Pub Date : 2018-10-01DOI: 10.1109/ICIIBMS.2018.8550029
Chen Nan, Song Zhi-Li
Aiming at how to accurately position the UAV in the environmental safety monitoring, a new positioning and navigation method is proposed in this paper. This method can make good use of the regional landmark features to realize the precise positioning and navigation of the UAV. The method can comprehensively utilize the point feature of the image and the image contour feature to perform image matching, and overcomes the deficiencies of the unilateral only through the contour feature or the point feature matching, thereby forming a new landmark feature registration method. Experiments show that the method has certain robustness and stability, and it is improved in efficiency and accuracy when applied to environmental safety monitoring and detection.
{"title":"Application of UAV Precise Navigation in Environmental Safety Monitoring and Detection","authors":"Chen Nan, Song Zhi-Li","doi":"10.1109/ICIIBMS.2018.8550029","DOIUrl":"https://doi.org/10.1109/ICIIBMS.2018.8550029","url":null,"abstract":"Aiming at how to accurately position the UAV in the environmental safety monitoring, a new positioning and navigation method is proposed in this paper. This method can make good use of the regional landmark features to realize the precise positioning and navigation of the UAV. The method can comprehensively utilize the point feature of the image and the image contour feature to perform image matching, and overcomes the deficiencies of the unilateral only through the contour feature or the point feature matching, thereby forming a new landmark feature registration method. Experiments show that the method has certain robustness and stability, and it is improved in efficiency and accuracy when applied to environmental safety monitoring and detection.","PeriodicalId":430326,"journal":{"name":"2018 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130109590","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 : 2018-10-01DOI: 10.1109/ICIIBMS.2018.8549988
Naw Thiri Wai Khin, Nyo Nyo Yee
Information Retrieval (IR) system finds the relevant documents from a large dataset according to the user query. Queries submitted by users to search engines might be ambiguous, concise and their meaning may change over time. As a result, understanding the nature of information that is needed behind the queries has become an important research problem. So, various search engines emphasize the web query classification. For the efficient IR system, this system proposes the Web Query Classification Algorithm (WQCA) by using NoSQL graph database. This system classifies the web queries into each characteristic and each predefined target categories. In web query classification, the input query is first classified into web search taxonomies (characteristics). Then, domain terms are extracted from the query, and each of them is classified into their relevant categories that are stored in the NoSQL database. By using categories from WQCA, this system finds the relevant document from the document collection. The vector space IR model is used in this system to retrieve the relevant document.
{"title":"Query Classification based Information Retrieval System","authors":"Naw Thiri Wai Khin, Nyo Nyo Yee","doi":"10.1109/ICIIBMS.2018.8549988","DOIUrl":"https://doi.org/10.1109/ICIIBMS.2018.8549988","url":null,"abstract":"Information Retrieval (IR) system finds the relevant documents from a large dataset according to the user query. Queries submitted by users to search engines might be ambiguous, concise and their meaning may change over time. As a result, understanding the nature of information that is needed behind the queries has become an important research problem. So, various search engines emphasize the web query classification. For the efficient IR system, this system proposes the Web Query Classification Algorithm (WQCA) by using NoSQL graph database. This system classifies the web queries into each characteristic and each predefined target categories. In web query classification, the input query is first classified into web search taxonomies (characteristics). Then, domain terms are extracted from the query, and each of them is classified into their relevant categories that are stored in the NoSQL database. By using categories from WQCA, this system finds the relevant document from the document collection. The vector space IR model is used in this system to retrieve the relevant document.","PeriodicalId":430326,"journal":{"name":"2018 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123717259","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 : 2018-10-01DOI: 10.1109/ICIIBMS.2018.8549920
Kreadtisak Lappanitchayakul
The developed network monitoring system detected and alerted the abnormality of appliances in the network of Rajamangala University of Technology Phra Nakhon by applying ICMP Protocol (Ping). Moreover, the developed system displayed the connection status of network appliance and record of appliance connection on a website so it was easy to monitor and caution the possible problems. When the network monitoring system detected the abnormality in the network connection, it sent E-mail and SMS alert to the system administrator to make him aware of the location of abnormal appliance and fix the problem. Further, the developed system facilitated the system administrator to check the connection record of the appliance in the system to set the preventive plan.
{"title":"Development of Email and SMS Based Notification System to Detect Abnormal Network Conditions: A Case Study of Faculty of Business Administration, Rajamangala University of Technology Phra Nakhon, Thailand","authors":"Kreadtisak Lappanitchayakul","doi":"10.1109/ICIIBMS.2018.8549920","DOIUrl":"https://doi.org/10.1109/ICIIBMS.2018.8549920","url":null,"abstract":"The developed network monitoring system detected and alerted the abnormality of appliances in the network of Rajamangala University of Technology Phra Nakhon by applying ICMP Protocol (Ping). Moreover, the developed system displayed the connection status of network appliance and record of appliance connection on a website so it was easy to monitor and caution the possible problems. When the network monitoring system detected the abnormality in the network connection, it sent E-mail and SMS alert to the system administrator to make him aware of the location of abnormal appliance and fix the problem. Further, the developed system facilitated the system administrator to check the connection record of the appliance in the system to set the preventive plan.","PeriodicalId":430326,"journal":{"name":"2018 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116056826","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 : 2018-10-01DOI: 10.1109/ICIIBMS.2018.8550014
A. Bakshi, Arjun Bakshi
This paper illustrates a cost and energy efficient technique for navigating a visually impaired user through an obstacle ridden path. It analyses the most suitable sensors and their performance regarding the specific application. A control unit processes various sensor inputs relating obstacle's distance and spatial information, and provides a 3D sensory stimulus to the user by means of vibrating motors. With the sensory stimulus the user is able to predict the obstacles and navigate through them without collisions. The technique proposed is ergonomic and economic. Thus, it can provide an affordable aid to visually impaired users. The testing has been implemented using ultrasonic sensors, Arduino mini microcontroller and vibrator motors. The technique was successfully implemented by blind folding the subject (user) to record the results. (Abstract)
{"title":"Energy and Cost Efficient Navigation Technique for the Visually Impaired","authors":"A. Bakshi, Arjun Bakshi","doi":"10.1109/ICIIBMS.2018.8550014","DOIUrl":"https://doi.org/10.1109/ICIIBMS.2018.8550014","url":null,"abstract":"This paper illustrates a cost and energy efficient technique for navigating a visually impaired user through an obstacle ridden path. It analyses the most suitable sensors and their performance regarding the specific application. A control unit processes various sensor inputs relating obstacle's distance and spatial information, and provides a 3D sensory stimulus to the user by means of vibrating motors. With the sensory stimulus the user is able to predict the obstacles and navigate through them without collisions. The technique proposed is ergonomic and economic. Thus, it can provide an affordable aid to visually impaired users. The testing has been implemented using ultrasonic sensors, Arduino mini microcontroller and vibrator motors. The technique was successfully implemented by blind folding the subject (user) to record the results. (Abstract)","PeriodicalId":430326,"journal":{"name":"2018 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115276679","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 : 2018-10-01DOI: 10.1109/ICIIBMS.2018.8549931
Kyi PyarWin, Y. Kitjaidure
This paper proposes a system for biomedical images stitching using feature based approach. The proposed system aims to stitch the high resolution images with low processing time. The proposed system is designed with five stages., preprocessing., features extraction., features matching., homography estimation and images stitching. In feature detection stage., ORB feature based approach is used. The proposed method is improved in term of performance and accuracy. The proposed method was compared with many different features detectors., Harris corner detector., SIFT and SURF techniques. According to the experiments., ORB method had the better results than the other feature based methods in the detection rate of the corrected keypoints and processing time.
{"title":"Biomedical Images Stitching using ORB Feature Based Approach","authors":"Kyi PyarWin, Y. Kitjaidure","doi":"10.1109/ICIIBMS.2018.8549931","DOIUrl":"https://doi.org/10.1109/ICIIBMS.2018.8549931","url":null,"abstract":"This paper proposes a system for biomedical images stitching using feature based approach. The proposed system aims to stitch the high resolution images with low processing time. The proposed system is designed with five stages., preprocessing., features extraction., features matching., homography estimation and images stitching. In feature detection stage., ORB feature based approach is used. The proposed method is improved in term of performance and accuracy. The proposed method was compared with many different features detectors., Harris corner detector., SIFT and SURF techniques. According to the experiments., ORB method had the better results than the other feature based methods in the detection rate of the corrected keypoints and processing time.","PeriodicalId":430326,"journal":{"name":"2018 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"46 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120955465","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 : 2018-10-01DOI: 10.1109/ICIIBMS.2018.8549936
S. Tansuriyavong, Hideto Koja, Motoki Kyan, T. Anezaki
In recent year, damaging crops by wildlife is becoming serious all over the country. On the other hand, unmanned aerial vehicle systems such as GPS, communication technology and drone have been further developed, and it is becoming possible to develop an automatic tracking system that accurately grasps the position of wildlife. Therefore, in this research, to elucidate the ecology and behavioral characteristics of wildlife, we aim to develop an automatic tracking system using drone. From the experimental results, it was confirmed that the GPS tracking by the drone is possible by sending a command using the mobile phone communication network. In this paper, we report about these details.
{"title":"The Development of Wildlife Tracking System Using Mobile Phone Communication Network and Drone","authors":"S. Tansuriyavong, Hideto Koja, Motoki Kyan, T. Anezaki","doi":"10.1109/ICIIBMS.2018.8549936","DOIUrl":"https://doi.org/10.1109/ICIIBMS.2018.8549936","url":null,"abstract":"In recent year, damaging crops by wildlife is becoming serious all over the country. On the other hand, unmanned aerial vehicle systems such as GPS, communication technology and drone have been further developed, and it is becoming possible to develop an automatic tracking system that accurately grasps the position of wildlife. Therefore, in this research, to elucidate the ecology and behavioral characteristics of wildlife, we aim to develop an automatic tracking system using drone. From the experimental results, it was confirmed that the GPS tracking by the drone is possible by sending a command using the mobile phone communication network. In this paper, we report about these details.","PeriodicalId":430326,"journal":{"name":"2018 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116733916","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 : 2018-10-01DOI: 10.1109/ICIIBMS.2018.8549993
Y. Wan-jun, Wang Jian, Zhao Huai-lin
In order to solve the shortcomings of coal mine enterprises in gas safety management, according to the big data theory, a safety management analysis method is proposed. First, the behavioral safety theory is used to classify the causes of gas hazards. Then use the HDFS to storage the unsafe behavior and unsafe physical state that found by behavior observers, and finally use the MapReduce-based parallel FP-growth algorithm to find out the repeated and dangerous unsafe behaviors in daily operations, and form a Hadoop-based gas behavior security management model. The experimental results show that the model has certain practical reference value for the targeted implementation of gas safety management in coal mine enterprises. Through the unsafe behavior and physical state found, the shortcomings in safety management will be discover, it will help enterprises improve the safety management system. So it has certain prospects for improving the safety production culture of coal mine enterprises and reducing the occurrence of gas accidents.
{"title":"Research on Risk Management of Gas Safety based on Big Data","authors":"Y. Wan-jun, Wang Jian, Zhao Huai-lin","doi":"10.1109/ICIIBMS.2018.8549993","DOIUrl":"https://doi.org/10.1109/ICIIBMS.2018.8549993","url":null,"abstract":"In order to solve the shortcomings of coal mine enterprises in gas safety management, according to the big data theory, a safety management analysis method is proposed. First, the behavioral safety theory is used to classify the causes of gas hazards. Then use the HDFS to storage the unsafe behavior and unsafe physical state that found by behavior observers, and finally use the MapReduce-based parallel FP-growth algorithm to find out the repeated and dangerous unsafe behaviors in daily operations, and form a Hadoop-based gas behavior security management model. The experimental results show that the model has certain practical reference value for the targeted implementation of gas safety management in coal mine enterprises. Through the unsafe behavior and physical state found, the shortcomings in safety management will be discover, it will help enterprises improve the safety management system. So it has certain prospects for improving the safety production culture of coal mine enterprises and reducing the occurrence of gas accidents.","PeriodicalId":430326,"journal":{"name":"2018 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134221702","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 : 2018-10-01DOI: 10.1109/ICIIBMS.2018.8549972
Ray X. Lee, B. Kuhn
Outside from any behavioral task, animals irregularly initiate, keep, and suspend various behaviors in a homogenous and steady environment. The underlying neuronal dynamics for generating, maintaining, and terminating these spontanoues behaviors remain unclear. We approached this challenge by investigating neuronal population activity across cerebral cortical layers and areas using two-photon calcium imaging in head-restrained mice. We show that two distinct control mechanisms of neurobehavioral association employed in producing dynamic patterns of spontaneous behaviors. Our discovery in spontaneous behaviors potentially provides a fundamental and general framework for understanding the brain computations in a broader behavioral context.
{"title":"Neuronal Dynamic Framework of Cerebral Cortical Networks for Spontaneous Behaviors","authors":"Ray X. Lee, B. Kuhn","doi":"10.1109/ICIIBMS.2018.8549972","DOIUrl":"https://doi.org/10.1109/ICIIBMS.2018.8549972","url":null,"abstract":"Outside from any behavioral task, animals irregularly initiate, keep, and suspend various behaviors in a homogenous and steady environment. The underlying neuronal dynamics for generating, maintaining, and terminating these spontanoues behaviors remain unclear. We approached this challenge by investigating neuronal population activity across cerebral cortical layers and areas using two-photon calcium imaging in head-restrained mice. We show that two distinct control mechanisms of neurobehavioral association employed in producing dynamic patterns of spontaneous behaviors. Our discovery in spontaneous behaviors potentially provides a fundamental and general framework for understanding the brain computations in a broader behavioral context.","PeriodicalId":430326,"journal":{"name":"2018 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114795685","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 : 2018-10-01DOI: 10.1109/ICIIBMS.2018.8550025
J. Ravikumar, A. Ramachandra, K. Raja, V. R.
Physiological face biometric trait is used to identify a person for many real time applications. The convolution based feature extraction technique for face identification using Discrete Wavelet Transform (DWT) and Histogram of Oriented Gradient (HOG) is proposed to recognize human beings effectively. The four standard face databases with different sizes are considered and resized to $128mathrm{X}128$ to have uniform size of images. The 2D-DWT (Two Dimensional Discrete Wavelet Transform) is applied on resized face images and considered only (LL) sub-band. The HOG is applied on LL subband to obtain HOG coefficients. The 2D convolution is used on LL sub-band and HOG matrix to obtain final features. The resized face image is compressed using DWT and HOG. The Euclidean distance(ED) is used to compare features of database face images with test images to compute performance parameters. The performance of the proposed method is better than the existing methods.
{"title":"Convolution Based Face Recognition Using DWT and HOG","authors":"J. Ravikumar, A. Ramachandra, K. Raja, V. R.","doi":"10.1109/ICIIBMS.2018.8550025","DOIUrl":"https://doi.org/10.1109/ICIIBMS.2018.8550025","url":null,"abstract":"Physiological face biometric trait is used to identify a person for many real time applications. The convolution based feature extraction technique for face identification using Discrete Wavelet Transform (DWT) and Histogram of Oriented Gradient (HOG) is proposed to recognize human beings effectively. The four standard face databases with different sizes are considered and resized to $128mathrm{X}128$ to have uniform size of images. The 2D-DWT (Two Dimensional Discrete Wavelet Transform) is applied on resized face images and considered only (LL) sub-band. The HOG is applied on LL subband to obtain HOG coefficients. The 2D convolution is used on LL sub-band and HOG matrix to obtain final features. The resized face image is compressed using DWT and HOG. The Euclidean distance(ED) is used to compare features of database face images with test images to compute performance parameters. The performance of the proposed method is better than the existing methods.","PeriodicalId":430326,"journal":{"name":"2018 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124688274","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 : 2018-10-01DOI: 10.1109/ICIIBMS.2018.8550026
Md. Yousuf Hossain, Fabian Parsia George
At present time, drowsy driving has become one of the major issues of the traffic collision. According to statistics, a large number of road accidents occur due to drowsy driving which results in severe injuries and deaths. For this reason, various studies were done in designing systems that can examine the driver fatigue and alert him beforehand, thus preventing him to fall asleep behind the wheel and cause an accident. Some traditional approaches used vehicle-based measures to design their system, however, such measurements are highly influenced by the structure of the road, type of vehicle and the driving skill. Other approaches used psychological measures for their system that tend to provide better accuracy in monitoring the drowsiness of the driver. However, such techniques are usually intrusive as electrodes are required to be placed on the head and body. Furthermore, there are few existing researches in which subjective measurements are used as the input for the system, but, such methods can distract the driver and lead to an ambiguous result. In this paper, we proposed a system that is absolutely nonintrusive and real-time. Our proposed system used the eye closure ratio as input parameter to detect the drowsiness of the driver. If the eye closure ratio deteriorates from the standard ratio, the driver is alerted with the help of a buzzer. For our system, a Pi camera is used to capture the images of the driver's eye and the entire system is incorporated using Raspberry-Pi.
{"title":"IOT Based Real-Time Drowsy Driving Detection System for the Prevention of Road Accidents","authors":"Md. Yousuf Hossain, Fabian Parsia George","doi":"10.1109/ICIIBMS.2018.8550026","DOIUrl":"https://doi.org/10.1109/ICIIBMS.2018.8550026","url":null,"abstract":"At present time, drowsy driving has become one of the major issues of the traffic collision. According to statistics, a large number of road accidents occur due to drowsy driving which results in severe injuries and deaths. For this reason, various studies were done in designing systems that can examine the driver fatigue and alert him beforehand, thus preventing him to fall asleep behind the wheel and cause an accident. Some traditional approaches used vehicle-based measures to design their system, however, such measurements are highly influenced by the structure of the road, type of vehicle and the driving skill. Other approaches used psychological measures for their system that tend to provide better accuracy in monitoring the drowsiness of the driver. However, such techniques are usually intrusive as electrodes are required to be placed on the head and body. Furthermore, there are few existing researches in which subjective measurements are used as the input for the system, but, such methods can distract the driver and lead to an ambiguous result. In this paper, we proposed a system that is absolutely nonintrusive and real-time. Our proposed system used the eye closure ratio as input parameter to detect the drowsiness of the driver. If the eye closure ratio deteriorates from the standard ratio, the driver is alerted with the help of a buzzer. For our system, a Pi camera is used to capture the images of the driver's eye and the entire system is incorporated using Raspberry-Pi.","PeriodicalId":430326,"journal":{"name":"2018 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122185582","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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