2021 5th International Conference on Trends in Electronics and Informatics (ICOEI)最新文献

Design of an Instrumentation Amplifier using Bulk-Driven Op-Amp 基于块驱动运算放大器的仪表放大器设计

2021 5th International Conference on Trends in Electronics and Informatics (ICOEI) Pub Date : 2021-06-03 DOI: 10.1109/ICOEI51242.2021.9452986

G. R, S. Singh, Deepam Dubey

引用次数: 0

Research on Smart City and Information Security in Digital Economy Era 数字经济时代的智慧城市与信息安全研究

2021 5th International Conference on Trends in Electronics and Informatics (ICOEI) Pub Date : 2021-06-03 DOI: 10.1109/ICOEI51242.2021.9452893

Lujian Huang

引用次数: 2

Computer aided mass segmentation in mammogram images using Grey wolf Optimized Region growing technique 利用灰狼优化区域生长技术对乳房x线图像进行计算机辅助质量分割

2021 5th International Conference on Trends in Electronics and Informatics (ICOEI) Pub Date : 2021-06-03 DOI: 10.1109/ICOEI51242.2021.9453051

Ashi Ashok, Devi Vijayan, L. R

{"title":"Computer aided mass segmentation in mammogram images using Grey wolf Optimized Region growing technique","authors":"Ashi Ashok, Devi Vijayan, L. R","doi":"10.1109/ICOEI51242.2021.9453051","DOIUrl":"https://doi.org/10.1109/ICOEI51242.2021.9453051","url":null,"abstract":"One of the dangerous threats, that affect women all around the globe is breast cancer, leading to early mortality in women. According to researchers the survival rate of the breast cancer affected person can be improved by a greater amount by its early detection. Hence, there is need for development of an automated system, which can act as an aid for supporting the radiologists in making proper diagnostic decision. The proposed work involves detection of the breast masses by making use of an optimized region growing method, in which the optimal seed point selection and optimal threshold generation was achieved using Grey Wolf Optimization (GWO). In the proposed work the extraction of both global and local features are being considered. The global features considered includes shape features, Grey Level Co-occurrence Matrix (GLCM) and Grey Level Run Length Matrix (GLRLM) for extracting texture feature and local texture feature is extracted using Local Binary Pattern (LBP) and Scale invariant feature transform (SIFT). The fusion of the local and global features were being fed to Support Vector Machine (SVM) classifier, which differentiates the masses as either benign or malignant in nature. The proposed methodology achieved a highest accuracy of 96% by the fusion of global texture feature GLCM and LBP.","PeriodicalId":420826,"journal":{"name":"2021 5th International Conference on Trends in Electronics and Informatics (ICOEI)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116988340","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

Review on Gait Analysis using Pose Estimation 基于姿态估计的步态分析研究进展

2021 5th International Conference on Trends in Electronics and Informatics (ICOEI) Pub Date : 2021-06-03 DOI: 10.1109/ICOEI51242.2021.9453038

Dimple Sethi, Taniya Sharma, Parul Sehrawat, Himanshi, Aditi Mohanty

引用次数: 0

Detection of COVID-19 Using X-ray Image Classification 基于x线图像分类的COVID-19检测

2021 5th International Conference on Trends in Electronics and Informatics (ICOEI) Pub Date : 2021-06-03 DOI: 10.1109/ICOEI51242.2021.9452745

Kavya Garlapati, N. Kota, Yasaswini Swarna Mondreti, Preethi Gutha, Aswathy K. Nair

{"title":"Detection of COVID-19 Using X-ray Image Classification","authors":"Kavya Garlapati, N. Kota, Yasaswini Swarna Mondreti, Preethi Gutha, Aswathy K. Nair","doi":"10.1109/ICOEI51242.2021.9452745","DOIUrl":"https://doi.org/10.1109/ICOEI51242.2021.9452745","url":null,"abstract":"COVID 19 disease rooted in China, spread across other parts of the world and became a devastating pandemic. The detection of COVID-19 has become a crucial task in the medical sector because of the soaring cases and the paucity of pharmaceutical supplies for detection. Considering the urgency, an immediate auxiliary automatic detection system is required for early diagnosis of the disease and helps the affected patients to be under immediate care. In this work, we aimed to propose an automatic detection system based on lung X-ray images, as radiography modalities is a promising way of faster diagnosis. In this work, we built a machine learning model considering X-ray images taken from publicly available data sets of 2000 images. The relevant features from the images were taken for building the model, prior that proper segmentation was applied to the X-ray images. The X-ray images are prone to noise and spatial aliasing which leads the boundary to be indistinguishable, so proper image segmentation is required Comprehensive validation has been performed on different segmentation techniques, among those, Sobel demonstrated an accurate result, which is not only effective in detecting edges but also good in removing noises within the image. Further, the preprocessed image is fed to a support vector machine (SVM) model, which accomplished the maximum classification accuracy of 99.17%, also SVM achieved precision, recall, and F1 score of 99.24%,98.13%,98.68% respectively in predicting the COVID-19 versus other pulmonary diseases. Taking the advantage. the model can be helpful to medical persons that can be used as an initial screening of individuals.","PeriodicalId":420826,"journal":{"name":"2021 5th International Conference on Trends in Electronics and Informatics (ICOEI)","volume":"66 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127116263","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: 6

On Assisted Quantum Key Authentication Protocol 辅助量子密钥认证协议研究

2021 5th International Conference on Trends in Electronics and Informatics (ICOEI) Pub Date : 2021-06-03 DOI: 10.1109/ICOEI51242.2021.9453009

Supriyo Banerjee, B. Maiti, Banani Saha

引用次数: 0

Effective Network Communication Based on Blockchain Based Trusted Networks 基于区块链可信网络的有效网络通信

2021 5th International Conference on Trends in Electronics and Informatics (ICOEI) Pub Date : 2021-06-03 DOI: 10.1109/ICOEI51242.2021.9452989

R. Agrawal, S. Dorle, Chetan Dhule, Urvashi Agrawal

{"title":"Effective Network Communication Based on Blockchain Based Trusted Networks","authors":"R. Agrawal, S. Dorle, Chetan Dhule, Urvashi Agrawal","doi":"10.1109/ICOEI51242.2021.9452989","DOIUrl":"https://doi.org/10.1109/ICOEI51242.2021.9452989","url":null,"abstract":"Blockchain technology has become increasingly popular as the internet of things (IoT) has grown in popularity. Over NDN(Named Data Networking), blockchain provides an innovative technique to preserve reliable records without relying on a community blockchain machine. A decentralized network and data management has been established throughout the community by utilizing blockchain is proposed in this paper. Moreover, this research work has developed a trust model to enhance the trustworthiness of messages by relying on the popularity of the sender based on parallel mining. Blockchain has been determined as growing generation for establishing decentralized and transactional information sharing throughout a big community of untrusted people. It permits the advent of decentralized surroundings, in which transaction and data below the manipulation of any one third of the party organization. Some transactions are always completed in a public account in a checkable, visible, and permanent manner, accompanied by a stamp and other data. The work gives the comparative analysis on serial mining and parallel mining of data by using blockchain. Also in the study, it is proven that, parallel mining outperforms well when compared to the serial mining of data.","PeriodicalId":420826,"journal":{"name":"2021 5th International Conference on Trends in Electronics and Informatics (ICOEI)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126043250","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

Effect of Network Topologies on Localization using DV-Hop based PSO Algorithm 网络拓扑结构对基于DV-Hop的PSO算法定位的影响

2021 5th International Conference on Trends in Electronics and Informatics (ICOEI) Pub Date : 2021-06-03 DOI: 10.1109/ICOEI51242.2021.9453031

Jyotisha Azad, V. Kanwar, Ashok Kumar

{"title":"Effect of Network Topologies on Localization using DV-Hop based PSO Algorithm","authors":"Jyotisha Azad, V. Kanwar, Ashok Kumar","doi":"10.1109/ICOEI51242.2021.9453031","DOIUrl":"https://doi.org/10.1109/ICOEI51242.2021.9453031","url":null,"abstract":"In WSN, Localization of node plays significant role. Localization is applied to obtain the location of node. Without the knowledge of exact location of node, information collected from this particular node is not much useful. There are various techniques of Localization of nodes in WSN like Range-based and Range-free. In range-based technique extra hardwares required which make it costly but range free required comparatively less hardware. So, we prefer range free localization. Most commonly used range free algorithm is DV-Hop localization algorithm, which is used to evaluate the position of nodes using distance vector method. The proposed research work has analysed the effect of different network topology on the performance of localization algorithm using optimization (like PSO). Here, the simulation has been performed by using MATLAB and comprehensive study on the network topology of different shapes like square-shaped, C-shaped, O-shaped topology has also been performed. The proposed simulation result shows that, the comparison between these different shaped network topology's localization error and its variance.","PeriodicalId":420826,"journal":{"name":"2021 5th International Conference on Trends in Electronics and Informatics (ICOEI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126130127","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

Evaluation of DC Characteristics for a Zinc Oxide (ZnO) based Thin Film Transistor by influence of a Cobalt material 钴材料对氧化锌薄膜晶体管直流特性的影响

2021 5th International Conference on Trends in Electronics and Informatics (ICOEI) Pub Date : 2021-06-03 DOI: 10.1109/ICOEI51242.2021.9452886

J. Pravin, A. Anumanjari, T. Pandimeena, J. S. Fathima

引用次数: 0

Paddy Disease Classifier using Deep learning Techniques 基于深度学习技术的水稻病害分类器

2021 5th International Conference on Trends in Electronics and Informatics (ICOEI) Pub Date : 2021-06-03 DOI: 10.1109/ICOEI51242.2021.9452883

Gowtham Kishore Indukuri, Vedha Krishna Yarasuri, Aswathy K. Nair

引用次数: 2