2021 IEEE 18th India Council International Conference (INDICON)最新文献_第9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

Computer Vision-based Social Distancing Surveillance with Automated Camera Calibration for Large-scale Deployment 大规模部署中基于计算机视觉的自动摄像机标定社会距离监控

2021 IEEE 18th India Council International Conference (INDICON) Pub Date : 2021-12-19 DOI: 10.1109/INDICON52576.2021.9691485

Sreetama Das, Anirban Nag, Dhruba Adhikary, Ramswaroop Jeevan Ram, BR Aravind, S. Ojha, Guruprasad M. Hegde

{"title":"Computer Vision-based Social Distancing Surveillance with Automated Camera Calibration for Large-scale Deployment","authors":"Sreetama Das, Anirban Nag, Dhruba Adhikary, Ramswaroop Jeevan Ram, BR Aravind, S. Ojha, Guruprasad M. Hegde","doi":"10.1109/INDICON52576.2021.9691485","DOIUrl":"https://doi.org/10.1109/INDICON52576.2021.9691485","url":null,"abstract":"Social distancing has been suggested as one of the effective measures to break the chain of viral transmission in the ongoing COVID-19 pandemic. We herein describe a computer vision-based AI-assisted solution to aid compliance with social distancing norms. The solution consists of modules to detect and track people, and to identify distance violations. It provides the flexibility to choose between a tool-based mode requiring user input or a fully automated mode of camera calibration (devised in-house), making the latter suitable for large-scale deployments. We also outline a strategy to estimate the number of video feeds which can be supported in parallel for scalability. Finally, we discuss different metrics to assess the risk associated with social distancing violations, including the use of “violation clusters”, and how we can differentiate between transient or persistent violations. Our proposed solution performs satisfactorily under different test scenarios, processes video feed at real-time speed, as well as addresses data privacy regulations by blurring faces of detected people, making it ideal for deployments.","PeriodicalId":106004,"journal":{"name":"2021 IEEE 18th India Council International Conference (INDICON)","volume":"4 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":"127290469","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: 3

Design Considerations for Low Spur Charge Pump in High Performance Phase Locked Loops 高性能锁相环中低杂散电荷泵的设计考虑

2021 IEEE 18th India Council International Conference (INDICON) Pub Date : 2021-12-19 DOI: 10.1109/INDICON52576.2021.9691703

A. Choudhary, Aniruddha Khade, R. Zele

引用次数: 1

PRFL: Predicate Rank based Fault Localization PRFL:基于谓词秩的故障定位

2021 IEEE 18th India Council International Conference (INDICON) Pub Date : 2021-12-19 DOI: 10.1109/INDICON52576.2021.9691646

Sangharatna Godboley, A. Dutta

引用次数: 1

Malicious URL Classification Using Deep Neural Network 基于深度神经网络的恶意URL分类

2021 IEEE 18th India Council International Conference (INDICON) Pub Date : 2021-12-19 DOI: 10.1109/INDICON52576.2021.9691762

Mainak Sen, K. Ray, A. Chakrabarti

引用次数: 1

Exploiting Web Snippets for Multi-label Anime Genre Prediction 利用Web片段进行多标签动漫类型预测

2021 IEEE 18th India Council International Conference (INDICON) Pub Date : 2021-12-19 DOI: 10.1109/INDICON52576.2021.9691726

Joyeta Sharma, Abu Nowshed Chy

{"title":"Exploiting Web Snippets for Multi-label Anime Genre Prediction","authors":"Joyeta Sharma, Abu Nowshed Chy","doi":"10.1109/INDICON52576.2021.9691726","DOIUrl":"https://doi.org/10.1109/INDICON52576.2021.9691726","url":null,"abstract":"Anime is a type of animation film attributed with highly stylized, colorful-art, imaginary locations, and mature topics that follow the traditional Japanese 2D animation. It is one of the prominent means of entertainment for the young generation. The widespread use of the Internet has led to large volumes of anime-related data being generated and shared online. But it is difficult to find the proper genres information about particular animes. Though some studies exploited the synopsis for movie genre prediction, very few studies focused on anime genres. Therefore, it is a formidable task to design an effective system regarding this to meet the viewers’ satisfaction. In this paper, we exploit the web-search snippets to distill the anime genres information. Upon extracting a set of web snippets for each anime, we employ the naive preprocessing techniques to remove noises from snippet texts. Next, we make use of the n-gram and embedding-based features for effective data representation. Then, a set of state-of-the-art classifiers are employed in our multilabel anime genre prediction framework. We present a comparative performance analysis among these methods that yields a significant insight of using web snippets on genre prediction. Experimental findings demonstrated the efficacy of deep learning-based approaches for this task.","PeriodicalId":106004,"journal":{"name":"2021 IEEE 18th India Council International Conference (INDICON)","volume":"57 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":"128422521","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

Measurement and Evaluation of Human Vital Sign using 77GHz AWR1642 FMCW Radar Sensor 基于77GHz AWR1642 FMCW雷达传感器的人体生命体征测量与评价

2021 IEEE 18th India Council International Conference (INDICON) Pub Date : 2021-12-19 DOI: 10.1109/INDICON52576.2021.9691483

P. Srihari, G. Vandana, B. S. Raghavendra

引用次数: 1

Full Duplex Relay Assisted Coded Cooperation for Next Generation Wireless Networks 下一代无线网络全双工中继辅助编码合作

2021 IEEE 18th India Council International Conference (INDICON) Pub Date : 2021-12-19 DOI: 10.1109/INDICON52576.2021.9691566

Sagnik Bhattacharyya, Pankaj Kumar, S. Darshi, Omraj Burnwal, Kushal Singhal

引用次数: 1

Privacy preserving and secure machine learning 隐私保护和安全机器学习

2021 IEEE 18th India Council International Conference (INDICON) Pub Date : 2021-12-19 DOI: 10.1109/INDICON52576.2021.9691706

Akshay Prabhu, Niranjan Balasubramanian, Chinmay Tiwari, R. Deolekar

引用次数: 1