2021 IEEE 18th India Council International Conference (INDICON)最新文献_第8页

Modeling and Control Implementation of Interleaved Coupled and Uncoupled Boost Converter for EV Drive Applications 电动汽车驱动用交错耦合与非耦合升压变换器的建模与控制实现

2021 IEEE 18th India Council International Conference (INDICON) Pub Date : 2021-12-19 DOI: 10.1109/INDICON52576.2021.9691491

Yedukondalu Guttula, S. Samanta

{"title":"Modeling and Control Implementation of Interleaved Coupled and Uncoupled Boost Converter for EV Drive Applications","authors":"Yedukondalu Guttula, S. Samanta","doi":"10.1109/INDICON52576.2021.9691491","DOIUrl":"https://doi.org/10.1109/INDICON52576.2021.9691491","url":null,"abstract":"Electric vehicle (EV) drive train includes a motor drive system and battery. Due to the limited voltage level of the battery, there will be huge current flow through the motor windings, so conduction losses of the motor will increase, which will affect the motor drive performance. Therefore, a bidirectional dc-dc converter is placed in between the battery and motor drive to maintain high dc-link voltage. In general, a high-power dc-dc converter is used for practical EV applications. The conventional high power converter draws a very high current during the acceleration and deceleration of the motor drive. But, in an interleaved technique, the input current will be shared by each phase. The interleaving process can be done by using either uncoupled and coupled inductors. In this paper, the design and analysis of uncoupled and coupled interleaved boost converter (IBC) have been studied by considering the parasitics of all the components. The state-space averaging technique has been used to study the small-signal modeling of IBC. Two-phase IBC uncoupled and coupled has been studied using continuous current mode (CCM). Average current mode controller (ACMC) implemented for both the coupled and uncoupled converters, simulations have tested for 2 KW power rating using MATLAB software.","PeriodicalId":106004,"journal":{"name":"2021 IEEE 18th India Council International Conference (INDICON)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122427873","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

AI Driven Edge Device for Screening Skin Lesion and Its Severity in Peripheral Communities 人工智能驱动边缘设备筛选周边社区皮肤病变及其严重程度

2021 IEEE 18th India Council International Conference (INDICON) Pub Date : 2021-12-19 DOI: 10.1109/INDICON52576.2021.9691666

Chathura.N. Jaikishore, Venkanna Udutalapally, Debanjan Das

{"title":"AI Driven Edge Device for Screening Skin Lesion and Its Severity in Peripheral Communities","authors":"Chathura.N. Jaikishore, Venkanna Udutalapally, Debanjan Das","doi":"10.1109/INDICON52576.2021.9691666","DOIUrl":"https://doi.org/10.1109/INDICON52576.2021.9691666","url":null,"abstract":"It is vital to treat any skin disorder as early as possible. Neglecting the rudimentary skin disease may lead to acute skin cancer. Skin diseases are mostly neglected in peripheral regions because of a lack of awareness and accessibility to dermatologists. Therefore, it is important to diagnose skin diseases promptly and take countermeasures to treat them effectively. The paper presents a novel method to detect skin disease and its severity using a mobile application. A dataset consisting of four classes- Eczema, Measles, Leprosy, and Healthy Normal Skin is chosen in this proposed work. The images are passed through two modified CNN architectures. The first layer is a modified Mobile Net V2 architecture that aids in predicting the type of skin disease, which is referred to as SkinLesion Net. The next layer that predicts the severity of the disease is named SeverityNet. Observant comparison on four different CNN architectures - VGGl6,Inception V3, Xception and the proposed SkinLesion Net, is performed using this image dataset. Skin Lesion Net outperforms the other networks with 94.32% accuracy, 93.02% F1-Score, 93.53% Precision and 92.76% Recall. The model is lightweight, about 14 MB in size, which is appropriate for deployment into an Android application.","PeriodicalId":106004,"journal":{"name":"2021 IEEE 18th India Council International Conference (INDICON)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122629937","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

Benchmarking Shallow and Deep Neural Networks for Contextual Representation of Social Data 对社会数据上下文表示的浅层和深层神经网络进行基准测试

2021 IEEE 18th India Council International Conference (INDICON) Pub Date : 2021-12-19 DOI: 10.1109/INDICON52576.2021.9691551

Reshma Unnikrishnan, S. Sowmya Kamath, V. S. Ananthanarayana

引用次数: 3

Machine Comprehension Comparison using Latest Advancements in Deep Learning 使用深度学习最新进展的机器理解比较

2021 IEEE 18th India Council International Conference (INDICON) Pub Date : 2021-12-19 DOI: 10.1109/INDICON52576.2021.9691737

Aryan Kumar Singh, Kapil Gyanchandani, Pramod Kumar Singh, J. Prakash

{"title":"Machine Comprehension Comparison using Latest Advancements in Deep Learning","authors":"Aryan Kumar Singh, Kapil Gyanchandani, Pramod Kumar Singh, J. Prakash","doi":"10.1109/INDICON52576.2021.9691737","DOIUrl":"https://doi.org/10.1109/INDICON52576.2021.9691737","url":null,"abstract":"Machine Comprehension or Question Answering (QA) is one of the most challenging natural language processing tasks due to the language’s dynamic nature and understanding the context of the question. In this paper, we propose a similarity attention layer with an aim to reduce human labor by automating tedious QA tasks using the attention mechanism in deep learning model; it uses attention scores and obtains good results even without pre-training. The QA using attention has immense scope in search engine optimization, page ranking, and chatbots. The traditional rule-based models and statistical methods underperform due to variations in the language. This dynamic nature of the language is well captured by the nonlinear learning of the neural networks. The conventional encoder-decoder architecture of neural networks for QA works well in the case of short sentences. However, the performance comes down for paragraphs and very long sentences as it is difficult for the network to memorize the super-long sentences. In contrast, the attention model helps the network focus on smaller attention areas in the complex input paragraph, part by part, until the entire text is processed. The results are very promising; our (single) model outperforms the existing ensemble method too.","PeriodicalId":106004,"journal":{"name":"2021 IEEE 18th India Council International Conference (INDICON)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126663914","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

SCADA WebView: A State-of-the-Art Enterprise Transmission SCADA Engine SCADA WebView:一个最先进的企业传输SCADA引擎

2021 IEEE 18th India Council International Conference (INDICON) Pub Date : 2021-12-19 DOI: 10.1109/INDICON52576.2021.9691604

S. Saurav, P. Sudhakar, K. J. Mohan, R. Senthil Kumar, S. Bindhumadhava Bapu

{"title":"SCADA WebView: A State-of-the-Art Enterprise Transmission SCADA Engine","authors":"S. Saurav, P. Sudhakar, K. J. Mohan, R. Senthil Kumar, S. Bindhumadhava Bapu","doi":"10.1109/INDICON52576.2021.9691604","DOIUrl":"https://doi.org/10.1109/INDICON52576.2021.9691604","url":null,"abstract":"The Industrial Control System is experiencing a massive redesign because of the digital transition and the promises of Industry 4.0 and Industry 5.0. The convergence of Information Technology and Operational Technology has reinforced the Process Industry as a cyber-physical ecosystem. In today’s industrial automation environment, the Internet of Things and Industrial Internet of Things have become intrinsically tied. SCADA systems are crucial for monitoring and managing control parameters and notifying system failures to reduce downtime in the process industry. The SCADA operations, such as data collection, control operations, and visualization, have undergone substantial changes because of technological advancements. These transformations have motivated us to design and implement a novel SCADA engine using the latest technologies. The SCADA WebView is an innovative Enterprise Transmission SCADA engine developed under the COPS framework for the power sector. It can also be tailored to different process industries. This product has been extensively deployed across the Indian Power Grid. In the future, an AI-based cognitive decision-making system will be incorporated for optimal control.","PeriodicalId":106004,"journal":{"name":"2021 IEEE 18th India Council International Conference (INDICON)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125301235","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

Multi-object Foreground Extraction in Streaming Video using Low Rank Sparse Decomposition 基于低秩稀疏分解的流视频多目标前景提取

2021 IEEE 18th India Council International Conference (INDICON) Pub Date : 2021-12-19 DOI: 10.1109/INDICON52576.2021.9691672

Yogesh Sanku, Soumyo Bhattacharjee, Saumik Bhattacharya

引用次数: 1

Hospital Assistant Robotic Vehicle (HARVi) 医院助理机器人车(HARVi)

2021 IEEE 18th India Council International Conference (INDICON) Pub Date : 2021-12-19 DOI: 10.1109/INDICON52576.2021.9691738

Yadu Krishnan, Vaisakh Udayan, S. Akhil

引用次数: 1

Multi-attribute based prosumers prioritization for energy trading in Smart Grid 基于多属性的智能电网产消能源交易优先排序

2021 IEEE 18th India Council International Conference (INDICON) Pub Date : 2021-12-19 DOI: 10.1109/INDICON52576.2021.9691544

N. N. Devi, Surmila Thokchom

引用次数: 0

Cognitive State Classification using Optimized Feature Selection Approach 基于优化特征选择方法的认知状态分类

2021 IEEE 18th India Council International Conference (INDICON) Pub Date : 2021-12-19 DOI: 10.1109/INDICON52576.2021.9691622

J. S. Ramakrishna

引用次数: 0

Quality Assessment of Deep Learning Based Super Resolution Techniques on Thermal Images 基于深度学习的热图像超分辨率技术质量评估

2021 IEEE 18th India Council International Conference (INDICON) Pub Date : 2021-12-19 DOI: 10.1109/INDICON52576.2021.9691653

Shashwat Pandey, Darshika Sharma, B. Kumar, Himanshu Singh

{"title":"Quality Assessment of Deep Learning Based Super Resolution Techniques on Thermal Images","authors":"Shashwat Pandey, Darshika Sharma, B. Kumar, Himanshu Singh","doi":"10.1109/INDICON52576.2021.9691653","DOIUrl":"https://doi.org/10.1109/INDICON52576.2021.9691653","url":null,"abstract":"This paper presents a new quality assessment parameter for the evaluation of deep learning based super resolution techniques applied on thermal images. Three widely used deep learning-based models namely Super-Resolution Convolutional Neural Network (SRCNN), Thermal Enhancement Network (TEN) and Very Deep Super Resolution (VDSR) have been implemented for achieving super resolution of thermal images. Peak Signal to Noise Ratio (PSNR) and Structural Similarity Index (SSIM) have been the most widely used conventional evaluation metrics for performance measurement of super resolution algorithms. Since these parameters require a reference image for the evaluation of the resultant images, we propose a new quality assessment parameter based on strength of the edges. Edge detection of the super resoluted image is performed utilizing Canny Edge Detection method and the entropy of the edge detection image is computed to provide a new parameter, Edge Detection Entropy Score (EDES). For the comparison and validation of the proposed image quality assessment techniques, Mean Opinion Score (MOS) of the target images have been obtained to be used as a benchmark. The obtained results indicate that the proposed EDES of the super resoluted images has high degree of correlation with the MOS as well as PSNR and SSIM.","PeriodicalId":106004,"journal":{"name":"2021 IEEE 18th India Council International Conference (INDICON)","volume":"1992 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128609839","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