2022 IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)最新文献_第9页

Supervised Machine Learning System Based Segmentation and Classification of Strokes Using Deep Learning Techniques 基于监督机器学习系统的笔画分割和分类使用深度学习技术

2022 IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE) Pub Date : 2022-04-23 DOI: 10.1109/icdcece53908.2022.9792818

A. V, A. S, Metun Metun, P. R

{"title":"Supervised Machine Learning System Based Segmentation and Classification of Strokes Using Deep Learning Techniques","authors":"A. V, A. S, Metun Metun, P. R","doi":"10.1109/icdcece53908.2022.9792818","DOIUrl":"https://doi.org/10.1109/icdcece53908.2022.9792818","url":null,"abstract":"Machine learning has gained importance in recent years, helped by lower computer power and also more economical data collection, enabling the safe storage, processing, and analysis of an ever-increasing volume of information. Enhanced procedures were created and deployed in huge datasets for examining hidden information and connections within non-human data sources. These analytics allow corporations to make better decisions and improve key aspects of their applicability. Machine learning has increased in popularity as just an outcome of the balanced utilization of learning techniques. The investigation takes into account various machinery and equipment, as well as supplementary cancer cell treatments for spreading medical resources and several other innovative methods to use these reserves during the period of machine learning to consider making human life a part of this process and explore the better conditions transmitted both by medicine and the computer industry. That the quality of a captured image should be increased directly, and then properly obtained information would be used to identify the image's strokes. This technique provides artifact removal, skull extraction, and system elements to improve those images. This stroke's limits and size are calculated using the feature extraction procedure. The H2O machine learning approach is used to classify strokes, combining texture-based and analytical information.","PeriodicalId":417643,"journal":{"name":"2022 IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128450502","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

Study on Integration of Electric Vehicle with Wind Energy 电动汽车与风能的集成研究

2022 IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE) Pub Date : 2022-04-23 DOI: 10.1109/icdcece53908.2022.9792686

S. Lenka, P. Sinha, C. Jena

{"title":"Study on Integration of Electric Vehicle with Wind Energy","authors":"S. Lenka, P. Sinha, C. Jena","doi":"10.1109/icdcece53908.2022.9792686","DOIUrl":"https://doi.org/10.1109/icdcece53908.2022.9792686","url":null,"abstract":"Presently due to various environmental issues, the clean renewable energy is getting more and more attention attracting more people. Example solar power and wind power. But out of all types of clean energy the wind power is generally utilized for charging the clean-emission electric vehicles (EVs). This is one of the important usages of wind energy. In various micro grids, the wind power output from the wind power plants and subsequent charging of Electric Vehicles (EV) may partially cancel each other. For the reduction in wind power variation to the grid stations, the charging of electric vehicle connected at the load end is one of the effective methods. Due to the forecasting error, the demand of EV charging should be scheduled properly as it is very much necessary under the power crisis of wind. The main reason of scheduling is the unpredictability in the wind power and movable EV. So this task is a arduous one, but in other side improving the wind power utilization is very much necessary. In this paper problems arising in robust scheduling is discussed. The various existing models and the solving methods are studied meticulously. In first step, the tested models for the prediction of wind energy are reviewed and the disparity among models are analysed. In second step, the existing tested models are reviewed for the prediction of movable EV and its challenges. In third step, various existing scheduling methods are reviewed so that the load that is charging of electric vehicle and the generated power that is wind source input match each other.","PeriodicalId":417643,"journal":{"name":"2022 IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131220635","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

Smart Virtual Trial Room For Apparel Industry 服装行业智能虚拟试验室

2022 IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE) Pub Date : 2022-04-23 DOI: 10.1109/icdcece53908.2022.9793030

Finney Daniel Shadrach, M. Santhosh, S. Vignesh, S. Sneha, T. Sivakumar

{"title":"Smart Virtual Trial Room For Apparel Industry","authors":"Finney Daniel Shadrach, M. Santhosh, S. Vignesh, S. Sneha, T. Sivakumar","doi":"10.1109/icdcece53908.2022.9793030","DOIUrl":"https://doi.org/10.1109/icdcece53908.2022.9793030","url":null,"abstract":"In accordance with the development of new technologies, e-commerce is revolutionizing the world, especially in the COVID-19 pandemic. It becomes a major part of the industry in improving revenue. A lot of potential time-consuming in traditional purchasing may lead to failing customer’s trust in apparel industry. So, in e-commerce purchasing, customers get more new collections of apparel, saving money and time. Buying apparel through e-commerce has certain limitations of trying apparel before buying it. However, the proposed system allows customers to experience the fit virtually according to their needs. The main motive of the project is experiencing customer’s outfits before purchasing so that customers can improve their decision-making process. A virtual trial room system improves the accessibility of the garments virtually without any discomfort, enhances customers to feel free to try the fit, comfortable to engage with the environment and there are fewer chances of returning and cancelling products. It detects the customer’s posture and provides 2D virtual garments that are adjusted according to the posture, thus predicting the right fit by measuring the height and width of the body. This application provides interactive, rich and engaging surroundings to the clients.","PeriodicalId":417643,"journal":{"name":"2022 IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128119245","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: 8

Smart Home Automation System Powered by Renewable Energy 可再生能源驱动的智能家居自动化系统

2022 IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE) Pub Date : 2022-04-23 DOI: 10.1109/icdcece53908.2022.9792706

M. Hasan, Touhidul Islam Talukder, Fatema Tauze Zohora Saima, MD. Nazim Uddin Joy, Adrik Das, MD. Nursari Hasan Sheham

{"title":"Smart Home Automation System Powered by Renewable Energy","authors":"M. Hasan, Touhidul Islam Talukder, Fatema Tauze Zohora Saima, MD. Nazim Uddin Joy, Adrik Das, MD. Nursari Hasan Sheham","doi":"10.1109/icdcece53908.2022.9792706","DOIUrl":"https://doi.org/10.1109/icdcece53908.2022.9792706","url":null,"abstract":"The paper's object is to develop a smart home automation system with sustainable renewable energy. The paper presents a conceptualization and implementation of developing a smart home system that uses solar panels to maximize the use of abundant renewable energy. This system is created to minimize the carbon footprint and energy consumption. This will simultaneously be a great solution for the climate issues in the world as well while using renewable energy simultaneously. Integrated renewable energy in this project to build an IoT-based smart automated home system. One of the major features of the system is to integrate the sun tracking method for maximum solar power harnessing. In this SHAS or Smart Home Automation System, lighting, climate, entertainment systems, and appliances are all monitored and controlled by the system. Home security systems such as access control, face recognition, and alarm systems are also be included. The project has features like activating loads using a Bluetooth system. The Arduino UNO board, a Bluetooth module controlled by a remote, and an infrared sensor are used to offer a low-cost and user-friendly remote-controlled home automation system in this work. IoT or Internet of Things technology is used to connect device communication in smart home appliances. In this home automation system technologies are used like Wi-Fi, Bluetooth where several types of electrical devices are used for controlling and monitoring various kinds of appliances of a household. This project offers a low-cost, eco-friendly smart home solution for individuals in underdeveloped nations like Bangladesh.","PeriodicalId":417643,"journal":{"name":"2022 IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","volume":"131 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124594572","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

Data Access Control in Cloud Computing 云计算中的数据访问控制

2022 IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE) Pub Date : 2022-04-23 DOI: 10.1109/icdcece53908.2022.9793300

G. N, Channakrishnaraju

引用次数: 1

Determining Water Quality for Productivity in Aquaculture using Information and Communication Technologies 利用信息和通信技术确定水产养殖生产的水质

2022 IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE) Pub Date : 2022-04-23 DOI: 10.1109/icdcece53908.2022.9792874

K. Rohan, Om Roria, C. Raghavendra, S. Awanti, C. Shruthishree, Srijoni Chakravorty

{"title":"Determining Water Quality for Productivity in Aquaculture using Information and Communication Technologies","authors":"K. Rohan, Om Roria, C. Raghavendra, S. Awanti, C. Shruthishree, Srijoni Chakravorty","doi":"10.1109/icdcece53908.2022.9792874","DOIUrl":"https://doi.org/10.1109/icdcece53908.2022.9792874","url":null,"abstract":"In India, the aquaculture industry makes up around 1.07 percent of the GDP and generate employment for approximately 145 million people according to a recent survey conducted by national fisheries development board. The aquaculture industry generates income of approximately 334.41 billion. This defines the importance of the aquaculture industry in India. In this paper, a system has been designed that is simply based on determining the water quality by monitoring and controlling its parameters for increasing the productivity in aquaculture with the help of Internet of Thing (IoT). The system can help in sharing the value of the parameters and control them. Parameters such as temperature, pH value, dissolved oxygen, turbidity in the water are found. The sensors nodes mentioned above are used to gather the data collected from the sample of water under observation which is further sent to the raspberry pi processor for processing. The measured values from the sensors are viewed on a monitor. Furthermore, the values are noted on a timely basis for the betterment of the aquaculture. The proposed system can work for any type of aquaculture system flawlessly.","PeriodicalId":417643,"journal":{"name":"2022 IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114611899","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

An Analysis of Electro Encephalo Gram Recording Systems and Signal Processing Techniques 脑电图记录系统及信号处理技术分析

2022 IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE) Pub Date : 2022-04-23 DOI: 10.1109/icdcece53908.2022.9793190

B. Pavan, P. Rani

{"title":"An Analysis of Electro Encephalo Gram Recording Systems and Signal Processing Techniques","authors":"B. Pavan, P. Rani","doi":"10.1109/icdcece53908.2022.9793190","DOIUrl":"https://doi.org/10.1109/icdcece53908.2022.9793190","url":null,"abstract":"Electroencephalography (EEG), a monitoring technique for recording the electrical activity of the brain, is typically non-invasive and involves the implantation of electrodes along the scalp to capture the electrical activity. Artifacts are undesirable signals recorded by the EEG that are not created by the brain and are thus not considered to be normal. These artefacts reproduce or imitate real epileptiform abnormalities or seizures in a way that is accurate. This anomaly has the potential to lead to erroneous data analysis. Therefore, it is critical to differentiate between artefacts and the electrical activity of the brain. Establishing an artifact-free EEG recording system is a difficult endeavor since the recorded EEG data is processed to remove artefacts and noisy lines before being used for research. This paper proposes the fejer-korovkin filtering with deep learning LSTM) method. The knowledge-based neural network on the artefacts removed from the fejer-Korovkin filtering data must be utilised to extract the features from the DLN LSTM. In order to improve the accuracy of the previously trained data as well as relevant photos, the PSO naive bayes classifier algorithm must be used for this data. Because of this, it is possible to recover the EEG signal with high accuracy using the classified output that has been generated. From the simulation results the proposed methods shows better results.","PeriodicalId":417643,"journal":{"name":"2022 IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124172668","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

GoogLeNet Application towards Gesture Recognition for ASL Character Identification GoogLeNet手势识别在手语字符识别中的应用

2022 IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE) Pub Date : 2022-04-23 DOI: 10.1109/icdcece53908.2022.9793165

Sushant S Jadhav, Basavaraj Chougula, Gujanatti Rudrappa, Nataraj A. Vijapur, A. Tigadi

{"title":"GoogLeNet Application towards Gesture Recognition for ASL Character Identification","authors":"Sushant S Jadhav, Basavaraj Chougula, Gujanatti Rudrappa, Nataraj A. Vijapur, A. Tigadi","doi":"10.1109/icdcece53908.2022.9793165","DOIUrl":"https://doi.org/10.1109/icdcece53908.2022.9793165","url":null,"abstract":"Gesture recognition plays a vital role in multiple applications; the applications may be related to simple aspects such as playing video games to complex tasks such as related to communication using sign symbols. In this paper, we propose a robust hand gesture recognition system using skin detection technique. Gesture recognition plays a key role for different applications. In this regard, we attempt to take out the type features of the fingers, for instance their orientation, their status in terms of raised or folded fingers and their respective image position, which require the processing of images as a matter of principle. In order to recognize the terms used for contact the program uses a complex approach to distinguish different hand movements. The dynamic sequence of the images that function as a contribution to the hand gesture recognition system is captures using the camera. GoogLeNet is used for hand gesture recognition training and detection. In order to train GoogLeNet, we use transfer learning. We also used American Sign Language (ASL) to map the sign to a particular alphabet.","PeriodicalId":417643,"journal":{"name":"2022 IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","volume":"241 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121471138","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

Application Oriented SEPIC Converter with Improved Voltage Gain for Electric Vehicle Battery Charger 面向应用的提高电压增益的SEPIC变换器用于电动汽车电池充电器

2022 IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE) Pub Date : 2022-04-23 DOI: 10.1109/icdcece53908.2022.9793169

Nirbhay Tiwari, O. P. Rahi

{"title":"Application Oriented SEPIC Converter with Improved Voltage Gain for Electric Vehicle Battery Charger","authors":"Nirbhay Tiwari, O. P. Rahi","doi":"10.1109/icdcece53908.2022.9793169","DOIUrl":"https://doi.org/10.1109/icdcece53908.2022.9793169","url":null,"abstract":"This paper proposes an application-oriented SEPIC (Single-Ended Primary Inductance) converter with modified buck converter for an electric vehicle (EV) charger with high voltage gain. The key benefit of this converter is lowering the switching voltage for the same output voltage. Lower duty cycle leads to lower the conduction losses. As a result, the suggested converter is appropriate for EV chargers with large power ratings. As a result, total efficiency of charger will improve. Discontinuous conduction mode (DCM) is used to provide soft switching for diodes and switches. This improved converter is coupled with a modified buck converter, designed to regulate the current through the battery during the charging period. Modified buck converter has less number of switches and diodes, results in lower switching losses. To confirm the inherent Power Factor (PF) correction qualities to meet the IEC 61000-3-2 criteria, a SIMULINK model has been proposed and tested on electric vehicle battery. The results of this proposed converter have established better performance in terms of greater gain, reduced conduction loss, and an improved efficiency over a traditional one.","PeriodicalId":417643,"journal":{"name":"2022 IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122689125","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

Condition Assessment of Transformer Health by using Intelligent Technique 基于智能技术的变压器健康状态评估

2022 IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE) Pub Date : 2022-04-23 DOI: 10.1109/icdcece53908.2022.9793045

P. Samal, Veena Sharma, Rajesh Kumar

{"title":"Condition Assessment of Transformer Health by using Intelligent Technique","authors":"P. Samal, Veena Sharma, Rajesh Kumar","doi":"10.1109/icdcece53908.2022.9793045","DOIUrl":"https://doi.org/10.1109/icdcece53908.2022.9793045","url":null,"abstract":"The condition of Transformer insulation can be effectively calculated by using the concept of health index. The overall health of transformer can be determined by performing different diagnostic test in the transformer's insulation. The outcome of these tests is used to assess the health and for the estimation of remaining life of transformer. This shows that, the deterioration of transformer insulation takes place with the assistance of several transformer parameters. In this paper, different parameters such as Degree of Polymerization (DOP), Dissolved Gas Analysis (DGA), Insulation Resistance (IR), Dissipation Factor (DF), Frequency Response Analysis (FRA), Breakdown Voltage (BDV), Power Factor (PF), Moisture and Hotspot Temperature are used to develop Fuzzy model and Adaptive neuro fuzzy model for analyzing respective critical conditions of the transformer. The above-mentioned parameters are integrated into one by using Fuzzy logic in Fuzzy Inference System (FIS) and the same is done in case of Adaptive Neuro Fuzzy Logic in Adaptive Neuro Fuzzy Inference System (ANFIS) in MATLAB and it will decide the overall criticality of transformer insulation from which the overall Health index (HI) of Transformer can be found out. These two models give the provision to evaluate the condition of insulation and its criticality level. After calculating the health index by both the models, the results of Fuzzy model and Adaptive neuro fuzzy model are observed and from the observation, it can be said that adaptive neuro fuzzy model has numerous advantages over fuzzy model.","PeriodicalId":417643,"journal":{"name":"2022 IEEE International Conference on Distributed Computing and Electrical Circuits and Electronics (ICDCECE)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129039340","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