Pub Date : 2021-12-16DOI: 10.1109/ICSTCEE54422.2021.9708549
K. Sumalatha, E. Muneender
In order to overcome these disadvantages, hybrid interconnection of Solar and Wind systems is proposed for a three phase grid connections. To improve the system’s functionality, this proposed combination circulation device contains sunlight as well as wind energy systems that need to be combined to the grid at an Aspect of Popular Coupling (PCC). If you want to obtain the greatest electrical power under all weather conditions, an easy Maximum Power Point Monitoring (MPPT) protocol is worked with each photovoltaic and also wind system. The 3 phase diode clamped multilevel inverter, which is handled due to the unclear logic controller (FLC) based upon angle control procedures, is carried out to manage the DC-link at the intended current. The experimentations on accomplished on software application platforms to assess the efficacy of the proposed method. The outcomes display a superior performance of FLC compared with conventional PI controller in improving the step response of dc link voltage. Additionally, this control technique effectively sustains the constant grid voltage and ensures unity power factor regardless to the weather conditions even when combined with the solar-wind hybrid power system’s injected active electricity.
{"title":"Fuzzy Logic Controller Strategy for Ameliorating DC Link Voltage for Grid Connected Hybrid PV-Wind Generation Systems","authors":"K. Sumalatha, E. Muneender","doi":"10.1109/ICSTCEE54422.2021.9708549","DOIUrl":"https://doi.org/10.1109/ICSTCEE54422.2021.9708549","url":null,"abstract":"In order to overcome these disadvantages, hybrid interconnection of Solar and Wind systems is proposed for a three phase grid connections. To improve the system’s functionality, this proposed combination circulation device contains sunlight as well as wind energy systems that need to be combined to the grid at an Aspect of Popular Coupling (PCC). If you want to obtain the greatest electrical power under all weather conditions, an easy Maximum Power Point Monitoring (MPPT) protocol is worked with each photovoltaic and also wind system. The 3 phase diode clamped multilevel inverter, which is handled due to the unclear logic controller (FLC) based upon angle control procedures, is carried out to manage the DC-link at the intended current. The experimentations on accomplished on software application platforms to assess the efficacy of the proposed method. The outcomes display a superior performance of FLC compared with conventional PI controller in improving the step response of dc link voltage. Additionally, this control technique effectively sustains the constant grid voltage and ensures unity power factor regardless to the weather conditions even when combined with the solar-wind hybrid power system’s injected active electricity.","PeriodicalId":146490,"journal":{"name":"2021 Second International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128343056","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}
Pub Date : 2021-12-16DOI: 10.1109/ICSTCEE54422.2021.9708560
B. Bairwa, Mrinal Sarvagya, Sanjeev Kumar, Arpita Banik
This paper provides a novel approach for providing battery swapping services to electric vehicle users, centered around a Battery swapping mobile station. Firstly, this paper establishes the structural architecture for the smooth and efficient to provide swapping services to users. Also establishes the functions and roles of the various entities present in the organization and defines the difference between charging stations and swapping stations. Secondly, gives a brief description of the working of the mechanism involved in the mobile swapping unit. Also, the mobile application and the communication between the user and the service management system and establishes how the user can send requests, raise complaints through the application. Thirdly, the power consumed by the battery swapping unit, its run time, and how the solar-assisted charging is done. The above is backed by mathematical analysis.
{"title":"Battery Swapping Mobile Service Station for Electric Vehicles Application","authors":"B. Bairwa, Mrinal Sarvagya, Sanjeev Kumar, Arpita Banik","doi":"10.1109/ICSTCEE54422.2021.9708560","DOIUrl":"https://doi.org/10.1109/ICSTCEE54422.2021.9708560","url":null,"abstract":"This paper provides a novel approach for providing battery swapping services to electric vehicle users, centered around a Battery swapping mobile station. Firstly, this paper establishes the structural architecture for the smooth and efficient to provide swapping services to users. Also establishes the functions and roles of the various entities present in the organization and defines the difference between charging stations and swapping stations. Secondly, gives a brief description of the working of the mechanism involved in the mobile swapping unit. Also, the mobile application and the communication between the user and the service management system and establishes how the user can send requests, raise complaints through the application. Thirdly, the power consumed by the battery swapping unit, its run time, and how the solar-assisted charging is done. The above is backed by mathematical analysis.","PeriodicalId":146490,"journal":{"name":"2021 Second International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124606009","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}
Pub Date : 2021-12-16DOI: 10.1109/ICSTCEE54422.2021.9708593
G. Usha, L. Dharmanna
Sentiment Analysis, also known as Opinion Mining, is the systematic identification, extraction, quantification, and study of affective states and subjective information using natural language processing and text analysis. For applications ranging from marketing to customer service, sentiment analysis is commonly used on reviews and survey answers, online and social media, and healthcare materials.The aim of this study is to determine the accuracy of the various algorithms for sentiment analysis of product reviews. For this study, 4,444 online product reviews were received from an e-commerce site.
{"title":"Sentiment Analysis on Business Data using Machine Learning","authors":"G. Usha, L. Dharmanna","doi":"10.1109/ICSTCEE54422.2021.9708593","DOIUrl":"https://doi.org/10.1109/ICSTCEE54422.2021.9708593","url":null,"abstract":"Sentiment Analysis, also known as Opinion Mining, is the systematic identification, extraction, quantification, and study of affective states and subjective information using natural language processing and text analysis. For applications ranging from marketing to customer service, sentiment analysis is commonly used on reviews and survey answers, online and social media, and healthcare materials.The aim of this study is to determine the accuracy of the various algorithms for sentiment analysis of product reviews. For this study, 4,444 online product reviews were received from an e-commerce site.","PeriodicalId":146490,"journal":{"name":"2021 Second International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116308018","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}
Pub Date : 2021-12-16DOI: 10.1109/ICSTCEE54422.2021.9708564
S. Kadge, S. Nalbalwar, A. Nandgaonkar, Digvijay Singh
In this paper we propose feature extraction and classification of Retinopathy of prematurity (ROP) images with semi-automated approach. Retinopathy of prematurity is a condition present in premature neonates affecting the vision which can lead to blindness. The early detection can help to prevent loss of vision in new born. Diagnosis of ROP requires continuous monitoring of fundus images in the first four weeks. Because of advanced science the survival of premature neonates is on rise which leads to more number of high risk neonates for ROP. The fundus image analysis by human readers may lack accuracy because of excessive workload as the number of qualified doctors is less compared to the number of patients. The proposed semi-automation method is based on thresholding technique. As the images vary in size & illumination preprocessing of data is done. Based on thresholding technique, we can find the different stages of ROP. High accuracy is achieved to find the different stages.
{"title":"Semi-automated Clinical Staging of Retinopathy of Prematurity Images","authors":"S. Kadge, S. Nalbalwar, A. Nandgaonkar, Digvijay Singh","doi":"10.1109/ICSTCEE54422.2021.9708564","DOIUrl":"https://doi.org/10.1109/ICSTCEE54422.2021.9708564","url":null,"abstract":"In this paper we propose feature extraction and classification of Retinopathy of prematurity (ROP) images with semi-automated approach. Retinopathy of prematurity is a condition present in premature neonates affecting the vision which can lead to blindness. The early detection can help to prevent loss of vision in new born. Diagnosis of ROP requires continuous monitoring of fundus images in the first four weeks. Because of advanced science the survival of premature neonates is on rise which leads to more number of high risk neonates for ROP. The fundus image analysis by human readers may lack accuracy because of excessive workload as the number of qualified doctors is less compared to the number of patients. The proposed semi-automation method is based on thresholding technique. As the images vary in size & illumination preprocessing of data is done. Based on thresholding technique, we can find the different stages of ROP. High accuracy is achieved to find the different stages.","PeriodicalId":146490,"journal":{"name":"2021 Second International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115804304","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}
Pub Date : 2021-12-16DOI: 10.1109/ICSTCEE54422.2021.9708591
P. Patro, R. Azhagumurugan, R. Sathya, K.Vinoth kumar, T. R. Kumar, M. V. S. Babu
For Remaining useful life (RUL) prediction, this article presents a paradigm that separates the whole bearing life into many health states and then builds unique local regression models for each of those states, rather than searching for an overall regression model with multiple health state assessments. A method that utilised both unsupervised learnings and supervised learning to estimate a bearing’s real-time health status is presented without previous information. The primary technology used to perform health status assessment and RUL prediction is the support vector machine. The efficacy of the suggested framework has been shown via experiments, including accelerated deterioration testing on rolling element bearings.
{"title":"A hybrid approach estimates the real-time health state of a bearing by accelerated degradation tests, Machine learning","authors":"P. Patro, R. Azhagumurugan, R. Sathya, K.Vinoth kumar, T. R. Kumar, M. V. S. Babu","doi":"10.1109/ICSTCEE54422.2021.9708591","DOIUrl":"https://doi.org/10.1109/ICSTCEE54422.2021.9708591","url":null,"abstract":"For Remaining useful life (RUL) prediction, this article presents a paradigm that separates the whole bearing life into many health states and then builds unique local regression models for each of those states, rather than searching for an overall regression model with multiple health state assessments. A method that utilised both unsupervised learnings and supervised learning to estimate a bearing’s real-time health status is presented without previous information. The primary technology used to perform health status assessment and RUL prediction is the support vector machine. The efficacy of the suggested framework has been shown via experiments, including accelerated deterioration testing on rolling element bearings.","PeriodicalId":146490,"journal":{"name":"2021 Second International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132219245","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}
Pub Date : 2021-12-16DOI: 10.1109/ICSTCEE54422.2021.9708583
Y. Sri, Y. Sravani, Y. B. S. Surendra, S. Rishitha, M. Sobhana
Expenditure analysis should be done by every household to manage all the expenses of the family. Income prediction gives an overview of the income earned by the household to manage all the family’s financial needs. Based on the expenses and other required data from the user, the system will predict the user’s annual income to meet the expenses. The predicted annual income can be used by the government for initiating policies for the poor people. This prediction task is performed using Decision Tree and Random Forest Regression algorithms, as the data used for this model is continuous. Our proposed Random Forest model predicts with an accuracy of 74.35%. Based on accuracy metrics, our model is compared with Decision Tree, accuracy of 48%. Clearly, the our proposed model is more suitable for classifying than the Decision Tree model. As decision trees are best suitable for predictions based on non-linear data, we cannot depend on a single decision tree for the prediction of income. Bagging technique-based Random forest Regression is made use for the prediction of the income.
{"title":"Family Expenditure and Income Analysis using Machine Learning algorithms","authors":"Y. Sri, Y. Sravani, Y. B. S. Surendra, S. Rishitha, M. Sobhana","doi":"10.1109/ICSTCEE54422.2021.9708583","DOIUrl":"https://doi.org/10.1109/ICSTCEE54422.2021.9708583","url":null,"abstract":"Expenditure analysis should be done by every household to manage all the expenses of the family. Income prediction gives an overview of the income earned by the household to manage all the family’s financial needs. Based on the expenses and other required data from the user, the system will predict the user’s annual income to meet the expenses. The predicted annual income can be used by the government for initiating policies for the poor people. This prediction task is performed using Decision Tree and Random Forest Regression algorithms, as the data used for this model is continuous. Our proposed Random Forest model predicts with an accuracy of 74.35%. Based on accuracy metrics, our model is compared with Decision Tree, accuracy of 48%. Clearly, the our proposed model is more suitable for classifying than the Decision Tree model. As decision trees are best suitable for predictions based on non-linear data, we cannot depend on a single decision tree for the prediction of income. Bagging technique-based Random forest Regression is made use for the prediction of the income.","PeriodicalId":146490,"journal":{"name":"2021 Second International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131008988","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}
Pub Date : 2021-12-16DOI: 10.1109/ICSTCEE54422.2021.9708572
Deekshith Krishnegowda
Semiconductor chips are manufactured for different end applications. Memory controller chips are used in SSDs, while high-speed ethernet transceivers are used in datacenters. Be it for any end applications, all semiconductor chips consist of internal and external bus protocols. Internal bus protocols such as AMBA AHB, APB, and AXI are used to communicate data within the chip. External bus protocols such as SPI, I2C, and MDIO are used to transfer data in and out of chips using chip input-output ports. Verification of these bus protocols is crucial before taping out the chip else the chip might come out faulty and render useless. Verification of bus protocols can be done using less efficient traditional verification methods or by building a flexible verification environment using Universal Verification Methodology. In addition to that, Bus Functional Model can be developed to make the testbench more reusable. In this paper, the development of APB Bus Functional Model is discussed. The model is later used to do a functional verification of a simple Analog to Digital and Digital to Analog converter interfaced through APB protocol. Simulations are done using Synopsys VCS tool and GTK waveform viewer is used to analyze waveforms.
{"title":"Developing a Bus Functional Model for APB slave using Universal Verification Methodology","authors":"Deekshith Krishnegowda","doi":"10.1109/ICSTCEE54422.2021.9708572","DOIUrl":"https://doi.org/10.1109/ICSTCEE54422.2021.9708572","url":null,"abstract":"Semiconductor chips are manufactured for different end applications. Memory controller chips are used in SSDs, while high-speed ethernet transceivers are used in datacenters. Be it for any end applications, all semiconductor chips consist of internal and external bus protocols. Internal bus protocols such as AMBA AHB, APB, and AXI are used to communicate data within the chip. External bus protocols such as SPI, I2C, and MDIO are used to transfer data in and out of chips using chip input-output ports. Verification of these bus protocols is crucial before taping out the chip else the chip might come out faulty and render useless. Verification of bus protocols can be done using less efficient traditional verification methods or by building a flexible verification environment using Universal Verification Methodology. In addition to that, Bus Functional Model can be developed to make the testbench more reusable. In this paper, the development of APB Bus Functional Model is discussed. The model is later used to do a functional verification of a simple Analog to Digital and Digital to Analog converter interfaced through APB protocol. Simulations are done using Synopsys VCS tool and GTK waveform viewer is used to analyze waveforms.","PeriodicalId":146490,"journal":{"name":"2021 Second International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125148266","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}
Pub Date : 2021-12-16DOI: 10.1109/ICSTCEE54422.2021.9708557
Ayaskanta Mishra, A. K. Ray
The recent developments in the field of Internet of Things (IoT) has opened up vast prospects for design, development and deployment of Next-generation Cyber Physical System (NG-CPS). The proposed NG-CPS would have advanced features and functionalities to be future ready for inter-connecting physical-realm with cyber-realm. The vision is to achieve intelligent next-gen IoT-based system by harnessing all key technology enablers like modern low-power and smarter embedded system with support for 5G/6G and beyond wireless network integration to conventional CPS with better and smarter algorithms. In this paper, we have proposed an Energy-efficient self-sustainable wireless sensor mote design for such envisioned NG-CPS. The idea is to split the computational framework of NG-CPS using a Mobile Edge Computing (MEC). Instead of sending real-time raw sensor data to cloud, a Store-Process-Then-Forward (SPTF) mechanism is implemented on Edge device to reduce the wireless trans-receiver duty-cycle hence reducing the energy requirement of sensor mote. Additionally, integrating a solar powered energy harvester to make the wireless sensor mote completely self-reliance in energy requirement. The proposed novel algorithm is validated with help of hardware prototyping and the results shows 720 Joules of energy saving with a consumption of only 700 mW considering 80% power efficiency.
{"title":"Energy-efficient Design of Wireless Sensor Mote using Mobile-Edge Computing and Novel scheduling mechanism for self-sustainable Next-gen Cyber Physical System","authors":"Ayaskanta Mishra, A. K. Ray","doi":"10.1109/ICSTCEE54422.2021.9708557","DOIUrl":"https://doi.org/10.1109/ICSTCEE54422.2021.9708557","url":null,"abstract":"The recent developments in the field of Internet of Things (IoT) has opened up vast prospects for design, development and deployment of Next-generation Cyber Physical System (NG-CPS). The proposed NG-CPS would have advanced features and functionalities to be future ready for inter-connecting physical-realm with cyber-realm. The vision is to achieve intelligent next-gen IoT-based system by harnessing all key technology enablers like modern low-power and smarter embedded system with support for 5G/6G and beyond wireless network integration to conventional CPS with better and smarter algorithms. In this paper, we have proposed an Energy-efficient self-sustainable wireless sensor mote design for such envisioned NG-CPS. The idea is to split the computational framework of NG-CPS using a Mobile Edge Computing (MEC). Instead of sending real-time raw sensor data to cloud, a Store-Process-Then-Forward (SPTF) mechanism is implemented on Edge device to reduce the wireless trans-receiver duty-cycle hence reducing the energy requirement of sensor mote. Additionally, integrating a solar powered energy harvester to make the wireless sensor mote completely self-reliance in energy requirement. The proposed novel algorithm is validated with help of hardware prototyping and the results shows 720 Joules of energy saving with a consumption of only 700 mW considering 80% power efficiency.","PeriodicalId":146490,"journal":{"name":"2021 Second International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129287748","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}
Pub Date : 2021-12-16DOI: 10.1109/ICSTCEE54422.2021.9708582
Girish Hegde, Vishwanath R. Hulipalled, J. B. Simha
The advancement in communication technology helped a lot for people in rural India. People can access the information over internet and use the smart phone. Majority of the people in India employed with agriculture. But still the farmers are not aware or the technology development in agriculture domain. The major gap is farmers not able to get the details in their local language or the language they are able to understand. Another major issue is farmers are not getting the enough return or good price for the commodities what they produced. They are not having information about the market trend and inter market information. Due to lack of unknown future price, they are not able to take informed decision about when and here to sell their produce. In this paper we proposed a model for forecasting the commodities price using machine learning techniques such as ARIMA, SARIMA, RNN. Also, we proposed a model to build the conversation system, voice bot for Kannada a regional language of Karnataka. With this model farmers in Karnataka will get benefitted with forecasted commodity price and get the information in Kannada. To build the voice bot the Natural Language Processing techniques can be used.
{"title":"Price Prediction of Agriculture Commodities Using Machine Learning and NLP","authors":"Girish Hegde, Vishwanath R. Hulipalled, J. B. Simha","doi":"10.1109/ICSTCEE54422.2021.9708582","DOIUrl":"https://doi.org/10.1109/ICSTCEE54422.2021.9708582","url":null,"abstract":"The advancement in communication technology helped a lot for people in rural India. People can access the information over internet and use the smart phone. Majority of the people in India employed with agriculture. But still the farmers are not aware or the technology development in agriculture domain. The major gap is farmers not able to get the details in their local language or the language they are able to understand. Another major issue is farmers are not getting the enough return or good price for the commodities what they produced. They are not having information about the market trend and inter market information. Due to lack of unknown future price, they are not able to take informed decision about when and here to sell their produce. In this paper we proposed a model for forecasting the commodities price using machine learning techniques such as ARIMA, SARIMA, RNN. Also, we proposed a model to build the conversation system, voice bot for Kannada a regional language of Karnataka. With this model farmers in Karnataka will get benefitted with forecasted commodity price and get the information in Kannada. To build the voice bot the Natural Language Processing techniques can be used.","PeriodicalId":146490,"journal":{"name":"2021 Second International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126967102","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}
Pub Date : 2021-12-16DOI: 10.1109/icstcee54422.2021.9708565
{"title":"ICSTCEE 2021 Cover Page","authors":"","doi":"10.1109/icstcee54422.2021.9708565","DOIUrl":"https://doi.org/10.1109/icstcee54422.2021.9708565","url":null,"abstract":"","PeriodicalId":146490,"journal":{"name":"2021 Second International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124890249","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}
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