2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT)最新文献_第3页

Nejat Control Gain Series Method Nejat控制增益级数法

2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT) Pub Date : 2022-10-07 DOI: 10.1109/GCAT55367.2022.9972147

Cyrus Nejat

{"title":"Nejat Control Gain Series Method","authors":"Cyrus Nejat","doi":"10.1109/GCAT55367.2022.9972147","DOIUrl":"https://doi.org/10.1109/GCAT55367.2022.9972147","url":null,"abstract":"Fuzzy logic control and digital logic control are in two different realm of control systems because one is dealing with uncertainty of true or false (Fuzzy) and the other one is based on either true or false that is in most cases 0 and 1 (digital). In this paper, there is an attempt to introduce a method that can be used to tune either Fuzzy logic control and digital logic control. Nejat Control Gain Series Method is created by the author to reach the desire output and in some cases to stabilize a SISO or MIMO system in order to achieve desired output(s). It uses series of gains in the system by multiplications and divisions, in the other word: gaining up and gaining down of the systems by placing gains at multiple locations in a system. It is a good method when using controller and notch filter in a system. By multiply the open loop input by gain to increase or decrease the magnitude of a system and then divide the output by another gain to increase decrease the magnitude of a system in which a controller and Notch filter would be designed based on these back and forward gain multiplication and divisions. This Method is compared PID controllers, gain scheduling to show its efficiency. Just to note, gain scheduling is usually being used for non-linear control system.","PeriodicalId":133597,"journal":{"name":"2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132355341","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

Matrix Formulated λ-Iteration Method for Economic Load Scheduling With B-Coefficients 具有b系数的经济负荷调度的矩阵表示λ迭代法

2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT) Pub Date : 2022-10-07 DOI: 10.1109/GCAT55367.2022.9972153

I. R. Rao, J. Gonda, Surya Teja Surampudi

引用次数: 0

Audio Synthesis Translation and Auto-Summarization (ASTA) 音频合成翻译与自动摘要(ASTA)

2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT) Pub Date : 2022-10-07 DOI: 10.1109/GCAT55367.2022.9971977

Jivin Varghese, Pakshal Ranawat, Ruvin Rodrigues, Phiroj Shaikh

{"title":"Audio Synthesis Translation and Auto-Summarization (ASTA)","authors":"Jivin Varghese, Pakshal Ranawat, Ruvin Rodrigues, Phiroj Shaikh","doi":"10.1109/GCAT55367.2022.9971977","DOIUrl":"https://doi.org/10.1109/GCAT55367.2022.9971977","url":null,"abstract":"Availability of time has been a major issue in recent years for mankind. There has always been a huge demand for automation, since it can tremendously decrease time for doing menial tasks. This proposed project focuses on automation of text translation, summarization and speech synthesis which could reduce time required for reading books. In this paper, we present multiple machine learning models that synthesize text into speech and also into summarized text of Devanagari script. The main objective of the project is to conduct proper examination of the existing architecture of the text translation and summarization methodologies and to provide a robust system which is a cumulation of converting PDF files to audio files and also summarization of the PDF and translating into Devanagari text of the summarized English narrative. The architecture is called Audio Synthesis Translation and Auto-summarization (ASTA) and uses multiple models such as RNN sequence to sequence, NMT, Tacotron 2 and Waveglow. In addition to this, we use Google Vision OCR for text extraction from PDF. This system is an integration of multiple machine learning models and works as a pipelined system.","PeriodicalId":133597,"journal":{"name":"2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134336255","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 Analysis of Brushless DC Motor 无刷直流电机的性能分析

2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT) Pub Date : 2022-10-07 DOI: 10.1109/GCAT55367.2022.9971962

Hardik A Prajapati, Grupesh Tapiawala

引用次数: 1

Development of NavIC Based Asset Tracking System 基于NavIC的资产跟踪系统的开发

2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT) Pub Date : 2022-10-07 DOI: 10.1109/GCAT55367.2022.9972052

Yuvraj Dewangan, Sateesh Kumar Awasthi

引用次数: 0

Fuzzy Controller Based Partial Charging System For Electric Vehicles 基于模糊控制器的电动汽车部分充电系统

2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT) Pub Date : 2022-10-07 DOI: 10.1109/GCAT55367.2022.9972073

P. Narayana, V. Sailaja, K. Deepa

{"title":"Fuzzy Controller Based Partial Charging System For Electric Vehicles","authors":"P. Narayana, V. Sailaja, K. Deepa","doi":"10.1109/GCAT55367.2022.9972073","DOIUrl":"https://doi.org/10.1109/GCAT55367.2022.9972073","url":null,"abstract":"In this paper, an EV charging station is implemented using partial charging system for Fast Charging which can charge the multiple electric vehicles (EV) simultaneously. A power electronic transformer is used to connect the DC source with the medium voltage grid and provides galvanic isolation between the source and the load. The partial power DC-DC converters process only a fraction of the total battery charging power. This charging technic help in reducing the power conversion by using partial charging systems which are used for charging the EV's. The EV's battery is charged by a full bridge converter. The EV's battery operation is controlled by a controller called Fuzzy controller for getting optimistic results. A battery energy storage system is connected to the grid which can reduce the voltage stress on the Main Grid and make use of non-conventional energy sources. In BESS, bidirectional converter is used for charging and discharging operation of the battery. Due to power electronic transformer, the capital cost of the proposed charging station increases but the performance of the system is improved and the system size is reduced. PCS will improve the efficiency of the charging station. The simulation work is carried out in MATLAB.","PeriodicalId":133597,"journal":{"name":"2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT)","volume":"197 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131807018","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

COVID-19 risk factors specification using Decision Tree based on the degree of redundancy between features 基于特征之间冗余度的决策树规范COVID-19风险因素

2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT) Pub Date : 2022-10-07 DOI: 10.1109/GCAT55367.2022.9971950

S. Mohammed, Mohammed Sami Mohammed

{"title":"COVID-19 risk factors specification using Decision Tree based on the degree of redundancy between features","authors":"S. Mohammed, Mohammed Sami Mohammed","doi":"10.1109/GCAT55367.2022.9971950","DOIUrl":"https://doi.org/10.1109/GCAT55367.2022.9971950","url":null,"abstract":"Based on the latest diseases which spread in the whole world and need to be predicted and classified. In addition, when testing and examining the samples will be safer with far data collecting such as COVID-19 cases. Therefore; this research provides a safe and accurate data mining prediction system to make a decision with high performance to prevent this spread. Such a study prevents or at least reduces the effect of contacting suspicious patients with others by providing a discovery system to detect this disease in these samples. Also, this study will reduce the effects of COVID-19 on marketing, teaching, and other different business, which lead to holding this disease separated at home with high knowledge of some symptoms that will be studied to specify the most affected features on this classification. However, this study could provide some information about viruses moving and keeping away at home with an early prediction. In this study, three techniques are applied for 1486 patients after data preprocessing and preparing for the performance evaluation. Risk factors are determined using a features selector and study of the effect of these features before and after minimization on the whole proposed model. Differences and reasons are shown in this paper due to different results which occurred while omitting unnecessary data. All the proposed models showed an enhancement in their performances after selecting the most affected features. But, DT showed the best prediction accuracy with about 96% compared to other models. On the other hand, other parameters are explained and showen some more advanced in the DT model than in other models.","PeriodicalId":133597,"journal":{"name":"2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131077874","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

Energy Scalable Brent Kung Adder with Non-Zeroing Bit Truncation 具有非零位截断的能量可伸缩Brent Kung加法器

2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT) Pub Date : 2022-10-07 DOI: 10.1109/GCAT55367.2022.9972236

M. Veena, N. Suhana Khanum, D. H. Soundaryya, P. Mamatha Sarathi

引用次数: 0

Performance Evaluation of Predictive Machine Learning Models for Diabetic Disease Using Python 基于Python的糖尿病疾病预测机器学习模型的性能评估

2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT) Pub Date : 2022-10-07 DOI: 10.1109/GCAT55367.2022.9972220

M. Bhattacharya, D. Datta

{"title":"Performance Evaluation of Predictive Machine Learning Models for Diabetic Disease Using Python","authors":"M. Bhattacharya, D. Datta","doi":"10.1109/GCAT55367.2022.9972220","DOIUrl":"https://doi.org/10.1109/GCAT55367.2022.9972220","url":null,"abstract":"The discovery of knowledge from medical database is always beneficial as well as challenging task for diagnosis. For example, patients having high blood glucose are required to diagnose as they fall within a group of Diabetes mellitus. Prediction of diabetes mellitus is an essential research in the domain of medical industry. With the advent of artificial intelligence and machine learning this type of prediction removes the hurdles faced in data mining used for similar task. In case of data mining, extraction of knowledge from information stored in database takes place and an understandable description of patterns is achieved. A large number of researches have been already taken place to predict diabetes using traditional machine learning algorithm such as artificial neural network, Naïve Bayes theorem, decision tree, etc. However, determination of diabetes with a certain degree of confidence is required from the accuracy or any other performance measures point of view. In this context, this research work presents machine learning models such as decision tree, support vector machine, random forest, k-nearest neighbours and Naïve-Bayes as classifier to classify whether a patient is diabetic or prone to diabetic. Performance measures of these algorithms have been carried out in terms of accuracy score. Dataset for training and testing the algorithms mentioned is retrieved from Pima Indian Database. On the basis of their comparative evaluation, most important feature with respect to identification of diabetic is extracted. A complete python code has been developed for this research work.","PeriodicalId":133597,"journal":{"name":"2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124378254","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

EV Control in G2V and V2G modes using SOGI Controller 使用SOGI控制器的G2V和V2G模式下的EV控制

2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT) Pub Date : 2022-10-07 DOI: 10.1109/GCAT55367.2022.9972182

Sudhanshu Mittal, Alka Singh, P. Chittora

{"title":"EV Control in G2V and V2G modes using SOGI Controller","authors":"Sudhanshu Mittal, Alka Singh, P. Chittora","doi":"10.1109/GCAT55367.2022.9972182","DOIUrl":"https://doi.org/10.1109/GCAT55367.2022.9972182","url":null,"abstract":"Electric vehicle (EV) technology is developing at a very fast pace. The Vehicle to grid (V2G) and Grid to vehicle (G2V) technology enables bidirectional power transfer between an electric vehicle and the grid. It is an emergent area of research. In the G2V operation mode EV, batteries are charged from the grid. The energy stored in the batteries may also be supplied back to the power grid during the V2G operation mode, which helps in maximum demand saving, load balancing voltage management and improved system reliability. An onboard bilateral battery charger for EV is proposed in this research paper, with G2V and V2G applications. Bi-directional power electronics-based converter is interfaced between EV and the grid to provide G2V and V2G modes. A Second Order Generalized Integrator (SOGI) control technique is used to control the H-bridge inverter which shows stable steady state and good dynamic performance. The battery charging/discharging current and voltage are controlled using a PWM controller further effect of nonlinear load dynamics on the system performance is also studied. Exhaustive simulation study is performed in MATLAB/Simulink environment which is also reflected in this paper.","PeriodicalId":133597,"journal":{"name":"2022 IEEE 3rd Global Conference for Advancement in Technology (GCAT)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114479877","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