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2024 International Conference on System, Computation, Automation and Networking, ICSCAN 2024

作者： Sowmiya, X.L. Sanjana, R. Nishintha, A. Pavithra, S. Kannan, Shree Charan Ponnusamy, R. Chennai Institute of Technology Dept. of Computer Science and Engineering Tamilnadu Chennai India Chennai Institute of Technology Dept. of Computer Science and Engineering Tamil Nadu India

ISBN: (纸本)9798331510022

Cirrhosis is one of the major causes of death around the world. Hence, the possibility of survival prediction among patients affected by this disease constitutes the principal factor in properly planning treatment and management procedures. This work aims to design a predictive model of the probability of survival of patients who have cirrhosis based on patient data, including clinical parameters, medical history, and laboratory findings of these patients. The data-driven machine learning algorithm improves the predictive accuracy and significantly enhances the clinical decision-making process. This considers multiple predictors: the patient's liver function tests, the demographic factors, and the indicators of disease progression in the body. It will be validated for reliability and accuracy using real-world patient case data. Therefore, this tool could aid clinicians in devising treatment plans that improve patient outcomes and efficiently utilise healthcare resources. This study also contributes to the emerging genre of AI-assisted care because chronic liver disease management, specifically cirrhosis, in this case, requires constituting predictive analytics. © 2024 IEEE.

关键词： Predictive analytics

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Home Energy Optimization Strategies in Bangladesh to Minimize Electricity Cost and Grid Energy Consumption Using Optimization Algorithm 3

Home Energy Optimization Strategies in Bangladesh to Minimiz...

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3rd IEEE International Conference on Robotics, Automation, Artificial-Intelligence and Internet-of-Things, RAAICON 2024

作者： Dey, Sumitra Barua, Sancoy Chittagong University of Engineering and Technology Dept. of Electrical & Electronic Engineering Chittagong Bangladesh

ISBN: (纸本)9798331534400

Due to rapid urbanization and increasing energy use, Bangladesh is facing challenges in ensuring a reliable electricity supply, therefore it makes sensible to use more renewable resources in order to meet the rising energy demand. This research develops an energy management system (EMS) with two different approaches based on the facilities of various types of consumers. One approach uses renewable energy resource (RER) and energy storage system (ESS) with block rate tariff. Based on the state of charge (SOC) of the ESS and the availability of solar energy, this optimization system schedules energy resources, decides when to use or turn off the grid. Then the optimization problem is resolved using Interior-Point method. Another approach is load scheduling based on time-of-use tariff without utilizing of ESS and RER, solved by applying Genetic Algorithm. All of these methods are simulated in MATLAB. The optimization results are compared with the real-time electricity bills to confirm validate the model. It is shown that the simulation result of block rate tariff model using RER and ESS is more effective which reduces electricity costs by 68.97% and usages of grid energy by 75.23% than the load scheduling model. © 2024 IEEE.

关键词： Home Energy Management System Load Scheduling Optimization Renewable Energy Resources State of Charge Tariff

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Observation-Transformed Distributed Detection in Sensor Networks 59

Observation-Transformed Distributed Detection in Sensor Netw...

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59th Annual Conference on Information Sciences and Systems, CISS 2025

作者： Cao, Lei Viswanathan, Ramanarayanan University of Mississippi Dept. of Electrical and Computer Engineering OxfordMS38677 United States

ISBN: (纸本)9798331513269

Distributed detection (DD) plays a crucial role in sensor networks, where sensors gather data from a region of interest and report their observations to a fusion center (FC). The FC then makes a decision regarding a specific task, such as determining the presence or absence of a target. Given the constraints imposed by the transmission power, bandwidth, and noise impact in both sensing and data reporting channels, what should be reported from the sensors significantly affects the final detection accuracy. Existing methods include observation-untransformed DD (UDD), codewords-based DD (CDD), and quantized-but-uncoded DD (QDD). In this paper, we attempt to find the optimal sensor decision rule, i.e., the best transform for the observed data to be reported, by formulating the task as a functional optimization problem. To bypass the difficulty of theoretically solving the problem, we present two methods: an approximation function and a numerical solution for the Gaussian noise case. Our simulation results demonstrate that a variation of the hyperbolic tangent function can be an effective approximation of the optimal transform. This work could lead to further studies on the optimal design for distributed detection. © 2025 IEEE.

关键词： Hyperbolic functions

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A Comparative Analysis of Ensemble Methods for Short-Term Load Forecasting 2

A Comparative Analysis of Ensemble Methods for Short-Term Lo...

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2nd International Conference on Power, electrical, Electronics and Industrial Applications, PEEIACON 2024

作者： Nigar, Meher Mohammad, Nur Das, Ankita Chittagong University of Engineering and Technology Dept. of Electrical and Electronic Engineering Chittagong Bangladesh

ISBN: (纸本)9798331517984

Forecasting electricity load is essential to the effective administration and functioning of power systems. This paper investigates the efficacy of various ensemble methods in Short-Term Load Forecasting (STLF) using a real-world dataset. We explore the implementation and comparative performance of four advanced ensemble models: Random Forest (RF) with Extra Trees Regressor (ETR), RF with XGBoost (XGB), XGB with ETR, and a Voting Regressor combining all aforementioned models. Our study focuses on developing these models, preprocessing data, and meticulously tuning parameters to optimize forecasting accuracy and robustness. The models are evaluated using different precision matrices such as R2, Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE). The Voting Regressor model exhibited the best performance in this work, as indicated by their low RMSE and MAE values and high R2 scores. © 2024 IEEE.

关键词： Electric load forecasting

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IMPROVED INDOOR FORMALDEHYDE MONITORING SYSTEM USING ENHANCED SELF-DEVELOPED CIRCUITS AND LOCAL OUTLIER FACTOR ALGORITHM

UPB Scientific Bulletin, Series C: Electrical Engineering an...

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UPB Scientific Bulletin, Series C: electrical engineering and computer Science 2022年第2期84卷 137-152页

作者： Li, Bin Zhong, Kai Niu, Yongyue Cui, Peng Xue, Liang Ji, Nan Wei, Dahui Dept. of Electrical and Computer Engineering Jilin Jianzhu University China

An indoor distributed formaldehyde monitoring system has been developed with multiple self-developed sensor nodes and wireless communication circuits. Local outlier factor algorithm has been adopted to increase the accuracy of the system. In addition, software has been developed based on LabVIEW for data receiving, data storing, data displaying and remote accessing. Experiments were carried out to evaluate the performance of this improved system. Compared to our previous work, the proposed system exhibits some improvements in performance of formaldehyde sensing ability, software function and quality of wireless communication due to the enhancement of hardware and software in the system. © 2022, Politechnica University of Bucharest. All rights reserved.

关键词： Remote control

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Inverter Control of Scheme for IEEE1547-2018 Category3 in Fuel Cell Systems

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Transactions of the Korean Institute of electrical Engineers 2022年第1期71卷 90-97页

作者： Won, Su-Yeon Lee, Kyo-Beum Dept. of Electrical and Computer Engineering Ajou University Korea Republic of

This paper presents an inverter control scheme for fuel cell systems in IEEE1547-2018 Category3. The current configuration of Grid-Connected fuel cell system has limitations Category3's LVRT (Low Voltage Ride Through) reponse, additional inverter are needed. The inverter operates in an abnormal state where the grid voltage is unstable, and normally supplies the voltage to BOP (Balance of Plant) of the fuel cell system. Simulated verification of the inverter control scheme was performed to change the voltage source to the BOP from grid to inverter during abnormal conditions. © 2022 Korean Institute of electrical Engineers. All rights reserved.

关键词： Fuel cells

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DGA Based Transformer Fault Analysis Using Machine Learning

DGA Based Transformer Fault Analysis Using Machine Learning

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2024 International Conference on electrical, Electronics and Computing Technologies, ICEECT 2024

作者： Kumar, Abhinn Saxena, Anmol Ratna Shrivastava, Vivek National Institute of Technology Delhi Dept. of Electrical Engineering Delhi110036 India National Institute of Technology Uttarakhand Dept. Of Electrical Engineering Uttarakhand Srinagar246174 India

ISBN: (纸本)9798350378092

In power transmission network transformer plays an important role, so its protection attains much more attention in order to have fault free supply. When the mineral oil inside the transformer is subjected to high thermal and electrical stress gases are created from the decay of mineral oil. Distinct type of fault creates diverse gases and extractions of these gases from the sample gives helpful data about the state of oil and type of fault. Early identification of fault reduces the failure rate. This work proposed Machine Learning Based Dissolved gas analysis (DGA) technique to diagnose transformer faults. In this work multiple machine learning models are developed and tested using the DGA dataset. Outputs are generated under different Validation schemes. Also the optimization algorithm with feature selection using ANOVA test and hyper parameter tuning using random optimization is proposed and acquired the Validation removes over 100% accuracy. © 2024 IEEE.

关键词： Mineral oils

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A DYC system for 4WID Electric Vehicles via Fuzzy-Nonsingular Fast Terminal Sliding Mode Control

A DYC system for 4WID Electric Vehicles via Fuzzy-Nonsingula...

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2025 IEEE International Conference on Mechatronics, ICM 2025

作者： Eun Lee, Jung Woo Kim, Byeong Electronic and Computer Engineering University of Ulsan City of Ulsan Dept. of Electrical Korea Republic of

ISBN: (纸本)9798331533892

In this paper, we introduce a novel Direct Yaw Moment Control (DYC) system designed to bolster the stability of four-wheel independent drive (4WID) electric vehicles in diverse extreme driving conditions. Our proposed system is developed based on the design of Non-singular Fast Terminal Sliding Mode Control (NFTSMC) methods to calculate two optimal additional yaw moments, each targeting specific control objectives: the desired yaw rate and the desired sideslip angle. These calculated values are then intelligently weighted in real time using a Fuzzy Logic system to determine the final additional yaw moment applied to the vehicle. The stability of the NFTSMC methods is rigorously ensured through the Lyapunov theory. Simulation results underscore the efficacy of our proposed DYC system, particularly in navigating through extreme driving scenarios. Comparisons with no control and fixed weight-based SMC strategies demonstrated significant improvements in both yaw rate and sideslip angle tracking performance. The proposed method not only amplifies control effectiveness, ensuring swift convergence and high precision, but also substantially mitigates chattering phenomena, as evidenced by yaw moment and torque observations. © 2025 IEEE.

关键词： Lyapunov methods

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Mutiphysics Analysis for Electromagnetics-Structural Deformation-Circuit Coupled Problem of Electromagnetic Expulsive De-icing System

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Transactions of the Korean Institute of electrical Engineers 2022年第11期71卷 1599-1607页

作者： Kang, Sung-Jun Lee, Jun-Sung Rho, Seung-Eun Park, Jong-Oh Jung, Eun-Chae Park, Il-Han Dept. of Electrical and Computer Engineering Sungkyunkwan University Korea Republic of

One of the ice protection systems for flights above medium altitudes is the electromagnetic explusive deicing system(EEDS). EEDS is composed of a coil which is structurally deformed by electromagnetic repulsion of electric current supplied by external circuit, a complex multiphysics phenomenon requiring electromagnetic, structural, and circuit analysis simultaneously. In this paper, we suggest electromagnetic(EM)-structural deformation-circuit coupled lumped parameter system for the analysis of EEDS. The results of the numerical analysis using the coupled lumped parameter system is compared with the results of measuring experiment using the EEDS prototype, which showed high concordance in current, electromagnetic force, and displacement. The coupled lumped parameter system enables bi-directional analysis which takes into account the interdependence between the different systems. Furthermore, it can significantly reduce the computational cost, which enables complex performance evaluation on various design variables and saves time and cost in the initial design steps. Copyright © The Korean Institute of electrical Engineers.

关键词： Timing circuits

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IoT based Automated Irrigation and Fertilization System using Arduino

IoT based Automated Irrigation and Fertilization System usin...

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

作者： Prasad, Avagaddi Phaniram, Mulagala Yugadeep, Ghantasala Manikanta, Lakamsani L. S. Saradhi, Ganta Pardha Sasi Institute of Technology and Engineering Dept. of Electrical and Electronics Engineering Tadepalligudem India

ISBN: (纸本)9798350381887

This paper addresses a critical gap in existing smart irrigation systems, which primarily focus on moisture content without considering the essential factor of NPK (Nitrogen, Phosphorus, Potassium) levels in the soil. This work aims to revolutionize smart irrigation by upgrading it to incorporate NPK and water level sensing technologies. By precisely monitoring and responding to NPK and water levels, the enhanced system optimizes fertilizer and water supply, promoting healthier plant growth. This innovative approach not only contributes to environmental sustainability but also significantly reduces labor, water, and fertilizer wastage. The paper outlines the technical aspects of the upgraded smart irrigation system, emphasizing its ability to provide real-time data on soil conditions. Importantly, all data, including NPK and water levels, is seamlessly transmitted to farmers' mobile devices, empowering them with insights for informed decision-making. This paper serves as a valuable contribution to the evolving landscape of precision agriculture, highlighting the importance of comprehensive soil monitoring for sustainable and efficient crop management. © 2024 IEEE.

关键词： Agriculture Arduino Moisture sensors NPK sensors smart irrigation water efficiency

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