Pub Date : 2022-03-16DOI: 10.1109/ICEARS53579.2022.9752328
Guanqi Tao
In order to better understand the research hotspots and status quo of my country’s education big data, the article uses bibliometrics and scientific knowledge mapping methods, taking the domestic education big data papers from 2013 to 2017 included in the CNKI (China Knowledge Network) journal database. Object, through the visualization software CiteSpace to analyze the journal distribution, time distribution and keywords of the paper, and explore the development status of domestic education big data. This article is based on CiteSpace’s educational big data mining algorithm, which increases the discovery rate of research hotspots by 10.2%; CiteSpace-based heat map modeling method increases the hotspot research to 98.2%.
{"title":"Research on Heat Map Modeling of Guiding Big Data Research Hotspots Based on CiteSpace","authors":"Guanqi Tao","doi":"10.1109/ICEARS53579.2022.9752328","DOIUrl":"https://doi.org/10.1109/ICEARS53579.2022.9752328","url":null,"abstract":"In order to better understand the research hotspots and status quo of my country’s education big data, the article uses bibliometrics and scientific knowledge mapping methods, taking the domestic education big data papers from 2013 to 2017 included in the CNKI (China Knowledge Network) journal database. Object, through the visualization software CiteSpace to analyze the journal distribution, time distribution and keywords of the paper, and explore the development status of domestic education big data. This article is based on CiteSpace’s educational big data mining algorithm, which increases the discovery rate of research hotspots by 10.2%; CiteSpace-based heat map modeling method increases the hotspot research to 98.2%.","PeriodicalId":252961,"journal":{"name":"2022 International Conference on Electronics and Renewable Systems (ICEARS)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125236902","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 : 2022-03-16DOI: 10.1109/ICEARS53579.2022.9751796
Mehrunnisa, J. Priyanka, B. S. Chandra
During the next half-century, generating energy for reduction of petroleum products is an endless task. When compared to other sustainable resources, Idea of converting sun-light oriented energy into energy using solar boards is on the leading edge. Regardless, the regular substitution in the related mentality of the sunlight based toward the earth reduces the watts delivered through the sun powered charger. As per the present circumstance the sunlight based following device is the top -notch way to build the effectiveness of a solar board. The sun board which screens the sun incorporates two LDRs, a sun-light based charger and a servo engine and an ATmega328 Micro regulator. Gentle principally put together resistors are mounted with respect to the edges of the sun powered charger. While delicate falls on them, light-based wounds cause no obstacle. A servo engine connected to the board rotates the board in the direction of the light. Boards are coordinated at the sorted way so delicate within the LDRs interestingly, with boards are pivoted near the LDR which has a prevalent limit with regards to bring down check conversely, with the backwards. The Servo engine turns the board at an uplifting perspective. At the point when slight pressure drops to the right side of the higher LDR, the board focuses on the right side to some extent and accepts pressure on the left side of 50% of the higher LDR, the board developments slower to the left. The light moves toward the front over the time, and the depth of gentle on the two boards is indistinguishable. In such circumstances, Board may or may not be recoverable, and there may or may not be a pivot.
{"title":"The Solar Tracker Using Micro-controller","authors":"Mehrunnisa, J. Priyanka, B. S. Chandra","doi":"10.1109/ICEARS53579.2022.9751796","DOIUrl":"https://doi.org/10.1109/ICEARS53579.2022.9751796","url":null,"abstract":"During the next half-century, generating energy for reduction of petroleum products is an endless task. When compared to other sustainable resources, Idea of converting sun-light oriented energy into energy using solar boards is on the leading edge. Regardless, the regular substitution in the related mentality of the sunlight based toward the earth reduces the watts delivered through the sun powered charger. As per the present circumstance the sunlight based following device is the top -notch way to build the effectiveness of a solar board. The sun board which screens the sun incorporates two LDRs, a sun-light based charger and a servo engine and an ATmega328 Micro regulator. Gentle principally put together resistors are mounted with respect to the edges of the sun powered charger. While delicate falls on them, light-based wounds cause no obstacle. A servo engine connected to the board rotates the board in the direction of the light. Boards are coordinated at the sorted way so delicate within the LDRs interestingly, with boards are pivoted near the LDR which has a prevalent limit with regards to bring down check conversely, with the backwards. The Servo engine turns the board at an uplifting perspective. At the point when slight pressure drops to the right side of the higher LDR, the board focuses on the right side to some extent and accepts pressure on the left side of 50% of the higher LDR, the board developments slower to the left. The light moves toward the front over the time, and the depth of gentle on the two boards is indistinguishable. In such circumstances, Board may or may not be recoverable, and there may or may not be a pivot.","PeriodicalId":252961,"journal":{"name":"2022 International Conference on Electronics and Renewable Systems (ICEARS)","volume":"54 3","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113959813","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}
In the education industry answering questions is used as a common parameter to judge one’s understanding of a topic. Taking quizzes on a regular basis helps an individual feel confident and it also helps the professor assess the student’s understanding on a particular topic. Generating question and answer pairs is a time-consuming task. To solve this problem, this paper discusses methods to generate automatic Natural Language Processing models which creates diverse types of question-answer pairs. The model takes an input in the form of text in the English language and produces output as Complex Questions, Multiple Choice Questions with relevant distractors, and Fill in the Blanks type of questions. To generate Complex Questions a Rule-Based Algorithm is used. To generate Multiple Choice Questions and Fill in the Blanks type questions, a Vector Algorithm from the GLoVe Model is used along with Rule-Based Algorithms. This paper also includes a detailed explanation of the analysis of the pattern and rules that are observed in the question-making process. SQuAD dataset is used for this analysis and used the same dataset to train the model. The implementation process of this model focused on generating diverse questions with higher syntactic correctness than the existing models. The approach mentioned in this paper can be used in the fields of education, entertainment, generation of quizzes, virtual learning assistance and to get a deeper insight into any topic.
{"title":"Generating QA from Rule-based Algorithms","authors":"Pratiksha Rajesh Rao, Tanay Navneet Jhawar, Yash Avinash Kachave, V. Hirlekar","doi":"10.1109/ICEARS53579.2022.9751723","DOIUrl":"https://doi.org/10.1109/ICEARS53579.2022.9751723","url":null,"abstract":"In the education industry answering questions is used as a common parameter to judge one’s understanding of a topic. Taking quizzes on a regular basis helps an individual feel confident and it also helps the professor assess the student’s understanding on a particular topic. Generating question and answer pairs is a time-consuming task. To solve this problem, this paper discusses methods to generate automatic Natural Language Processing models which creates diverse types of question-answer pairs. The model takes an input in the form of text in the English language and produces output as Complex Questions, Multiple Choice Questions with relevant distractors, and Fill in the Blanks type of questions. To generate Complex Questions a Rule-Based Algorithm is used. To generate Multiple Choice Questions and Fill in the Blanks type questions, a Vector Algorithm from the GLoVe Model is used along with Rule-Based Algorithms. This paper also includes a detailed explanation of the analysis of the pattern and rules that are observed in the question-making process. SQuAD dataset is used for this analysis and used the same dataset to train the model. The implementation process of this model focused on generating diverse questions with higher syntactic correctness than the existing models. The approach mentioned in this paper can be used in the fields of education, entertainment, generation of quizzes, virtual learning assistance and to get a deeper insight into any topic.","PeriodicalId":252961,"journal":{"name":"2022 International Conference on Electronics and Renewable Systems (ICEARS)","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122897125","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 : 2022-03-16DOI: 10.1109/ICEARS53579.2022.9752265
Sanjay S Tippannavar, Shivaprasad N, P. S
The 21st century is an era of technology. Technology has undoubtedly changed the way of living. It has an impact on the lives and redefined the fact of living. The smart home can monitor the temperature, fire, water level, automatic door lock, PIR sensor along with IR sensor placed around the house to monitor the house which guarantees the family's safety, smoke sensor and non-contact water level controller. It comprises of a personal computer (PC) as the communication medium, including the LabVIEW software installed on the PC and the Arduino micro-controller board coded and integrated with sensors and voice synthesizers which provide feedback thus assuring & notifying the user about the Smart Home. Invention of this smart home gives us a safe, convenient, and fully automated system.
{"title":"Smart Home Automation Implemented using LabVIEW and Arduino","authors":"Sanjay S Tippannavar, Shivaprasad N, P. S","doi":"10.1109/ICEARS53579.2022.9752265","DOIUrl":"https://doi.org/10.1109/ICEARS53579.2022.9752265","url":null,"abstract":"The 21st century is an era of technology. Technology has undoubtedly changed the way of living. It has an impact on the lives and redefined the fact of living. The smart home can monitor the temperature, fire, water level, automatic door lock, PIR sensor along with IR sensor placed around the house to monitor the house which guarantees the family's safety, smoke sensor and non-contact water level controller. It comprises of a personal computer (PC) as the communication medium, including the LabVIEW software installed on the PC and the Arduino micro-controller board coded and integrated with sensors and voice synthesizers which provide feedback thus assuring & notifying the user about the Smart Home. Invention of this smart home gives us a safe, convenient, and fully automated system.","PeriodicalId":252961,"journal":{"name":"2022 International Conference on Electronics and Renewable Systems (ICEARS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131281758","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 : 2022-03-16DOI: 10.1109/ICEARS53579.2022.9751843
A. Amudha, M. Siva Ramkumar, K. Balachander, G. Emayavaramban, G. N, S. S, Suresh Mt
There is a considerable chance of fire breakouts in industries such as petroleum, chemical, oils, & gas, resulting in massive devastation, destruction of livelihood, and the great majority of all, the loss of life. When an event happens, it's essential to have a mechanism in place that can alert authorized personnel and ensure that the premises are safe. In order to detect fires (via smoke as well as temperature sensors) and LPG leaks, an IOT-based industrial problem detection project was created. Data is sent to a remote location through the Internet of Things (IoT). 'Things' can communicate with sensors, circuits, programs, and accessibility through the Internet of Things (IOT). Human interaction is unnecessary for these technologies.(p)(p)Monitoring voltage and current consumption by industry is also a feature of this system. Use this tool to locate the hottest area, which may be assessed by determining the most hazardous area for people or production. A current sensor measures the overall amount of current consumed by the industrial sector. ' If the power exceeds the threshold and the load is tripped, the IOT cloud app will notify the appropriate person.
{"title":"Monitoring Of Industrial Electrical Equipments","authors":"A. Amudha, M. Siva Ramkumar, K. Balachander, G. Emayavaramban, G. N, S. S, Suresh Mt","doi":"10.1109/ICEARS53579.2022.9751843","DOIUrl":"https://doi.org/10.1109/ICEARS53579.2022.9751843","url":null,"abstract":"There is a considerable chance of fire breakouts in industries such as petroleum, chemical, oils, & gas, resulting in massive devastation, destruction of livelihood, and the great majority of all, the loss of life. When an event happens, it's essential to have a mechanism in place that can alert authorized personnel and ensure that the premises are safe. In order to detect fires (via smoke as well as temperature sensors) and LPG leaks, an IOT-based industrial problem detection project was created. Data is sent to a remote location through the Internet of Things (IoT). 'Things' can communicate with sensors, circuits, programs, and accessibility through the Internet of Things (IOT). Human interaction is unnecessary for these technologies.(p)(p)Monitoring voltage and current consumption by industry is also a feature of this system. Use this tool to locate the hottest area, which may be assessed by determining the most hazardous area for people or production. A current sensor measures the overall amount of current consumed by the industrial sector. ' If the power exceeds the threshold and the load is tripped, the IOT cloud app will notify the appropriate person.","PeriodicalId":252961,"journal":{"name":"2022 International Conference on Electronics and Renewable Systems (ICEARS)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133223307","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 : 2022-03-16DOI: 10.1109/ICEARS53579.2022.9752343
Ellia Twinamatsiko, Dinesh Kumar
Over the years, the number of firms measuring and reporting environmental, social, and governance data has seen a massive shift due to the overwhelming demand and pressure from different stakeholders. The introduction of various international regulatory bodies like the Corporate Sustainability Reporting Directive (CSRD), has also been intentional in encouraging companies to disclose publicly documents like annual reports, integrated reports in regards to topics like social, environmental, employee affairs and human rights. When it comes to investing, ESG issues take into account a firm’s operational influence on the native environment. Customers, policy makers, investors, and regulators are exerting huge amount of pressure on Companies to carry out Environmental, Social, and Governance ("ESG") reporting also known as non-financial reporting. Sustainability reporting has previously exhibited numerous advantages to businesses as accurate data collection and reporting are essential for managing the company’s sustainability performance as well as improving financial decision making. It is vital for a company’s long-term performance to actively disclose and communicate its non-financial practices and approaches. Therefore, in order to answer questions like; “Is it vital for developing market firms to disclose non-financial information, such as that relating to environmental, social, and governance (ESG)?”, this paper will attempt to provide a deeper insight into ESG disclosure and the impact it has on Firm Performance using Machine Learning techniques (Regression) and performance Ratios (Return On Assets & Return On Equity).
{"title":"Incorporating ESG in Decision Making for Responsible and Sustainable Investments using Machine Learning","authors":"Ellia Twinamatsiko, Dinesh Kumar","doi":"10.1109/ICEARS53579.2022.9752343","DOIUrl":"https://doi.org/10.1109/ICEARS53579.2022.9752343","url":null,"abstract":"Over the years, the number of firms measuring and reporting environmental, social, and governance data has seen a massive shift due to the overwhelming demand and pressure from different stakeholders. The introduction of various international regulatory bodies like the Corporate Sustainability Reporting Directive (CSRD), has also been intentional in encouraging companies to disclose publicly documents like annual reports, integrated reports in regards to topics like social, environmental, employee affairs and human rights. When it comes to investing, ESG issues take into account a firm’s operational influence on the native environment. Customers, policy makers, investors, and regulators are exerting huge amount of pressure on Companies to carry out Environmental, Social, and Governance (\"ESG\") reporting also known as non-financial reporting. Sustainability reporting has previously exhibited numerous advantages to businesses as accurate data collection and reporting are essential for managing the company’s sustainability performance as well as improving financial decision making. It is vital for a company’s long-term performance to actively disclose and communicate its non-financial practices and approaches. Therefore, in order to answer questions like; “Is it vital for developing market firms to disclose non-financial information, such as that relating to environmental, social, and governance (ESG)?”, this paper will attempt to provide a deeper insight into ESG disclosure and the impact it has on Firm Performance using Machine Learning techniques (Regression) and performance Ratios (Return On Assets & Return On Equity).","PeriodicalId":252961,"journal":{"name":"2022 International Conference on Electronics and Renewable Systems (ICEARS)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133451755","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 : 2022-03-16DOI: 10.1109/ICEARS53579.2022.9752267
P. William, Siddhartha Choubey, M. Ramkumar, Apurv Verma, K. Vengatesan, Abha Choubey
In this study, we suggest a revolutionary network architectural design strategy for future 5G mobile networks, which we believe would be beneficial. The proposed design is based on a mobile environment that is centered on the user and incorporates a range of wireless and mobile technologies to achieve this. Because it is impossible to make changes to any wireless technology, new or old, in a heterogeneous wireless environment, each solution for next-generation mobile and wireless networks should be implemented in the service stratum, whereas radio access technologies should be implemented in the transport stratum in the Next-Generation Networks approach. The user terminal in the proposed design has the option of altering the Radio Access Technology - RAT based on the parameters that have been supplied. This paper introduces the Policy-Router, which is a node in the core network that constructs IP tunnels to the mobile terminal across many available RATs to the terminal, while enabling the mobile terminal to change RATs in an unobtrusive manner. After learning about the RAT via the mobile terminal's performance measurements, the mobile terminal selects the RAT by executing a multi-criteria decision-making process using the specified user agent. In this paper, we describe the QoSPRO methodology, which allows control information to be shared between the mobile terminal and the Policy Router throughout the performance evaluation procedure.
{"title":"Implementation of 5G Network Architecture with Interoperability in Heterogeneous Wireless Environment using Radio Spectrum","authors":"P. William, Siddhartha Choubey, M. Ramkumar, Apurv Verma, K. Vengatesan, Abha Choubey","doi":"10.1109/ICEARS53579.2022.9752267","DOIUrl":"https://doi.org/10.1109/ICEARS53579.2022.9752267","url":null,"abstract":"In this study, we suggest a revolutionary network architectural design strategy for future 5G mobile networks, which we believe would be beneficial. The proposed design is based on a mobile environment that is centered on the user and incorporates a range of wireless and mobile technologies to achieve this. Because it is impossible to make changes to any wireless technology, new or old, in a heterogeneous wireless environment, each solution for next-generation mobile and wireless networks should be implemented in the service stratum, whereas radio access technologies should be implemented in the transport stratum in the Next-Generation Networks approach. The user terminal in the proposed design has the option of altering the Radio Access Technology - RAT based on the parameters that have been supplied. This paper introduces the Policy-Router, which is a node in the core network that constructs IP tunnels to the mobile terminal across many available RATs to the terminal, while enabling the mobile terminal to change RATs in an unobtrusive manner. After learning about the RAT via the mobile terminal's performance measurements, the mobile terminal selects the RAT by executing a multi-criteria decision-making process using the specified user agent. In this paper, we describe the QoSPRO methodology, which allows control information to be shared between the mobile terminal and the Policy Router throughout the performance evaluation procedure.","PeriodicalId":252961,"journal":{"name":"2022 International Conference on Electronics and Renewable Systems (ICEARS)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133755655","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 : 2022-03-16DOI: 10.1109/ICEARS53579.2022.9752263
yellamma pachipala, M. Harika, B. Aakanksha, M. Kavitha
Objects in the home that are often used tend to follow specific patterns in terms of time and location. Analyzing these trends can help us keep track of our belongings and increase efficiency by reducing the amount of time wasted forgetting or looking for them. Tensor Flow, a relatively new framework from Google, was utilised to model our neural network in our project. Multiple objects in real-time video streams are detected using the Tensor Flow Object Detection API. The system then detects trends and alerts the user if an abnormality is discovered. Finding REMO—detecting relative mobility patterns in geographic lifelines is a study reported by Laube et al. A neural network model is constructed and trained with the goal of being able to accurately identify digits from handwritten photographs. For this, the Tensor Flow syntax was employed, using Keras as the front end. The trained model can take an image of a handwritten digit as input and predict the digit's class, that is, it can predict the digit or the input picture's class. Machine vision improvements, in combination with a camera and artificial intelligence programming, may now be used by PCs to recognize images.
{"title":"Object Detection using TensorFlow","authors":"yellamma pachipala, M. Harika, B. Aakanksha, M. Kavitha","doi":"10.1109/ICEARS53579.2022.9752263","DOIUrl":"https://doi.org/10.1109/ICEARS53579.2022.9752263","url":null,"abstract":"Objects in the home that are often used tend to follow specific patterns in terms of time and location. Analyzing these trends can help us keep track of our belongings and increase efficiency by reducing the amount of time wasted forgetting or looking for them. Tensor Flow, a relatively new framework from Google, was utilised to model our neural network in our project. Multiple objects in real-time video streams are detected using the Tensor Flow Object Detection API. The system then detects trends and alerts the user if an abnormality is discovered. Finding REMO—detecting relative mobility patterns in geographic lifelines is a study reported by Laube et al. A neural network model is constructed and trained with the goal of being able to accurately identify digits from handwritten photographs. For this, the Tensor Flow syntax was employed, using Keras as the front end. The trained model can take an image of a handwritten digit as input and predict the digit's class, that is, it can predict the digit or the input picture's class. Machine vision improvements, in combination with a camera and artificial intelligence programming, may now be used by PCs to recognize images.","PeriodicalId":252961,"journal":{"name":"2022 International Conference on Electronics and Renewable Systems (ICEARS)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132345427","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 : 2022-03-16DOI: 10.1109/ICEARS53579.2022.9751872
P. A, V. Dhanakoti
The medical technology has seen a tremendous growth in this century. Innovative high- end technologies that are created for health care benefits the patients as well as the medical professional in a wider perspective. Diabetes mellitus is a medical complaint among all age groups which occurs due to the increase in the blood sugar level. Diabetic retinopathy is said to be a symptomless diabetic eye illness which affects the retina of human eye and leads to blindness. It affects the retinal blood vessels. There is a growth of abnormal blood vessels in the retinal surface. Diabetic retinopathy can be detected using Ridge based vessel segmentation, Computer Driven Tracing of Vessel Network, Adaptive Local Thresholding it does not have uniform illuminations. Latest technological advancements in image processing provide a more efficient diagnosis of diabetic retinopathy with the help of feature extraction. The retinal scanned image is first pre-processed and feature extraction is done using HAAR wavelet Transform for the quantitative measure of the accuracy of the disease. The image is segmented and classified based on the training sets of data using SVM classifier. This process tends to provides more accuracy and about 98% sensitivity in+ the retinal classification.
{"title":"Efficient Diabetic Retinopathy Detection using Machine Learning Techniques","authors":"P. A, V. Dhanakoti","doi":"10.1109/ICEARS53579.2022.9751872","DOIUrl":"https://doi.org/10.1109/ICEARS53579.2022.9751872","url":null,"abstract":"The medical technology has seen a tremendous growth in this century. Innovative high- end technologies that are created for health care benefits the patients as well as the medical professional in a wider perspective. Diabetes mellitus is a medical complaint among all age groups which occurs due to the increase in the blood sugar level. Diabetic retinopathy is said to be a symptomless diabetic eye illness which affects the retina of human eye and leads to blindness. It affects the retinal blood vessels. There is a growth of abnormal blood vessels in the retinal surface. Diabetic retinopathy can be detected using Ridge based vessel segmentation, Computer Driven Tracing of Vessel Network, Adaptive Local Thresholding it does not have uniform illuminations. Latest technological advancements in image processing provide a more efficient diagnosis of diabetic retinopathy with the help of feature extraction. The retinal scanned image is first pre-processed and feature extraction is done using HAAR wavelet Transform for the quantitative measure of the accuracy of the disease. The image is segmented and classified based on the training sets of data using SVM classifier. This process tends to provides more accuracy and about 98% sensitivity in+ the retinal classification.","PeriodicalId":252961,"journal":{"name":"2022 International Conference on Electronics and Renewable Systems (ICEARS)","volume":"479 1-2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131744403","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 : 2022-03-16DOI: 10.1109/ICEARS53579.2022.9751820
V. Kannagi, M. Rajkumar, I. Chandra, K. Sangeethalakshmi, V. Mohanavel
An estimated 350 million young adults (between the ages of 30 and 40) would have heart disease by 2030, according to the WHO. These individuals will be at risk for renal problems, stroke, as well as peripheral vascular disease. Heart disease is the leading cause of death in the modern era. Most individuals cannot afford the high expense of heart disease therapy. Because of this, a Heart Disease Prediction Scheme can help alleviate this issue. It aids in the earlier detection of cardiovascular disease. For the development of the Heart Disease Prediction Scheme, data mining methods are employed. A variety of healthcare data formats, including pictures, text, charts, and figures, are used in various systems. To diagnose cardiac disease early, we examine risk factors including system conditions. the selection of risk predictors, the use of efficient methods for identifying and extract key information to describe aspects of developing a prediction model We can quickly diagnose heart illness with multiple features and risk factor specifications using the new technique called Intelligent Learning Assisted Support Vector [ILASV]. Mining concepts are used to identify high-risk variables for heart disease based on these criteria. Fast and accurate illness predictions will be made possible by the application of data mining methods.
{"title":"Logical Mining Assisted Heart Disease Prediction Scheme in Association with Deep Learning Principles","authors":"V. Kannagi, M. Rajkumar, I. Chandra, K. Sangeethalakshmi, V. Mohanavel","doi":"10.1109/ICEARS53579.2022.9751820","DOIUrl":"https://doi.org/10.1109/ICEARS53579.2022.9751820","url":null,"abstract":"An estimated 350 million young adults (between the ages of 30 and 40) would have heart disease by 2030, according to the WHO. These individuals will be at risk for renal problems, stroke, as well as peripheral vascular disease. Heart disease is the leading cause of death in the modern era. Most individuals cannot afford the high expense of heart disease therapy. Because of this, a Heart Disease Prediction Scheme can help alleviate this issue. It aids in the earlier detection of cardiovascular disease. For the development of the Heart Disease Prediction Scheme, data mining methods are employed. A variety of healthcare data formats, including pictures, text, charts, and figures, are used in various systems. To diagnose cardiac disease early, we examine risk factors including system conditions. the selection of risk predictors, the use of efficient methods for identifying and extract key information to describe aspects of developing a prediction model We can quickly diagnose heart illness with multiple features and risk factor specifications using the new technique called Intelligent Learning Assisted Support Vector [ILASV]. Mining concepts are used to identify high-risk variables for heart disease based on these criteria. Fast and accurate illness predictions will be made possible by the application of data mining methods.","PeriodicalId":252961,"journal":{"name":"2022 International Conference on Electronics and Renewable Systems (ICEARS)","volume":"161 7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-03-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129088971","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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