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Techno-Economic Performance Analysis of GridInterfaced Microgrid for Different Facilities 不同设施并网微电网的技术经济性能分析
2021 International Conference on Intelligent Technologies (CONIT) Pub Date : 2021-06-25 DOI: 10.1109/CONIT51480.2021.9498432
S. Bohra, H. Desai
{"title":"Techno-Economic Performance Analysis of GridInterfaced Microgrid for Different Facilities","authors":"S. Bohra, H. Desai","doi":"10.1109/CONIT51480.2021.9498432","DOIUrl":"https://doi.org/10.1109/CONIT51480.2021.9498432","url":null,"abstract":"This paper presents technical and economic analysis of hybrid ac microgrid (MG). The MG comprises conventional source like diesel generator (DiGen), renewable energy source such as roof-top solar photo-voltaic (PV) installation and battery energy storage system (BESS). The primary objective of this analysis is to study and compare levelised cost-of-energy (LCoE) and net-present value (NPV) for blend of energy sources catering electrical energy to various set-ups along with other vital economic instruments like internal rate of return(IRR), return on investment(ROI) and simple payback period(SPP). The analysis has been performed with existing utility-grid in operation. In order to compare the combination of micro-sources, same average annual electricity consumption has been considered as reference for comparison for various load profiles, viz. academic institutional, residential pocket, commercial, community and small/medium industrial loads. Moreover, the two tariff structures, with grid selling and non-grid selling are considered. The model has been developed in HOMER application software. The reference location for academic institution selected for study is situated in southern part of Gujarat, India and has longitude and $21.17^{circ}mathrm{N}$ latitude of $72.83^{circ}mathrm{E}$.","PeriodicalId":426131,"journal":{"name":"2021 International Conference on Intelligent Technologies (CONIT)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115409936","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 Efficiency Analysis in Spectrum Sensing Cognitive Radio Network 频谱感知认知无线电网络的能量效率分析
2021 International Conference on Intelligent Technologies (CONIT) Pub Date : 2021-06-25 DOI: 10.1109/CONIT51480.2021.9498405
R. Chougule, H. P. Rajani
{"title":"Energy Efficiency Analysis in Spectrum Sensing Cognitive Radio Network","authors":"R. Chougule, H. P. Rajani","doi":"10.1109/CONIT51480.2021.9498405","DOIUrl":"https://doi.org/10.1109/CONIT51480.2021.9498405","url":null,"abstract":"The spectrum scarcity problem is addressed by number solutions by various researchers in cognitive network field. The dynamic spectrum allocation using cooperative spectrum sensing is required to analyze with respect to errors present in detection due to fixed threshold. The spectrum allocation on the basis of demand may involve the priority based requests for spectrum allocation. This paper contributes in terms of efficient energy sensing using dynamic threshold strategy. The principle of sensing is optimized using energy sensing using effects of Marcum q function for the PU presence sensing. The effective detection analysis is performed along with energy consumption which shows effective efficiency during sensing work.","PeriodicalId":426131,"journal":{"name":"2021 International Conference on Intelligent Technologies (CONIT)","volume":"93 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124435571","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
Analysis of Dimensionality Reduction Techniques for Effective Text Classification 有效文本分类的降维技术分析
2021 International Conference on Intelligent Technologies (CONIT) Pub Date : 2021-06-25 DOI: 10.1109/CONIT51480.2021.9498287
K. Swarnalatha, N. V. Kumar, D. S. Guru, B. S. Anami
{"title":"Analysis of Dimensionality Reduction Techniques for Effective Text Classification","authors":"K. Swarnalatha, N. V. Kumar, D. S. Guru, B. S. Anami","doi":"10.1109/CONIT51480.2021.9498287","DOIUrl":"https://doi.org/10.1109/CONIT51480.2021.9498287","url":null,"abstract":"In this paper, the different dimensionality reduction techniques are presented for effective text classification. The feature selection technique and feature transformation fallowed by feature selection techniques are recommended to reduce the dimension of the features. For more compactness of data, the symbolic interval data type is recommended. The techniques are evaluated using SVM classifier and Symbolic classifier on standard benchmark datasets viz., Reuters-21578 and TDT2. The effectiveness of the techniques is verified with the performance F-1 score measure. The dimensionality reduction techniques which perform better are recommended when compared to the others.","PeriodicalId":426131,"journal":{"name":"2021 International Conference on Intelligent Technologies (CONIT)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114904106","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
Free Space Optical Wireless Communication using Lasers Array for Data Transmission 利用激光阵列进行数据传输的自由空间光无线通信
2021 International Conference on Intelligent Technologies (CONIT) Pub Date : 2021-06-25 DOI: 10.1109/CONIT51480.2021.9498473
Durgesh, Deepak Ghanshala, N. Panwar, P. Tewari
{"title":"Free Space Optical Wireless Communication using Lasers Array for Data Transmission","authors":"Durgesh, Deepak Ghanshala, N. Panwar, P. Tewari","doi":"10.1109/CONIT51480.2021.9498473","DOIUrl":"https://doi.org/10.1109/CONIT51480.2021.9498473","url":null,"abstract":"Free-space optical (FSO) communication using Light Fidelity (Li-Fi) is a booming field with several advantages over optical fiber communication such as low cost, lower losses, lower complexity, and higher data rate. The Data transmission with the help of LASERs through a transmitter suffers with various interruptions along the channel such as obstacles, rain, wind, and fog. In this work, we have proposed a Li-Fi technology-based reliable FSO wireless communication system model using LASERs. The suggested system is implemented using an array of LASERs for uninterrupted high-speed communication. Converging lens is used just before the receiver to converge the multiple LASER beams transmitted by the array of LASERs to the receiver. The converging lens also increases the intensity of the LASERs beams at the receiver side. In this work, first we investigate the performance of the proposed system in the OptiSystem tool in terms of quality factor (Q-factor), bit error rate (BER), received power, Eye diagram with respect to the link distance. We also present a hardware prototype for the proposed communication system and analyze its performance.","PeriodicalId":426131,"journal":{"name":"2021 International Conference on Intelligent Technologies (CONIT)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122060260","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
Batteries For Active Implantable Medical Devices 有源植入式医疗设备用电池
2021 International Conference on Intelligent Technologies (CONIT) Pub Date : 2021-06-25 DOI: 10.1109/CONIT51480.2021.9498319
Deepali Newaskar, B. Patil
{"title":"Batteries For Active Implantable Medical Devices","authors":"Deepali Newaskar, B. Patil","doi":"10.1109/CONIT51480.2021.9498319","DOIUrl":"https://doi.org/10.1109/CONIT51480.2021.9498319","url":null,"abstract":"Millions of active implanted devices like pacemakers are implanted every year. Life of those devices depends on the life of battery used for powering. If the battery is drained out then the patient needs to undergo surgery for the second time to replace the device, which potentially increases the risk for other complications and infections. With increase in the demand for implantable devices, researchers are expected to look for extending the life of the device by recharging them wirelessly or by making them self-powered device. This paper gives overall idea about evolution of battery, its specifications to be used in medical device or categorization of batteries, charge pump technology to boost the available charge and factors need to be considered while selecting the battery for any application. With the proper selection of rechargeable battery, if the implanted device is recharged successfully without causing any harm to human body, then the life of the device can be increased as well as its size can be reduced as much of the device space is consumed by the battery.","PeriodicalId":426131,"journal":{"name":"2021 International Conference on Intelligent Technologies (CONIT)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122144963","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
Deep Diabetic Retinopathy Detection System (DDRDS) using Convolutional Neural Network: A Comparative Study 卷积神经网络深度糖尿病视网膜病变检测系统(DDRDS)的比较研究
2021 International Conference on Intelligent Technologies (CONIT) Pub Date : 2021-06-25 DOI: 10.1109/CONIT51480.2021.9498420
Subhadip Das, Dolly Das, S. K. Biswas, B. Purkayastha
{"title":"Deep Diabetic Retinopathy Detection System (DDRDS) using Convolutional Neural Network: A Comparative Study","authors":"Subhadip Das, Dolly Das, S. K. Biswas, B. Purkayastha","doi":"10.1109/CONIT51480.2021.9498420","DOIUrl":"https://doi.org/10.1109/CONIT51480.2021.9498420","url":null,"abstract":"Diabetic Retinopathy (DR) is a medical condition in the retina of human eye, triggered due to diabetes mellitus which causes formation of lesions in the retina and leads to blurred vision and even blindness. The statistical data estimations show 80% of diabetic patients, suffering from protracted diabetes, also suffers from DR. Hence, early DR evaluation and assessment can reduce susceptibility to severe blindness, especially amongst the working generation. The process of physical diagnosis is laborious, inefficient and liable to cause error, and the lack of resources and expert opinions, makes early detection and treatment infeasible. Thus, advanced intelligent systems using innovative Machine Learning (ML) techniques such as Deep Learning (DL) are proposed by researchers. This paper proposes an intelligent system named Deep Diabetic Retinopathy Detection System (DDRDS) which employs four Deep Convolutional Neural Networks (DCNNs), for fundus image classification, for early detection of DR.","PeriodicalId":426131,"journal":{"name":"2021 International Conference on Intelligent Technologies (CONIT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129838954","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
Improving Health Risks Prediction Mechanism in Cloud Using RT-TKRIBC Technique 利用RT-TKRIBC技术改进云健康风险预测机制
2021 International Conference on Intelligent Technologies (CONIT) Pub Date : 2021-06-25 DOI: 10.1109/CONIT51480.2021.9498324
Venkateswara Raju Konduru, Manjula R. Bharamagoudra
{"title":"Improving Health Risks Prediction Mechanism in Cloud Using RT-TKRIBC Technique","authors":"Venkateswara Raju Konduru, Manjula R. Bharamagoudra","doi":"10.1109/CONIT51480.2021.9498324","DOIUrl":"https://doi.org/10.1109/CONIT51480.2021.9498324","url":null,"abstract":"Numerous gadgets are utilized for recording and creating large health data sets. With the increasing volume of information in the medical services industry, individuals need more health supervising. A cloud-empowered investigation of medical care information is used to anticipate the risk variables of the patients at anyplace. An AI strategy has been created to address these clinical consideration issues. An innovative procedure called Radix Trie based Tanimoto Kernel Regressive Infomax Boost Classification (RT-TKRIBC) method is presented for examining the heterogeneous cloud information to forecast the problems of patient security and sent warnings. From the start, the radix trie is applied for putting away the patient wellbeing data into a cloud server farm. From that point onward, the Tanimoto Kernel Regressive Infomax Boost strategy is utilized for examining the patient’s wellbeing information to distinguish the patient’s dangers. Infomax Boost Classification utilizes the Tanimoto Kernel relapse work as a delicate student for investigating the preparation of welfare information with the testing information utilizing comparability work.The Infomax Boost group strategy improves forecast exactness by finding the greatest common data bringing about it limits the mean square mistake. At last, the RT-TKRIBC procedure acquires solid expectation results with higher precision. Exploratory appraisal is completed with the clinical datasets and various measurements to assess the viability of the RT-TKRIBC method. The acquired outcomes show that the proposed work performs well than the current frameworks","PeriodicalId":426131,"journal":{"name":"2021 International Conference on Intelligent Technologies (CONIT)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128733379","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
Implementation of High Performance 4-Bit ALU using Dual Mode Pass Transistor Logic 用双模通型晶体管逻辑实现高性能4位ALU
2021 International Conference on Intelligent Technologies (CONIT) Pub Date : 2021-06-25 DOI: 10.1109/CONIT51480.2021.9498553
Anurag Chauhan, K. K. Saini, Nitin Rajput, Rushil Domah
{"title":"Implementation of High Performance 4-Bit ALU using Dual Mode Pass Transistor Logic","authors":"Anurag Chauhan, K. K. Saini, Nitin Rajput, Rushil Domah","doi":"10.1109/CONIT51480.2021.9498553","DOIUrl":"https://doi.org/10.1109/CONIT51480.2021.9498553","url":null,"abstract":"In this paper, we present a four bit arithmetic logic unit which is energy efficient and temperature invariant implemented using the dual mode pass transistor logic. The basic logic gates such as NOR and NAND are designed using both CMOS logic and dual mode pass transistor logic and are used in the proposed design. Simulations performed demonstrated that DMPL can reduce the computed worst case delay by 42.39%and 39.13%for NOR and NAND gates respectively in dynamic mode and average power dissipation by 67.96%and 24.09%for NOR and NAND gates respectively in static mode. In the implemented Arithmetic and Logic Unit, we observe a reduction in worst case delay and average power dissipation by 62.67%and 28.28%. The proposed logic was implemented in 90nm bulk technology using Cadence® Virtuoso® Schematic Editor.","PeriodicalId":426131,"journal":{"name":"2021 International Conference on Intelligent Technologies (CONIT)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128950601","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
Modeling of 3-φ Induction Motor and Analysis using Numerical Methods 3-φ感应电机的建模与数值分析
2021 International Conference on Intelligent Technologies (CONIT) Pub Date : 2021-06-25 DOI: 10.1109/CONIT51480.2021.9498512
Manjunath B. Ranadev, V. Sheelavant, R. L. Chakrasali
{"title":"Modeling of 3-φ Induction Motor and Analysis using Numerical Methods","authors":"Manjunath B. Ranadev, V. Sheelavant, R. L. Chakrasali","doi":"10.1109/CONIT51480.2021.9498512","DOIUrl":"https://doi.org/10.1109/CONIT51480.2021.9498512","url":null,"abstract":"Electrical Drives are used in broad power range in various applications. Induction motors particularly squirrel cage motor operates under all operating condition and widely used. Further, for variable speed applications squirrel cage motors have been the workhouses in the industry. The performance of the motors needs to be studied before using for a given application. Theoretical and numerical analysis can be carried out from mathematical modeling of 3$-varphi$ induction motor. This paper presents a technique for the analysis of a 3$-varphi$ induction motor using d-q model approach. The numerical analysis method is used to determine the performance of the motor under steady state condition. Determination of behavior of induction motor through numerical methods meant to compare the results obtained by Gauss-Seidel and Successive Over-Relaxation methods. The comparison confirms the validity and accuracy of the proposed methods.","PeriodicalId":426131,"journal":{"name":"2021 International Conference on Intelligent Technologies (CONIT)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132460968","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
Electrical Load Forecasting 电力负荷预测
2021 International Conference on Intelligent Technologies (CONIT) Pub Date : 2021-06-25 DOI: 10.1109/CONIT51480.2021.9498349
Ujjwal Singh, Aditya Negi, Vaibhav Garg, Rohan Pillai
{"title":"Electrical Load Forecasting","authors":"Ujjwal Singh, Aditya Negi, Vaibhav Garg, Rohan Pillai","doi":"10.1109/CONIT51480.2021.9498349","DOIUrl":"https://doi.org/10.1109/CONIT51480.2021.9498349","url":null,"abstract":"Since the electricity demand is increasing globally, load forecasting techniques have become immensely important in forecasting the electricity demands and it also helps the policy makers. The aim of our project is to perform short-term load forecasting, i.e. up to a week ahead. Household owners can estimate the upcoming load and power distribution organization would know the demand and could be prepared henceforth. Our attempt is to generate useful insights and forecast as accurately as possible. We are using different techniques starting from Naive Bayes, Classical Linear Methods (like ARIMA), and some Machine Learning Algorithms (like LinearRegression, Ridge, Lasso, HuberRegressor, ElasticNet, Lars, LassoLars, PassiveAggressiveRegressor, RANSAC Regressor, SGD Regressor) to make predictions. And we are also using Deep Learning algorithms like CNN, LSTM and combining CNN-LSTM to get more accurate predictions. In the end we will compare all the predictions from all the models that we have used and determine which model makes the best prediction.","PeriodicalId":426131,"journal":{"name":"2021 International Conference on Intelligent Technologies (CONIT)","volume":"145 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132492247","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
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