Pub Date : 2019-03-01DOI: 10.1109/ICSCAN.2019.8878784
K. Vasu Babu, B. Anuradha
In modern telecommunications system MIMO antenna plays an important role having the capability to radiate wave is extra than one radiation pattern & polarization is also another critical factor. This article describes the design & reduction of isolation between the two symmetrical patches. The separation between the two patches must be maintained to reduce the isolation is 0.02 λ0 The proposed system having a compact size of $38,,mathrm {m}mathrm {m}times 25$ mm with a FR-4 substrate and loss tangent of 0.02 is considered. The MIMO system is resonate at a frequency of 3.98 GHz obtained the reflection coefficient (S11) of −39.71 dB & greatly reducing the isolation (S12) of −50 dB. At the resonant band of frequency the impedance bandwidth of the systems is around 1.76 GHz. The proposed design maintained the VSWR ≤ 2 and ECC < 0.04 is maintained at the resonant band of frequency. The different time domain analysis parameters like group delay, diversity gain, real/ imaginary impedances and peak gain is also measured here. The group delay and diversity gain at the resonant frequency of proposed MIMO structure is observed −2.48 ± 1nsec & 9.999 dBi.
{"title":"Design & Isolation Reduction of Circle Inserted MIMO Antenna","authors":"K. Vasu Babu, B. Anuradha","doi":"10.1109/ICSCAN.2019.8878784","DOIUrl":"https://doi.org/10.1109/ICSCAN.2019.8878784","url":null,"abstract":"In modern telecommunications system MIMO antenna plays an important role having the capability to radiate wave is extra than one radiation pattern & polarization is also another critical factor. This article describes the design & reduction of isolation between the two symmetrical patches. The separation between the two patches must be maintained to reduce the isolation is 0.02 λ0 The proposed system having a compact size of $38,,mathrm {m}mathrm {m}times 25$ mm with a FR-4 substrate and loss tangent of 0.02 is considered. The MIMO system is resonate at a frequency of 3.98 GHz obtained the reflection coefficient (S11) of −39.71 dB & greatly reducing the isolation (S12) of −50 dB. At the resonant band of frequency the impedance bandwidth of the systems is around 1.76 GHz. The proposed design maintained the VSWR ≤ 2 and ECC < 0.04 is maintained at the resonant band of frequency. The different time domain analysis parameters like group delay, diversity gain, real/ imaginary impedances and peak gain is also measured here. The group delay and diversity gain at the resonant frequency of proposed MIMO structure is observed −2.48 ± 1nsec & 9.999 dBi.","PeriodicalId":363880,"journal":{"name":"2019 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122361784","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 : 2019-03-01DOI: 10.1109/ICSCAN.2019.8878726
Nikhil Joshi, Rewanth Tammana
Trained Machine learning models are core components of proprietary products. Business models are entirely built around these ML powered products. Such products are either delivered as a software package (containing the trained model) or they are deployed on cloud with restricted API access for prediction. In ML-as-a-service, users are charged per-query or per-hour basis, generating revenue for businesses. Models deployed on cloud could be vulnerable to Model Duplication attacks. Researchers found ways to exploit these services and clone the functionalities of black box models hidden in the cloud by continuously querying the provided APIs. After successful execution of attack, the attacker does not require to pay the cloud service provider. Worst case scenario, attackers can also sell the cloned model or use them in their business model.Traditionally attackers use convex optimization algorithm like Gradient Descent with appropriate hyper-parameters to train their models. In our research we propose a modification to traditional approach called as GDALR (Gradient Driven Adaptive Learning Rate) that dynamically updates the learning rate based on the gradient values. This results in stealing the target model in comparatively less number of epochs, decreasing the time and cost, hence increasing the efficiency of the attack. This shows that sophisticated attacks can be launched for stealing the black box machine learning models which increases risk for MLaaS based businesses.
{"title":"GDALR: An Efficient Model Duplication Attack on Black Box Machine Learning Models","authors":"Nikhil Joshi, Rewanth Tammana","doi":"10.1109/ICSCAN.2019.8878726","DOIUrl":"https://doi.org/10.1109/ICSCAN.2019.8878726","url":null,"abstract":"Trained Machine learning models are core components of proprietary products. Business models are entirely built around these ML powered products. Such products are either delivered as a software package (containing the trained model) or they are deployed on cloud with restricted API access for prediction. In ML-as-a-service, users are charged per-query or per-hour basis, generating revenue for businesses. Models deployed on cloud could be vulnerable to Model Duplication attacks. Researchers found ways to exploit these services and clone the functionalities of black box models hidden in the cloud by continuously querying the provided APIs. After successful execution of attack, the attacker does not require to pay the cloud service provider. Worst case scenario, attackers can also sell the cloned model or use them in their business model.Traditionally attackers use convex optimization algorithm like Gradient Descent with appropriate hyper-parameters to train their models. In our research we propose a modification to traditional approach called as GDALR (Gradient Driven Adaptive Learning Rate) that dynamically updates the learning rate based on the gradient values. This results in stealing the target model in comparatively less number of epochs, decreasing the time and cost, hence increasing the efficiency of the attack. This shows that sophisticated attacks can be launched for stealing the black box machine learning models which increases risk for MLaaS based businesses.","PeriodicalId":363880,"journal":{"name":"2019 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128428825","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 : 2019-03-01DOI: 10.1109/ICSCAN.2019.8878738
V. Shruthi, B. Subhiksha, S. Hariniperiyanayagi
in product production statement about a possible future event is a major process that has to be done in order to improve organization good thing received as well as to satisfy customer needs. Our project idea is to develop Manon-demand statement about a possible future event software that is based on “information-giving numbers”, where analysis is done on the current product sale with past sale history and describe a possible future event on product demands. There are different ways of doing things that are been involved in describing a possible future event on new product demand, but they have some limits. Those limits can be overcome by using Manon. The main scope of our project is to record and guess a number the average sale of the products. Our most important goal is to describe a possible future event in the future sale of the product. By our project, we are bringing across that is it very useful for the organization to produce products based on the statement about a possible future event made as well as the customer’s needs can be satisfied
{"title":"Manon-An Insightful Approach to Insistence Indicator by Using Data Analytics","authors":"V. Shruthi, B. Subhiksha, S. Hariniperiyanayagi","doi":"10.1109/ICSCAN.2019.8878738","DOIUrl":"https://doi.org/10.1109/ICSCAN.2019.8878738","url":null,"abstract":"in product production statement about a possible future event is a major process that has to be done in order to improve organization good thing received as well as to satisfy customer needs. Our project idea is to develop Manon-demand statement about a possible future event software that is based on “information-giving numbers”, where analysis is done on the current product sale with past sale history and describe a possible future event on product demands. There are different ways of doing things that are been involved in describing a possible future event on new product demand, but they have some limits. Those limits can be overcome by using Manon. The main scope of our project is to record and guess a number the average sale of the products. Our most important goal is to describe a possible future event in the future sale of the product. By our project, we are bringing across that is it very useful for the organization to produce products based on the statement about a possible future event made as well as the customer’s needs can be satisfied","PeriodicalId":363880,"journal":{"name":"2019 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129611424","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 : 2019-03-01DOI: 10.1109/ICSCAN.2019.8878748
E. Thamizhselvi, V. Geetha
This paper provides a brief survey about the anthropometric traits in various fields. The word “anthropo” refers to human and “metric” refers to measurement. Anthropometry is essentially refers to the measurement of human individuals for the purpose of identifying the human physical variations. Anthropometry plays a predominant role in medical science, Forensic medicine and criminology, Biometric, sports etc. Anthropometric is used to access the size, shape and composition of human body. The purpose of anthropometric indicator criteria to select features and they have been justified mainly on the basis of being correlated with other risk factors. Due to its significance, the statistical mean and standard deviation measurements are highly followed to monitor the human body based on its measurement. Since this measurement vary according to the fields, it is indeed important to undergo a detailed analysis of anthropometric traits. Hence, this paper discusses about the potential researches on the use of anthropometric traits for different fields in association with the data mining to solve the complex problem by selecting the best features.
{"title":"A Comparative Study of Anthropometric Measures and its significance on Diverse Applications","authors":"E. Thamizhselvi, V. Geetha","doi":"10.1109/ICSCAN.2019.8878748","DOIUrl":"https://doi.org/10.1109/ICSCAN.2019.8878748","url":null,"abstract":"This paper provides a brief survey about the anthropometric traits in various fields. The word “anthropo” refers to human and “metric” refers to measurement. Anthropometry is essentially refers to the measurement of human individuals for the purpose of identifying the human physical variations. Anthropometry plays a predominant role in medical science, Forensic medicine and criminology, Biometric, sports etc. Anthropometric is used to access the size, shape and composition of human body. The purpose of anthropometric indicator criteria to select features and they have been justified mainly on the basis of being correlated with other risk factors. Due to its significance, the statistical mean and standard deviation measurements are highly followed to monitor the human body based on its measurement. Since this measurement vary according to the fields, it is indeed important to undergo a detailed analysis of anthropometric traits. Hence, this paper discusses about the potential researches on the use of anthropometric traits for different fields in association with the data mining to solve the complex problem by selecting the best features.","PeriodicalId":363880,"journal":{"name":"2019 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130920042","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 : 2019-03-01DOI: 10.1109/ICSCAN.2019.8878718
Immanuel Zion Ramdinthara, P. Bala
Agriculture is the backbone of every country. It produces all the necessary needs such as wheat, rice, fruits, grains which are consumed by a human for everyday survival. So, it is important for the country to develop and sustain a productive agricultural system. As demand is increasing for food, food security is very important to sustain and increase yield production at a higher rate and at the same time preserve the ecosystem. So, the technologies in the agricultural domain may be incorporated to enhance food supplies and production. In many countries like the USA, China and Israel have a prominently high implementation of technologies with a high rate of food production and even exported in many parts of the world. These countries have implemented advanced techniques such as the Internet of Things (IoT), Cloud Computing, Machine Learning and Deep Learning algorithm for agriculture domain. Sensor technology used in this domain is highly effective, accurate and productive for precision agriculture. In this topic, agriculture in some developed and developing countries are compared also discusses the way in which these countries could possibly exchange feasible ideas from a different perspective for the development of sustainable agriculture.
{"title":"A Comparative study of IoT Technology in Precision Agriculture","authors":"Immanuel Zion Ramdinthara, P. Bala","doi":"10.1109/ICSCAN.2019.8878718","DOIUrl":"https://doi.org/10.1109/ICSCAN.2019.8878718","url":null,"abstract":"Agriculture is the backbone of every country. It produces all the necessary needs such as wheat, rice, fruits, grains which are consumed by a human for everyday survival. So, it is important for the country to develop and sustain a productive agricultural system. As demand is increasing for food, food security is very important to sustain and increase yield production at a higher rate and at the same time preserve the ecosystem. So, the technologies in the agricultural domain may be incorporated to enhance food supplies and production. In many countries like the USA, China and Israel have a prominently high implementation of technologies with a high rate of food production and even exported in many parts of the world. These countries have implemented advanced techniques such as the Internet of Things (IoT), Cloud Computing, Machine Learning and Deep Learning algorithm for agriculture domain. Sensor technology used in this domain is highly effective, accurate and productive for precision agriculture. In this topic, agriculture in some developed and developing countries are compared also discusses the way in which these countries could possibly exchange feasible ideas from a different perspective for the development of sustainable agriculture.","PeriodicalId":363880,"journal":{"name":"2019 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"123 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128706566","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 : 2019-03-01DOI: 10.1109/ICSCAN.2019.8878729
S. Naresh, R. Arunkumar, I. Suriya, T. Vinodh, B. Radjaram
We know that the needs of many people with disabilities can be overcome with power wheelchair, but some portion of this community is finding it difficult to operate power wheelchair. Though we have evolved in the field of health care and technology, but we are still not good enough to solve difficulties of this sector of population. This project is related to an arduino controlled wheel chair along with an alternative use of manual joystick. The main objective of this project is to felicitate and increase the movement of people who are handicapped and the ones who are not able to move freely. Therefore, we are coming up with a design of wheelchair which will be an asset for medical department and to make it more advanced in existing technology and allows the victim to live a free life.
{"title":"Design of Powered Wheelchair for a Differently Abled Person","authors":"S. Naresh, R. Arunkumar, I. Suriya, T. Vinodh, B. Radjaram","doi":"10.1109/ICSCAN.2019.8878729","DOIUrl":"https://doi.org/10.1109/ICSCAN.2019.8878729","url":null,"abstract":"We know that the needs of many people with disabilities can be overcome with power wheelchair, but some portion of this community is finding it difficult to operate power wheelchair. Though we have evolved in the field of health care and technology, but we are still not good enough to solve difficulties of this sector of population. This project is related to an arduino controlled wheel chair along with an alternative use of manual joystick. The main objective of this project is to felicitate and increase the movement of people who are handicapped and the ones who are not able to move freely. Therefore, we are coming up with a design of wheelchair which will be an asset for medical department and to make it more advanced in existing technology and allows the victim to live a free life.","PeriodicalId":363880,"journal":{"name":"2019 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"74 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113988678","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 : 2019-03-01DOI: 10.1109/ICSCAN.2019.8878868
D. Mohanapriya, R. Reshma, D. Priyadharshini, Swathi Vinod
Smart meters have been came into existence during earliest and started using in various countries. There are lot of argument for the values of smart meters. The smart meter will collect the information of electricity consumed by each and every devices in smart homes. It will help to identify the amount of electricity used by the devices in smart homes and pass it to the sensor which sense it and produce a valuable output. The output thus obtained has been passed to the consumer for the awareness of the particular usage of electricity in devices. Valued storage of electricity will be helpful in comparing the rate of usage of the previous month. By providing an awareness to the user through this smart metering will help the future to save and use electricity in an efficient manner.
{"title":"IoT Based Automation of Electricity Consumption in Smarthomes","authors":"D. Mohanapriya, R. Reshma, D. Priyadharshini, Swathi Vinod","doi":"10.1109/ICSCAN.2019.8878868","DOIUrl":"https://doi.org/10.1109/ICSCAN.2019.8878868","url":null,"abstract":"Smart meters have been came into existence during earliest and started using in various countries. There are lot of argument for the values of smart meters. The smart meter will collect the information of electricity consumed by each and every devices in smart homes. It will help to identify the amount of electricity used by the devices in smart homes and pass it to the sensor which sense it and produce a valuable output. The output thus obtained has been passed to the consumer for the awareness of the particular usage of electricity in devices. Valued storage of electricity will be helpful in comparing the rate of usage of the previous month. By providing an awareness to the user through this smart metering will help the future to save and use electricity in an efficient manner.","PeriodicalId":363880,"journal":{"name":"2019 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121049743","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 : 2019-03-01DOI: 10.1109/ICSCAN.2019.8878767
R. Keerthiga, S. Kalpana, M. Gomathi
The cognitive WSN is used to reduce the spectrum unavailability and to increases the energy efficiency by using SWIPT and DSDV protocol. The SWIPT is the energy harvesting method to overcome the spectrum scarcity and Destination Sequence Vector routing protocol is used to reduce the power consumption by reducing the active sensor nodes which is stimulated in network stimulator software is used to increases the energy efficiency. By using this protocol the delay is reduced and it improve the life time of sensor nodes and energy efficiency through NS2 software stimulation.
{"title":"Energy Efficiency in Cognitive Wireless Sensor Network Using DSDV Protocol","authors":"R. Keerthiga, S. Kalpana, M. Gomathi","doi":"10.1109/ICSCAN.2019.8878767","DOIUrl":"https://doi.org/10.1109/ICSCAN.2019.8878767","url":null,"abstract":"The cognitive WSN is used to reduce the spectrum unavailability and to increases the energy efficiency by using SWIPT and DSDV protocol. The SWIPT is the energy harvesting method to overcome the spectrum scarcity and Destination Sequence Vector routing protocol is used to reduce the power consumption by reducing the active sensor nodes which is stimulated in network stimulator software is used to increases the energy efficiency. By using this protocol the delay is reduced and it improve the life time of sensor nodes and energy efficiency through NS2 software stimulation.","PeriodicalId":363880,"journal":{"name":"2019 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"256 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123265826","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 : 2019-03-01DOI: 10.1109/ICSCAN.2019.8878833
M. Suresh, M. Anbarasi, R. Jayasre, C. Shivani, P. Sowmiya
Smart meter data are raw data. The pervasive recognition of smart meters generates an enormous quantity of electricity utilization data to be collected. The huge amount of data generated by smart meters are collected periodically and it will be analyzed for predicting the electricity demand which will be for convenience companies and inhabitants. Now our proposed work is to Forecasting the usage and price of smart meter data analytics using particle swarm optimization and k-means algorithm. The k-means algorithm is using for given best solution for prediction.
{"title":"Smart Meter Data Analytics Using Particle Swarm Optimization","authors":"M. Suresh, M. Anbarasi, R. Jayasre, C. Shivani, P. Sowmiya","doi":"10.1109/ICSCAN.2019.8878833","DOIUrl":"https://doi.org/10.1109/ICSCAN.2019.8878833","url":null,"abstract":"Smart meter data are raw data. The pervasive recognition of smart meters generates an enormous quantity of electricity utilization data to be collected. The huge amount of data generated by smart meters are collected periodically and it will be analyzed for predicting the electricity demand which will be for convenience companies and inhabitants. Now our proposed work is to Forecasting the usage and price of smart meter data analytics using particle swarm optimization and k-means algorithm. The k-means algorithm is using for given best solution for prediction.","PeriodicalId":363880,"journal":{"name":"2019 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123478633","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 : 2019-03-01DOI: 10.1109/ICSCAN.2019.8878831
V. Lakshmi, V. Nithya, K. Sripriya, C. Preethi, K. Logeshwari
Nowadays technology has improved the worldwide and has become vital part of our life. It aid for doctors to analyze and diagnose the medical problems and diseases. With help artificial intelligence in medicine science become high demand now. This work focuses on clinical decision support system which aid medical people to diagnose of disease. In this paper first present related work in various aspects of clinical decision support systems to provide diagnosis solutions to medical related problems. In this paper a proposed method to identify patient with diabetes disease risk level is indentified. In this work diabetes patient risk level is been detected by using ontology and machine learning technique. Ontology holds disease symptoms, causes and treatments. In machine learning, nave base algorithm is used to make decision on patient record also it defines possibilities of risk level. The proposed algorithm will be evaluated against the following metrics namely confusion matrix, precision level, mean and this proposed work is found to have better prediction level when compared with existing work.
{"title":"Prediction of Diabetes Patient Stage Using Ontology Based Machine Learning System","authors":"V. Lakshmi, V. Nithya, K. Sripriya, C. Preethi, K. Logeshwari","doi":"10.1109/ICSCAN.2019.8878831","DOIUrl":"https://doi.org/10.1109/ICSCAN.2019.8878831","url":null,"abstract":"Nowadays technology has improved the worldwide and has become vital part of our life. It aid for doctors to analyze and diagnose the medical problems and diseases. With help artificial intelligence in medicine science become high demand now. This work focuses on clinical decision support system which aid medical people to diagnose of disease. In this paper first present related work in various aspects of clinical decision support systems to provide diagnosis solutions to medical related problems. In this paper a proposed method to identify patient with diabetes disease risk level is indentified. In this work diabetes patient risk level is been detected by using ontology and machine learning technique. Ontology holds disease symptoms, causes and treatments. In machine learning, nave base algorithm is used to make decision on patient record also it defines possibilities of risk level. The proposed algorithm will be evaluated against the following metrics namely confusion matrix, precision level, mean and this proposed work is found to have better prediction level when compared with existing work.","PeriodicalId":363880,"journal":{"name":"2019 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"362 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132695625","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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