Pub Date : 2019-03-01DOI: 10.1109/ICATIECE45860.2019.9063803
V. Chethana, Evlin Vidyu Latha P
An approach to find the best answers from the multiple answer posted for given question in Community Question Answering(CQA) sites is tedious and most time consuming if manual process used. And also the experts are required to do this by analysis all given answers. So we presented an new approach based on topic modeling and classifier. To evaluate correctness of the proposed model, a set of parameters are used, such as Receiver Operating Characteristics Area Under Curve, Precision Recall Area Under Curve, Confussion matrix, F1 score and Accuracy. Results show that the proposed model is effective in predicting the best answer.
{"title":"Kweri ME: A Q&A based model which predicts the accepted answers of questions in CQA sites","authors":"V. Chethana, Evlin Vidyu Latha P","doi":"10.1109/ICATIECE45860.2019.9063803","DOIUrl":"https://doi.org/10.1109/ICATIECE45860.2019.9063803","url":null,"abstract":"An approach to find the best answers from the multiple answer posted for given question in Community Question Answering(CQA) sites is tedious and most time consuming if manual process used. And also the experts are required to do this by analysis all given answers. So we presented an new approach based on topic modeling and classifier. To evaluate correctness of the proposed model, a set of parameters are used, such as Receiver Operating Characteristics Area Under Curve, Precision Recall Area Under Curve, Confussion matrix, F1 score and Accuracy. Results show that the proposed model is effective in predicting the best answer.","PeriodicalId":106496,"journal":{"name":"2019 1st International Conference on Advanced Technologies in Intelligent Control, Environment, Computing & Communication Engineering (ICATIECE)","volume":"33 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":"116747756","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/ICATIECE45860.2019.9063828
M. P, B. Lakshmikantha, K. Sundar
Demand for electrical power is growing day-today and utilities are forced to operate nearer to their load ability limits. Voltage stability has become main concern for ensuring healthy grid operations. In literature various indices are proposed for predicting the voltage stability limits of radial power system but in-depth analysis is hardly done. An attempt has been made to study the behavior of various indices proposed in the literature with the equivalent electrical distance of the load bus from the source. A new index named equivalent electrical distance index (Zth) is proposed which is calculated using the equivalent electrical distance from bus to the source. The proposed index is compared with existing indices and progress of voltage stability with location of DSTATCOM is tested on 15 bus and 28 bus radial rural electrification networks using MATLAB software.
{"title":"Effect of Equivalent Electrical Distance and Voltage Stability Improvement Using DSTATCOM in Radial Distribution System","authors":"M. P, B. Lakshmikantha, K. Sundar","doi":"10.1109/ICATIECE45860.2019.9063828","DOIUrl":"https://doi.org/10.1109/ICATIECE45860.2019.9063828","url":null,"abstract":"Demand for electrical power is growing day-today and utilities are forced to operate nearer to their load ability limits. Voltage stability has become main concern for ensuring healthy grid operations. In literature various indices are proposed for predicting the voltage stability limits of radial power system but in-depth analysis is hardly done. An attempt has been made to study the behavior of various indices proposed in the literature with the equivalent electrical distance of the load bus from the source. A new index named equivalent electrical distance index (Zth) is proposed which is calculated using the equivalent electrical distance from bus to the source. The proposed index is compared with existing indices and progress of voltage stability with location of DSTATCOM is tested on 15 bus and 28 bus radial rural electrification networks using MATLAB software.","PeriodicalId":106496,"journal":{"name":"2019 1st International Conference on Advanced Technologies in Intelligent Control, Environment, Computing & Communication Engineering (ICATIECE)","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":"128632946","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/ICATIECE45860.2019.9063846
P. Shruthi
Certifying the quality of food product is the major concern of the country. The citizens of the country are recommended to use only quality assured products. The same thing need to be applied for the wine industry also. The quality of wine need to be assessed and it should be classified into different category based on the quality assessment. Data mining is the right approach to achieve this as it extracts the useful information by analyzing the data set. In this paper, the samples of different wines with their attributes required for quality assurance is collected and different data mining classification algorithms- Naive Bayes, Simple Logistic, KStar, JRip, J48 are applied on it. The wine will be classified into three main categories and the accuracy of the algorithms are compared.
{"title":"Wine Quality Prediction Using Data Mining","authors":"P. Shruthi","doi":"10.1109/ICATIECE45860.2019.9063846","DOIUrl":"https://doi.org/10.1109/ICATIECE45860.2019.9063846","url":null,"abstract":"Certifying the quality of food product is the major concern of the country. The citizens of the country are recommended to use only quality assured products. The same thing need to be applied for the wine industry also. The quality of wine need to be assessed and it should be classified into different category based on the quality assessment. Data mining is the right approach to achieve this as it extracts the useful information by analyzing the data set. In this paper, the samples of different wines with their attributes required for quality assurance is collected and different data mining classification algorithms- Naive Bayes, Simple Logistic, KStar, JRip, J48 are applied on it. The wine will be classified into three main categories and the accuracy of the algorithms are compared.","PeriodicalId":106496,"journal":{"name":"2019 1st International Conference on Advanced Technologies in Intelligent Control, Environment, Computing & Communication Engineering (ICATIECE)","volume":"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":"125857080","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/ICATIECE45860.2019.9063797
Rajendra Prasad Patil, Nawaz A. Shariff, M. Kusuma
Brain-Computer Interface enables interaction between the human brain and the computer (any computing device). This facilitates to create an application and to interact with the surrounding environment. The use of dry electrodes helped to capture brain signals non-invasively and designing application would be easy as it does not involve the preparation of the subject or individual. This paper shows the experience in designing and developing application prototype using BCI framework and brain signals. The application involves capturing of eye events signals which are then used to control the application. Furthermore, Neurosky Mind-wave Headset, which is an electroencephalograph (EEG) recording device available in the market is used to measure brain activity using one strategically placed dry electrode sensor. Brain activity is recorded non-invasively and is sufficient to control the application.
{"title":"Brain-Computer Interface: Text Reader for Paralyzed Patients","authors":"Rajendra Prasad Patil, Nawaz A. Shariff, M. Kusuma","doi":"10.1109/ICATIECE45860.2019.9063797","DOIUrl":"https://doi.org/10.1109/ICATIECE45860.2019.9063797","url":null,"abstract":"Brain-Computer Interface enables interaction between the human brain and the computer (any computing device). This facilitates to create an application and to interact with the surrounding environment. The use of dry electrodes helped to capture brain signals non-invasively and designing application would be easy as it does not involve the preparation of the subject or individual. This paper shows the experience in designing and developing application prototype using BCI framework and brain signals. The application involves capturing of eye events signals which are then used to control the application. Furthermore, Neurosky Mind-wave Headset, which is an electroencephalograph (EEG) recording device available in the market is used to measure brain activity using one strategically placed dry electrode sensor. Brain activity is recorded non-invasively and is sufficient to control the application.","PeriodicalId":106496,"journal":{"name":"2019 1st International Conference on Advanced Technologies in Intelligent Control, Environment, Computing & Communication Engineering (ICATIECE)","volume":"2 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":"117074376","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}
Microarray is an important tool and powerful technique that is used to analyze the expression of DNA in organisms for large scale gene sequences and gene expressions. Microarray technology allows massively parallel, high throughput profiling of gene expression in a single hybridization experiment. Processing of microarray images provides the input for further analysis of the extracted microarray data. This work deals on the basic principles on the methods used to grid an image. Gridding has become a prominent objective in microarray image analysis. To grid an image various methods such as grid alignment, sub grid detection, Bayesian Model, hill climbing approach, genetic algorithm and optimal multilevel thresholding has been taken for this study. This paper focuses on the various methods that are widely used to grid the image.
{"title":"A Review on Gridding Techniques of Microarray Images","authors":"Karthik Sa, Manjunath Ss, Prakyath Dp, Prashanth S, Vamshi Krishna, Siddartha","doi":"10.1109/ICATIECE45860.2019.9063822","DOIUrl":"https://doi.org/10.1109/ICATIECE45860.2019.9063822","url":null,"abstract":"Microarray is an important tool and powerful technique that is used to analyze the expression of DNA in organisms for large scale gene sequences and gene expressions. Microarray technology allows massively parallel, high throughput profiling of gene expression in a single hybridization experiment. Processing of microarray images provides the input for further analysis of the extracted microarray data. This work deals on the basic principles on the methods used to grid an image. Gridding has become a prominent objective in microarray image analysis. To grid an image various methods such as grid alignment, sub grid detection, Bayesian Model, hill climbing approach, genetic algorithm and optimal multilevel thresholding has been taken for this study. This paper focuses on the various methods that are widely used to grid the image.","PeriodicalId":106496,"journal":{"name":"2019 1st International Conference on Advanced Technologies in Intelligent Control, Environment, Computing & Communication Engineering (ICATIECE)","volume":"45 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":"121498968","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/ICATIECE45860.2019.9063773
K. S, Neela R R, S. M., Madhuchandra, H. K
A system of interrelated computing devices, mechanical, and digital machines that are provided with the ability to transfer data over a network without requiring human interaction constitutes Internet of Things. This brings out automation of things. It is achieved through sensor and actuator devices. This paper brings out a survey on various sensors and actuator which is used in the implementation of Smart Cradle.
{"title":"Analysis on IoT Based Smart Cradle System with an Android Application for Baby Monitoring","authors":"K. S, Neela R R, S. M., Madhuchandra, H. K","doi":"10.1109/ICATIECE45860.2019.9063773","DOIUrl":"https://doi.org/10.1109/ICATIECE45860.2019.9063773","url":null,"abstract":"A system of interrelated computing devices, mechanical, and digital machines that are provided with the ability to transfer data over a network without requiring human interaction constitutes Internet of Things. This brings out automation of things. It is achieved through sensor and actuator devices. This paper brings out a survey on various sensors and actuator which is used in the implementation of Smart Cradle.","PeriodicalId":106496,"journal":{"name":"2019 1st International Conference on Advanced Technologies in Intelligent Control, Environment, Computing & Communication Engineering (ICATIECE)","volume":"126 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":"116094406","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/ICATIECE45860.2019.9063781
D. Tl, Vijayalakshmi Mn, A. S
Forest fire is a natural calamity which causes immense loss to the ecology. The high severity fire causes most loss to the vegetation. So this fire has to be detected within forest region in order to save vegetation. Currently frameworks are available with the image processing system which does analysis over the static forest fire image which provides information of fire hot spots. The fire motion/movement analysis with forest zone analysis is a challenging task with such static images. This problem can be solved with continuous monitoring of the fire with videos. Hence proposed framework provides novel forest fire flame movement analysis system based on spatiotemporal features using videos.
{"title":"Speculation of Forest Fire Using Spatial and Video Data","authors":"D. Tl, Vijayalakshmi Mn, A. S","doi":"10.1109/ICATIECE45860.2019.9063781","DOIUrl":"https://doi.org/10.1109/ICATIECE45860.2019.9063781","url":null,"abstract":"Forest fire is a natural calamity which causes immense loss to the ecology. The high severity fire causes most loss to the vegetation. So this fire has to be detected within forest region in order to save vegetation. Currently frameworks are available with the image processing system which does analysis over the static forest fire image which provides information of fire hot spots. The fire motion/movement analysis with forest zone analysis is a challenging task with such static images. This problem can be solved with continuous monitoring of the fire with videos. Hence proposed framework provides novel forest fire flame movement analysis system based on spatiotemporal features using videos.","PeriodicalId":106496,"journal":{"name":"2019 1st International Conference on Advanced Technologies in Intelligent Control, Environment, Computing & Communication Engineering (ICATIECE)","volume":"60 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":"121681392","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/ICATIECE45860.2019.9063615
K. J. Ghanashyam, Vatsala G A, A. Chaturvedi
In this mechanical life, each work is associated with the more than one goal which leads to the different multi decision model. In this rational world garbage is predominant problem which is faced by all country especially developing nations like India. The primary goal of this paper is to give a complete optimal solution for the wet garbage recycling plants such as bio methanation plant and compost plant. In this study, we designed a progressive Goal Programming model for fiscal management of wet garbage recycling plant at the apartment level. We discus about wet garbage compost plant and the optimal management of production of compost with the minimum usage of resources. Next, we took a wet garbage biogas plant for the study which produces the methane gas which can be used for lightings of apartment utility area which can save the electricity and to use the gas for cooking purpose also optimal management of production of the biogas. we have given this goal programming model for the fiscal management which can reduce the cost of maintenance in the apartments by minimizing the budget allocation to the maintain the compost production plant and biogas production plant.
{"title":"A Complete Optimal Solution for the Wet Garbage Recycling Plant in Apartments Cluster by Radical Multi-Objective Decision Model","authors":"K. J. Ghanashyam, Vatsala G A, A. Chaturvedi","doi":"10.1109/ICATIECE45860.2019.9063615","DOIUrl":"https://doi.org/10.1109/ICATIECE45860.2019.9063615","url":null,"abstract":"In this mechanical life, each work is associated with the more than one goal which leads to the different multi decision model. In this rational world garbage is predominant problem which is faced by all country especially developing nations like India. The primary goal of this paper is to give a complete optimal solution for the wet garbage recycling plants such as bio methanation plant and compost plant. In this study, we designed a progressive Goal Programming model for fiscal management of wet garbage recycling plant at the apartment level. We discus about wet garbage compost plant and the optimal management of production of compost with the minimum usage of resources. Next, we took a wet garbage biogas plant for the study which produces the methane gas which can be used for lightings of apartment utility area which can save the electricity and to use the gas for cooking purpose also optimal management of production of the biogas. we have given this goal programming model for the fiscal management which can reduce the cost of maintenance in the apartments by minimizing the budget allocation to the maintain the compost production plant and biogas production plant.","PeriodicalId":106496,"journal":{"name":"2019 1st International Conference on Advanced Technologies in Intelligent Control, Environment, Computing & Communication Engineering (ICATIECE)","volume":"13 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":"132577075","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/ICATIECE45860.2019.9063836
S. Jahnavi, C. Nandini
Privacy and security are two pivotal rights in day-to-day life. At present, keys, passwords and PIN’s are used to secure the confidential data. However the above mentioned methods can be compromised and thus propose threats to security. This paper provides an advanced method to enhance the security system using face detection and recognition algorithms integrated with raspberry pi that is used to control the access to the door. Since face is indubitably related to an individual, it cannot be duplicated. This paper consists of three subsystems-Face detection, Feature extraction and Face recognition for door access. Initially the system is trained with authorized persons features, stored in the database. Firstly, the process is started by capturing the image of an object using raspberry pi camera followed by face detection done using Viola Jones algorithm as it provides a greater accuracy in real-time object detection. Next the feature extraction and face detection is done using Local Binary Pattern (LBP) algorithm that can extract local neighboring texture information of grey scale image and can efficiently differentiate between object and background. The extracted features are dimensionally reduced using Principal Component Analysis (PCA) algorithm .The detected face is compared against the stored features and if there is a match the access is provided to the authorized person. If not, the access to the door is denied and an alarm is raised alerting the admin.
{"title":"Smart Anti-Theft Door locking System","authors":"S. Jahnavi, C. Nandini","doi":"10.1109/ICATIECE45860.2019.9063836","DOIUrl":"https://doi.org/10.1109/ICATIECE45860.2019.9063836","url":null,"abstract":"Privacy and security are two pivotal rights in day-to-day life. At present, keys, passwords and PIN’s are used to secure the confidential data. However the above mentioned methods can be compromised and thus propose threats to security. This paper provides an advanced method to enhance the security system using face detection and recognition algorithms integrated with raspberry pi that is used to control the access to the door. Since face is indubitably related to an individual, it cannot be duplicated. This paper consists of three subsystems-Face detection, Feature extraction and Face recognition for door access. Initially the system is trained with authorized persons features, stored in the database. Firstly, the process is started by capturing the image of an object using raspberry pi camera followed by face detection done using Viola Jones algorithm as it provides a greater accuracy in real-time object detection. Next the feature extraction and face detection is done using Local Binary Pattern (LBP) algorithm that can extract local neighboring texture information of grey scale image and can efficiently differentiate between object and background. The extracted features are dimensionally reduced using Principal Component Analysis (PCA) algorithm .The detected face is compared against the stored features and if there is a match the access is provided to the authorized person. If not, the access to the door is denied and an alarm is raised alerting the admin.","PeriodicalId":106496,"journal":{"name":"2019 1st International Conference on Advanced Technologies in Intelligent Control, Environment, Computing & Communication Engineering (ICATIECE)","volume":"28 4 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":"131377525","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/ICATIECE45860.2019.9063816
B. Roopa, R. Manjunatha Prasad
Autism Spectrum Disorder (ASD) is highly complicated neurodevelopment disorder whose increasing prevalence is 1 in 68 individuals (survey of Centers for Disease Control and Preventions). There are various influential’s for ASD. The root cause is not known predominantly even today. But the state of the art of autism in research is, due to autism risk genes showcasing structural & functional brain differences and behavioral features of ASD. Some of the key measuring tools which are multifaceted indicators help to diagnose autism are like: 1.Physiological Detection (emotion assessment from autistic individual), which uses 4 Physiological signals namely electrocardiogram (ECG), skin conductance (SC), respiration and skin temperature. Outcomes were addressed by rating on three scales: arousal, valance and dominance. This approach is non invasive and economical. 2. Exploring the network connectivity in brain, the magnetic resonance imaging (MRI) and functional magnetic resonance imaging (f-MRI) fetches a non invasive approach to map the ordinal patterns of interaction in brain regions to better understand the pathology. 3. Most common machine learning classifier applied to diagnose ASD is Support vector machine (SVM) algorithm. The further implication of Robust SVM (variant of the single SVM) in research progress has improved the accuracy of diagnosing ASD from control group (CG). 4. Last but not the least Deep learning models helps in building model of profound classification accuracy. Early and accurate diagnosis of ASD intensity level leading to selection of correct treatment procedures and thus helps the autistic individual to undergo worth therapies or other relevant treatments.
{"title":"Concatenating framework in ASD analysis towards research progress","authors":"B. Roopa, R. Manjunatha Prasad","doi":"10.1109/ICATIECE45860.2019.9063816","DOIUrl":"https://doi.org/10.1109/ICATIECE45860.2019.9063816","url":null,"abstract":"Autism Spectrum Disorder (ASD) is highly complicated neurodevelopment disorder whose increasing prevalence is 1 in 68 individuals (survey of Centers for Disease Control and Preventions). There are various influential’s for ASD. The root cause is not known predominantly even today. But the state of the art of autism in research is, due to autism risk genes showcasing structural & functional brain differences and behavioral features of ASD. Some of the key measuring tools which are multifaceted indicators help to diagnose autism are like: 1.Physiological Detection (emotion assessment from autistic individual), which uses 4 Physiological signals namely electrocardiogram (ECG), skin conductance (SC), respiration and skin temperature. Outcomes were addressed by rating on three scales: arousal, valance and dominance. This approach is non invasive and economical. 2. Exploring the network connectivity in brain, the magnetic resonance imaging (MRI) and functional magnetic resonance imaging (f-MRI) fetches a non invasive approach to map the ordinal patterns of interaction in brain regions to better understand the pathology. 3. Most common machine learning classifier applied to diagnose ASD is Support vector machine (SVM) algorithm. The further implication of Robust SVM (variant of the single SVM) in research progress has improved the accuracy of diagnosing ASD from control group (CG). 4. Last but not the least Deep learning models helps in building model of profound classification accuracy. Early and accurate diagnosis of ASD intensity level leading to selection of correct treatment procedures and thus helps the autistic individual to undergo worth therapies or other relevant treatments.","PeriodicalId":106496,"journal":{"name":"2019 1st International Conference on Advanced Technologies in Intelligent Control, Environment, Computing & Communication Engineering (ICATIECE)","volume":"29 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":"131589349","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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