Pub Date : 2017-11-01DOI: 10.1109/ICIIBMS.2017.8279712
Y. Liu, Hao Wu
Based on the random forest classification algorithm, a warning model of water bloom is proposed. Using the collected data, Select the water quality, meteorological factors which like Chlorophyll a (Chl-a), water temperature (T), PH, nitrogen and phosphorus ratio (TN:TP), chemical oxygen demand (COD), total nitrogen (TN), total phosphorus (TP), dissolved oxygen Light (E) and so on as the impact factor and use them establish a warning model for Water bloom. And compared with the prediction accuracy of neural network model and SVM model. The results show that the water bloom warning model is established by using stochastic forest classification algorithm, the prediction accuracy is slightly higher than other algorithms. And the random forest algorithm has the characteristics of high robustness, China good performance, strong practicability, can effectively carry out water bloom early warning.
{"title":"Water bloom warning model based on random forest","authors":"Y. Liu, Hao Wu","doi":"10.1109/ICIIBMS.2017.8279712","DOIUrl":"https://doi.org/10.1109/ICIIBMS.2017.8279712","url":null,"abstract":"Based on the random forest classification algorithm, a warning model of water bloom is proposed. Using the collected data, Select the water quality, meteorological factors which like Chlorophyll a (Chl-a), water temperature (T), PH, nitrogen and phosphorus ratio (TN:TP), chemical oxygen demand (COD), total nitrogen (TN), total phosphorus (TP), dissolved oxygen Light (E) and so on as the impact factor and use them establish a warning model for Water bloom. And compared with the prediction accuracy of neural network model and SVM model. The results show that the water bloom warning model is established by using stochastic forest classification algorithm, the prediction accuracy is slightly higher than other algorithms. And the random forest algorithm has the characteristics of high robustness, China good performance, strong practicability, can effectively carry out water bloom early warning.","PeriodicalId":122969,"journal":{"name":"2017 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123118332","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 : 2017-11-01DOI: 10.1109/ICIIBMS.2017.8279683
Anilkumar Kothalil Gopalakrishnan
This paper presents a Recommended Weight Prediction System (RWPS) to be used in predicting the number of days needed for a person to attain a normal weight state based on his or her Body Mass Index (BMI), Basal Metabolic Rate (BMR), Daily Food calorie Intake (DFI) and a backpropagation neural network (BPNN). By using the BMI value, the system estimates the weight value of a person, where the individual with a normal BMI has a weight value of zero. Based on the BMR, the Daily Needed Calorie (DNC) of a person is calculated, and from the DNC, the weight value and the DFI, the number of days needed for a person to attain a “normal” BMI state could be predicted. The same could be applied when an underweight person under 30 years of age is being considered. The person in the later case would be checked for any eating disorders by the BPNN before applying the day prediction section of the system. The experimental results showed that the proposed approach could be an effective way for predicting any eating disorders and the number of days needed for a person to regain normal BMI.
{"title":"Recommended weight prediction system based on BMI, BMR, food calorie and a neural network","authors":"Anilkumar Kothalil Gopalakrishnan","doi":"10.1109/ICIIBMS.2017.8279683","DOIUrl":"https://doi.org/10.1109/ICIIBMS.2017.8279683","url":null,"abstract":"This paper presents a Recommended Weight Prediction System (RWPS) to be used in predicting the number of days needed for a person to attain a normal weight state based on his or her Body Mass Index (BMI), Basal Metabolic Rate (BMR), Daily Food calorie Intake (DFI) and a backpropagation neural network (BPNN). By using the BMI value, the system estimates the weight value of a person, where the individual with a normal BMI has a weight value of zero. Based on the BMR, the Daily Needed Calorie (DNC) of a person is calculated, and from the DNC, the weight value and the DFI, the number of days needed for a person to attain a “normal” BMI state could be predicted. The same could be applied when an underweight person under 30 years of age is being considered. The person in the later case would be checked for any eating disorders by the BPNN before applying the day prediction section of the system. The experimental results showed that the proposed approach could be an effective way for predicting any eating disorders and the number of days needed for a person to regain normal BMI.","PeriodicalId":122969,"journal":{"name":"2017 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117116017","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 : 2017-11-01DOI: 10.1109/ICIIBMS.2017.8279741
Eun-Young Lee, Myeong-Hyeon Heo, Dongho Kim
In this paper, we suggest a gait training system for the foot drop patients. The intent of this system is to control electrical stimulation pattern by utilizing the plantar pressure distributions as a source of the real-time gait event detection. The design of a prototype of the ankle-foot orthosis to test this concept is described. In the future, this gait assistive system could be an alternative rehabilitation device for the foot drop patients.
{"title":"Design of a pressure sensitive ankle-foot orthosis for FES-aided gait training","authors":"Eun-Young Lee, Myeong-Hyeon Heo, Dongho Kim","doi":"10.1109/ICIIBMS.2017.8279741","DOIUrl":"https://doi.org/10.1109/ICIIBMS.2017.8279741","url":null,"abstract":"In this paper, we suggest a gait training system for the foot drop patients. The intent of this system is to control electrical stimulation pattern by utilizing the plantar pressure distributions as a source of the real-time gait event detection. The design of a prototype of the ankle-foot orthosis to test this concept is described. In the future, this gait assistive system could be an alternative rehabilitation device for the foot drop patients.","PeriodicalId":122969,"journal":{"name":"2017 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122220970","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 : 2017-11-01DOI: 10.1299/JSMERMD.2017.2P1-G01
Keisuke Yoneda, Akisue Kuramoto, N. Suganuma
This Automated driving is an emerging technology in which a car performs recognition, decision making, and control. Recognizing surrounding vehicles is a key technology in order to generate a trajectory of ego vehicle. This paper is focused on detecting a turn signal information as one of the driver's intention for surrounding vehicles. Such information helps to predict their behavior in advance especially about lane change and turn left-or-right on intersection. Using their intension, the automated vehicle is able to generate the safety trajectory before they begin to change their behavior. The proposed method recognizes the turn signal for target vehicle based on mono-camera. It detects lighting state using Convolutional Neural Network, and then calculates a flashing frequency using Fast Fourier Transform.
{"title":"Convolutional neural network based vehicle turn signal recognition","authors":"Keisuke Yoneda, Akisue Kuramoto, N. Suganuma","doi":"10.1299/JSMERMD.2017.2P1-G01","DOIUrl":"https://doi.org/10.1299/JSMERMD.2017.2P1-G01","url":null,"abstract":"This Automated driving is an emerging technology in which a car performs recognition, decision making, and control. Recognizing surrounding vehicles is a key technology in order to generate a trajectory of ego vehicle. This paper is focused on detecting a turn signal information as one of the driver's intention for surrounding vehicles. Such information helps to predict their behavior in advance especially about lane change and turn left-or-right on intersection. Using their intension, the automated vehicle is able to generate the safety trajectory before they begin to change their behavior. The proposed method recognizes the turn signal for target vehicle based on mono-camera. It detects lighting state using Convolutional Neural Network, and then calculates a flashing frequency using Fast Fourier Transform.","PeriodicalId":122969,"journal":{"name":"2017 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116722130","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 : 2017-11-01DOI: 10.1109/ICIIBMS.2017.8279724
Jittima Wongwuttiwat, A. Lawanna
The size of test case reduction using test cases of the improved program is considered as a primary purpose of developing various regression test selections. This also concerns with fault avoidance that could be found from some test cases selections. This study focuses and compares the proficiency of solving these two problems using the three methods from previous studies; original regression test, code coverage based, and filtering-based selections; and a new proposed model. This model carries on five processes; 1) testing test suit and looking for passed or failed test cases, 2) correcting failures that can be restored, 3) categorizing all passed test cases into four areas: user, system, functional, and non-functional cases, 4) taking out irrelevant objects, 5) selecting the proper test case. The study found that the result of the size reduction using the proposed model is much larger than the existing methods by 2.49%-8.55%, while the percentage of avoiding faults using the existing algorithms are lower than the new proposed algorithm around 0.58%-2.36%.
{"title":"Performance improvement model of regression test selection","authors":"Jittima Wongwuttiwat, A. Lawanna","doi":"10.1109/ICIIBMS.2017.8279724","DOIUrl":"https://doi.org/10.1109/ICIIBMS.2017.8279724","url":null,"abstract":"The size of test case reduction using test cases of the improved program is considered as a primary purpose of developing various regression test selections. This also concerns with fault avoidance that could be found from some test cases selections. This study focuses and compares the proficiency of solving these two problems using the three methods from previous studies; original regression test, code coverage based, and filtering-based selections; and a new proposed model. This model carries on five processes; 1) testing test suit and looking for passed or failed test cases, 2) correcting failures that can be restored, 3) categorizing all passed test cases into four areas: user, system, functional, and non-functional cases, 4) taking out irrelevant objects, 5) selecting the proper test case. The study found that the result of the size reduction using the proposed model is much larger than the existing methods by 2.49%-8.55%, while the percentage of avoiding faults using the existing algorithms are lower than the new proposed algorithm around 0.58%-2.36%.","PeriodicalId":122969,"journal":{"name":"2017 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128360854","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 : 2017-11-01DOI: 10.1109/ICIIBMS.2017.8279695
K. Komoku, Takuya Emi, Tomoyuki Yokogawa, H. Yamauchi, Yoichiro Sato, Kazutami Arimoto, H. Takao
In this paper, a motion-tracking method that obtains the position (motion) information of each part of a running MEMS (Micro Electro Mechanical Systems) tactile sensor is proposed as the first step toward developing a material surface shape detection model. By observation and motion tracking with a high-speed camera, the motion information of each part of the sensor can be obtained, and the motion of the top of the contactor is acquired from the calculation. Results show that the top of the contactor follows the sample surface closely.
{"title":"Study of material surface shape detection model for MEMS tactile sensor by motion tracking","authors":"K. Komoku, Takuya Emi, Tomoyuki Yokogawa, H. Yamauchi, Yoichiro Sato, Kazutami Arimoto, H. Takao","doi":"10.1109/ICIIBMS.2017.8279695","DOIUrl":"https://doi.org/10.1109/ICIIBMS.2017.8279695","url":null,"abstract":"In this paper, a motion-tracking method that obtains the position (motion) information of each part of a running MEMS (Micro Electro Mechanical Systems) tactile sensor is proposed as the first step toward developing a material surface shape detection model. By observation and motion tracking with a high-speed camera, the motion information of each part of the sensor can be obtained, and the motion of the top of the contactor is acquired from the calculation. Results show that the top of the contactor follows the sample surface closely.","PeriodicalId":122969,"journal":{"name":"2017 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123811877","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 : 2017-11-01DOI: 10.1109/ICIIBMS.2017.8279685
Mitsuki Doi, O. Fukuda, H. Okumura, K. Arai
This study proposes and develops a consultive sales system with a communication robot. The verbal communication ability is implemented in the robot to enhance familiarity between the customer and the robot. The vocabulary is restricted to small number of items related to coffee sales, though. Three management functions are installed into the developed system, which are sales management function, sales strategy management function, inventory management function, respectively. The sales management function creates an Excel spreadsheet that records sales contents. The sales strategy management function determines the discount sales with an electronic lottery. And, the inventory management function sends e-mails to administrator before stocks of goods run out. The experiments were conducted and confirmed that the operation of each function was properly implemented.
{"title":"Consultive sales system with a communication robot","authors":"Mitsuki Doi, O. Fukuda, H. Okumura, K. Arai","doi":"10.1109/ICIIBMS.2017.8279685","DOIUrl":"https://doi.org/10.1109/ICIIBMS.2017.8279685","url":null,"abstract":"This study proposes and develops a consultive sales system with a communication robot. The verbal communication ability is implemented in the robot to enhance familiarity between the customer and the robot. The vocabulary is restricted to small number of items related to coffee sales, though. Three management functions are installed into the developed system, which are sales management function, sales strategy management function, inventory management function, respectively. The sales management function creates an Excel spreadsheet that records sales contents. The sales strategy management function determines the discount sales with an electronic lottery. And, the inventory management function sends e-mails to administrator before stocks of goods run out. The experiments were conducted and confirmed that the operation of each function was properly implemented.","PeriodicalId":122969,"journal":{"name":"2017 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"128 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121303517","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 : 2017-11-01DOI: 10.1109/ICIIBMS.2017.8279688
Daiki Yano, Mayuko Doi, M. Koeda, Kodai Okumoto, Shogo Yoshida, Katsuhiko Onishi, H. Noborio, Kaoru Watanabe
We are developing a surgical support system for liver abdominal surgery. In this research, an actual liver and virtual liver were registered, and the distance from the knife tip to the blood vessel of the mock organ was measured. The experimental results and verification of the accuracy are shown.
{"title":"Verification of accuracy of knife tip position estimation in liver surgery support system","authors":"Daiki Yano, Mayuko Doi, M. Koeda, Kodai Okumoto, Shogo Yoshida, Katsuhiko Onishi, H. Noborio, Kaoru Watanabe","doi":"10.1109/ICIIBMS.2017.8279688","DOIUrl":"https://doi.org/10.1109/ICIIBMS.2017.8279688","url":null,"abstract":"We are developing a surgical support system for liver abdominal surgery. In this research, an actual liver and virtual liver were registered, and the distance from the knife tip to the blood vessel of the mock organ was measured. The experimental results and verification of the accuracy are shown.","PeriodicalId":122969,"journal":{"name":"2017 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"148 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114004691","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 : 2017-11-01DOI: 10.1109/ICIIBMS.2017.8279691
Hyeongsuk Lee, Sukwha Kim, Jeongeun Kim, Jisan Lee, Ahjung Byun, Hyeongju Ryu, H. Kong
The purpose of this study was to investigate the essential elements and functions that should be included in a robot-based point-of-care service. The telepresence robot and the bedside robot were evaluated through simulation. The evaluators reported that two types of robots were feasible. Incorporating this technology into healthcare services will enhance communication and teamwork skills across distances, and will enhance the quality of inpatient hospital experiences.
{"title":"Assessment of user needs for the teleconsultation robot and the bedside robot using simulation","authors":"Hyeongsuk Lee, Sukwha Kim, Jeongeun Kim, Jisan Lee, Ahjung Byun, Hyeongju Ryu, H. Kong","doi":"10.1109/ICIIBMS.2017.8279691","DOIUrl":"https://doi.org/10.1109/ICIIBMS.2017.8279691","url":null,"abstract":"The purpose of this study was to investigate the essential elements and functions that should be included in a robot-based point-of-care service. The telepresence robot and the bedside robot were evaluated through simulation. The evaluators reported that two types of robots were feasible. Incorporating this technology into healthcare services will enhance communication and teamwork skills across distances, and will enhance the quality of inpatient hospital experiences.","PeriodicalId":122969,"journal":{"name":"2017 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131512877","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 : 2017-11-01DOI: 10.1109/ICIIBMS.2017.8279746
Kyunghyun Lee, Hyungkwan Kwon, K. You
The geolocation method using the wireless signal processing system is widely used in many industrial areas. The time difference of arrival (TDOA) method is one of the most commonly used geolocation methods. The TDOA signal based geolocation system can estimate the position of a mobile object by using at least three base stations in two dimensional space. In geolocation problem, the precise estimation of mobile's position is the most significant issue. The measurement noise that is contained in measured TDOA data causes the estimation inaccuracy in a mobile geolocation. In this paper, the objective function that represents the scalar error of position estimation is formulated using the concept of L -norm approximation. Also we suggest the iterative reweighted least square (IRLS) scheme for minimizing of the objective function. The optimal solution can be obtained using the limited measurement data through the reweighted iteration process of the IRLS scheme.
{"title":"TDOA based geolocation using IRLS algorithm","authors":"Kyunghyun Lee, Hyungkwan Kwon, K. You","doi":"10.1109/ICIIBMS.2017.8279746","DOIUrl":"https://doi.org/10.1109/ICIIBMS.2017.8279746","url":null,"abstract":"The geolocation method using the wireless signal processing system is widely used in many industrial areas. The time difference of arrival (TDOA) method is one of the most commonly used geolocation methods. The TDOA signal based geolocation system can estimate the position of a mobile object by using at least three base stations in two dimensional space. In geolocation problem, the precise estimation of mobile's position is the most significant issue. The measurement noise that is contained in measured TDOA data causes the estimation inaccuracy in a mobile geolocation. In this paper, the objective function that represents the scalar error of position estimation is formulated using the concept of L -norm approximation. Also we suggest the iterative reweighted least square (IRLS) scheme for minimizing of the objective function. The optimal solution can be obtained using the limited measurement data through the reweighted iteration process of the IRLS scheme.","PeriodicalId":122969,"journal":{"name":"2017 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115224429","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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