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International Conference on Advances in Computing, Communication and Control (ICAC3)

作者： Vemula Sai Saketh Srinivas Khatravath Yashvanth Kumar Guntupalli B.Tech Computer Science PES University Bangalore India M.Tech Electronics and Electrical Communication IIT Kharagpur Kharagpur India

ISBN: (纸本)9781665426350

State of mind is essential in every person’s life to keep their life stable, calm and peaceful. The key factors that contribute towards them are mood, emotion and thoughts. Monitoring them is key to a person's overall development and allows family and friends to support them to a greater extent. One aspect of getting a report on this is using the words being typed by the person on their computer or mobile, browser history, songs and movies played. This paper proposes a sentiment analysis system where information about mood and thoughts are conveyed by means of natural language processing. These logs captured during each time session are classified to gain insights about the person. This reduces the likelihood of any drastic decisions taken by the person and provides a better means of conveying the information and maintaining communication between them and their relations.

关键词： Sentiment analysis Mood Motion pictures browsers History Monitoring

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Investigations of electricity expansion environmental planning using LEAP model for sustainability

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International Journal of Energy technology and Policy 2021年第4期17卷 384-397页

作者： Karunanithi, K. Ramesh, S. Raja, S.P. Rayaguru, N.K. Saravanan, S. Department of Electrical and Electronics Engineering Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology Tamil Nadu Chennai India School of Computer Science and Engineering Vellore Institute of Technology Tamil Nadu Vellore632 014 India Department of Electrical and Electronics Engineering B V Raju Institute of Technology Telangana Narsapur India

Electricity expansion planning is finding an optimal solution for the power system planning problem in which installation of new generation units satisfies both technical and financial constraints. Nowadays, renewable power generation plays an important role in power generation since it is pollution free and has zero fuel cost. In this paper, an attempt is made to design a future power system for Andhra Pradesh, an Indian state in which the electricity is generated mainly from non-renewable energy sources which increase greenhouse gases (GHGs) emission and hence global warming. Keeping in mind about pollution impacts, renewable energy sources like wind, solar, biomass are considered for Andhra Pradesh using long-range energy alternative planning system (LEAP) software. The various scenarios have been developed with LEAP and in all scenarios, the system installed capacity, 100-year global warming potential, social cost, production cost and total cost are investigated quantitatively. Copyright © 2021 Inderscience Enterprises Ltd.

关键词： Renewable energy resources

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Optimum Charging Scheduling of an EV PL Owning Smart Reservation System 11

Optimum Charging Scheduling of an EV PL Owning Smart Reserva...

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11th International Conference on Power Science and engineering, ICPSE 2022

作者： Gokcek, Tayfur Guner, Sitki Sadreddini, Jale Erdinc, Ozan Yildiz Tech. University Electrical Engineering Istanbul Turkey Eskişehir Tech. University Electrical-Electronics Eng Eskişehir Turkey Ericsson Research Er Networks Istanbul34469 Turkey Carleton University Department of Systems and Computer Engineering OttawaONK1S 5B6 Canada

ISBN: (数字)9781665451291

ISBN: (纸本)9781665451291

With increasing the penetration rate of electric vehicle (EV) usage, the challenge of finding an available parking slot has been turned into finding an available parking slot having EV charger in metropolitans. Smart charging reservation systems considering EV drivers' preferences can facilitate finding an available charging station as well as managing the charging load of EVs in a parking lot. In this study, a bi-level optimization model is defined for minimizing the parking price of EV users, maximizing the profit of EV parking lot (PL) operator and the last one minimizing total power losses of the distribution network. A smart charging reservation system is used to select the EVs which are accepted for giving charging service considering several parameters. This reservation system was generated using Analytical Hierarchy Process (AHP) from Multi-Criteria Decision Making (MCDM) techniques. A PV system on the roof the PL is modelled to support the charging load of EVs at the PL. A mixed-integer linear programming model is established for solving the generated optimization problem. © 2022 IEEE.

关键词： Electric vehicles

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VLSI implementation using fully connected neural networks for energy consumption over neurons

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SUSTAINAbLE ENERGY techNOLOGIES AND ASSESSMENTS 2022年第PartA期52卷

作者： Mehbodniya, Abolfazl Kumar, Ravi Mohanty, Sachi Nandan Geetha, A. bedi, Pradeep Tripathi, Rohit [a]Department of Electronics and Communications Engineering Kuwait College of Science and Technology (KCST) Doha Area 7th Ring Road Kuwait [b]Department of Electronics and Communication Engineering Jaypee University of Engineering and Technology Guna Madhya Pradesh India [c]Department of ECE Saveetha School of Engineering SIMATS Thadalam Chennai - 602105 Tamil Nadu India [d]Department of Computer Science & Engineering Vardhaman College of Engineering (Autonomous) Hyderabad India [e]B.Tech Department of ECE Indian Institute of Space Science and Technology Thiruvananthapuram 695547 Kerala India [f]Department of Electrical and Electronics Engineering SRM Institute of Science and Technology Kattankulathur Tamil Nadu 603203 India

Increasingly, the capacity of artificial neural networks to identify and express top-level concepts in sets of data has become quite significant. Deep learning models like fully connected layer machine learning have demonstrated outstanding results in range of identification and verification applications. It's technology deployments suffered as from complexity and huge silicone areas with energy consumption. Memory accesses, the bulk from which happens in fully connected systems, comprise the energy usage of machine learning. It has many of the depths of neural network. Throughout this work, researchers suggest densely connected networks by demonstrating that there is indeed a drop in the number of links inside fully connected systems of up to 90% enhancing the quality of three popular sets of data. To decrease the memory needs have suggested low-connected grid networks, researchers present perhaps an effective hardware implementation based on the linear response registers. In comparison to the traditional design of fully connected layer neural network models, the suggested design could save up to 90 percent of storage. Findings of execution further reveal that artificial neurons of suggested weak network connections have a power consumption decrease up to 84 percent compared to one single atom of fully connected layer machine learning.

关键词： Neural Network Deep learning Energy consumption VLSI

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Implementation of 5G technology in Rural Education of India

Implementation of 5G Technology in Rural Education of India

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IEEE bombay Section Signature Conference (IbSSC)

作者： Unnati Agarwal Pranjal Dave Aarushi Tiwari Vinit Upadhyay Manoj Sankhe Saurav Shrivastav B.Tech Student Electronics and Telecommunications SVKM's NMIMS Mukesh Patel School of Technology Management and Engineering Mumbai India Head JIO Network Academy Reliance Jio Limited Mumbai India

ISBN: (纸本)9781665492928

The potential of the 5G network model to revolutionize Industry and Education is exemplified through 5G technology use cases. Enhanced Mobile broadband, Massive Machine Type Communication, and Ultra Reliable and Low Latency Communication are the three key components of the 5G concept. The services that 5G provides to users are contained inside these blocks. This study focuses on the concept of a “School on Wheels” as a beneficiary of 5G technologies. Rural Education will benefit from the implementation of 5G-enabled services that are specialized to this industry. We offered frameworks for advancing tools that will accelerate the idea of a Smart Educational System by linking 5G and its disruptive technologies. As a result, this paper provides a thorough examination of 5G technologies, which will facilitate new teaching and learning trends in the educational environment.

关键词： Industries 5G mobile communication IEEE Sections Education Wheels Massive machine type communications Market research

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Cloud-based fault prediction using IoT in office automation for improvisation of the health of employees

Cloud-based fault prediction using IoT in office automation ...

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Advance Computing and Innovative technologies in engineering (ICACITE), International Conference on

作者： Nakul Shahdadpuri Somanchi Hari Krishna SathiJyothirmaye Reddy C. Ganesh Kirti Agarwal Sourabh bhattacharya IPG Programme {(B.Tech + M.Tech (It)} IIITM Gwalior Department of Business Management Vignana Bharathi Institute of Technology Malkajigiri Telangana Department of Management Marwadi University Rajkot Gujarat Computer and Communication Engineering Sri Eshwar College of Engineering Anna University Chennai ITERC College Delhi (NCR) India Department of Management and Social Science Haldia Institute of Technology West Bengal

Modern technology is the best thing to be used in every commercial sector. The devices are well equipped to understand the problems of the users. The offices are now been maintained by technology the devices for daily monitoring even the electrical appliances are been monitored and maintained by technology. In previous times the best method of this work is to make it via cloud computing, but now as technology has evolved and evolved new adding devices are making system malfunction. The fault of cloud computing needs to be identified, So the best method is to automate the office with the introduction of IoT. it is a platform equipped with all the facilities for monitoring and maintaining the devices inside the office, even the working capacity of employees is also measured via this method. The study is showing the effectiveness of the IoT to identify the faults of cloud computing related to maintaining the working method of the office. The data collected for this study is secondary data like articles, books, journals and many more. Then gathered data is analyzed by qualitative data analysis. The results are quite positive about the use of it to automate the office and its working procedure.

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Weather and Climate Forecasting System for Cultivation using Naive's Algorithm 2

Weather and Climate Forecasting System for Cultivation using...

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2nd International Conference on Computing and Information technology, ICCIT 2022

作者： Sheela, M. Sahaya banu, S. Shahar Rajendran, T. Raj, S. Saran Sreeja, b.P. Pavai College of Technology Department of Electronics and Communication Engineering Pachal Namakkal India B S Abdur Rahman Crescent Institute of Science and Technology Department of Computer Applications Vandalur Chennai India Tamilnadu Coimbatore India Vel Tech Rangarajan Dr. Sagunthala Rd Institute of Science and Technology Department of Computer Science and Engineering Chennai India Karpagam College of Engineering Department of Information Technology Coimbatore India

ISBN: (纸本)9781665436052

Agriculture based advisory services and climatic information are more considerable in providing assistance for pastoralists and small farmers to manage climatic changes and risks factors to be adopted during changes. Moreover, there is some gap in providing climatic information that significantly addresses the requirement of pastoralists and farmers. Huge farmers rely over indigenous knowledge where experiences and indicators are utilized to forecast and observe weather conditions. When this prediction is inbuilt and implemented by many farmers, documentations, coordinators and so on for predicting weather, it should be accurate and reliable manner. This work concentrates on building a weather predictor system for farmers to identify the velocity flow that is needed during farming. This model includes Naives equation for performing this velocity prediction. The outcomes demonstrate that pastoralists and farmers utilize combination of biological and meteorological indications to predict weather conditions. Henceforth, it seems to be more crucial in providing assistance to enhance access to climatic information in various regions of India in vulnerable and poor resource communities. © 2022 IEEE.

关键词： Cultivation

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EASYDIAGNOS: A FRAMEWORK FOR ACCURATE FEATURE SELECTION FOR AUTOMATIC DIAGNOSIS IN SMART HEALTHCARE

arXiv

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arXiv 2024年

作者： Maji, Prasenjit Mondal, Amit Kumar Mondal, Hemanta Kumar Mahanty, Saraju P. Computer Science and Design Dr. B. C. Roy Engineering College WB 713206 India Computer Science and Engineering Bengal College of Engg. and Tech. WB 713212 India Electronics and Communication Engg. National Institute of Technology WB Durgapur713209 India Dept. of Computer Science and Engineering University of North Texas United States

The rapid advancements in artificial intelligence (AI) have revolutionized smart healthcare, driving innovations in wearable technologies, continuous monitoring devices, and intelligent diagnostic systems. However, security, explainability, robustness, and performance optimization challenges remain critical barriers to widespread adoption in clinical environments. This research presents an innovative algorithmic method using the Adaptive Feature Evaluator (AFE) algorithm to improve feature selection in healthcare datasets and overcome problems. AFE integrating Genetic Algorithms (GA), Explainable Artificial Intelligence (XAI), and Permutation and Combination techniques (PCT), the algorithm optimizes Clinical Decision Support Systems (CDSS), thereby enhancing predictive accuracy and interpretability. The proposed method is validated across three diverse healthcare datasets using six distinct machine learning algorithms, demonstrating its robustness and superiority over conventional feature selection techniques. The results underscore the transformative potential of AFE in smart healthcare, enabling personalized and transparent patient care. Notably, the AFE algorithm, when combined with a Multi-layer Perceptron (MLP), achieved an accuracy of up to 98.5%, highlighting its capability to improve clinical decision-making processes in real-world healthcare applications. © 2024, CC bY.

关键词： Electronic health record

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Direct Voltage Mtpa Control of Interior Permanent Magnet Synchronous Motor Driven Electric Vehicles

SSRN

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SSRN 2024年

作者： Elhaj, Alaref Alzayed, Mohamad Chaoui, Hicham Department of Electronics Carleton University 1125 Colonel By Drive OttawaONK1S 5B6 Canada Department of Electrical and Computer Engineering Texas Tech University LubbockTX79409 United States

An efficient, straightforward, direct voltage maximum torque per ampere (MTPA) control schemefor interior permanent magnet synchronous motor (IPMSM) propelling an electric vehicle (EV) isproposed in this manuscript. The main feature of the proposed traction control scheme is that theMTPA is attained by directly varying the amplitude and the angle of the voltage vector, eliminatingthe need for current control loops and the associated regulators. Instead, a single-speed controller isadopted. Furthermore, an analytical formulation based on the motor voltage model is developed toextract the desired voltage’s magnitude and angle to run the motor within the MTPA operating points,disregarding numerical solutions, control law approximation, long-winded iterative calculations,or approximate representation of the IPMSM. Such a methodology significantly reduces controlscheme complexity, enhances computation efficiency, and mitigates the delays associated with thecascaded-based control systems. Additionally, it facilitates straightforward real-time *** performance of the designed algorithm is experimentally validated using the commonly adopteddriving cycles, namely the Federal Test Procedure (US06) drive cycle and the New European DrivingCycle (NEDC). An intensive comparative evaluation against the MTPA field-oriented control (FOC)is established based on the driving cycles employed. Nevertheless, a quantitative assessment isconducted, revealing that the designed strategy achieved an average speed tracking improvement of14% and energy savings of 2.26% over the MTPA FOC. Also, the proposed method’s computationefficiency is investigated and compared to both the FOC and existing direct voltage approaches,demonstrating superior computational efficiency. © 2024, The Authors. All rights reserved.

关键词： Traction control

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brain Tumor Detection Using MRI Image Processing techniques

Brain Tumor Detection Using MRI Image Processing Techniques

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Innovation and Novelty in engineering and technology (INNOVA), International Conference on

作者： Ambaji. S. Jadhav Rashmi Pawar Sunilkumar. M. Hattaraki Shwetha bagali Rajeshwari S. Patil bhagyashree Patil Department of Elecrtical and Electronics Engineering B.L.D.E. As.V.P. Dr. P.G.H. College of Engg. and Tech. Vijayaapura India Department of Electronics and Communication Engineering B.L.D.E. As. V.P. Dr. P.G.H. College of Engg. and Tech. Vijayaapura India Department of Computer Science and Engineering Sri Krishna Institute of Technology Bengaluru India

ISBN: (数字)9798331505134

ISBN: (纸本)9798331505141

Medical image processing is highly developed and critical in the medical field, encompassing methods like X-rays, MRI, and CT scans. These techniques help to identify minute defects in the human body. brain tumors, which disrupt normal brain function, are detected through MRI using segmentation, feature extraction, and classification, processes that are time-consuming and depend on the expertise of clinical professionals. computer-aided technology addresses these challenges. This work aims to diagnose brain tumors accurately and quickly using MRI images. Image pre-processing is done using CLAHE and median filter to enhance contrast and eliminate noise. Thresholding is used for segmentation and a lightweight U-net is used for tumor segmentation, achieving high accuracy and efficiency without extensive training data. Finally, an MSD-CNN classifies the tumor, capturing both local and global features for better image recognition. Our proposed model outperforms over existing methods in terms of accuracy, robustness, and efficiency in brain tumor detection.

关键词： Image segmentation technological innovation Accuracy Thresholding (Imaging) Magnetic resonance imaging Noise brain tumors Training data X-rays Robustness

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