2021 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)最新文献

Experimental And Numerical Studies on Mechanical Resonance of Piezoelectric Hemispherical Resonator Gyroscope 压电半球形谐振陀螺仪机械共振的实验与数值研究

2021 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT) Pub Date : 2021-07-09 DOI: 10.1109/CONECCT52877.2021.9622701

Pradnya Chabbi, Diplesh Gautam, Venkatesh K. P. Rao

引用次数: 3

Path Planning Scheme for Collision Avoidance in Unmanned Aerial Vehicle Traffic Management System 无人机交通管理系统中避碰路径规划方案

2021 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT) Pub Date : 2021-07-09 DOI: 10.1109/CONECCT52877.2021.9622656

Amaanullah, Muhammed Ahmed Lamba, S. S, Shrikant S. Tangade, Syed Sehraab Nawaz, S. Manvi

引用次数: 0

Synthetic Vertebral Column Fracture Image Generation by Deep Convolution Generative Adversarial Networks 基于深度卷积生成对抗网络的合成脊柱骨折图像生成

2021 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT) Pub Date : 2021-07-09 DOI: 10.1109/CONECCT52877.2021.9622527

Sindhura D N, R. Pai, Shyamasunder N. Bhat, M. M

{"title":"Synthetic Vertebral Column Fracture Image Generation by Deep Convolution Generative Adversarial Networks","authors":"Sindhura D N, R. Pai, Shyamasunder N. Bhat, M. M","doi":"10.1109/CONECCT52877.2021.9622527","DOIUrl":"https://doi.org/10.1109/CONECCT52877.2021.9622527","url":null,"abstract":"In the field of medical imaging, the challenging objective is to generate synthetic, realistic images which resembles the original images. The generated synthetic images would enhance the accuracy of the computer-assisted classification, Decision Support System, which aid the doctor in diagnosis of diseases. The Generative Adversarial Networks (GANs), is a method of data augmentation which can be used to generate synthetic realistic looking images, however low quality images are generated. For AI models, it is challenging tasks to do classification using this low quality images. In this work, generation of high quality synthetic medical image using Deep Convolutional Generative Adversarial Networks (DCGANs) is presented. Data augmentation method by DCGANs is illustrated on the limited dataset of CT (Computed Tomography) images of vertebral column fracture. A total of 340 CT scan images were taken for the study, which comprises of complete burst fracture scans of vertebral column. The evaluation of the generated images was done with Visual Turing Test.","PeriodicalId":164499,"journal":{"name":"2021 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126731982","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

Comparison of Containerization and Virtualization in Cloud Architectures 云架构中容器化和虚拟化的比较

2021 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT) Pub Date : 2021-07-09 DOI: 10.1109/CONECCT52877.2021.9622668

Anirnddh M, Anubhav Dinkar, Shashank C Mouli, S. B, Abhay A Deshpande

引用次数: 2

Human Activity Recognition Using Elliptical and Archimedean R-Vine Copulas with Multimodal Data 基于多模态数据的椭圆和阿基米德R-Vine copula人类活动识别

2021 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT) Pub Date : 2021-07-09 DOI: 10.1109/CONECCT52877.2021.9622736

Shreyas Kulkarni, S. R, Rahul Rk, Harshith M, Sahana Srikanth, Sanjeev Gurugopinath

引用次数: 0

Contingency Ranking for Voltage Stability in Power System 电力系统电压稳定的应急排序

2021 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT) Pub Date : 2021-07-09 DOI: 10.1109/CONECCT52877.2021.9622724

Fida Hussian, G. Goyal, A. Arya, B. Soni

{"title":"Contingency Ranking for Voltage Stability in Power System","authors":"Fida Hussian, G. Goyal, A. Arya, B. Soni","doi":"10.1109/CONECCT52877.2021.9622724","DOIUrl":"https://doi.org/10.1109/CONECCT52877.2021.9622724","url":null,"abstract":"Continuous assessment of voltage stability is vital to ensure a secure operation of the power system. Several voltage stability indicators have been developed in an attempt to quantify proximity to voltage collapse. Some of them are computationally expensive, whereas others are reported not to perform as expected under all conditions. This paper deals with the voltage stability index for an outage of a power transmission line. This index indicates that how sensitive the line is to voltage stability after the occurrence of a fault. The voltage stability index of the line becomes low when it gets faulted. The voltage stability index is determined for all possible outage conditions in each line of the system. After that, according to their stability indexing lines are ranked in descending order. This kind of ranking is very helpful in preventing the system from complete blackouts or failure. The effectiveness of the proposed methodology is demonstrated on IEEE 6-bus power system. The approach can be beneficial tool which is less time consuming and accurate security assessment and contingency analysis at energy management center. The simulation results show that the severity of a line outage can be indicated by contingency ranking analysis.","PeriodicalId":164499,"journal":{"name":"2021 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129619493","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: 4

A Multiband CPW-Fed Flexible Frequency and Radiation Pattern Reconfigurable Antenna 一种多波段cpw馈电柔性频率和辐射方向图可重构天线

2021 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT) Pub Date : 2021-07-09 DOI: 10.1109/CONECCT52877.2021.9622643

Samiyalu Usurupati, Immanuel Raja, C. Saha

引用次数: 0

Role of Substrates on SAW Filter Performance and Comparative Analysis 基片对SAW滤波性能的影响及对比分析

2021 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT) Pub Date : 2021-07-09 DOI: 10.1109/CONECCT52877.2021.9622653

Nirupam Sharma, B. Darukesha, Shiv Pratap Singh, Kamaljeet Singh, A. V. Nirmal

引用次数: 0

Evolution of 3D images from 2D images 从2D图像到3D图像的演化

2021 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT) Pub Date : 2021-07-09 DOI: 10.1109/CONECCT52877.2021.9622698

V. S, S. M

{"title":"Evolution of 3D images from 2D images","authors":"V. S, S. M","doi":"10.1109/CONECCT52877.2021.9622698","DOIUrl":"https://doi.org/10.1109/CONECCT52877.2021.9622698","url":null,"abstract":"To present a model, which will reshape the raw 3D specific single-view images by learning the deformable object categories using unsupervised techniques. Using Convolutional autoencoders, each raw image will be taken as input, then this will be compressed by considering factors such as depth, albedo, viewpoint and illumination of a particular input. Autoencoders are basically used for efficient data codings in an unsupervised manner. These components can disentangled without any labels or supervisor based on the symmetric structure of the object. This model shows the reasoning about illumination which allows us to exploit the underlying object symmetry even if the appearance is not symmetric due to shading. Furthermore, this model objects that are probably, but not certainly, symmetric by predicting a symmetry probability map, learned end-to-end with the other components of the model. This model can recover very accurately the 3D shape of human faces, cat faces and cars from single-view images, without any supervision or a prior shape model. On benchmarks, model will be demonstrated with superior accuracy when compared to another method that uses supervision at the level of 2D image correspondences.","PeriodicalId":164499,"journal":{"name":"2021 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)","volume":"03 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130551118","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

Performance Evaluation of Mobile Edge Computing using 5G Networks 基于5G网络的移动边缘计算性能评估

2021 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT) Pub Date : 2021-07-09 DOI: 10.1109/CONECCT52877.2021.9622523

V. S, N. E., Vijay G R

{"title":"Performance Evaluation of Mobile Edge Computing using 5G Networks","authors":"V. S, N. E., Vijay G R","doi":"10.1109/CONECCT52877.2021.9622523","DOIUrl":"https://doi.org/10.1109/CONECCT52877.2021.9622523","url":null,"abstract":"With the number of people increased in using mobile devices, the usage of internet is exponentially growing and it causes more traffic congestion with the emerging devices like Internet of Things. So with this the requirements of delay and bandwidth for the network performance are increasing along with the latency in accessing the required information is increasing. Therefore, the new devices which support minimal delay have major issues. That is why the Mobile Edge Computing devices are introduced, which can reduce the latency in accessing and it can be used in both wired and wireless networks or mobile applications All the activities can be performed with the network edge in Edge Computing. Communication latency can be reduced in the devices and in between cloud and the devices, this technology is mainly used. All the resources of the cloud and local devices can be utilised in Edge Computing. This paper gives the detailed description of the performance analysis of Mobile Edge Computing devices with the single tier BS in communication with the remote cloud computing servers. The proposed work also discusses about the challenges faced in designing the Mobile Edge Computing enabled networks which is deployed in the single tier BS offloading for dynamic mobile users. The performance of edge computing is more when the network nodes are within the proximity of the end devices. The small amount of data is received also can reduce the end-to-end latency and bandwidth usage. The performance of Edge Computing can be measured easily with the fast networking speed with low delay supporting mobile applications for the dynamic mobile users.","PeriodicalId":164499,"journal":{"name":"2021 IEEE International Conference on Electronics, Computing and Communication Technologies (CONECCT)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114689409","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