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DDGAN: Deep Dense Generative Adversarial Networks for Improvement in Arrhythmia Classification 3rd

DDGAN: Deep Dense Generative Adversarial Networks for Improv...

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3rd International Conference on Sustainable Expert Systems, ICSES 2022

作者： Sanamdikar, S.T. Hamde, S.T. Asutkar, V.G. Sahu, R.M. Moje, R.K. Department of Instrumentation Engineering Shri Guru Gobind Singhji Institute of Engineering and Technology Nanded India Department of Instrumentation and Control PDEA COE Manjari Pune India Department of Electronics and Telecommunication PDEA COE Manjari Pune India

ISBN: (纸本)9789811978739

The purpose of this research is to examine ECG arrhythmia classification using a deep dense generative adversarial network. The DDGAN architecture shown in this paper can be taught to produce ECG signals that are comparable to real-world ECG signals. The results indicate that using a sequence-based strategy for all ECG-beat types substantially improves the area under curve on our test set. This paper describes improvements to the GAN architecture’s intrinsic capacity to address the temporal structure of the signal. Traditional architecture does not naturally address this structure, and therefore suffers from decreased performance when such a structure is informative. This paper compares the proposed technique to kernel principle component analysis with incremental support vector regression, discrete wavelet transforms with incremental support vector regression and general sparse neural network. From obtained results, it is concluded that the planned DDGAN technique is better than this technique with an overall accuracy of 97.44 percent. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Generative adversarial networks

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NANOHEXCOOL: Advanced Thermal control for Lithium-Ion Batteries 8

NANOHEXCOOL: Advanced Thermal Control for Lithium-Ion Batter...

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8th International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud), I-SMAC 2024

作者： Ragul, S. Rajeshwari, M. Meganthan, P. Dhanaselvam, J. Saravanakumar, K. Rajesh, R. Sri Krishna College of Technology Dept of Instrumentation and Control Engineering Coimbatore India Sri Krishna College of Technology Dept. of Electrical and Electronics Engineering Coimbatore India Indian Institute of Technology Madras Department of Engineering Design Chennai India

ISBN: (数字)9798350376425

ISBN: (纸本)9798350376425

This study evaluates thermal management strategies for lithium-ion batteries in electric vehicles, addressing safety concerns like thermal runaway and performance degradation under extreme temperatures. A comprehensive assessment considers factors such as production costs, maintenance needs, system complexity, and internal temperature control. Among various techniques explored, a hexagon-structured cooling chamber utilizing nano-fluids emerges as a promising solution. Liquid cooling systems, categorized into direct and indirect systems, are assessed based on fluid interaction with the battery surface. Hexagonal cooling chambers offer innovative thermal regulation, demonstrating efficient mitigation of temperature-related challenges. Numerical simulations confirm the effectiveness of the devised thermal management mechanism in maintaining battery cell temperatures within specified ranges. Implementation of such strategies is crucial for enhancing battery safety and performance in electric vehicles, ensuring reliable operation across diverse temperature conditions while mitigating risks associated with thermal runaway events. © 2024 IEEE.

关键词： Temperature control

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Optimizing Thermo-Electric Generation with Quasi-Z-Source Converter in Energy Harvesting for Wearable Devices 3

Optimizing Thermo-Electric Generation with Quasi-Z-Source Co...

引用

3rd International Conference on Mechatronics and Automation technology, ICMAT 2024

作者： Lotfy, Mostafa Wageh Hussein, Aziza I. Dept. of Process Control Technology Faculty of Technology and Education Beni-Suef University Beni-Suef Egypt Electrical and Computer Engineering Department College of Engineering Effat University Jeddah Saudi Arabia

ISBN: (纸本)9781643685649

Recent advances in semiconductors industry and microelectronics have created new opportunities for integrating various technologies in energy harvesting projects. These advancements have simplified the process of capturing energy from different sources, such as thermal energy, and converting it into electrical power. Thermo-Electric Generators (TEGs) are commonly used in many applications such as wearable devices. However Thermo-Electric Generators produce very low output voltages, which is insufficient for most low-power electronic circuits to operate. Therefore, a boost converter is essential to step up the voltage output from the TEG to a usable level. In this paper, a DC-DC converter with a high performance in terms of voltage gain is implemented. The proposed quasi-Z-source (q-ZSC) DC-DC converter not only offers high voltage gain but also several significant advantages. The proposed q-ZSC is capable of both boosting and regulating the voltage output efficiently, even under variable input conditions, making it highly suitable for low-power energy harvesting systems such as Thermo-Electric Generators. The design is simulated using MATLAB Simulink software, focusing on integrated circuits, with a strong emphasis on optimizing the circuit's efficiency. This work underscores critical factors in improving energy harvesting circuits, enhancing their performance and effectiveness in low-power applications for wearable technology. © 2024 The Authors.

关键词： DC generator motors

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A Bio-inspired Robot for Structural Health Monitoring of Natural Gas Pipeline 11

A Bio-inspired Robot for Structural Health Monitoring of Nat...

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11th RSI International Conference on Robotics and Mechatronics, ICRoM 2023

作者： Sanjana, C. Dhanush, S. Jain, Moksh Maithreyan, G. National Institute of Technology Tiruchirappalli Department of Mechanical Engineering Tiruchirappalli India National Institute of Technology Tiruchirappalli Department of Instrumentation and Control Engineering Tiruchirappalli India National Institute of Technology Tiruchirappalli Department of Production Engineering Tiruchirappalli India

ISBN: (纸本)9798350308105

The natural gas sector depends significantly on pipeline pigging for in-line inspections, a standard practice. However, the usefulness of conventional pigs for this purpose is being questioned because of their inherent limits, resulting in rare deployment. This paper introduces a new bio-inspired pig design to address the limitations posed by the existing pigs. The solution aims to enhance the inspection methodologies, its adaptability to various pipe diameters, maneuverability around bends, and precise speed control. © 2023 IEEE.

关键词： Gas industry

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Experimental Interfacial Reconstruction and Mass Transfer Modelling of a Slug Bubble During Co-current Flow in a Millimetric Tube 1

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9th International and 49th National Conference on Fluid Mechanics and Fluid Power, FMFP 2022

作者： Rohilla, Lokesh Prakash, Ravi Verma, Raj Kumar Das, Arup Kumar Process Engineering and Instrumentation Department CSIR-IMMT Bhubaneshwar751013 India Department of Chemical Engineering IIT Roorkee Roorkee247667 India Department of Chemical Engineering Chaitanya Bharathi Institute of Technology Hyderabad500075 India Department of Mechanical and Industrial Engineering IIT Roorkee Roorkee247667 India

ISBN: (数字)9789819960743

ISBN: (纸本)9789819960736

Mass transfer during the gas liquid interactions in a monolith reactor has been an area of paramount importance due to its prevalence in process intensification. The present study experimentally investigates the mass transfer from slug bubble train in a glass tube by using the colorimetric method and a high-speed camera. An oxygen sensitive dye resazurin is used with the pure oxygen cap/slug bubble train for the current study. An in-house code has been developed for image thresholding, interface detection, bubble mask generation, and concentration measurement. It is investigated that the overall mass transfer coefficient increases with the gas superficial velocity. The role of the Taylor recirculation vortices in the mass transfer enhancement has been observed from the radial concentration profile. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Mass transfer

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Segmentation for Lumbar Spinal Stenosis Using Convolutional Neural Networks

Segmentation for Lumbar Spinal Stenosis Using Convolutional ...

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2022 International Conference on Machine Learning and Data engineering, ICMLDE 2022

作者： Shukla, Abhinav Bhardwaj, Saurabh Singh, Mandeep Engineering in Electronics Instrumentation and Control Electrical Instrumentation and Engineering Department Thapar Institute of Engineering and Technology Punjab Patiala147001 India Electrical Instrumentation and Engineering Department Thapar Institute of Engineering and Technology Punjab Patiala147001 India

Lumbar spinal stenosis (LSS) is a dwindling situation where transformation in discs, ligamentum flavum, and facet joints with aging causes contraction of area around neurovascular structures of the spine. Given research work is divided into two stages. First stage of research does a thorough study of the given health issue and reviews some of the methods which are useful in extracting features of given biomedical image. As of now, main objective of the research is to segment given axial view MRI image into four specific regions which are clearly specified in the labelled images and performance of segmentation model is checked by using IoU metrics. After this, Next stage of research is connected with this work and it will be focusing on development of a system which will identify and detect whether the patient is having the problem of spinal stenosis or not. Also based on the given MRI image, developed system can also mention various stages of spinal stenosis. For image segmentation Unet based CNN Architecture is used which will segment the given MRI image in four regions and those regions are IVD, PE, TS, AAP. Intersection-Over-Union (IoU) metric is the commonly used metric that checks performance of given CNN model which does semantic segmentation. It was observed that regions like IVD, PE, TS, IoU value ranges between 0.80 and 1.0 because IVD is the easiest region to label and PE has a specific shape which is identical to the letter Y. And region like AAP, IoU metric value is 0.6568, that less than the previous regions, because it was the hardest region to label. © 2023 The Authors. Published by Elsevier B.V.

关键词： Semantic Segmentation

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Active control of railway vehicle suspension using PID controller with pole placement technique

Active control of railway vehicle suspension using PID contr...

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作者： Nitish Kumar Singh, Amit Department of Instrumentation and Control Engineering Dr. B R Ambedkar National Institute of Technology Punjab Jalandhar144011 India

With the advancement of technology in high-speed railway vehicles, ride comfort must be taken care of, which can be accomplished by employing effective vibration control techniques. Hence, this study focuses on the development of effective controllers which mitigate the vibration level and improves the ride quality of railway vehicle. A full-scale railway vehicle dynamic model of twenty-seven degrees of freedom with rail wheel contact and active suspension has been introduced. The required amount of optimum force for the active suspension has been achieved using a Proportional-Integral-Derivative controller tuned with the pole placement method. The performance of the active suspension system on the body's displacement, acceleration, and suspension deflection is evaluated in the time domain under the periodic track irregularities. The system's characteristics and control ability are discussed by analyzing the responses regarding percentage overshoots and settling time. From the simulations, it is found that the proposed control schemes reduce the overshoot to a more significant extent and consequently have a positive effect on improving the ride quality of railway vehicles. © 2023

关键词： Dynamic models

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Machine Learning-Based Power Loss Analysis in Photovoltaic Systems

Machine Learning-Based Power Loss Analysis in Photovoltaic S...

引用

Smart and Sustainable Developments in Electrical engineering (SSDEE), IEEE International Conference on

作者： Anuradha Tomar Hritik Kumar Department of Instrumentation & Control Engineering Netaji Subhas University of Technology

ISBN: (数字)9798331542108

ISBN: (纸本)9798331542115

This research estimates the power loss in photovoltaic (PV) systems through a Random Forest model by using 15-min interval data for two years (2021–2023) of operation from a university campus located in Delhi, India. Irradiance, temperature and the dust concentration were used in the analysis to calculate and estimate actual and theoretical potentials and power losses based on factual, modelled and theoretical determinations under Standard test conditions (STC). Seasonal changes are of particular interest and therefore, the power loss is to be analyzed based on three power quality reports obtained over three different seasons in 2023. The results of the model show the Mean absolute error (MAE) to be 29.145 W along with Root mean square error (RMSE) to be 57.72 W. Interactions with power loss observed seasonally proved to have variations in dust and power loss, temperature, and so on; all of which confirmed the effectiveness of Random Forest model in providing valuable predictions of season-sensitive data. These results would be significant to enhance the efficiency of the PV system and how energy technologies for dusty areas should be designed.

关键词： Photovoltaic systems Temperature distribution Sensitivity System performance Predictive models Data models Sustainable development Root mean square Random forests Standards

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Particle Swarm Optimization Based control of a Differential Drive Mobile Wheeled Robot 14

Particle Swarm Optimization Based Control of a Differential ...

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14th International Conference on Computing Communication and Networking Technologies, ICCCNT 2023

作者： Sonowal, Arpita Rani, Asha Singh, Vijander Netaji Subhas University of Technology Department of Electrical Engineering New Delhi Dwarka India Netaji Subhas University of Technology Department of Electrical Engineering and Instrumentation and Control Engineering New Delhi Dwarka India

ISBN: (纸本)9798350335095

This work aims at the efficient control of a mobile robot using optimised PID controller. The two DC motors are controlled precisely which in turn regulate the movement of the robot. Numerous techniques have been developed to enhance the PID control strategy applied to linear and non-linear systems. In this work, first the actuator model of the mobile robot is simulated and then the optimal computation techniques i.e., Simulated Annealing (SA), Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) are considered to tune the gains of PID controller. ITAE is considered as the objective function for optimization. The comparative study reveals that PSO tuned PID provides the least ITAE and is thus used for the mobile robot. The velocity plots are analysed for various positions of wheels. The motion characteristics for different paths are also analysed which justify the effectiveness of the PSO-PID controller over the other considered techniques. © 2023 IEEE.

关键词： Soft computing

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Cheetah Optimizer based PIDA controller Design for Cyber-physical Power System under Cyberattacks and Uncertainty 3

Cheetah Optimizer based PIDA Controller Design for Cyber-phy...

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3rd IEEE International Conference on Smart Technologies for Power, Energy and control, STPEC 2023

作者： Kumar, Mahendra Altaf, Aatif Biswas, Deblina Dr. B R Ambedkar National Institute of Technology Jalandhar Department of Instrumentation and Control Engineering Punjab Jalandhar India

ISBN: (纸本)9798350304732

This paper presents a cheetah optimizer (CO) based PIDA controller scheme for frequency regulation of cyber-physical microgrid. CO is recently proposed nature inspired optimization algorithm. CO benefits in the terms of global optimization and few design parameters. The frequency control is important concerned regarding balance between generation of power and power demand in power system with high integration of the renewable-energy resources (RESs). Currently, power system is more dominated on the communication networks. So, the cyber-attacks have been raised in the current power system. The proposed control design is mitigated the effects of parametric uncertainty, cyber-attack, time-delays and random load-demand. Analysis based on simulation studied reveals the benefits of proposed LFC design under various practical cases. © 2023 IEEE.

关键词： Cheetah optimizer Cyber-attacks Cyber-physical system Load frequency control PIDA controller

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