3-1 Kagamiyama Higashi-Hiroshima739-8526 Japan

Blazars are attractive objects for astronomers to observe in order to burrow into the magnetic field in the relativistic jet. This paper presents TimeTubes as a novel visualization scheme that allows astronomers to interactively explore characteristic temporal variation patterns in observed blazar datasets. In the TimeTubes spatialization, the two Stokes parameters and their errors with a common timestamp are transformed into an ellipse. A series of such ellipses are aligned in parallel along the timeline to form a 3D volumetric tube. The resulting tube is then colorized by the observed intensities and colors of the blazar, and finally volume-rendered. A designated user interface is provided with visual exploration functions according to Shneiderman's Visual Information Seeking Mantra. In the latest version, an auxiliary mechanism, called visual data fusion, was incorporated to ameliorate data- and mapping-inherent uncertainties for more efficient and effective visual exploration. © Published under licence by IOP Publishing Ltd.

关键词： Data fusion

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Predicting the Customer Behavior Through Web Page and Content Mining Techniques

Predicting the Customer Behavior Through Web Page and Conten...

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International Conference on Communication, Computing and Internet of Things (IC3IoT)

作者： VM Sundharam M.S. Sriramm Priya Pachhaiammal Computer Science and Engineering Sri Sairam Institute of Technology Chennai India Assistant Professor Computer Science and Engineering Sri Sairam Institute of Technology Chennai India

ISBN: (纸本)9781538624609;9781538624593

The ideology of the people has changed over the decades, with the people's interest shifting towards a more closed environment, thinking about themselves, rather than their environment, consisting of their kith and kin and others. The result of this isolation is that the mental psychology of the people changes in accordance with the technological advancement. The major disadvantage is that the people's mental psychology could not be identified to follow any specific pattern. But the root of the tree is clear, the technology. Hence the analysis of the behavior of the user is done by allowing them answer a series of questions.

关键词： Handheld computers Internet of Things Amplitude modulation

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Discovering Clusters of nearby Routes in Spatial Networks

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IOP Conference Series: Materials science and Engineering 2019年第1期590卷

作者： Vellampalli Vikas Debasish Das B. Bharathi student Department of Computer Science and Engineering Sathyabama Institute of Science and Technology professor Department of Computer Science and Engineering Sathyabama Institute of Science and Technology

Now-a-days finding which is the best path to travel from one place to another place is difficult and also confusing. So TSR(Trajectory search by regions of interest) query is *** query takes set of inputs called places and returns best possible path to travel between this two places. To find this best path, decision tree(best first search) and naïve bayes classification along with sentiment analysis are being used.

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Design and Development of 'VR + Arduino' Immersion Interactive Experiment Case

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Journal of Physics: Conference Series 2021年第3期1802卷

作者： Jiu Yong Yangping Wang Jianwu Dang Introduction of Computer Science and Technology Experimental Teaching Demonstration Center of national Lanzhou Jiaotong University LanZhou 730070 China The National Virtual Simulation Experiment Teaching Center of Railway Traffic Information and Control Lanzhou Jiaotong University Lanzhou 730070 China Gansu Provincial Engineering Research Center for Artificial Intelligence and Graphics & Image Processing LanZhou 730070 China

In order to guide students to master Arduino development board, sensors, unity3d and other software and hardware application methods, familiar with the development process of virtual reality and intelligent hardware control platform. Learning from the WeChat 'jump and jump' finger game, based on virtual reality technology and Arduino intelligent hardware control platform, the virtual intelligent fitness device with good immersion, strong interactivity, and combining entertainment, exercise and virtual experience is developed and designed. The 'virtual reality + Arduino' immersion interactive experimental platform provides immersive and interactive immersive helmet and desktop screen display modes, uses a variety of intelligent control methods such as in-situ jumping action or grip to replace the finger pressing action in WeChat to control the jump of the game model, and can choose the sky, ocean, land and other fitness Scene, to achieve physical exercise and intellectual purposes. In the process of case design and production, virtual reality immersion equipment, grip and running pad are combined with fitness to cultivate students' comprehensive practical innovation ability.

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A Methodology to Determine the Sites of Variability in an LED Assembly

A Methodology to Determine the Sites of Variability in an LE...

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IEEE Symposium on Semiconductor Thermal Measurement and Management (SEMI-THERM)

作者： Robin Bornoff Thomas Mérelle Josephine Sari Alessandro Di Bucchianico Gabor Farkas Mentor Graphics Mechanical Analysis Division 81 Bridge Road Hampton Court Surrey UK Pi-Lighting Avenue Ritz 19 Sion Switzerland Department of Mathematics and Computer Science 513 Eindhoven University of Technology MB Eindhoven The Netherlands Mentor Graphics Mechanical Analysis Division Infopark D Gábor Dénes u. 2 Budapest Hungary

ISBN: (数字)9781735532509

ISBN: (纸本)9781728191294

Variations in the manufacturing assembly process together with any changes in materials sourcing can give rise to variation in the functional performance of an LED. These variations can lead to differences in thermal characteristics such as Zth (transient thermal impedance) and RthJC (thermal resistance between chip junction and case. This study aims to analyze the measured variations of a number of LED samples and explore a methodology that will provide insights into the root cause of those variations, In addition the statistical properties of the variations are applied in a Monte Carlo thermal modelling context. Such insights and modelling methods would be employed by a lighting engineer when selecting LEDs and when simulating their thermal dependent optical behavior.

关键词： LED Structure Function Variation Light emitting diodes SMIM10L2A gene Variation structure functions ROOT CAUSES functional performance assembly process thermal characteristics

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CIRCA: comprehensible online system in support of chest X-rays-based COVID-19 diagnosis

arXiv

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arXiv 2022年

作者： Prazuch, Wojciech Suwalska, Aleksandra Socha, Marek Tobiasz, Joanna Foszner, Pawel Jaroszewicz, Jerzy Gruszczynska, Katarzyna Sliwinska, Magdalena Walecki, Jerzy Popiela, Tadeusz Przybylski, Grzegorz Cieszanowski, Andrzej Nowak, Mateusz Pawlowska, Malgorzata Flisiak, Robert Simon, Krzysztof Zapolska, Gabriela Gizycka, Barbara Szurowska, Edyta Marczyk, Michal Polanska, Joanna Department of Data Science and Engineering Silesian University of Technology Gliwice Poland Department of Computer Graphics Vision and Digital Systems Silesian University of Technology Gliwice Poland Department of Infectious Diseases and Hepatology Medical University of Silesia Katowice Poland Department of Diagnostic Imaging Voivodship Specialist Hospital Wroclaw Poland Department of Diagnostic Radiology Central Clinical Hospital of The Ministry of Internal Affairs and Administration Warsaw Poland Department of Radiology Jagiellonian University Medical College Krakow Poland Department of Lung Diseases Cancer and Tuberculosis Kujawsko-Pomorskie Pulmonology Center Bydgoszcz Poland Department of Imaging Diagnostics National Institute of Oncology Warsaw Poland Department of Radiology Silesian Hospital Cieszyn Poland Department of Infectious Diseases and Hepatology Collegium Medicum in Bydgoszcz Nicolaus Copernicus University Torun Poland Department of Infectious Diseases and Hepatology Medical University of Bialystok Bialystok Poland Department of Infectious Diseases and Hepatology Wroclaw Medical University Wroclaw Poland Department of Radiology Czerniakowski Hospital Warsaw Poland PDepartment of Imaging Diagnostics MEGREZ Hospital Tychy Poland 2nd Department of Radiology Medical University of Gdansk Poland Yale Cancer Center Yale School of Medicine New HavenCT United States

Background: Due to the large accumulation of patients requiring hospitalization, the COVID-19 pandemic disease caused a high overload of health systems, even in developed countries. Deep learning techniques based on medical imaging data can help in the faster detection of COVID-19 cases and monitoring of disease progression. However, regardless of the numerous proposed solutions using lung X-rays, none of them is a product that can be used in the clinic. Methods: Five different datasets (clinical POLCOVID and AIforCOVID databases, a public collection of images called COVIDx set, pneumonia patients from NIH, and artificially generated data) were used to construct a representative dataset of 23 799 CXRs for model training, 1 050 images as a hold-out test set and 44 247 CXRs as independent test set (BIMCV database). A U-Net-based model was developed to identify a clinically relevant region of the CXR that contains the lungs and each class (normal, pneumonia, and COVID-19) was divided into 3 subtypes using a 2D Gaussian mixture model. A decision tree was used to aggregate predictions from the InceptionV3 convolutional network based on processed CXRs and a dense 7-layer neural network on radiomic features determined independently for the upper, middle, and lower lung fragments. Results: The lung segmentation model gave the Sorensen-Dice coefficient of 94.86% in the validation dataset, and 93.36% in the testing dataset. In 5-fold cross-validation, the accuracy for all classes ranged from 91% to 93%, keeping slightly higher specificity than sensitivity. Also, NPV was higher than PPV for each class to guarantee a low rate of false negative cases. In the hold-out test set, the balanced accuracy ranged between 68% and 100%. The highest performance was obtained for the subtypes N1, P1, and C1, while images assigned to subtypes N3, P3, or C3 have been wrongly predicted among themselves. A similar performance was obtained on the independent dataset for normal and COVID-19 class

关键词： COVID-19

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Innovative Task Scheduling Algorithm in Cloud Computing

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IOP Conference Series: Materials science and Engineering 2020年第2期981卷

作者： S. Magesh Kumar V. Auxilia Osvin Nancy A Balasundaram Seena Naik korra D Kothandaraman E Sudarshan Associate Professor Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Chennai Tamil Nadu India Assistant professor Department of IT S. A. Engineering College Chennai Tamil Nadu India Assistant Professor Center for Cyber Physical Systems (CPS) School of Computer Science and Engineering Vellore Institute of Technology (VIT) Chennai Tamil Nadu India Associate Professor School of Computer Science and Artificial Intelligence S R University Warangal India Associate Professor Sumathi Reddy Institute of Technology for Women Warangal India

This work concentrates around the task scheduling depends on QoS and imperative of desire. Under nature of vibrant cloud computing, effectiveness improving of scheduling of task and load balancing are interminable issues. For clients, be that as it may, it's progressively imperative to meet their necessities of QoS. This paper identifies with an improvement decency intention depends on new Berger's model under the earth of vibrant cloud computing. As indicated by the distinctive kind of task scheduling, we portray the need of decency, proficiency and the Balance among advantage and reasonableness separately. We recompile the CloudSim and recreate the three undertaking task scheduling above based on expanded CloudSim individually. The exploratory outcomes show that this calculation portion not just meet the guideline of offering need to profit with because of thought to decency, yet additionally address clients' issues of orchestrated QoS.

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Study on Techniques for Analyzing Semantic Similarity in Question Answering System

Study on Techniques for Analyzing Semantic Similarity in Que...

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International Conference on Trends in Electronics and Informatics (ICEI)

作者： K.M. Shivani M.R. Aswathy PG Scholar. Computer Science and Engineering Vidya Academy of Science and Technology Kerala India Asst. Professor. Computer Science and Engineering Vidya Academy of Science and Technology Kerala India

Semantic similarity standards are an inevitable factor in Natural Language Processing tasks. Semantic similarity uses actual meaning of words to decide similarity. Semantic similarity only contains “is a” relation. However Semantic similarity standards developed for regular use do not perform well within specific domains. Sentiment analysis, Natural language understanding, Machine translation, artificial intelligence, psychology and cognitive science are a few of the important areas where it is employed. The paper contains a study of the state of art measures containing path based measures, information based measures, feature based measures and hybrid measures. The features, performance, advantages, disadvantages and related issues of different standards are discussed. This paper gives a review of semantic similarity standards with different approaches.

关键词： Semantics Knowledge discovery Conferences Standards Natural language processing Market research

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Design of energy efficient datacenter with optimized virtual infrastructure

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AIP Conference Proceedings 2020年第1期2271卷

作者： K. MuthuPandi K. Somasundaram 1Research Scholar department of computer science Bharathiar University Coimbatore India. 2Professor department of CSE Chennai institute of technology Chennai India.

The Cloud computing concepts provide everything as a service to global users without any limitation on regions and technology. The individual user requirement, medium or large scale industry needs will be fulfill virtual infrastructure bycloud service provider with less cost. The existing most of data center has major issue on energy management, pollution and carbon emission. The power conception would be monitor in all the levels in data center helps to implementing optimizationtechnique will be to reduce energy usage. The server consolidation, schedule, optimization, automation technique will reduce power and carbon emission. The effective hardware and software usage and selection of right power source also reducepollution. This paper has been used virtualization technology for the green cloud data center to provide resources such asapplication, desktop VDI, hosted servers and server virtualization. Those resources have been hosted on hypervisors. It was monitoring and based on resource usage category, load, priority, threshold and implemented possible optimization, to reduceenergy. The experimental setup based on monitoring data and implemented referred optimization techniques helps to achievereduce energy and carbon emission.

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