2021 IEEE 6th International Conference on Computing, Communication and Automation (ICCCA)最新文献_第10页

UWB Circular Monopole Antenna Integrated with Spiral EBG on Ground Plane for Reduced SAR 超宽带圆形单极天线与螺旋EBG集成在地平面上用于降低SAR

2021 IEEE 6th International Conference on Computing, Communication and Automation (ICCCA) Pub Date : 2021-12-17 DOI: 10.1109/iccca52192.2021.9666332

M. Munde, Jaswantsing Rajput, D. Chikhale, Abhay Wagh

引用次数: 0

Studies on Electrical and Optical Properties of PVC Composites Filled with ZnO Micro Particles ZnO微粒子填充PVC复合材料的电学和光学性能研究

2021 IEEE 6th International Conference on Computing, Communication and Automation (ICCCA) Pub Date : 2021-12-17 DOI: 10.1109/ICCCA52192.2021.9666421

M. Saha, Supriya Sasmal, Subhas Das, R. Sahana, A. Banerjee, A. Lahiri

引用次数: 0

Investigation on Object Detection Models for Plant Disease Detection Framework 植物病害检测框架中目标检测模型的研究

2021 IEEE 6th International Conference on Computing, Communication and Automation (ICCCA) Pub Date : 2021-12-17 DOI: 10.1109/ICCCA52192.2021.9666441

K. R., N. Savarimuthu

{"title":"Investigation on Object Detection Models for Plant Disease Detection Framework","authors":"K. R., N. Savarimuthu","doi":"10.1109/ICCCA52192.2021.9666441","DOIUrl":"https://doi.org/10.1109/ICCCA52192.2021.9666441","url":null,"abstract":"Plant diseases are the most common and severe threat to precision agriculture. Therefore, identification and diagnosis of illnesses at a premature stage are vital. In addition, manual observation according to specific selection criteria is difficult and expensive. While various deep learning-based solutions have been proposed for this process, they usually suffer from lengthy training/testing times with massive datasets. In this paper, to address this problem, we explore the potential of computer vision-based object detection methods for early plant disease detection. A comparative study has been performed with three different benchmark object detection models YOLOv4, EfficientDet, Scaled-YOLOV4. The experimental results were evaluated with precision, recall, F1-score, and mean Average Precision (mAP) as performance metrics. All models are trained using the PlantVillage dataset. Empirical results show that the Scaled-YOLOv4 model is a well suitable object detection model providing a real-time solution in detecting even small infected regions of the plant leaves within less time duration. Therefore, detection and diagnosis of diseases at an early stage of infection are essential.","PeriodicalId":399605,"journal":{"name":"2021 IEEE 6th International Conference on Computing, Communication and Automation (ICCCA)","volume":"13 8","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113967477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Reweighted Error Minimization Algorithm to Enhance Current Following Adaptability in a Multiobjective EV Charging Architecture 多目标电动汽车充电结构中增强电流跟随适应性的加权误差最小化算法

2021 IEEE 6th International Conference on Computing, Communication and Automation (ICCCA) Pub Date : 2021-12-17 DOI: 10.1109/ICCCA52192.2021.9666355

Debasish Mishra, Bhim Singh, B. Panigrahi

{"title":"Reweighted Error Minimization Algorithm to Enhance Current Following Adaptability in a Multiobjective EV Charging Architecture","authors":"Debasish Mishra, Bhim Singh, B. Panigrahi","doi":"10.1109/ICCCA52192.2021.9666355","DOIUrl":"https://doi.org/10.1109/ICCCA52192.2021.9666355","url":null,"abstract":"This paper presents a multi-objective EV charging dynamics with a hybrid configuration of AC and DC charging compatibility. A single-stage photovoltaic (PV) array with battery energy storage (BES) integration is also provided to enhance the charging reliability in presence of grid vulnerability. The hybrid charging architecture provides a seamless charging environment during both grid-connected and islanded operation. A PV-maximum power point tracking algorithm is employed that simultaneous utilizes the BES and PV -array energy sources to minimize the grid dependency during peak hour charging implementation. Unity power factor operation is guaranteed through the grid-connected charging operation to ensure an improved power quality at the grid and EV charging interface. To enable DC fast charging operation a 3-phase isolated dual active bridge (DAB) converter is implemented that operates in phase-shifting modulation to carry out power flow in either of the direction. Similar operation is also depicted with single phase DAB for slow charging operation. A normalized least mean square algorithm is implemented to fasten and stabilize the current tracking operation during multi-mode charging implementation. The charging algorithm is implemented in MATLAB platform with the hybrid EV charging architecture to verify the EV dynamics through multi-objective grid power compensation and enhanced power quality operation.","PeriodicalId":399605,"journal":{"name":"2021 IEEE 6th International Conference on Computing, Communication and Automation (ICCCA)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116361302","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Variable Step Size Adaptive Control for Solar PV-Diesel Generated Based Standalone System 基于独立系统的变步长自适应控制

2021 IEEE 6th International Conference on Computing, Communication and Automation (ICCCA) Pub Date : 2021-12-17 DOI: 10.1109/iccca52192.2021.9666404

G. K. Taneja, Gaurav Modi, Bhim Singh, Ashu Verma

引用次数: 0

Pico-Hydro Power Generation with Seamless Power Transition 具有无缝功率转换的微水力发电

2021 IEEE 6th International Conference on Computing, Communication and Automation (ICCCA) Pub Date : 2021-12-17 DOI: 10.1109/ICCCA52192.2021.9666369

Kripa Tiwari, Bhim Singh

引用次数: 0

Solar PV Fed Multifunctional Power Conversion System 太阳能光伏联供多功能电力转换系统

2021 IEEE 6th International Conference on Computing, Communication and Automation (ICCCA) Pub Date : 2021-12-17 DOI: 10.1109/iccca52192.2021.9666233

Hina Parveen, Utkarsh Sharma, Bhim Singh

引用次数: 0

Deep Learning-based Parkinson disease Classification using PET Scan Imaging Data 基于PET扫描成像数据的深度学习帕金森病分类

2021 IEEE 6th International Conference on Computing, Communication and Automation (ICCCA) Pub Date : 2021-12-17 DOI: 10.1109/iccca52192.2021.9666251

Hetav Modi, Jigna J. Hathaliya, Mohammad S. Obaidiat, Rajesh Gupta, S. Tanwar

{"title":"Deep Learning-based Parkinson disease Classification using PET Scan Imaging Data","authors":"Hetav Modi, Jigna J. Hathaliya, Mohammad S. Obaidiat, Rajesh Gupta, S. Tanwar","doi":"10.1109/iccca52192.2021.9666251","DOIUrl":"https://doi.org/10.1109/iccca52192.2021.9666251","url":null,"abstract":"Parkinson's disease (PSD) is a neurodegenerative disease responsible for damaging the nerve cells inside the human brain. It is classically associated with a loss of dopaminergic neurons (DNs) inside the human brain. DNs can communicate with other nerve cells to generate smooth cooperation, but their insufficiency affects the motor and non-motor symptoms. Earlier, the PSD was recognized via manual examination of its symptoms. Researchers across the globe have given diverse automated solutions to recognize the PSD. Most existing solutions used the standard MRI and SPECT datasets for PSD recognition and less emphasis on the PET scan dataset. Existing PET scan dataset based solutions using machine learning techniques such as linear regression and SVM, which requires manual feature extraction. Motivated from these, we proposed a VGG16-based convolutional neural network (CNN) system to recognize the PSD. It automatically extracts features from the PET scan image dataset, which is collected from the PPMI source. The performance of the proposed system is evaluated using specificity, accuracy, sensitivity, and precision, which is achieved as 97.5%, 84.6%, 71.6%, and 96.7%, respectively.","PeriodicalId":399605,"journal":{"name":"2021 IEEE 6th International Conference on Computing, Communication and Automation (ICCCA)","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128597673","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5

WD-EEMD based Voting Classifier for hand gestures classification using sEMG signals 基于WD-EEMD的基于表面肌电信号的手势分类器

2021 IEEE 6th International Conference on Computing, Communication and Automation (ICCCA) Pub Date : 2021-12-17 DOI: 10.1109/ICCCA52192.2021.9666291

Puru Lokendra Singh, S. Verma, Ankit Vijayvargiya, Rajesh Kumar

{"title":"WD-EEMD based Voting Classifier for hand gestures classification using sEMG signals","authors":"Puru Lokendra Singh, S. Verma, Ankit Vijayvargiya, Rajesh Kumar","doi":"10.1109/ICCCA52192.2021.9666291","DOIUrl":"https://doi.org/10.1109/ICCCA52192.2021.9666291","url":null,"abstract":"In the biomedical field, there are many applications available based on surface EMG (sEMG) signal classification such as human-machine interaction, diagnosis of kinesiological studies and neuromuscular diseases. However, These signals are complicated because noise is generated during the recording of the sEMG signal. In this study, a hybridization of two signal pre-processing techniques, Wavelet Decomposition and Ensemble Empirical Mode Decomposition, called WD-EEMD with Voting classifier, is introduced to classify hand gestures based on sEMG signals. A study of different Decision Tree ensembles has been done for the classification process. Signals are preprocessed, segmented and then classified after extracting relevant features from them. The final prediction of the signal's class is done via a voting mechanism. Different studied pre-processing techniques, similar to that of the proposed methodology with different classifiers have been compared. A new performance metric called confidence has been introduced to analyze the classification procedure. The models have been evaluated and compared on performance criteria like accuracy and overall confidence (gross and true confidence). It has been observed that Gradient Tree Boosting along with WD-EEMD gives the best classification accuracy with high confidence.","PeriodicalId":399605,"journal":{"name":"2021 IEEE 6th International Conference on Computing, Communication and Automation (ICCCA)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127236956","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Advanced Level Shifted Carrier Based Bus Clamping PWM Technique for a 54 Pulse AC to DC Converter Fed MLI Based Induction Motor Drive 54脉冲交直流变换器馈入MLI感应电机驱动的先进水平移位载波母线箝位PWM技术

2021 IEEE 6th International Conference on Computing, Communication and Automation (ICCCA) Pub Date : 2021-12-17 DOI: 10.1109/iccca52192.2021.9666334

S. P. Biswas, S. Haq, Md. Rabiul Islam, M. K. Hosain, R. Shaw

{"title":"Advanced Level Shifted Carrier Based Bus Clamping PWM Technique for a 54 Pulse AC to DC Converter Fed MLI Based Induction Motor Drive","authors":"S. P. Biswas, S. Haq, Md. Rabiul Islam, M. K. Hosain, R. Shaw","doi":"10.1109/iccca52192.2021.9666334","DOIUrl":"https://doi.org/10.1109/iccca52192.2021.9666334","url":null,"abstract":"Power quality improvement at both grid and motor ends is always an industrial concern for multilevel inverter (MLI) fed induction motor drives. The power quality of an induction motor drive (IMD) is vehemently influenced by the pulse width modulation (PWM) technique of the drive systems. The conventional triangle carrier based level shifted (LS) space vector PWM (LS-CSVPWM) technique provides less power quality problems than the LS sinusoidal PWM (LS-SPWM). In this paper, an advanced LS carrier based bus-clamping PWM (ALS-BCPWM) technique is proposed to mitigate the power quality problems of the IMD systems. The proposed technique utilizes center-aligned harmonic injected saturation LS sinusoidal carriers. In this paper, a 54-pulse AC-DC converter is utilized to feed a 7-level (7L) cascaded H-bridge (CHB) inverter based IMD. The proposed ALS-BCPWM technique employed in CHB inverter's switching reduces the total harmonic distortion (THD) of grid current, stator voltage, stator current, inverter switching and conductor power losses, and torque ripple of the IMD. The performance of the proposed ALS-BCPWM technique for IMD is verified in the MATLAB/Simulink environment and through some preliminary experimental tests.","PeriodicalId":399605,"journal":{"name":"2021 IEEE 6th International Conference on Computing, Communication and Automation (ICCCA)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121903872","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 5