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Graph-Informed Neural Networks with Green Anaconda Optimization Algorithm Based on Automated Classification of Condition of Mental Health Using Alpha Band EEG Signal

Graph-Informed Neural Networks with Green Anaconda Optimizat...

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Sustainable Expert Systems (ICSES), International Conference on

作者： Sumit Kushwaha Sivakrishna Kondaveeti S. Mary Vasanthi Thamba Meshach W D. Leela Rani J. Megala Department of Computer Applications University Institute of Computing Chandigarh University Punjab India Department of CSE-AIML MLR Institute of Technology Hyderabad Telangana India Department of Electronics and Communication Engineering St Xavier's Catholic College of Engineering Nagercoil Tamil Nadu India Department of Computer Science and Engineering Prathyusha Engineering College Chennai Tamil Nadu India Department of Electronics and Communication Engineering School of Engineering Mohan Babu University Tirupati Andhra Pradesh India Department of Electrical and Electronics Engineering S.A.Engineering College Tamil Nadu India

ISBN: (数字)9798331540364

ISBN: (纸本)9798331540371

Mental Health Status (MHS) Using Alpha Band EEG Signal” is the process of evaluating and categorizing a person's mental state by examining the electroencephalogram (EEG) recording of their alpha wave activity, which usually occurs between 8 and 13 Hz. The goal of this method is to find alpha wave patterns that correspond, but the existing methods have IoT of disadvantages such as, low precision, low accuracy and high error rate. mental health issues. To overcome these problems, Graph-informed neural networks with Green Anaconda Optimization Algorithm (G-INN- GAOA) is proposed. In this, input data is taken from two dataset such as AVEC2013 and AVEC2014 datasets. It pre-processed data using Memory-Boosted Guidance Filtering (M-BGF), Following that, Next, the Alpha Band EEG Signal for Mental Health Status is the features extracted using One-Dimensional Spectrum (O-DS), Following that Feature selection using White Shark Optimizer (WSO) and classification Graph-informed neural networks (G-INN) and the optimization using Green Anaconda Optimization Algorithm (GAOA) for detecting the type of Mental Health Status and to find the Neutral, Focus, Relax for MHS. The introduced system is executed in python. The efficiency of the proposed BAQNN-SGA is analyzed using a datasets and attains 99.9% accuracy, 99.8% recall and attains better results compared with the existing methods. This indicates the approach's superior efficiency and potential for further development in the field.

关键词： Accuracy Filtering Error analysis Neural networks Mental health Sharks Feature extraction Electroencephalography Classification algorithms Optimization

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Implementation of an Effective Methodology to Avoid DDoS Attacks using Cybersecurity Norms

Implementation of an Effective Methodology to Avoid DDoS Att...

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Intelligent and Innovative Technologies in Computing, Electrical and Electronics (IITCEE), International Conference

作者： R Balamurugan B. Anni Princy D. Kanchana M. Murugesan A Josphin Selsia M Dinesh Department of Artificial Intelligence and Machine Learning AJK College of Arts and Science Coimbatore Tamil Nadu India Department of Computer and Communication Engineering Panimalar Engineering College Chennai Tamil Nadu India Department of Computer Applications SRM Institute of Science and Technology Chennai Tamil Nadu India Department of CSE Vel Tech Multi Tech Dr. Rangarajan Dr. Sakunthala Engineering College Chennai Tamil Nadu India Department of ECE Prince Shri Venkateshwara Padmavathy Engineering College Chennai Tamil Nadu India Department of VLSI Microelectronics Saveetha School of Engineering SIMATS Chennai Tamil Nadu India

Today’s world wouldn't function without the Internet. Because the internet is a universal resource for information gathering, its accessibility is crucial. This research focuses on the Distributed Denial of Service (DDoS) attack because of the severe impact it has on network availability. DDoS attacks work by flooding the target with a large amount of unauthorized data, thereby occupying its available bandwidth as well as preventing genuine traffic from passing throughout. Modern cyber attacks are highly complex and difficult to detect in a decentralized network. In a distributed context, Denial of Service (DoS) and Distributed Denial of Service (DDoS) assaults induce resource unavailability. This has spurred the scientific community to develop viable ways in dispersed situations as a means of minimizing such attacks. This research focuses on the Distributed Denial of Service assault due to its devastating effects on network accessibility as a result of its flood of illegal data that usurps the victim’s bandwidth and stifles the flow of lawful traffic. This paper introduces a new method for detecting DDoS attacks, the Novel Attack Detection Protocol (NADP), and validates its effectiveness by comparing it to a more traditional routing protocol, Dynamic Source Routing (DSR). We have also detailed the various methods used in distributed denial of service attacks on Internet service providers. The goal of this project is to identify potential solutions to this problem, including methods for preventing and mitigating these attacks.

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Anomaly Detection in Conventional Meters and Electricity Consumption Using Optimized Extreme Gradient Boosting

Anomaly Detection in Conventional Meters and Electricity Con...

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Distributed Computing and Electrical Circuits and Electronics (ICDCECE), IEEE International Conference on

作者： Laith H. Alzubaidi B. Sathyavani Mamatha Bai B G Papiya Dutta N. Naga Saranya Department of Computers Techniques Engineering College of Technical Engineering The Islamic University Najaf Iraq Department of Electrical and Electronics Engineering SR University Warangal India Department of CSE Nitte Meenakshi Institute of Technology Bengaluru Karnataka India Department of Electronics and Communication Engineering Bharat Institute of Engineering and Technology Hyderabad India Department of Computer Applications Saveetha College of Liberal Arts & Science SIMATS Chennai India

ISBN: (数字)9798350318609

ISBN: (纸本)9798350318616

With the progress of innovative information technologies, smart energy meters have designed a substantial quantity of real-time electricity consumption. Energy consumption is based on the various factors such as humidity, building area, temperature, habitation and so on and these factors are cooperatively describing the energy meter background. The smart meter supports to capable to identify data abnormalities for efficient monitoring as well as investigation. The anomaly detection supports for better decision making for minimizing the energy consumption. In this research, Machine Learning (ML) approach of Optimized Extreme Gradient Boosting (OXGBoosting) for the detection and classification of anomaly for energy consumption in conventional meters. This research collects the large-scale anomaly dataset for estimating the effectiveness. The proposed method is estimated by various performance metrices and it achieves an accuracy of 0.95, precision of 0.92, recall of 0.92, F1-score of 0.91 and AUC of 0.95 respectively when compared to the previous studies such as Extreme Gradient Boosting (XGB), Two-Class Boosted Decision Tree and NGBoost.

关键词： Meters Energy consumption Temperature Electricity Boosting Feature extraction Smart meters

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Machine Learning Approaches for Efficient Traffic Flow in Smart Cities

Machine Learning Approaches for Efficient Traffic Flow in Sm...

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Electrical Power Engineering, Communication and Computing Technology(ODICON), Odisha International Conference on

作者： Aniket Kulkarni P. Anitha John Yesudas Valluri M V Sunena Rose U Hemavathi Omar M. Hussein Software QA Manager Drata Inc San Diego CA USA Department of Computer Applications Kalasalingam Academy of Research and Education Srivilliputhur Tamil Nadu India Faculty of Management Studies CMS Business School Jain (Deemed-to-be University) Bengaluru India Department of Computer Science and Engineering Jain (Deemed-to-be University) Bengaluru India Department of CSE Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Avadi Chennai India Medical Technical College Medical Instrumentation Engineering Al-Farahidi University Baghdad Iraq

ISBN: (数字)9798350354379

ISBN: (纸本)9798350354386

These days, a lot of towns struggle with traffic jams during peak hours, which increment contamination, commotion, and feelings of anxiety for the general population. Because neural networks (NN) and machine learning (ML) techniques can handle large numbers of parameters in massive amounts of data and dynamic behaviour over time, they are replacing analytical and statistical methods in the solving of real-world problems. This research presents a convergence of machine-learning (ML) and deep-learning (DL) calculations for traffic stream prediction; this paves the way for flexible traffic signals, which can be implemented through the use of a calculation that adjusts the timing in accordance with the anticipated traffic flow or by controlling traffic signals to some degree. The proposed ML and DL models are constructed, validated, and tested using two publicly accessible datasets. The first depicts the total number of cars subjected to checks using various sensors at six junctions over the course of 56 days. In this research, ML and DL models are created using data from four of the six junctions. The excellent performance metrics obtained by all ML and DL computations suggest that their application to intelligent traffic light management is feasible.

关键词： Measurement Power engineering Machine learning algorithms Statistical analysis Smart cities Transportation Machine learning Prediction algorithms Timing Junctions

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A Novel Method of Evaluating the Harmonic Power Analyzer's Performance for PC-Based Testing and Measurement applications Related to Electromagnetic Compatibility

A Novel Method of Evaluating the Harmonic Power Analyzer's P...

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Computing and Data Analytics (ICCDA), International Conference on

作者： J Adeline Sneha N. R Wilfred Blessing Suresh Palarimath S Poorana Senthilkumar Manigandansekar G Sutherlin Subitha School of Computing Asia Pacific University of Technology & Innovation Kuala Lumpur Malaysia College of Computing and Information Sciences University of Technology and Applied Sciences Ibri Sultanate of Oman College of Computing and Information Sciences University of Technology and Applied Sciences Salalah Sultanate of Oman Department of Computer Applications Dr. N. G. P Arts and Science College Coimbatore Tamil Nadu Newyork University Abudhabi United Arab Emirates Department of Computer Science and Engineering Stella Mary's College of Engineering Kanyakumari Dt Tamil Nadu

ISBN: (数字)9798331542573

ISBN: (纸本)9798331542580

This paper discusses the methods for performance analysis of a PC-based harmonic power analyzer used in EMC testing and measuring applications. According to IEC 61000-3-2, this is an easy-to-use, reasonably priced way to assess how well a harmonics emission measurement system is performing in real time. There is no mention of any alternative approach or calibration method to verify the performance analysis in the IEC 61000-3-2 standard. Different vendor equipment is used to create a single harmonic emission monitoring setup. Thus, getting calibrating services is a highly difficult task that also requires a significant financial investment. Using this straightforward, low-cost analysis technique, it is possible to monitor the operation of the measurement setup locally and address all of these problems. Overall, the paper provides a comprehensive overview of the new approach to performance analysis of a PC-based harmonics power analyzer for EMC test and measurement applications, emphasizing the importance of a simple, cost-effective, and reliable method for maintaining measurement system performance.

关键词： Power measurement Power system harmonics Harmonic analysis Electromagnetic compatibility Real-time systems Performance analysis IEC Standards Standards Monitoring Testing

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SDN-Enhanced Cloud Computation: A Systematic Taxonomy

SDN-Enhanced Cloud Computation: A Systematic Taxonomy

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2024 International Conference on Communication, Computing and Energy Efficient Technologies, I3CEET 2024

作者： Sapaev, B. Kuppuraj, T. Al-Jawahry, Hassan M. Kumar, Sanjeev Khandelwal, Utkal Giri, Neeraj Alfraganus University Faculty of Medicine Department of Pharmaceuticals and Chemistry Tashkent Uzbekistan Western Caspian University Baku Azerbaijan Karpagam Academy of Higher Education Department of Computer Applications Coimbatore India The Islamic University College of Technical Engineering Department of Computers Techniques Engineering Najaf Iraq The Islamic University of Al Diwaniyah College of Technical Engineering Department of Computers Techniques Engineering Al Diwaniyah Iraq Chandigarh Engineering College Chandigarh Group of Colleges Department of Computer Application Jhanjeri Punjab Mohali140307 India Gla University Institute of Business Management Mathura India Ies Institute of Technology and Management Ies University Department of Computer Science & Engineering M.P. Bhopal462044 India

ISBN: (纸本)9798331541583

By bifurcating the control and data-forwarding hardware, a new era in networking has emerged that could well serve network customization at IN function level to realise programmability and dynamic reconfiguration capabilities. Given such a paradigm shift, it is easy to see why cloud computing holds so much promise as well - the way in which resources are consumed on-demand. Although experts have expressed interest in integrating SDN (Software-Defined Networking) with cloud computing, there are still problems that need to be addressed. This paper addresses these gaps by providing a taxonomy that characterizes fundamental cloud computing capabilities in an SDN-enabled environment, based on each of the components. A broad survey of SDN literature in internet technology is presented with study on traffic engineering, network virtualization, data center power saving and security. Moreover, simulation approaches dedicated to SDN-based cloud are also explored and discussed in extension of practical assessment. Our conclusion outlines the existing research gaps and future directions for investigation.. © 2024 IEEE.

关键词： Virtual reality

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Research on the Trusted Online Examination Systems

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International Journal of Network Security 2022年第3期24卷 541-550页

作者： Liao, Anthony Y. H. Hsieh, Yu-Ying Yang, Cheng-Ying Hwang, Min-Shiang Department of M-Commerce and Multimedia Applications Asia University Taiwan Department of Computer Science and Information Engineering Asia University Taiwan Department of Computer Science University of Taipei No. 500Lioufeng Rd Taichung41354 Taiwan Department of Medical Research China Medical University Hospital China Medical University No. 91 Xueshi Rd Taichung40402 Taiwan

In recent years, due to the threat of the new crown pneumonia (Covid-19), to avoid cluster infections, the way of online teaching has rapidly formed a trend. To maintain the authenticity and fairness of exams, teachers in many colleges and universities have formulated various solutions for students cheating in online exams. Therefore, cheating methods and proctoring techniques have become the two most important issues in online teaching. This paper collects and analyzes relevant literature on online cheating and online proctoring techniques from 2015 to 2022. We concluded that personal and environmental factors mainly influenced why students cheated. Most types of cheating are plagiarism, plagiarism, collusion, and imposter. Teachers do their best to prevent students from cheating. Electronic monitoring, authentication, and change assessment methods are the most common method. However, no matter which method is used, it cannot obtain satisfactory results. Other academics object to using technology or methods to control student exams. Return to the essence of education and cultivate talents who can manage themselves. Such arguments are not an immediate solution to the current problem of cheating on online exams. This paper synthesizes the opinions and practices of various works of literature and argues that adopting multiple evaluation methods is the closest approach to fairness and effectiveness. The essence of education is to guide value creation, cultivate ethical thinking, and acquire knowledge and ability. It is also necessary to rely on the advancement of information technology to improve the design of learning management systems (LMS) to break through the blind spots of current online exam cheating and proctoring techniques © 2022. International Journal of Network *** Rights Reserved

关键词： Students

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A Comparative Study of Fuzzy Logic and WQI for Groundwater Quality Assessment 3

A Comparative Study of Fuzzy Logic and WQI for Groundwater Q...

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3rd International Conference on Computing and Network Communications, CoCoNet 2019

作者： Shwetank Suhas Chaudhary, Jitendra Kumar Department of Computer Science Gurukula Kangri Vishwavidyalaya Haridwar Uttrakhand India Department of Chemistry Gurukula Kangri Vishwavidyalaya Haridwar Uttrakhand India Department of Computer Applications Invertis University Bareilly Uttar Pradesh India

Nowadays, human health, as well as environment, are at risk due to uncontrolled usage on natural resources. Groundwater is one of the crucial natural resource, excessively used and contaminated by human beings. It is, majorly contaminated by anthropogenic activities. Such contaminated water, when used for drinking purpose, may cause serious effects on human health. Therefore, it is necessary to precisely estimate the quality of groundwater. Conventionally, the WQI, a weighted arithmetic index method, is commonly used to estimate groundwater quality by researchers. As time rolled on, some drawbacks, such as uncertainty of data, of WQI came into light. So researchers tried to find a new approach to mitigate the problems associated with WQI. In this direction, fuzzy logic has been used and proven by researchers to eliminate the ambiguity involved in qualitative and quantitative researches. The paper aims to do a comparative study between fuzzy logic and WQI to estimate groundwater quality. The objective is to represent complex groundwater data into clear and simple data that can be easily interpreted by the general public and policymakers. © 2020 The Authors. Published by Elsevier B.V.

关键词： Heavy metals

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E-Voting System Using Blockchain Technology

E-Voting System Using Blockchain Technology

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Advances in Computing, Communication Control and Networking (ICAC3N), International Conference on

作者： Nagesh H R Guru Prasad M S Shivaraj B G Dhawal Jain Puneeth B R M Anadkumar Dept. of Computer Science & Engg. Sahyadri College of Engg. & Management Mangaluru India Dept. of Computer Science & Engg. Graphic Era (Deemed to be University) Dehradun India Dept. of Computer Science & Engg. Mangalore Institute of Technology & Engg. Moodabidri India Dept. of Computer Science & Engg. SDM Institute of Technology Ujire India Department of MCA Nitte NMAM Institute of Technology (NMAMIT) Nitte (Deemed to be University) Karnataka India Dept. of Computer Applications Graphic Era (Deemed to be University) Dehradun India

In every nation, democratic elections are a momentous and weighty occurrence, and the voting system that is now in place requires the use of ballots or electronic voting machines (EVM). Transparency, poor turnout, vote manipulation, distrust of electoral organizations, fabrication of unique IDs (voting party IDs), and delays in posting results are some of the issues that arise as a result of these procedures. The matter of safety is of the utmost importance. When considering the installation of a computerized voting system, voter confidentiality has always been one of the most important concerns. There is no question regarding the system's capability to secure itself in contrast to prospective assaults and safeguard data in the face of such big choices. Utilization of blockchain technology is one approach that might be taken to resolve security concerns. The blockchain technology has an endless number of different uses that might be implemented. The technology known as blockchain is a distributed ledger that makes it possible for peer-to-peer networks all over the world to handle digital assets. In this context, distributed ledger technology represents an intriguing development. A grouping of all transactions is referred to as a block. Immutability, decentralisation, security, transparency, and anonymity are some of the outstanding properties offered by blockchain technology. The combination of blockchain technology with smart contracts has shown promise as a viable option for the development of trustworthy and open-source electronic voting systems. In this article, we demonstrate how to use blockchain technology with the help of a wallet and the Solidity programming language to build an electronic voting application. The programme was designed as a smart contract for the Ethereum network. In order to avoid having the same person vote twice, the user's wallet will only hold a certain number of tokens (gas), which will be depleted each time the user casts a vote. Thi

关键词： Fabrication Distributed ledger Smart contracts Organizations Blockchains Safety Peer-to-peer computing

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Blockchain based Smart Energy Trading in a Sustainable Community: A Comparative Technological Analysis

Blockchain based Smart Energy Trading in a Sustainable Commu...

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International Conference on Contemporary Computing and Informatics (IC3I)

作者： Vipina Valsan Kanakasabapathy P Maneesha Vinodini Ramesh Lokavarapu Varsha Mucharla Deeksha Suravarapu Ankith Department of Electrical and Electronics Engineering Amrita Vishwa Vidyapeetham Amritapuri India Amrita Center for Wireless Networks and Applications (AmritaWNA) Amrita School of Engineering Amrita Vishwa Vidyapeetham Amritapuri India Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Amritapuri India

The significance of blockchain enabled smart con- tracts for the energy market is widely recognized, given the continuous shift towards a more decentralized and flexible energy grid. Blockchain Technology (BCT) is viewed as a critical technology for facilitating the shift to a more economical, transparent, and transactive sustainable energy market because of its autonomous, configurable, and tamper-proof character. This paper explores the significance and scope of blockchain technology in various stages of smart energy trading in sustainable communities. Our investigation analyzes the existing processes, difficulties, and potential of energy trading mechanisms in renewable energy markets, providing an adequate basis for the research. This paper also proposes a blockchain based Peer to Peer Energy Trading (P2P-ET) architecture using Hyperledger Fabric, notably on the concepts of organizational focus, private channels, and chain code, as well as the flow of transactions in the Hyperledger Fabric network. These components must be successfully developed and implemented in order to establish a strong energy trading network.

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