2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT)最新文献_第5页

A Review on Charge Control Techniques for Batteries in Electric Vehicles 电动汽车电池充电控制技术研究进展

2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT) Pub Date : 2022-04-21 DOI: 10.1109/ICAECT54875.2022.9808007

Jeny Sophia S, K. R, S. P., Nandini G. Iyer, A. M, Nivethitha S B

引用次数: 2

High Frequency Response Pulse Processing Front-end for the Radiation Detector 辐射探测器高频响应脉冲处理前端

2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT) Pub Date : 2022-04-21 DOI: 10.1109/ICAECT54875.2022.9807851

V. Neha, Balaram Mohanty, Abhishek Basu, Mohammed Salah Shaikh, Sridhar Bonda, I. Mirza

引用次数: 0

Channel prior based Retinex model for underwater image enhancement 基于信道先验的水下图像增强Retinex模型

2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT) Pub Date : 2022-04-21 DOI: 10.1109/ICAECT54875.2022.9807919

Sathvik Srinivas, V. R. Siddharth, Surya Dutta, Nikhil S. Khare, Lavanya Krishna

{"title":"Channel prior based Retinex model for underwater image enhancement","authors":"Sathvik Srinivas, V. R. Siddharth, Surya Dutta, Nikhil S. Khare, Lavanya Krishna","doi":"10.1109/ICAECT54875.2022.9807919","DOIUrl":"https://doi.org/10.1109/ICAECT54875.2022.9807919","url":null,"abstract":"Since light undergoes absorption and scattering when it travels in water, images taken under water fall prey to color distortion, fuzziness/haziness, underexposure, and color cast. To alleviate these issues, this paper proposes a novel Retinex-based enhancing approach aimed at enhancing low-quality under-water images. Firstly, the input image undergoes pre-processing, where a color correction technique is employed to address the problem of color distortion. This is followed by conversion of the input image from the Red, Green and Blue color space to the Lab color space. Then, by means of the multi scale Retinex, the illumination component of the image is procured. Image dehazing algorithms, i.e., bright channel prior and underwater dark channel prior algorithms are applied individually on the procured illumination component. The image gets enhanced and is then converted back to the Red, Green and Blue color space from the Lab color space. The final enhanced image is obtained by performing histogram equalization on the enhanced Red, Green and Blue image. This is intended to make the output color intensity more realistic. The efficacy of the algorithms are gauged by means of some image quality metrics. Compared to pre-existing techniques, the method proposed manages to effectively enhance images while keeping detail loss to a minimum.","PeriodicalId":346658,"journal":{"name":"2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133489710","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

Cultivating Tulip at Extent by Using Machine Learning in Context to Bangladesh 在孟加拉国使用机器学习在一定程度上培育郁金香

2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT) Pub Date : 2022-04-21 DOI: 10.1109/ICAECT54875.2022.9807948

Md Riad Hasan, Abir Abdullha, Md. Forhad Hossain, A. Sattar

引用次数: 0

A Unified and Semantic Model Approach for Histopathologic Cancer Detection Based on Deep Double Transfer Learning 基于深度双迁移学习的组织病理学肿瘤检测统一语义模型方法

2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT) Pub Date : 2022-04-21 DOI: 10.1109/ICAECT54875.2022.9807873

U. R, S. B., S. G

{"title":"A Unified and Semantic Model Approach for Histopathologic Cancer Detection Based on Deep Double Transfer Learning","authors":"U. R, S. B., S. G","doi":"10.1109/ICAECT54875.2022.9807873","DOIUrl":"https://doi.org/10.1109/ICAECT54875.2022.9807873","url":null,"abstract":"Accurately predicting the risk of cancer recurrence and metastasis is very important for individual cancer treatment. Currently, doctors usually use a histological grade that pathologists determine by performing a semi-quantitative analysis of the three histopathological and cytological features of hematoxylin-eosin (HE) stained histopathological images. Evaluate the prognosis and treatment options of patients with breast cancer. In order to efficiently and objectively fully utilize the valuable information underlying HE-stained histopathological images, this work has potential as a feature for constructing a classification model of cancer prognosis. So, a calculation method is proposed to extract morphological information. Breast cancer is not a single disease, but it is composed of many different biological entities with different pathological features and clinical significance. With the advent of personalized medicine, pathologists are facing a significant increase in the workload and complexity of digital pathology in cancer diagnosis, and diagnostic protocols need to focus on equal efficiency and accuracy. Computer-aided image processing techniques have been shown to be able to improve the efficiency, accuracy, and consistency of histopathological assessments and provide decision support to ensure diagnostic consistency. First, a method for segmenting tumor lesions based on a pixel-by-pixel deep learning classifier is proposed and a method for segmenting cell nuclei based on marker-driven watersheds. It then subdivides all image objects and extracts a rich set of predefined quantitative morphological object feature. Then a classification model based on these measurements is used to predict disease-free survival in binary patients. Finally, the predictive model is tested in two independent cohorts of breast cancer patients.","PeriodicalId":346658,"journal":{"name":"2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122096922","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

Implementation of Z-Source Resonant Converter for Power Factor Correction & Wireless Charging Applications 用于功率因数校正和无线充电应用的z源谐振变换器的实现

2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT) Pub Date : 2022-04-21 DOI: 10.1109/ICAECT54875.2022.9807975

Ayush Srivastava, Narendra Kumar

引用次数: 0

CBMIR: Content Based Medical Image Retrieval Using Hybrid Texture Feature Extraction Method 基于内容的混合纹理特征提取医学图像检索

2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT) Pub Date : 2022-04-21 DOI: 10.1109/ICAECT54875.2022.9807970

R. B, M. Prasanna

{"title":"CBMIR: Content Based Medical Image Retrieval Using Hybrid Texture Feature Extraction Method","authors":"R. B, M. Prasanna","doi":"10.1109/ICAECT54875.2022.9807970","DOIUrl":"https://doi.org/10.1109/ICAECT54875.2022.9807970","url":null,"abstract":"Due to the revolution of digital era in the medical domain at various hospitals across the world, the online users on the internet access have been increased. So the amount of collections of digitized medical images has grown rapidly and continuously. As well it is ratting significant to mention that the images are globally used by radiologists, professors in medical colleges and Lab technicians, etc. These Images are increasingly applied to communicate information about patient history. In this context, there is a necessity to develop appropriate systems to manage these medical images in storage and retrieval for diagnosis of the patient information. Another big issue is the convolution of image data and that can be interpreted in different ways. In order to manipulate these data and establish policies to its content is very tedious job. This will raise another big question. These issues motivated the researchers to give more focus on the image retrieval area whose goal is trying to solve those problems to provide an efficient retrieval system to the user community. In this perspective, this work has been proposed to facilitate radiologists, professors in medical colleges, lab technicians, and all other medical image user communities for their purpose for easy access from the remote location.","PeriodicalId":346658,"journal":{"name":"2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131730387","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

ResMintage: Leveraging Blockchain Technology to Share Hardware Resources ResMintage:利用区块链技术共享硬件资源

2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT) Pub Date : 2022-04-21 DOI: 10.1109/ICAECT54875.2022.9808080

Meet Shah, Ankit Vishwakarma, Krish Sukhani, Nikahat Mulla

{"title":"ResMintage: Leveraging Blockchain Technology to Share Hardware Resources","authors":"Meet Shah, Ankit Vishwakarma, Krish Sukhani, Nikahat Mulla","doi":"10.1109/ICAECT54875.2022.9808080","DOIUrl":"https://doi.org/10.1109/ICAECT54875.2022.9808080","url":null,"abstract":"Data storage and protection are key concerns in today's world. Organizations have increased their network infrastructure to provide cloud storage and resource access to as many individuals as possible, which raises issues about the privacy of data stored or shared over a network. A centralized authority cannot manage such a vast data network. Cloud storage and other data infrastructure are becoming increasingly expensive as demand grows. Cases of data breaches and attacks have been recorded year after year, and the numbers continue to grow. Many firms, including LinkedIn and Facebook, have experienced massive data breaches in recent years. Another issue discovered was that idle hardware was not being used by many local computers. Although there are people and organizations with surplus local storage capacity, many organizations are looking for additional cloud storage. To address the aforementioned issues, this paper proposes a solution that uses Blockchain Technology to enable individuals or organizations to share hardware resources. Blockchain employs a peer-to-peer design. As Blockchain employs cryptographic techniques, it has the highest security factor of any system. This paper proposes a system in which users can share their local resources with users in need via a blockchain because there is a clear supply and demand requirement for resources. Users that share hardware resources will also be rewarded. There will be no need for any central authority to manage the data or the data kept with the shared resource with blockchain, preserving user privacy and security.","PeriodicalId":346658,"journal":{"name":"2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT)","volume":"144 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129195812","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

Design and Optimization of Transformer by Combining Finite Element Approach and Improved Genetic Algorithm 结合有限元法和改进遗传算法的变压器设计与优化

2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT) Pub Date : 2022-04-21 DOI: 10.1109/ICAECT54875.2022.9807885

Uma Bharathi, Kaaviya Vharshiny, Shreshth Verma, Asmita Ajay, B. Sreekeessoon, R. C. Naidu

{"title":"Design and Optimization of Transformer by Combining Finite Element Approach and Improved Genetic Algorithm","authors":"Uma Bharathi, Kaaviya Vharshiny, Shreshth Verma, Asmita Ajay, B. Sreekeessoon, R. C. Naidu","doi":"10.1109/ICAECT54875.2022.9807885","DOIUrl":"https://doi.org/10.1109/ICAECT54875.2022.9807885","url":null,"abstract":"The electrical transformer is a crucial component for altering voltage levels in the electricity system. Electrical transformers are normally constructed by trial and error, but some obstacles, such as expensive prices or unexpected performance, may occur from time to time. Often, transformer optimization design aims to reduce manufacturing costs or boost transformer efficiency. Several literatures have lately highlighted the finite element approach and artificial intelligence (AI) methodologies for enhancing transformer performance. For example, artificial neural networks(ANNs) may be used to forecast the function of core design parameters when employing AI to analyse transformer loss . Georgilakis and colleagues likewise employed artificial neural networks to minimize core loss in constructed transformers, and the Taguchi technique was used to improve individual core manufacturing process losses. A multiple technique is an effective solution even if the objective functions of transformer design are relatively complicated. For transformer optimization, one of the versatile approaches, which combines the finite element method (FEM) with the genetic algorithm (GA), is advantageous. The objective of the study is to provide the results of a multi-method investigation into transformer design optimization. The genetic algorithm (GA) and the finite element approach(FEM) are combined in this multiple methodology .","PeriodicalId":346658,"journal":{"name":"2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131824964","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

Traffic Prediction for Intelligent Transportation System Using Machine Learning 基于机器学习的智能交通系统交通预测

2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT) Pub Date : 2022-04-21 DOI: 10.1109/ICAECT54875.2022.9807652

V. Swathi, Sirisha Yerraboina, G. Mallikarjun, M. Jhansirani

{"title":"Traffic Prediction for Intelligent Transportation System Using Machine Learning","authors":"V. Swathi, Sirisha Yerraboina, G. Mallikarjun, M. Jhansirani","doi":"10.1109/ICAECT54875.2022.9807652","DOIUrl":"https://doi.org/10.1109/ICAECT54875.2022.9807652","url":null,"abstract":"It is commonly believed that ITS can assist relieve urban transportation congestion. Traffic forecasting is the most important function of an ITS. An accurate and timely traffic flow forecasting tool is the goal of this project. Every factor that can affect traffic flow on the road, from accidents to rallies to road repairs, is included in the Traffic Environment. A motorist or passenger can make an informed decision if they have prior information that is close to accurate about all of the above and many more everyday life conditions that can affect traffic. The development of self-driving cars will also benefit from this research. In the previous couple decades, we've seen a shift toward big data approaches for transportation as traffic data has risen tremendously. For real-world applications, the available prediction algorithms all use some form of traffic flow model, although this model is inadequate. Using a traffic forecasting and estimation system can assist reduce traffic congestion and increase the capacity of roadways. Smart cities' traffic forecasts are detailed in detail, as well as the issues and constraints that these forecasting models confront. This will be the subject of our discussion in this essay. The multiparameter integration theory. Co integration theory is a novel modelling method that studies time series data and long-term equilibrium links between non stationary variables. Random errors in traffic patterns gathered over the same period of time show a strong correlation. If speed, density, and occupancy rate are all taken into account together, it is possible to improve short-term projections of traffic flow.","PeriodicalId":346658,"journal":{"name":"2022 Second International Conference on Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132860323","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