Jay Bagrecha, Tanay Shah, Karan Shah, Tanvi Gandhi, Sushila Palwe
In India, almost 18 million visually impaired people have difficulties in managing their day-to-day activities. Hence, there is a need to develop an application that can assist them every time and give vocal instructions in both English and Hindi. In this paper, we introduced a robust lightweight Android application that facilitates visually impaired individuals by providing a variety of essential features such as object and distance detection, Indian currency note detection, and optical character recognition that can enhance their quality of life. This application aims to have a user-friendly GUI well suited to the needs of the blind user and modules like Object Recognition with Image Captioning so that the visually challenged user can gain a better understanding of their surroundings.
{"title":"VirtualEye: Android Application for the Visually Impaired","authors":"Jay Bagrecha, Tanay Shah, Karan Shah, Tanvi Gandhi, Sushila Palwe","doi":"10.3233/apc210204","DOIUrl":"https://doi.org/10.3233/apc210204","url":null,"abstract":"In India, almost 18 million visually impaired people have difficulties in managing their day-to-day activities. Hence, there is a need to develop an application that can assist them every time and give vocal instructions in both English and Hindi. In this paper, we introduced a robust lightweight Android application that facilitates visually impaired individuals by providing a variety of essential features such as object and distance detection, Indian currency note detection, and optical character recognition that can enhance their quality of life. This application aims to have a user-friendly GUI well suited to the needs of the blind user and modules like Object Recognition with Image Captioning so that the visually challenged user can gain a better understanding of their surroundings.","PeriodicalId":429440,"journal":{"name":"Recent Trends in Intensive Computing","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134108808","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}
Sivasaravanababu, T. R. Dineshkumar, Dr. G. Saravana Kumar
The Multiply-Accumulate Unit (MAC) is the core computational block in many DSP and wireless application but comes with more complicated architectures. Moreover the MAC block also decides the energy consumption and the performance of the overall design; due to its lies in the maximal path delay critical propagation. Developing high performance and energy optimized MAC core is essential to optimized DSP core. In this work, a high speed and low power signed booth radix enabled MAC Unit is proposed with highly configurable assertion driven modified booth algorithm (AD-MBE). The proposed booth core is based on core optimized booth radix-4 with hierarchical partial product accumulation design and associated path delay optimization and computational complexity reduction. Here all booth generated partial products are added as post summation adder network which consists of carry select adder (CSA) & carry look ahead (CLA) sequentially which narrow down the energy and computational complexity. Here increasing the operating frequency is achieved by accumulating encoding bits of each of the input operand into assertion unit before generating end results instead of going through the entire partial product accumulation. The FPGA implementation of the proposed signed asserted booth radix-4 based MAC shows significant complexity reduction with improved system performance as compared to the conventional booth unit and conventional array multiplier.
{"title":"Assertion Driven Modified Booth Encoding and Post Computation Model for Speed MAC Applications","authors":"Sivasaravanababu, T. R. Dineshkumar, Dr. G. Saravana Kumar","doi":"10.3233/apc210289","DOIUrl":"https://doi.org/10.3233/apc210289","url":null,"abstract":"The Multiply-Accumulate Unit (MAC) is the core computational block in many DSP and wireless application but comes with more complicated architectures. Moreover the MAC block also decides the energy consumption and the performance of the overall design; due to its lies in the maximal path delay critical propagation. Developing high performance and energy optimized MAC core is essential to optimized DSP core. In this work, a high speed and low power signed booth radix enabled MAC Unit is proposed with highly configurable assertion driven modified booth algorithm (AD-MBE). The proposed booth core is based on core optimized booth radix-4 with hierarchical partial product accumulation design and associated path delay optimization and computational complexity reduction. Here all booth generated partial products are added as post summation adder network which consists of carry select adder (CSA) & carry look ahead (CLA) sequentially which narrow down the energy and computational complexity. Here increasing the operating frequency is achieved by accumulating encoding bits of each of the input operand into assertion unit before generating end results instead of going through the entire partial product accumulation. The FPGA implementation of the proposed signed asserted booth radix-4 based MAC shows significant complexity reduction with improved system performance as compared to the conventional booth unit and conventional array multiplier.","PeriodicalId":429440,"journal":{"name":"Recent Trends in Intensive Computing","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133937333","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}
Upasana Sapra, Aiswarya Sakthivel, X. Shobana Macdalin, S. Siva Ranjini
Electrical energy consumption is alarmingly rising, but the availability of conventional sources is limited. To meet the increasing demand; the implementation of non-conventional sources is the need of the hour. Solar energy is the most sustainable alternative for power generation among non-conventional sources families. Resonant inverters are used in low-power high-frequency induction heating appliances. Full-bridge resonant inverters are most commonly used to convert solar received power into the suitable form required for high-frequency application device by providing maximum power to the load at resonant frequency The aim of the paper is to analyze the working of the resonant inverter by taking the input supply from the solar panel and converting the obtained dc input to ac input through the resonant inverter. This obtained output is supplied for the high-frequency industrial application which mainly includes Induction frequency heating Applications. Induction heating is one of the techniques used in casting foundry for the treatment of metals. It involves the heat treatment of the metals namely annealing, hardening tempering method. goes here.
{"title":"Solar-Powered Improved Full Bridge Resonant Inverter for High-Frequency Industrial Applications","authors":"Upasana Sapra, Aiswarya Sakthivel, X. Shobana Macdalin, S. Siva Ranjini","doi":"10.3233/apc210296","DOIUrl":"https://doi.org/10.3233/apc210296","url":null,"abstract":"Electrical energy consumption is alarmingly rising, but the availability of conventional sources is limited. To meet the increasing demand; the implementation of non-conventional sources is the need of the hour. Solar energy is the most sustainable alternative for power generation among non-conventional sources families. Resonant inverters are used in low-power high-frequency induction heating appliances. Full-bridge resonant inverters are most commonly used to convert solar received power into the suitable form required for high-frequency application device by providing maximum power to the load at resonant frequency The aim of the paper is to analyze the working of the resonant inverter by taking the input supply from the solar panel and converting the obtained dc input to ac input through the resonant inverter. This obtained output is supplied for the high-frequency industrial application which mainly includes Induction frequency heating Applications. Induction heating is one of the techniques used in casting foundry for the treatment of metals. It involves the heat treatment of the metals namely annealing, hardening tempering method. goes here.","PeriodicalId":429440,"journal":{"name":"Recent Trends in Intensive Computing","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133316571","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}
K. Kharade, S. Kharade, V. R. Sonawane, S. Bhamre, S. V. Katkar, R. K. Kamat
The security of any business plays a vital role. All enterprises expect high security because of the increase in robbery. It is challenging to manage security with traditional ways of protection. This paper emphasizes the sensor-based security system to protect against any unwanted entry in the business area. This system is developed using IoT-based sensors, and electronic materials develop the security system. The present scenario ensures protection and security have become inevitably necessary. There is regressive progress in the protection sector as the influence of new technology is hitting its height. It’s well-known as a modern home when there is a current home with minimal human effort. This technology aims to automate industrial area security and partially replace the security individual, enabling us to monitor unsuspecting activities and be warned during critical situations. Since wireless and emerging technology is taking place, an automated intelligent protection system is being introduced.
{"title":"IoT Based Security Alerts for the Safety of Industrial Area","authors":"K. Kharade, S. Kharade, V. R. Sonawane, S. Bhamre, S. V. Katkar, R. K. Kamat","doi":"10.3233/apc210185","DOIUrl":"https://doi.org/10.3233/apc210185","url":null,"abstract":"The security of any business plays a vital role. All enterprises expect high security because of the increase in robbery. It is challenging to manage security with traditional ways of protection. This paper emphasizes the sensor-based security system to protect against any unwanted entry in the business area. This system is developed using IoT-based sensors, and electronic materials develop the security system. The present scenario ensures protection and security have become inevitably necessary. There is regressive progress in the protection sector as the influence of new technology is hitting its height. It’s well-known as a modern home when there is a current home with minimal human effort. This technology aims to automate industrial area security and partially replace the security individual, enabling us to monitor unsuspecting activities and be warned during critical situations. Since wireless and emerging technology is taking place, an automated intelligent protection system is being introduced.","PeriodicalId":429440,"journal":{"name":"Recent Trends in Intensive Computing","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122166060","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}
The modem data is collected by using IoT, stored in distributed cloud storage, and issued for data mining or training artificial intelligence. These new digital technologies integrate into the data middle platform have facilitated the progress of industry, promoted the fourth industrial revolution. And it also has caused challenges in security and privacy-preventing. The privacy data breach can happen in any phase of the Big-Data life cycle, and the Data Middle Platform also faces similar situations. How to make the privacy avoid leakage is exigency. The traditional privacy-preventing model is not enough, we need the help of Machine-Learning and the Blockchain. In this research, the researcher reviews the security and privacy-preventing in Big-Data, Machine Learning, Blockchain, and other related works at first. And then finding some gaps between the theory and the actual work. Based on these gaps, trying to create a suitable framework to guide the industry to protect their privacy when the organization contribute and operate their data middle platform. No only academicians, but also industry practitioners especially SMEs will get the benefit from this research.
{"title":"Data Security and Privacy-Preserving Framework Using Machine Learning and Blockchain in Big-Data to Data Middle Platform in the Era of IR 4.0","authors":"Chuqiao Chen, S. B. Goyal","doi":"10.3233/apc210190","DOIUrl":"https://doi.org/10.3233/apc210190","url":null,"abstract":"The modem data is collected by using IoT, stored in distributed cloud storage, and issued for data mining or training artificial intelligence. These new digital technologies integrate into the data middle platform have facilitated the progress of industry, promoted the fourth industrial revolution. And it also has caused challenges in security and privacy-preventing. The privacy data breach can happen in any phase of the Big-Data life cycle, and the Data Middle Platform also faces similar situations. How to make the privacy avoid leakage is exigency. The traditional privacy-preventing model is not enough, we need the help of Machine-Learning and the Blockchain. In this research, the researcher reviews the security and privacy-preventing in Big-Data, Machine Learning, Blockchain, and other related works at first. And then finding some gaps between the theory and the actual work. Based on these gaps, trying to create a suitable framework to guide the industry to protect their privacy when the organization contribute and operate their data middle platform. No only academicians, but also industry practitioners especially SMEs will get the benefit from this research.","PeriodicalId":429440,"journal":{"name":"Recent Trends in Intensive Computing","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124828983","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}
Kavitha Srinivas, Saravanan Pitchai, Udayabhanu N P G Raju, Abhishek Kumar, B. Muthu Kumaran, K. Vengatesan
Current scenario around the globe we can find that physical or face to face learning got a very big full stop for a long period of time. Virtual learning took its place, somewhat leaving behind both its positive and negative impact on the education sector. E-learning is playing a chief part in maintaining the decorum of education sector. The research and surveys found that young learners got many benefits through this type of education but also it is undeniable that it has negative aspects too, which needs to be solved. Mainly private higher education suffered less as compared to institutions in rural areas. This research proposes how to bring out the quality of output through e-learning for all the learners equally. It has become a challenge for private and government institutions to make this smart or virtual learning as the best integral part of educational system.
{"title":"A Deep Analysis of Higher Education Cognitive and Psychological Learning Impact During Covid 19 Pandemic","authors":"Kavitha Srinivas, Saravanan Pitchai, Udayabhanu N P G Raju, Abhishek Kumar, B. Muthu Kumaran, K. Vengatesan","doi":"10.3233/apc210254","DOIUrl":"https://doi.org/10.3233/apc210254","url":null,"abstract":"Current scenario around the globe we can find that physical or face to face learning got a very big full stop for a long period of time. Virtual learning took its place, somewhat leaving behind both its positive and negative impact on the education sector. E-learning is playing a chief part in maintaining the decorum of education sector. The research and surveys found that young learners got many benefits through this type of education but also it is undeniable that it has negative aspects too, which needs to be solved. Mainly private higher education suffered less as compared to institutions in rural areas. This research proposes how to bring out the quality of output through e-learning for all the learners equally. It has become a challenge for private and government institutions to make this smart or virtual learning as the best integral part of educational system.","PeriodicalId":429440,"journal":{"name":"Recent Trends in Intensive Computing","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125721044","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 recent years, the number of user comments and text materials has increased dramatically. Analysis of the emotions has drawn interest from researchers. Earlier research in the field of artificial-intelligence concentrate on identification of emotion and exploring the explanation the emotions can’t recognized or misrecognized. The association between the emotions leads to the understanding of emotion loss. In this Work we are trying to fill the gap between emotional recognition and emotional co-relation mining through social media reviews of natural language text. The association between emotions, represented as the emotional uncertainty and evolution, is mainly triggered by cognitive bias in the human emotion. Numerous types of features and Recurrent neural-network (RNN) as deep learning model provided to mine the emotion co-relation from emotion detection using text. The rule on conflict of emotions is derived on a symmetric basis. TF-IDF, NLP Features and Co-relation features has used for feature extraction as well as section and Recurrent Neural Network (RNN) and Hybrid deep learning algorithm for classification has used to demonstrates the entire research experiments. Finally evaluate the system performance with various existing system and show the effectiveness of proposed system.
近年来，用户评论和文字材料的数量急剧增加。对情绪的分析引起了研究人员的兴趣。人工智能领域的早期研究主要集中在对情绪的识别和对无法识别或错误识别的情绪的解释。情绪之间的联系导致了对情绪丧失的理解。在这项工作中，我们试图通过对自然语言文本的社交媒体评论来填补情感识别和情感关联挖掘之间的空白。情绪之间的关联主要是由人类情绪的认知偏差引发的，表现为情绪的不确定性和进化。多种类型的特征和递归神经网络(RNN)作为深度学习模型，提供了从文本情感检测中挖掘情感关联的方法。关于情绪冲突的规则是在对称的基础上推导出来的。使用TF-IDF、NLP feature和Co-relation feature进行特征提取，并使用section和Recurrent Neural Network (RNN)和Hybrid deep learning算法进行分类，演示了整个研究实验。最后用现有的各种系统对系统的性能进行了评价，证明了所提系统的有效性。
{"title":"Aspect Based Emotion Detection and Topic Modeling on Social Media Reviews","authors":"Ganesh N. Jorvekar, Mohit Gangwar","doi":"10.3233/apc210242","DOIUrl":"https://doi.org/10.3233/apc210242","url":null,"abstract":"In recent years, the number of user comments and text materials has increased dramatically. Analysis of the emotions has drawn interest from researchers. Earlier research in the field of artificial-intelligence concentrate on identification of emotion and exploring the explanation the emotions can’t recognized or misrecognized. The association between the emotions leads to the understanding of emotion loss. In this Work we are trying to fill the gap between emotional recognition and emotional co-relation mining through social media reviews of natural language text. The association between emotions, represented as the emotional uncertainty and evolution, is mainly triggered by cognitive bias in the human emotion. Numerous types of features and Recurrent neural-network (RNN) as deep learning model provided to mine the emotion co-relation from emotion detection using text. The rule on conflict of emotions is derived on a symmetric basis. TF-IDF, NLP Features and Co-relation features has used for feature extraction as well as section and Recurrent Neural Network (RNN) and Hybrid deep learning algorithm for classification has used to demonstrates the entire research experiments. Finally evaluate the system performance with various existing system and show the effectiveness of proposed system.","PeriodicalId":429440,"journal":{"name":"Recent Trends in Intensive Computing","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129243705","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}
C. Pallavi, Girija R, Vedhapriyavadhana R, Barnali Dey, R. Vincent
Online financial transactions play a crucial role in today’s economy. It becomes an unavoidable part of the business and global activities. Transaction fraud executes thoughtful intimidations to e-commerce spending. Now-a-days, the online contract or business is fetching additional sound by knowing the types of online transaction frauds associated with, these are raising which disturbs the currency accompanying business. It has the capability to confine and encumber the contract accomplished by the intruder from an honest consumer’s credit card information. In order to avoid such a problem, the proposed system is established transaction limit for the customers. Efficient data is only considered for detecting fraudulent user action and it happens only at the time of registration. Transaction which is happening for any individual is not at all known to any FDS (Fraud Detection System) consecutively at the bank which mainly issues credit cards to customers. To speak out this problem, BLA (Behaviour and Location Analysis) is executed. The FDS tracks at a credit card provided by bank. All the inbound business is directed to the FDS aimed at confirmation, authentication and verification. FDS catches the card particulars and matter to confirm that the operation is fake or genuine. The pick-up merchandises are unknown to Fraud Detection System. If the transaction is assumed to be fraud, then the corresponding bank declines it. In order to verify the individuality, uniqueness or originality, it uses spending patterns and geographical area. In case, if any suspicious pattern is identified or detected, the FDS system needs verification. The information which is already registered by the user, the system identifies infrequent outlines in the disbursement method. After three invalid attempts, the system will hinder the user. In this proposed system, most of the algorithms are checked and investigated for online financial fraud detection techniques.
{"title":"A Relative Investigation of Various Algorithms for Online Financial Fraud Detection Techniques","authors":"C. Pallavi, Girija R, Vedhapriyavadhana R, Barnali Dey, R. Vincent","doi":"10.3233/apc210174","DOIUrl":"https://doi.org/10.3233/apc210174","url":null,"abstract":"Online financial transactions play a crucial role in today’s economy. It becomes an unavoidable part of the business and global activities. Transaction fraud executes thoughtful intimidations to e-commerce spending. Now-a-days, the online contract or business is fetching additional sound by knowing the types of online transaction frauds associated with, these are raising which disturbs the currency accompanying business. It has the capability to confine and encumber the contract accomplished by the intruder from an honest consumer’s credit card information. In order to avoid such a problem, the proposed system is established transaction limit for the customers. Efficient data is only considered for detecting fraudulent user action and it happens only at the time of registration. Transaction which is happening for any individual is not at all known to any FDS (Fraud Detection System) consecutively at the bank which mainly issues credit cards to customers. To speak out this problem, BLA (Behaviour and Location Analysis) is executed. The FDS tracks at a credit card provided by bank. All the inbound business is directed to the FDS aimed at confirmation, authentication and verification. FDS catches the card particulars and matter to confirm that the operation is fake or genuine. The pick-up merchandises are unknown to Fraud Detection System. If the transaction is assumed to be fraud, then the corresponding bank declines it. In order to verify the individuality, uniqueness or originality, it uses spending patterns and geographical area. In case, if any suspicious pattern is identified or detected, the FDS system needs verification. The information which is already registered by the user, the system identifies infrequent outlines in the disbursement method. After three invalid attempts, the system will hinder the user. In this proposed system, most of the algorithms are checked and investigated for online financial fraud detection techniques.","PeriodicalId":429440,"journal":{"name":"Recent Trends in Intensive Computing","volume":"24 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120984903","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}
S. Deepa, Lavanya Dhanesh, Danusha V, Divya Dath K, Pavadhaarini G K, Shobana Sri C
The number of elderly people worldwide is rigidly increasing due to decrease in birth rates and innovations implemented in medical field. Due to the increase in elderly people population diseases like dementia are also being increased year by year. Having done many kinds of research it is found that there is no permanent treatment for diseases like dementia, even if those patients come in public they look similar to normal people, however, people with dementia have abnormal behaviors like loss of patience, aggression, lack of thinking which in turn causes burden to family members and caretakers. In order to address this issues, this paper demonstrates a follow-up and rescue program for the elderly. The system includes a GPS receiver, a GSM module and a long-distance RF transmitter and receiver, real-time location. Families and care takers can obtain real-time information and history of patient location through GPS to avoid loss of elderly patients. With the help of this system, the number of losing patients will be decreased and the pressure on the caretakers and family people will be cut down to some extent.
{"title":"Dementia People Tracking System","authors":"S. Deepa, Lavanya Dhanesh, Danusha V, Divya Dath K, Pavadhaarini G K, Shobana Sri C","doi":"10.3233/apc210273","DOIUrl":"https://doi.org/10.3233/apc210273","url":null,"abstract":"The number of elderly people worldwide is rigidly increasing due to decrease in birth rates and innovations implemented in medical field. Due to the increase in elderly people population diseases like dementia are also being increased year by year. Having done many kinds of research it is found that there is no permanent treatment for diseases like dementia, even if those patients come in public they look similar to normal people, however, people with dementia have abnormal behaviors like loss of patience, aggression, lack of thinking which in turn causes burden to family members and caretakers. In order to address this issues, this paper demonstrates a follow-up and rescue program for the elderly. The system includes a GPS receiver, a GSM module and a long-distance RF transmitter and receiver, real-time location. Families and care takers can obtain real-time information and history of patient location through GPS to avoid loss of elderly patients. With the help of this system, the number of losing patients will be decreased and the pressure on the caretakers and family people will be cut down to some extent.","PeriodicalId":429440,"journal":{"name":"Recent Trends in Intensive Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132552614","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}
Heart diseases or Cardiovascular Diseases (CVDs) are the main cause of death on the planet throughout the most recent years and become the most dangerous disease in India and the entire world. The UCI repository is utilized to calculate the exactness of the AI calculations for foreseeing coronary illness, as k-nearest neighbor, decision tree, linear regression, and support vector machine. Different indications like chest pain, fasting of heartbeat, etc., are referenced. Large datasets, which are not available in medical and clinical research, are required in order to apply deep learning techniques. Surrogate data is generated from Cleveland dataset. The predicted results show that there is an improvement in classification accuracy. Heart disease is one of the most challenging diseases to diagnose as it is the most recognized killer in the present day. Utilizing AI algorithms, this paper gives anticipating coronary illness. Here, we will use the various machine learning algorithms such as Support Vector Machine, Random Forest, KNN, Naive Bayes, Decision Tree and LR.
{"title":"Coronary Illness Prediction Using Random Forest Classifier","authors":"Rekha G, Shanthini B, Ranjith Kumar V","doi":"10.3233/apc210285","DOIUrl":"https://doi.org/10.3233/apc210285","url":null,"abstract":"Heart diseases or Cardiovascular Diseases (CVDs) are the main cause of death on the planet throughout the most recent years and become the most dangerous disease in India and the entire world. The UCI repository is utilized to calculate the exactness of the AI calculations for foreseeing coronary illness, as k-nearest neighbor, decision tree, linear regression, and support vector machine. Different indications like chest pain, fasting of heartbeat, etc., are referenced. Large datasets, which are not available in medical and clinical research, are required in order to apply deep learning techniques. Surrogate data is generated from Cleveland dataset. The predicted results show that there is an improvement in classification accuracy. Heart disease is one of the most challenging diseases to diagnose as it is the most recognized killer in the present day. Utilizing AI algorithms, this paper gives anticipating coronary illness. Here, we will use the various machine learning algorithms such as Support Vector Machine, Random Forest, KNN, Naive Bayes, Decision Tree and LR.","PeriodicalId":429440,"journal":{"name":"Recent Trends in Intensive Computing","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131519851","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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