Pub Date : 2021-09-23DOI: 10.1109/CCGE50943.2021.9776454
Dharmendra Ambani, Kishor H. Atkotiya
Privacy Preserving Data-Mining is the major use of data- mining methods for ensuring privacy of personal information. Data-mining algorithms search for the information that is most valuable. A major aspect of Privacy Preserving Data Mining is the safeguarding of sensitive information against unauthorized access. The Secure Data Contribution Retrieval algorithm assigns a privacy policy and security is assigned depending on the application needs and compatibility. This method is capable of meeting the requirements for numerous datasets. Currently, social media sites such as Facebook, Twitter, and YouTube are quite popular. Then, the expanded attribute-based encryption methodology allows users to transfer data contents across orbit software networks. Data leakage occurs during the gathering and storage of user Orbit Software Networks in an insecure distributed or centralized system. Third, the suggested Level by Level Security Optimization and Content Visualization algorithm helps prevent privacy problems when sharing information and visualizing data. They use privacy levels at the individual level following the assessment of the privacy compatibility of orbit software networks application. Experimental analysis employs the data from social datasets.
{"title":"Secure Data Contribution and Retrieval in Social Networks Using Effective Privacy Preserving Data Mining Techniques","authors":"Dharmendra Ambani, Kishor H. Atkotiya","doi":"10.1109/CCGE50943.2021.9776454","DOIUrl":"https://doi.org/10.1109/CCGE50943.2021.9776454","url":null,"abstract":"Privacy Preserving Data-Mining is the major use of data- mining methods for ensuring privacy of personal information. Data-mining algorithms search for the information that is most valuable. A major aspect of Privacy Preserving Data Mining is the safeguarding of sensitive information against unauthorized access. The Secure Data Contribution Retrieval algorithm assigns a privacy policy and security is assigned depending on the application needs and compatibility. This method is capable of meeting the requirements for numerous datasets. Currently, social media sites such as Facebook, Twitter, and YouTube are quite popular. Then, the expanded attribute-based encryption methodology allows users to transfer data contents across orbit software networks. Data leakage occurs during the gathering and storage of user Orbit Software Networks in an insecure distributed or centralized system. Third, the suggested Level by Level Security Optimization and Content Visualization algorithm helps prevent privacy problems when sharing information and visualizing data. They use privacy levels at the individual level following the assessment of the privacy compatibility of orbit software networks application. Experimental analysis employs the data from social datasets.","PeriodicalId":130452,"journal":{"name":"2021 International Conference on Computing, Communication and Green Engineering (CCGE)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129831598","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 : 2021-09-23DOI: 10.1109/CCGE50943.2021.9776464
A. Dubey, Anmol Gulati, Ayush Choubey, S. Jaikar, Pranav More
Driving a vehicle at night or in low levels of natural light poses many risks, one of which is caused by the vehicle's headlight. Many drivers prefer to use high beam headlights while driving at night, which improves visibility by allowing them to see a larger area ahead of them. Aside from providing increased visibility and a clearer view of the road ahead, these high beams can strain the eyes of the driver of the vehicle approaching from the opposite direction. This strain on the eyes of the driver can cause a glare effect for a slight duration which can disrupt the vision of the driver and may cause accidents. The glare effect is caused by the use of high beam headlights from the opposite end of the vehicle. The system under consideration uses a LED matrix (Hardware module) in addition to a trained object detection module and a live camera feed (Software module) to detect vehicles, acquire their positions to control the LEDs in our matrix, and control the intensities of those LEDs. Using this system, we aim to control the headlights in an optimized way to reduce the glare effect from impacting the drivers of oncoming vehicles and also illuminate the road ahead without compromising the visibility of the driver. The model assists in overcoming the dizziness or glare effect that a driver may encounter while driving in the dark. It also aims to eliminate the need for the driver to manually control the headlights, which is rarely used.
{"title":"Adaptive Headlight System for Reducing the Dazzling Effect to Prevent Road Accident","authors":"A. Dubey, Anmol Gulati, Ayush Choubey, S. Jaikar, Pranav More","doi":"10.1109/CCGE50943.2021.9776464","DOIUrl":"https://doi.org/10.1109/CCGE50943.2021.9776464","url":null,"abstract":"Driving a vehicle at night or in low levels of natural light poses many risks, one of which is caused by the vehicle's headlight. Many drivers prefer to use high beam headlights while driving at night, which improves visibility by allowing them to see a larger area ahead of them. Aside from providing increased visibility and a clearer view of the road ahead, these high beams can strain the eyes of the driver of the vehicle approaching from the opposite direction. This strain on the eyes of the driver can cause a glare effect for a slight duration which can disrupt the vision of the driver and may cause accidents. The glare effect is caused by the use of high beam headlights from the opposite end of the vehicle. The system under consideration uses a LED matrix (Hardware module) in addition to a trained object detection module and a live camera feed (Software module) to detect vehicles, acquire their positions to control the LEDs in our matrix, and control the intensities of those LEDs. Using this system, we aim to control the headlights in an optimized way to reduce the glare effect from impacting the drivers of oncoming vehicles and also illuminate the road ahead without compromising the visibility of the driver. The model assists in overcoming the dizziness or glare effect that a driver may encounter while driving in the dark. It also aims to eliminate the need for the driver to manually control the headlights, which is rarely used.","PeriodicalId":130452,"journal":{"name":"2021 International Conference on Computing, Communication and Green Engineering (CCGE)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128381485","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 : 2021-09-23DOI: 10.1109/CCGE50943.2021.9776437
Sparsh Amarnani, N. Bhagat, Hritwik Ekade, Ajay Gupta, Sunita Sahu
MOOCs, after first being introduced in 2008, have since drawn attention around the world for their advantages and also criticism of their drawbacks. Interactivity with the instructor and personalized experience while learning are some of the main aspects in which the current MOOCs show scope of improvement. In this paper, we are proposing a novel chatbot architecture that can act as teaching assistance to answer queries faced by learners in MOOCs. The chatbot will be trained on the course material using the popular ALBERT model to develop its knowledge base. The chatbot will answer a large number of student's queries, thus reducing the workload of the instructor(s) to answer all the queries. This will open a new avenue for instructor-chatbot-learner interaction, where all of these three will compound each other's value.
{"title":"A Complete Chatbot based Architecture for answering user's Course-related queries in MOOC platforms","authors":"Sparsh Amarnani, N. Bhagat, Hritwik Ekade, Ajay Gupta, Sunita Sahu","doi":"10.1109/CCGE50943.2021.9776437","DOIUrl":"https://doi.org/10.1109/CCGE50943.2021.9776437","url":null,"abstract":"MOOCs, after first being introduced in 2008, have since drawn attention around the world for their advantages and also criticism of their drawbacks. Interactivity with the instructor and personalized experience while learning are some of the main aspects in which the current MOOCs show scope of improvement. In this paper, we are proposing a novel chatbot architecture that can act as teaching assistance to answer queries faced by learners in MOOCs. The chatbot will be trained on the course material using the popular ALBERT model to develop its knowledge base. The chatbot will answer a large number of student's queries, thus reducing the workload of the instructor(s) to answer all the queries. This will open a new avenue for instructor-chatbot-learner interaction, where all of these three will compound each other's value.","PeriodicalId":130452,"journal":{"name":"2021 International Conference on Computing, Communication and Green Engineering (CCGE)","volume":"143 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127290608","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 : 2021-09-23DOI: 10.1109/CCGE50943.2021.9776458
Manish Sharma, Namrata Choudhary, Rakesh Ahuja, S. Malhotra
In this reported-work, a compact MIMO antenna with 2x2 configuration is proposed for 5G applications working at 28GHz and 38GHz bands. The proposed antenna is useful for IoT (Internet of Things) and smart city applications. The designed antenna consist of rectangular patch printed on one plane of Rogers RTDuroid Substrate and ground on the opposite plane. Also, single element antenna is modified as MIMO antenna configuration by placing the radiating elements in adjacent or orthogonal configuration. The proposed antenna is validated by sketching the results in frequency domain and far-field region. Also, the parameter such as ECC, DG, TARC and CCL are evaluated which validates the diversity performance.
{"title":"A Compact Multiband 2x2 MIMO Antenna For 5G 28GHz/38GHz IoT and Smart City Applications","authors":"Manish Sharma, Namrata Choudhary, Rakesh Ahuja, S. Malhotra","doi":"10.1109/CCGE50943.2021.9776458","DOIUrl":"https://doi.org/10.1109/CCGE50943.2021.9776458","url":null,"abstract":"In this reported-work, a compact MIMO antenna with 2x2 configuration is proposed for 5G applications working at 28GHz and 38GHz bands. The proposed antenna is useful for IoT (Internet of Things) and smart city applications. The designed antenna consist of rectangular patch printed on one plane of Rogers RTDuroid Substrate and ground on the opposite plane. Also, single element antenna is modified as MIMO antenna configuration by placing the radiating elements in adjacent or orthogonal configuration. The proposed antenna is validated by sketching the results in frequency domain and far-field region. Also, the parameter such as ECC, DG, TARC and CCL are evaluated which validates the diversity performance.","PeriodicalId":130452,"journal":{"name":"2021 International Conference on Computing, Communication and Green Engineering (CCGE)","volume":"124-125 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133677675","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 : 2021-09-23DOI: 10.1109/CCGE50943.2021.9776405
S. Pangaonkar, R. Gunjan, Virendra Shete
Voice Emotion Recognition (VER) is a dynamic and has implications on a wide range of research areas. Use of a computer for voice emotion recognition is a way to study the voice signal of a speaker, as well as is a process that is altered by inner emotions. Human Machine Interface (HMI) is very vital and opted to implement this effectively and an innovative way. To develop new recognition methods, this research paper evaluates the basic emotions of human. Accurate detection of emotional states can be further used as a machine learning database for interdisciplinary experiments. The proposed system is an algorithmic method that first extracts the audio signal from the microphone, preprocesses it, and then evaluates the parameters based on various characteristics. The model is trained through the Mel Frequency Cepstral Coefficient (MFCC) and PRAAT (Speech Analysis in Phonetics) coefficients. By creating a feature map using these, Convolutional Neural Networks (CNN) effectively learn and classify the attributes of perceived signals of basic emotions such as sadness, surprise, happiness, anger, fear, neutral and disgust. The proposed method provides good recognition rate.
{"title":"Recognition of Human Emotion through effective estimations of Features and Classification Model","authors":"S. Pangaonkar, R. Gunjan, Virendra Shete","doi":"10.1109/CCGE50943.2021.9776405","DOIUrl":"https://doi.org/10.1109/CCGE50943.2021.9776405","url":null,"abstract":"Voice Emotion Recognition (VER) is a dynamic and has implications on a wide range of research areas. Use of a computer for voice emotion recognition is a way to study the voice signal of a speaker, as well as is a process that is altered by inner emotions. Human Machine Interface (HMI) is very vital and opted to implement this effectively and an innovative way. To develop new recognition methods, this research paper evaluates the basic emotions of human. Accurate detection of emotional states can be further used as a machine learning database for interdisciplinary experiments. The proposed system is an algorithmic method that first extracts the audio signal from the microphone, preprocesses it, and then evaluates the parameters based on various characteristics. The model is trained through the Mel Frequency Cepstral Coefficient (MFCC) and PRAAT (Speech Analysis in Phonetics) coefficients. By creating a feature map using these, Convolutional Neural Networks (CNN) effectively learn and classify the attributes of perceived signals of basic emotions such as sadness, surprise, happiness, anger, fear, neutral and disgust. The proposed method provides good recognition rate.","PeriodicalId":130452,"journal":{"name":"2021 International Conference on Computing, Communication and Green Engineering (CCGE)","volume":"312 10","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120983874","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 : 2021-09-23DOI: 10.1109/CCGE50943.2021.9776390
Monika Patel, P. Sajja
The whole world is completely upset because of the unexpected ejection of a lethal disease called Covid-19. Every single region is absolutely closed because of the effect of Covid. To prevent the unfold of this unwellness, everybody needs to maintain social distancing. Students are considered as the eventual fate of the country. To save the understudies from this infection the academic institute has begun internet educating and learning. Yet, giving information in online mode has become a testing task for understudies similarly as a tutor. Because of e-learning, customize learning has become vanish. To help intelligent instructing and learning systems an upgraded model is needed to boost the academic activities. This paper presents a style of projected model utilizing Reinforcement learning. The reinforcement learning (RL) approach provides effective pedagogical strategies for educating the learners with their interest in the subject. With the assistance of RL, the introduced model chooses the training difficulty level of scholars and recommends the student's understanding level to access the reading content. The proposed structure is planned in such a manner with the goal that the educator isn't needed to continually screen the understudy. Experimental results show that these approaches scale back the number of attentions needed from the teacher and enhance the training capability of understudy. The presented framework enhances personalized learning.
{"title":"Application for Multi-Agent System: A Case of Customised eLearning","authors":"Monika Patel, P. Sajja","doi":"10.1109/CCGE50943.2021.9776390","DOIUrl":"https://doi.org/10.1109/CCGE50943.2021.9776390","url":null,"abstract":"The whole world is completely upset because of the unexpected ejection of a lethal disease called Covid-19. Every single region is absolutely closed because of the effect of Covid. To prevent the unfold of this unwellness, everybody needs to maintain social distancing. Students are considered as the eventual fate of the country. To save the understudies from this infection the academic institute has begun internet educating and learning. Yet, giving information in online mode has become a testing task for understudies similarly as a tutor. Because of e-learning, customize learning has become vanish. To help intelligent instructing and learning systems an upgraded model is needed to boost the academic activities. This paper presents a style of projected model utilizing Reinforcement learning. The reinforcement learning (RL) approach provides effective pedagogical strategies for educating the learners with their interest in the subject. With the assistance of RL, the introduced model chooses the training difficulty level of scholars and recommends the student's understanding level to access the reading content. The proposed structure is planned in such a manner with the goal that the educator isn't needed to continually screen the understudy. Experimental results show that these approaches scale back the number of attentions needed from the teacher and enhance the training capability of understudy. The presented framework enhances personalized learning.","PeriodicalId":130452,"journal":{"name":"2021 International Conference on Computing, Communication and Green Engineering (CCGE)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125071467","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 : 2021-09-23DOI: 10.1109/CCGE50943.2021.9776354
Shweta Sharad Chavan, J. Jayaseeli
By providing a function called Cloud Storage, the company let participants outsource their confidential data to a third party and use the on-demand services and applications of data on the organization's cloud storage server. With this, researchers would be able to encrypt details, which would will be crucial in preventing security breaches of confidential details. In this exchange conference, businesses have to encrypt their data before they process it to the Cloud framework. Attribute Based Encryption (ABE) system is a symmetric key dependent cryptosystem used in cloud system that lets device users, software, data and programmers access managed digital data. Unfortunately, BAE suffers from a performance downside with outsourcing the operation of decrypting the secret. There has been a lot of suggestions put forward as to how to boost the performance of the method. It would be to the same investigation that was stated in the research study. We take the case of the Robust Paraphrasing and conclude there is a new implementation of the Electronic Referencing tool, even though it depends on the Actuals. The load testing strategy is used to minimize the expense of outsourcing the decryption phase to a third-party data decryption service provider. Load balancing may occur by considering features such as file space, memory, hard drive disc usage, etc. For the intent of revocation of key for a community, we often discuss the problem of the key consumer quitting the group. Therefore, in the case of the key user leaving the group, the latest key to open a group should be modified and circulated to all current key holders. The experimental findings of this proposed method proves that the time and memory consumptions of this proposed system were comparable to, if not higher than, the current system of time consumptions and memory usage.
{"title":"Efficient Attribute Based Encryption Outsourcing in Cloud Storage with User Revocation","authors":"Shweta Sharad Chavan, J. Jayaseeli","doi":"10.1109/CCGE50943.2021.9776354","DOIUrl":"https://doi.org/10.1109/CCGE50943.2021.9776354","url":null,"abstract":"By providing a function called Cloud Storage, the company let participants outsource their confidential data to a third party and use the on-demand services and applications of data on the organization's cloud storage server. With this, researchers would be able to encrypt details, which would will be crucial in preventing security breaches of confidential details. In this exchange conference, businesses have to encrypt their data before they process it to the Cloud framework. Attribute Based Encryption (ABE) system is a symmetric key dependent cryptosystem used in cloud system that lets device users, software, data and programmers access managed digital data. Unfortunately, BAE suffers from a performance downside with outsourcing the operation of decrypting the secret. There has been a lot of suggestions put forward as to how to boost the performance of the method. It would be to the same investigation that was stated in the research study. We take the case of the Robust Paraphrasing and conclude there is a new implementation of the Electronic Referencing tool, even though it depends on the Actuals. The load testing strategy is used to minimize the expense of outsourcing the decryption phase to a third-party data decryption service provider. Load balancing may occur by considering features such as file space, memory, hard drive disc usage, etc. For the intent of revocation of key for a community, we often discuss the problem of the key consumer quitting the group. Therefore, in the case of the key user leaving the group, the latest key to open a group should be modified and circulated to all current key holders. The experimental findings of this proposed method proves that the time and memory consumptions of this proposed system were comparable to, if not higher than, the current system of time consumptions and memory usage.","PeriodicalId":130452,"journal":{"name":"2021 International Conference on Computing, Communication and Green Engineering (CCGE)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125101895","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 : 2021-09-23DOI: 10.1109/CCGE50943.2021.9776411
Harsh Sudhanshu Sahu, Nellutla Himanish, K. Hiran, Janapala Leha
In this 21st century, one of the major issues faced by humans is, how to deal with the wastage of electricity. Mostly due to the carelessness of the management of the lamps or the streetlights are left ON in many places and one of the main sources of this wastage of electricity is in the sports complexes. In our paper, we try to solve this problem by using solar panels, and in addition to the proper utilization of electrical energy and water, we are using specific light and soil moisture sensors. To the maximum extend, our paper helps us to overcome the problems faced. The lights will be automatically turned on and turned off depending on the sunlight intensity, and also the water pumps will be controlled according to the moisture level present in the ground. The solar sensor which we are using is BH-1750 gives accurate values when compared with other sensors. In this research, we have collected the data on sunlight intensity which can be used further for developing a Machine Learning algorithm.
{"title":"Design of Automatic Lighting System based on Intensity of Sunlight using BH-1750","authors":"Harsh Sudhanshu Sahu, Nellutla Himanish, K. Hiran, Janapala Leha","doi":"10.1109/CCGE50943.2021.9776411","DOIUrl":"https://doi.org/10.1109/CCGE50943.2021.9776411","url":null,"abstract":"In this 21st century, one of the major issues faced by humans is, how to deal with the wastage of electricity. Mostly due to the carelessness of the management of the lamps or the streetlights are left ON in many places and one of the main sources of this wastage of electricity is in the sports complexes. In our paper, we try to solve this problem by using solar panels, and in addition to the proper utilization of electrical energy and water, we are using specific light and soil moisture sensors. To the maximum extend, our paper helps us to overcome the problems faced. The lights will be automatically turned on and turned off depending on the sunlight intensity, and also the water pumps will be controlled according to the moisture level present in the ground. The solar sensor which we are using is BH-1750 gives accurate values when compared with other sensors. In this research, we have collected the data on sunlight intensity which can be used further for developing a Machine Learning algorithm.","PeriodicalId":130452,"journal":{"name":"2021 International Conference on Computing, Communication and Green Engineering (CCGE)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125198568","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 : 2021-09-23DOI: 10.1109/CCGE50943.2021.9776385
Madhavi S. Darokar, A. D. Raut, V. Thakre
Emotion recognition and their analysis have become a very popular topic nowadays, as most of the world using the social media in the form of various applications such as Twitter, Facebook, Whatsapp, Instagram and many more. Also, there are quite a large number of users, who buy the different daily life products through the online shopping websites like Amazon, Flipkart where the online behaviors and emotions of the consumer buying the product is of great interest to the e-commerce industry. In accordance to, the development in the artificial intelligence field, there exist various algorithms that are programmed to analyze the user behavior and trap their emotions through various tools for analyzing the market trends and to increase the percentage of profit. Furthermore, a prolific rate of development is observed in the AI field. This now can be noticed presently, in the form of ‘Deep learning’ where a very huge amount of data is available and the decision-making process is very crucial. If the tremendous amount of data is accessible, “Machine Learning” algorithms are of utmost importance.
{"title":"Methodological Review of Emotion Recognition for Social Media: A Sentiment Analysis Approach","authors":"Madhavi S. Darokar, A. D. Raut, V. Thakre","doi":"10.1109/CCGE50943.2021.9776385","DOIUrl":"https://doi.org/10.1109/CCGE50943.2021.9776385","url":null,"abstract":"Emotion recognition and their analysis have become a very popular topic nowadays, as most of the world using the social media in the form of various applications such as Twitter, Facebook, Whatsapp, Instagram and many more. Also, there are quite a large number of users, who buy the different daily life products through the online shopping websites like Amazon, Flipkart where the online behaviors and emotions of the consumer buying the product is of great interest to the e-commerce industry. In accordance to, the development in the artificial intelligence field, there exist various algorithms that are programmed to analyze the user behavior and trap their emotions through various tools for analyzing the market trends and to increase the percentage of profit. Furthermore, a prolific rate of development is observed in the AI field. This now can be noticed presently, in the form of ‘Deep learning’ where a very huge amount of data is available and the decision-making process is very crucial. If the tremendous amount of data is accessible, “Machine Learning” algorithms are of utmost importance.","PeriodicalId":130452,"journal":{"name":"2021 International Conference on Computing, Communication and Green Engineering (CCGE)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125301594","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 : 2021-09-23DOI: 10.1109/CCGE50943.2021.9776395
Priyanka Pitale, D. Karia, Manish Parmar
Entire world got hit by a pandemic due to COVID-19 virus. This virus had a huge toll on the human race which is the reason there is a need to detect such a threat on anearly stage. To detect the virus, some of its symptoms like high fever, cough, cold, and congestion in lungs. Spreading of this virus occurs due to a physical touch between two living or non-living surfaces. Therefore, constant sanitization is required in the contaminated zones. An advanced machine that can take a human X-ray and analyze for infection, check the temperature of the body as well as sanitize while a person is leaving can be a boon to detect cases early. In the entry stage, an X-ray machinewill take a chest X-ray of the person and use machine learning classifiers in order to detect any infection in lungs. On the second stage a temperature monitoring device using infrared sensor will check for high or low temperatures. Alongside, a sterilizing unit having UVC rays will disinfect the person in front of it. In this way, an instant checkup for COVID-19symptoms can help to eradicate the virus. This system can be used for offices, public places as well as medical facilities for detection of the virus.
{"title":"Temperature Monitoring and Application of Machine Learning in Radiology for COVID-19 Pandemic","authors":"Priyanka Pitale, D. Karia, Manish Parmar","doi":"10.1109/CCGE50943.2021.9776395","DOIUrl":"https://doi.org/10.1109/CCGE50943.2021.9776395","url":null,"abstract":"Entire world got hit by a pandemic due to COVID-19 virus. This virus had a huge toll on the human race which is the reason there is a need to detect such a threat on anearly stage. To detect the virus, some of its symptoms like high fever, cough, cold, and congestion in lungs. Spreading of this virus occurs due to a physical touch between two living or non-living surfaces. Therefore, constant sanitization is required in the contaminated zones. An advanced machine that can take a human X-ray and analyze for infection, check the temperature of the body as well as sanitize while a person is leaving can be a boon to detect cases early. In the entry stage, an X-ray machinewill take a chest X-ray of the person and use machine learning classifiers in order to detect any infection in lungs. On the second stage a temperature monitoring device using infrared sensor will check for high or low temperatures. Alongside, a sterilizing unit having UVC rays will disinfect the person in front of it. In this way, an instant checkup for COVID-19symptoms can help to eradicate the virus. This system can be used for offices, public places as well as medical facilities for detection of the virus.","PeriodicalId":130452,"journal":{"name":"2021 International Conference on Computing, Communication and Green Engineering (CCGE)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121679232","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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