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5th IEEE International Conference on Advances in Computing, Communication Control and Networking, ICAC3N 2023

作者： Gautam, Vandita Singh Katiyar, Shanu Sharma, Kavita Ojha, Rudra Pratap Computer Science And Engineering Galgotias College Of Engineering And Technology Greater Noida India Computer Science And Engineering G.L Bajaj Institute Of Technology And Management Greater Noida India

ISBN: (纸本)9798350330861

Nowadays it has become very difficult to tell the legitimacy of news on social media news blogs and online newspaper. Hence there is a need of tools that can check these sources to identify fake news. The automatic detection of false content in news stories is the main topic of this research. We start by introducing a dataset for the false news detection job. To categorize fake news, we applied language processing methods based on logistic regression. Tokenizing, stemming, stopwords removal and data quality checks (i.e., null or missing values), are some of the tasks carried out by the pre-processing algorithms. We have also used SVM algorithm for fake news identification. We also determine which of the two algorithms logistic Regression or SVM offer greater performance overall. © 2023 IEEE.

关键词： logistic regression

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Comparative analysis of WEdM performance of Nitronic-30 using different wire electrode materials

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International Journal of Machining and Machinability of Materials 2024年第3-4期25卷 375-407页

作者： Mohite, Nilesh Tanaji Patil, Geetanjali Vijay Department of Mechanical Engineering B.L.D.E.A’s V.P. Dr. P.G. Halakatti College of Engineering and Technology Affiliated to Visvesvaraya Technological University Belagavi Vijayapur Karnataka586103 India

In order to make the machining process sustainable, it is essential to understand the reasons and mechanisms influencing wire failure in order to save machining time and conserve resources. different electrode materials perform differently due to variations in conductivity, composition, and tensile strength. Thus, a thorough comparative investigation was conducted to understand the impact of zinc-coated wire, diffused wire, and gamma-coated wire during WEdM of Nitronic-30. The investigation involved measuring the material removal rate and surface roughness for different input parameters like pulse on time, pulse off time, peak current, and servo voltage. The findings revealed that zinc-coated wire material was not suitable for machining due to multiple wire breakage incidents. Gamma-coated wire emerged as the ideal candidate, exhibiting a significant improvement in MRR, with 7.38% more compared to zinc-coated wire and 28.84% more compared to diffused wire. Furthermore, economic justification indicated an 18.87% cost saving with the use of gamma-coated wire. Copyright © 2023 Inderscience Enterprises ltd.

关键词： Wire

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Review of the effect of foldability and working fluid on the performance of flexible pulsating heat pipe for foldable applications

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Materials Today: Proceedings 2023年 82卷 234-240页

作者： Solanki A. Kapadia R.G. Department of Mechanical Engineering Gujarat Technological University Ahmedabad 382424 India Department of Mechanical Engineering L. D. College of Engineering Ahmedabad 382424 India

Pulsating Heat Pipe (PHP) is the most successful device used for thermal management in different application areas. Although it is having complex thermo-hydrodynamics, many researchers carried out theoretical as well as experimental investigations and reported important information regarding its operational phenomenon like a start-up, flow pattern, thermal performance, etc. To date, the majority of PHPs are built with rigid materials such as aluminum, glass, steel, and copper because of the simplicity of fabrication, high thermal conductivity, and of course good workability. However, foldable electronic devices have recently seen an increase in demand due to their flexibility, confined space, lesser weight, and also durability, where rigid PHP may not be compatible. This in turn leads to develop a PHP that fulfills the demand for foldability. Therefore, the present paper attempts to review the developments of flexible PHPs especially made of polymer materials over the last decade. Moreover, this paper also highlights the problems associated with flexible PHPs like flexibility limitation, the high gas permeability of base material, and reduced thermal performance. The paper also tried to suggest possible solutions to such problems. The present paper will help future researchers to fabricate and design flexible thermal management systems for foldable applications. © 2023

关键词： Electronics cooling Flexible pulsating heat pipe Foldable electronics Non-conventional fluid Thermal performance

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Soft computing approaches for mechanical property predictions for polypropylene fibre in Fly Ash Mortar based machine learning

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Asian Journal of Civil engineering 2024年第3期26卷 1143-1151页

作者： Grover, R.K. Mishra, Vivek Kumar Sahu, Bharti deshmukh, Mrunalini Thenmozhi, S. Department of Civil Engineering Jabalpur Engineering College Madhya Pradesh Jabalpur 482011 India Department of Structural Engineering University Teaching Department CSVTU Chhattisgarh Bhilai Durg 491107 India Department of Computer Engineering Dr. D. Y. Patil Institute of Technology Pimpri Pune 411018 India Department of Civil Engineering Shree L. R. Tiwari College of Engineering Mira Rad Thane 401107 India Department of Civil Engineering KCG College of Technology Karapakkam Chennai 600097 India

The current study combines four techniques: multi-linear regression (MlR), artificial neural networks (ANN), support vector machine (SVM) and Random Forest (RF) to introduce a novel, alternative approach to predict compressive strength using artificial intelligence techniques and modulus of elasticity of polypropylene fibre Mortar mixed with fly ash. Inputs included cement content, Fly Ash, and polypropylene fibre;the output was mortar compressive strength and modulus of elasticity. The four methods were compared according to their accuracy and stability to predict compressive strength. The results from training and testing models have shown the great potential of MlR, ANN, SVM and Random forest in predicting the compressive strengths and modulus of elasticity of polypropylene fibre mortar. Further, the study demonstrated that SVM and ANN are preferable to MlR and Random forest when estimating experimental parameters. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2024.

关键词： ANN Fly Ash MlR Random forest glass fiber SVM

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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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2024 International Conference on Computational Intelligence for Green and Sustainable Technologies, ICCIGST 2024

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

ISBN: (纸本)9798350381887

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： demulsification

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Survey: An IOT Based Approach for Hybrid Security Management in Health Care for Secure Cloud Storage 11

Survey: An IOT Based Approach for Hybrid Security Management...

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11th International Conference on Emerging Trends in engineering and Technology - Signal and Information Processing, ICETET - SIP 2023

作者： Gogte, Purva Purve, Shravankumar Bhave, Roshni Pethe, dipali H.chandankhede, Pankaj Thakre, Bhakti P. Computer Science & Engineering Shri.Ramdeobaba College of Engineering and Management Nagpur India Computer Science & Engineering Yeshwantrao Chavan College of Engineering Nagpur India Computer Science & Engineering J D College of Engineering & Management Nagpur India Electronics and Telecommunication Engineering G.H Raisoni College of Engineering Nagpur India Rashtrasant Tukadoji Maharaj Nagpur University Department of Information Security Nagpur India

ISBN: (纸本)9798350348422

In some Emergency Situations, Patients must be monitored continuously and treated for. However, going to the hospital to perform such work is challenging due to time restraints. A virtual care monitoring system can help with this. With the rising use of cloud computing, the suggested system presents an efficient data science technique for IoT enabled healthcare monitoring systems that improve the productivity of data processing and the use of data in the cloud. IoT sensors in plenty are used to gather health care data. For the purposes of science processing, these data are stored in the cloud. An altered data science technique is initially introduced in the Healthcare Monitoring - data Science Technique (HM-dST). The Upgraded Pigeon Optimization (IPO) technique is used to arrange the data that is kept in the cloud, which helps to increase prediction accuracy. The best method for selecting features is then illustrated for the removal and features selection. In order to analyze human healthcare, a backtracking search-based deep neural network (BS-dNN) is used. The performance of our system is then assessed using various real-time healthcare datasets, and changes are observed using the current smart healthcare monitoring systems. To assist the medical community in early detection of a patient's primary organs' health status, allowing for proper treatment, as well as to securely store patient health data in the cloud. The goal of the project is to demonstrate how the sensory system can be used to track a patient's movement invisibly. © 2023 IEEE.

关键词： Internet of things

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Channel-Feedback-Free Transmission for downlink Fd-RAN:A Radio Map Based Complex-Valued Precoding Network Approach

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China Communications 2024年第4期21卷 10-22页

作者： Zhao Jiwei Chen Jiacheng Sun Zeyu Shi Yuhang Zhou Haibo Xuemin(Sherman)Shen School of Electronic Science and Engineering Nanjing UniversityNanjing 210023China College of Information Science and Electronic Engineering Zhejiang UniversityHangzhou 310058China Department of Mathematics and Theories Peng Cheng LaboratoryShenzhen 518000China Department of Electrical and Computer Engineering University of WaterlooWaterlooOntarioN2L 3G1Canada

As the demand for high-quality services proliferates,an innovative network architecture,the fully-decoupled RAN(Fd-RAN),has emerged for more flexible spectrum resource utilization and lower network ***,with the decoupling of uplink base stations and downlink base stations in FdRAN,the traditional transmission mechanism,which relies on real-time channel feedback,is not suitable as the receiver is not able to feedback accurate and timely channel state information to the *** paper proposes a novel transmission scheme without relying on physical layer channel ***,we design a radio map based complex-valued precoding network(RMCPNet)model,which outputs the base station precoding based on user *** comprises multiple subnets,with each subnet responsible for extracting unique modal features from diverse input ***,the multimodal embeddings derived from these distinct subnets are integrated within the information fusion layer,culminating in a unified *** also develop a specific RMCPNet training algorithm that employs the negative spectral efficiency as the loss *** evaluate the performance of the proposed scheme on the public deepMIMO dataset and show that RMCPNet can achieve 16%and 76%performance improvements over the conventional real-valued neural network and statistical codebook approach,respectively.

关键词： beamforming complex neural networks deep learning Fd-RAN

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Impact of IoT data Integration on Real-Time Analytics for Smart City Management 10

Impact of IoT Data Integration on Real-Time Analytics for Sm...

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10th International Conference on Communication and Signal Processing, ICCSP 2024

作者： lakshmi, d. Jeyarani, J. Suguna, R. Muneeshwari, P. Valantina, G.Mary Jayaraman, Suganya Panimalar Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai India Care College of Engineering Department of Electronics and Communication Engineering Tamil Nadu Trichy India Vel Tech Rangarajan Dr. Sagunthala R&d Institute of Science and Technology Department of Computer Science and Engineering Chennai Tamil Nadu Avadi India Rajalakshmi Engineering College Department of Computer Science and Engineering Tamil Nadu Chennai India Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Department of Computer Science and Engineering Tamil Nadu Chennai India Adhiparasakthi Engineering College Department of Electronics and Communication Engineering Tamil Nadu Melmaruvathur India

ISBN: (纸本)9798350353068

The paper in illustration will emphasize the necessity for an IoT big data and analytics on time fusion as a futuristic smart city management approach. The framework deals with the main problems observed in data assimilation, analytics, security and scalability. As a result, cities will enjoy the services and operations utilization of the urban data with the precision. Our approach is based upon the data collection with the use of the edge technologies, preprocessing, integration, and analysis of the data resulting in the creation of the tools of machine learning and the adoption of interoperability standards. The results have especially brought to the limelight the fantastic performance of the live analytics pipeline when considered as a whole, and the impressive throughput of 5,000 events per second alongside the very low latency of 50 milliseconds, indicating how the urban information flow is processed in the blink of an eye. With AI therein creating the precision rate of 88.7%-95.2%, which therefore means this level of an urban situation can pronounce a traffic congestion and air quality fluctuations. The situation where security systems that involve encryption, access controls, and privacy-preserving protocols, among other mechanisms, have been used for the management of urban data in a safe manner, away from any unauthorized people and hackers, is factual. For the sake of achieving scalability, the replacement of certain bottlenecks is applied in the system by means of horizontal scaling and optimal performance procedures assisting smart cities handle their increasing quantity of data. Usually the results are factorized to bring out the fact that the particular methodology is strong and thus can be used in real practice to transform and enhance urban resilience level. © 2024 IEEE.

关键词： Smart city

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SQlIMl: A Comprehensive Analysis for SQl Injection detection Using Multiple Supervised and Unsupervised learning Schemes

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SN computer Science 2023年第3期4卷 281页

作者： Mehta, dhruv Suhagiya, Hartik Gandhi, Harvy Jha, Manish Kanani, Pratik Kore, Aniket Department of Computer Engineering D.J. Sanghvi College of Engineering Bhaktivedanta Swami Rd Maharashtra Mumbai 400056 India

SQl injection is a security concern that affects the majority of program’s that are built upon various types of databases. According to researchers, it is found that SQl injection is mainly vulnerable to database-driven software. The disadvantages of previously developed SQlI models include their inability to identify novel patterns;instead, they will only detect those that they have previously seen or have been trained on. Our model will be capable of determining how much of the data being entered has been SQl-injected by looking for patterns in the input. Our system will be able to recognize all injection procedures. All attributes will be extracted and chosen by the model. The text should only have to be entered once by the user. It can also be scaled and adapted to a variety of purposes. © 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte ltd.

关键词： detection Prevention Security SQl injection

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Exploring deep learning Methods for computer Vision Applications across Multiple Sectors:Challenges and Future Trends

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computer Modeling in engineering & Sciences 2024年第4期139卷 103-141页

作者： Narayanan Ganesh Rajendran Shankar Miroslav Mahdal Janakiraman SenthilMurugan Jasgurpreet Singh Chohan Kanak Kalita School of Computer Science and Engineering Vellore Institute of TechnologyChennai600127India Department of Computer Science and Engineering Koneru Lakshmaiah Education FoundationVaddeswaram522502India Department of Control Systems and Instrumentation Faculty of Mechanical EngineeringVSB-Technical University of OstravaOstrava70800Czech Republic Department of Computer Science and Engineering Vel Tech High Tech Dr.Rangarajan Dr.Sakunthala Engineering CollegeChennai600062India Department of Mechanical Engineering and University Centre for Research&Development Chandigarh UniversityMohali140413India Department of Mechanical Engineering Vel Tech Rangarajan Dr.Sagunthala R&D Institute of Science and TechnologyAvadi600062India

computer vision(CV)was developed for computers and other systems to act or make recommendations based on visual inputs,such as digital photos,movies,and other *** learning(dl)methods are more successful than other traditional machine learning(Ml)methods *** techniques can produce state-of-the-art results for difficult CV problems like picture categorization,object detection,and face *** this review,a structured discussion on the history,methods,and applications of dl methods to CV problems is *** sector-wise presentation of applications in this papermay be particularly useful for researchers in niche fields who have limited or introductory knowledge of dl methods and *** review will provide readers with context and examples of how these techniques can be applied to specific areas.A curated list of popular datasets and a brief description of them are also included for the benefit of readers.

关键词： Neural network machine vision classification object detection deep learning

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