Pub Date : 2018-10-01DOI: 10.1109/INCAE.2018.8579397
M. Lubis, W. Anurogo, M. Mufida, H. M. Taki, S. Antoni, Rasyid Alkhoir Lubis
Chlorophyll-a characteristics to temperature, and wind in Batam, Indonesia are parameters that are related to the changing seasons and global climate in the tropics. The results of research in the period 2012–2016 distribution of chlorophyll-a has the lowest value in 2013 is 0,96 mg/l and the highest in 2012 is 7,25 mg/l. Sea surface temperature has almost the same value that is in the range 29°C until 31°C. Statistical analyses were analyzed both individually and simultaneously characteristic of chlorophyll-a, and the temperatures in Batam waters had a real relationship, but not so closely with regression values r2 = 0,48.
{"title":"Physical Condition of the Ocean to Global Climate Change Variability: Case Study in The Batam Waters, Indonesia","authors":"M. Lubis, W. Anurogo, M. Mufida, H. M. Taki, S. Antoni, Rasyid Alkhoir Lubis","doi":"10.1109/INCAE.2018.8579397","DOIUrl":"https://doi.org/10.1109/INCAE.2018.8579397","url":null,"abstract":"Chlorophyll-a characteristics to temperature, and wind in Batam, Indonesia are parameters that are related to the changing seasons and global climate in the tropics. The results of research in the period 2012–2016 distribution of chlorophyll-a has the lowest value in 2013 is 0,96 mg/l and the highest in 2012 is 7,25 mg/l. Sea surface temperature has almost the same value that is in the range 29°C until 31°C. Statistical analyses were analyzed both individually and simultaneously characteristic of chlorophyll-a, and the temperatures in Batam waters had a real relationship, but not so closely with regression values r2 = 0,48.","PeriodicalId":387859,"journal":{"name":"2018 International Conference on Applied Engineering (ICAE)","volume":"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":"127824487","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/INCAE.2018.8579358
Aditya Gautama Darmoyono, H. Suwarman, Ai Nurhayati
This research aim is to design a simple renewable energy device that uses thermal energy from the sun to generate electricity. The main conversion component is the thermoelectric generator (TEG) Peltier. Due to the low Peltier output, low voltage and low current, improvement is needed. The improvement approaches in this research are by connecting the Peltier in series array and constructing a solar heat trap. In the end, the device managed to achieve 1.88 mW output (1 Volt and 1.88 miliAmpere). This experiment provides an insight on how to improve Peltier output in real-world environment.
{"title":"Utilizing Thermoelectric Generator Peltier in Using Solar Thermal Energy as Renewable Energy Source","authors":"Aditya Gautama Darmoyono, H. Suwarman, Ai Nurhayati","doi":"10.1109/INCAE.2018.8579358","DOIUrl":"https://doi.org/10.1109/INCAE.2018.8579358","url":null,"abstract":"This research aim is to design a simple renewable energy device that uses thermal energy from the sun to generate electricity. The main conversion component is the thermoelectric generator (TEG) Peltier. Due to the low Peltier output, low voltage and low current, improvement is needed. The improvement approaches in this research are by connecting the Peltier in series array and constructing a solar heat trap. In the end, the device managed to achieve 1.88 mW output (1 Volt and 1.88 miliAmpere). This experiment provides an insight on how to improve Peltier output in real-world environment.","PeriodicalId":387859,"journal":{"name":"2018 International Conference on Applied Engineering (ICAE)","volume":"100 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":"114855761","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/INCAE.2018.8579155
T. Badriyah, Lailul Rahmaniah, I. Syarif
Fraud is an actions that can cause harm to individuals or organizations. It can be used anomaly detection algorithm to detect the occurrence of a fraud. This study develops prediction modeling in the field of anomaly detection to detect the occurrence of a fraud using Nearest Neighbor based Method (distance based and density based) and Statistics Methods (interquartile range). In this study, we use open fraud dataset which has been used to demonstrate fraud detection capabilities. The dataset was a benchmarking dataset in the form of a minority report open dataset that is German car insurance data. The results of performance measurement are then compared with the results obtained by previous researchers using the same dataset. From the experiment results, the performance measurement obtained in the method used in this study is superior in some cases.
{"title":"Nearest Neighbour and Statistics Method based for Detecting Fraud in Auto Insurance","authors":"T. Badriyah, Lailul Rahmaniah, I. Syarif","doi":"10.1109/INCAE.2018.8579155","DOIUrl":"https://doi.org/10.1109/INCAE.2018.8579155","url":null,"abstract":"Fraud is an actions that can cause harm to individuals or organizations. It can be used anomaly detection algorithm to detect the occurrence of a fraud. This study develops prediction modeling in the field of anomaly detection to detect the occurrence of a fraud using Nearest Neighbor based Method (distance based and density based) and Statistics Methods (interquartile range). In this study, we use open fraud dataset which has been used to demonstrate fraud detection capabilities. The dataset was a benchmarking dataset in the form of a minority report open dataset that is German car insurance data. The results of performance measurement are then compared with the results obtained by previous researchers using the same dataset. From the experiment results, the performance measurement obtained in the method used in this study is superior in some cases.","PeriodicalId":387859,"journal":{"name":"2018 International Conference on Applied Engineering (ICAE)","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":"127452364","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/INCAE.2018.8579369
R. Melani, Abdullah Sani, B. Sugandi, Riska Analia
The image processing is not only used to detect and recognize the object. It also can be used to calculate the amount of a buckle object. This paper presented a method which can calculate the amount of a buckle gas cylinder seal. At first, the camera detected a buckle of the seal in real-time. Then, the HSL color space is used to remove background image so that blob counting can detect the seal easily. The pixel of blob counting obtained will be compared to an original pixel in order to build the relation using the polynomial equation to count the seal. By combining the blob counting result, the buckle of the seal can be counted as seen in the experimental results which are done in the real-time application.
{"title":"A Study of Image Processing for Automatic Counting Gas Cylinder Seal","authors":"R. Melani, Abdullah Sani, B. Sugandi, Riska Analia","doi":"10.1109/INCAE.2018.8579369","DOIUrl":"https://doi.org/10.1109/INCAE.2018.8579369","url":null,"abstract":"The image processing is not only used to detect and recognize the object. It also can be used to calculate the amount of a buckle object. This paper presented a method which can calculate the amount of a buckle gas cylinder seal. At first, the camera detected a buckle of the seal in real-time. Then, the HSL color space is used to remove background image so that blob counting can detect the seal easily. The pixel of blob counting obtained will be compared to an original pixel in order to build the relation using the polynomial equation to count the seal. By combining the blob counting result, the buckle of the seal can be counted as seen in the experimental results which are done in the real-time application.","PeriodicalId":387859,"journal":{"name":"2018 International Conference on Applied Engineering (ICAE)","volume":"59 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":"125093462","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/INCAE.2018.8579153
Sumantri R Kurniawan, D. Pamungkas
To control the robot hand can be used several methods; one of them is by using EMG sensor and time domain methods. In this study, Myo Arm Sensors combined with Neural Network algorithm are used. The Root Mean Square of the sensor signals is used to be learning by the system. The learning rate is 0.7 with two hidden layers. Each layer used three nodes. The results obtained that the system enabled to control robot real time a delay of around 1S. Moreover, the accuracy of the feedforward process in backpropagation Neural Network is 92.68%.
{"title":"MYO Armband sensors and Neural Network Algorithm for Controlling Hand Robot","authors":"Sumantri R Kurniawan, D. Pamungkas","doi":"10.1109/INCAE.2018.8579153","DOIUrl":"https://doi.org/10.1109/INCAE.2018.8579153","url":null,"abstract":"To control the robot hand can be used several methods; one of them is by using EMG sensor and time domain methods. In this study, Myo Arm Sensors combined with Neural Network algorithm are used. The Root Mean Square of the sensor signals is used to be learning by the system. The learning rate is 0.7 with two hidden layers. Each layer used three nodes. The results obtained that the system enabled to control robot real time a delay of around 1S. Moreover, the accuracy of the feedforward process in backpropagation Neural Network is 92.68%.","PeriodicalId":387859,"journal":{"name":"2018 International Conference on Applied Engineering (ICAE)","volume":"19 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":"125343645","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/INCAE.2018.8579150
Muhammad Hasan Albana, Budi Baharudin, Ibrahim, Cahyo Budi Nugroho, I. Saputra
This research objective is to convert heat from the exhaust manifold of the diesel engine to electrical energy by using the thermoelectric generator (TEG). TEG consist of six semiconductors and be equipped with the heat sink. Research shows that exhaust manifold heat can be used to generate electrical energy by using TEG although the electricity produced is very small. The maximum electrical voltage generated from the use of TEG is 1,84 volts. The maximum electrical current generated by TEG is 51,6 mA. The maximum electrical power generated by TEG is 94,7 mW. TEG efficiency in this study was 3.2% to 4%. The voltage and the electric current generated by the TEG will be higher if the temperature difference between the hot side and the cold side of the semiconductor is higher.
{"title":"Thermoelectric generator for electricity from the exhaust manifold of the diesel engine","authors":"Muhammad Hasan Albana, Budi Baharudin, Ibrahim, Cahyo Budi Nugroho, I. Saputra","doi":"10.1109/INCAE.2018.8579150","DOIUrl":"https://doi.org/10.1109/INCAE.2018.8579150","url":null,"abstract":"This research objective is to convert heat from the exhaust manifold of the diesel engine to electrical energy by using the thermoelectric generator (TEG). TEG consist of six semiconductors and be equipped with the heat sink. Research shows that exhaust manifold heat can be used to generate electrical energy by using TEG although the electricity produced is very small. The maximum electrical voltage generated from the use of TEG is 1,84 volts. The maximum electrical current generated by TEG is 51,6 mA. The maximum electrical power generated by TEG is 94,7 mW. TEG efficiency in this study was 3.2% to 4%. The voltage and the electric current generated by the TEG will be higher if the temperature difference between the hot side and the cold side of the semiconductor is higher.","PeriodicalId":387859,"journal":{"name":"2018 International Conference on Applied Engineering (ICAE)","volume":"53 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":"132562668","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/INCAE.2018.8579389
Purwono Prasetyawan, Imam Ahmad, Rohmat Indra Borman, Ardiansyah, Yogi Aziz Pahlevi, D. E. Kurniawan
The period of student study is one of the indicators of the determinants of the quality of a college. Based on the standard assessment of college accreditation by BAN-PT, the period of study became one of the elements of assessment of accreditation forms. Universities have an important role to monitor the development of student studies. For that, universities are required to always evaluate the performance of students. One way of evaluation that can be done is to explore the knowledge of academic data that will affect student performance. By utilizing data mining on student academic data, universities can obtain useful information. This information which later can be used as a reference in making improvements to the performance of student studies. Several previous studies used data mining techniques to predict the study period of students and this study will analyze the factors that influence the duration of undergraduate studies and modeling of ANN with backpropagation training algorithms to classify the study period. The result of this research is The BPNN algorithm is suitable for the classification of undergraduate study periods with accuracy rates above 85%.
{"title":"Classification of the Period Undergraduate Study Using Back-propagation Neural Network","authors":"Purwono Prasetyawan, Imam Ahmad, Rohmat Indra Borman, Ardiansyah, Yogi Aziz Pahlevi, D. E. Kurniawan","doi":"10.1109/INCAE.2018.8579389","DOIUrl":"https://doi.org/10.1109/INCAE.2018.8579389","url":null,"abstract":"The period of student study is one of the indicators of the determinants of the quality of a college. Based on the standard assessment of college accreditation by BAN-PT, the period of study became one of the elements of assessment of accreditation forms. Universities have an important role to monitor the development of student studies. For that, universities are required to always evaluate the performance of students. One way of evaluation that can be done is to explore the knowledge of academic data that will affect student performance. By utilizing data mining on student academic data, universities can obtain useful information. This information which later can be used as a reference in making improvements to the performance of student studies. Several previous studies used data mining techniques to predict the study period of students and this study will analyze the factors that influence the duration of undergraduate studies and modeling of ANN with backpropagation training algorithms to classify the study period. The result of this research is The BPNN algorithm is suitable for the classification of undergraduate study periods with accuracy rates above 85%.","PeriodicalId":387859,"journal":{"name":"2018 International Conference on Applied Engineering (ICAE)","volume":"1 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":"131065516","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/INCAE.2018.8579381
M. Bachtiar, Thiar Hasbiya Ditanaya, Sigit Wasista, Reinaldo Riant Kurnia Perdana
Data are the main demand of today's modern era. However, the cryptanalysis attack can compromise the security of any data. Consequently, unauthorized peoples can take the data. The reason is Cryptography is currently only based on the results of the same encryption. In reducing cryptanalysis attacks, this paper discusses data security using dynamic encryption. Cryptosystem in this paper uses a modified of AES 256-bit. Procedure to generate dynamic encryption by giving a character (salt) to plain text. Salt formed from the result of a Linear Congruential Generator (LCG) algorithm. Then a combination of salt and plain text will merge with the algorithm of One Time Pad (OTP). The advantage of this method is, can be used on two different systems, in addition to dynamic encryption results. The tests conducted in this paper shows that the percentage of NIST Tool Suite Test, the successful result is 72.5% from eight parameters that tested.
{"title":"Security Enhancement of AES Based Encryption Using Dynamic Salt Algorithm","authors":"M. Bachtiar, Thiar Hasbiya Ditanaya, Sigit Wasista, Reinaldo Riant Kurnia Perdana","doi":"10.1109/INCAE.2018.8579381","DOIUrl":"https://doi.org/10.1109/INCAE.2018.8579381","url":null,"abstract":"Data are the main demand of today's modern era. However, the cryptanalysis attack can compromise the security of any data. Consequently, unauthorized peoples can take the data. The reason is Cryptography is currently only based on the results of the same encryption. In reducing cryptanalysis attacks, this paper discusses data security using dynamic encryption. Cryptosystem in this paper uses a modified of AES 256-bit. Procedure to generate dynamic encryption by giving a character (salt) to plain text. Salt formed from the result of a Linear Congruential Generator (LCG) algorithm. Then a combination of salt and plain text will merge with the algorithm of One Time Pad (OTP). The advantage of this method is, can be used on two different systems, in addition to dynamic encryption results. The tests conducted in this paper shows that the percentage of NIST Tool Suite Test, the successful result is 72.5% from eight parameters that tested.","PeriodicalId":387859,"journal":{"name":"2018 International Conference on Applied Engineering (ICAE)","volume":"1 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":"131307800","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/INCAE.2018.8579372
Muhammad Yusril Helmi Setyawan, R. M. Awangga, S. Efendi
Chatbot is software that communicates using natural language. chatbots such as machine conversation systems, Chatterbot, virtual agents, and dialogue systems. This software enables to simulate human conversations. In this research, the chatbot system that will be created must be able to understand the natural language of what is entered by the user, and the chatbot will answer according to what the user is expecting. The researcher proposes a classification method to identify intent rather than user input or called intent classification on the chatbot system; the researcher also wants to know the level of accuracy, precision, and recall on the evaluation results of both methods. The classification method applied in this research is the Naive Bayes method and compared with the Logistic Regression method to determine the class intention. The evaluation results show the level of accuracy precision and recall in the Logistic Regression model is higher than the Naive Bayes model.
{"title":"Comparison Of Multinomial Naive Bayes Algorithm And Logistic Regression For Intent Classification In Chatbot","authors":"Muhammad Yusril Helmi Setyawan, R. M. Awangga, S. Efendi","doi":"10.1109/INCAE.2018.8579372","DOIUrl":"https://doi.org/10.1109/INCAE.2018.8579372","url":null,"abstract":"Chatbot is software that communicates using natural language. chatbots such as machine conversation systems, Chatterbot, virtual agents, and dialogue systems. This software enables to simulate human conversations. In this research, the chatbot system that will be created must be able to understand the natural language of what is entered by the user, and the chatbot will answer according to what the user is expecting. The researcher proposes a classification method to identify intent rather than user input or called intent classification on the chatbot system; the researcher also wants to know the level of accuracy, precision, and recall on the evaluation results of both methods. The classification method applied in this research is the Naive Bayes method and compared with the Logistic Regression method to determine the class intention. The evaluation results show the level of accuracy precision and recall in the Logistic Regression model is higher than the Naive Bayes model.","PeriodicalId":387859,"journal":{"name":"2018 International Conference on Applied Engineering (ICAE)","volume":"49 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":"131642182","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/INCAE.2018.8579151
Awria Awria, Muhammad Hasan Albana, Rahman Hakim
The automotive technology race to improve the efficiency of engine performance is increasing, one of which is the use of heat energy in car radiators. This is in addition to reducing the workload of the engine. It can also produce electrical energy. This experiment uses four pieces of TEC1-12706 thermoelectric generators (TEG) which are arranged in series with heat sink construction in the direction of the fluid flow mounted directly above the TEG fixture. TEG Fixture will be installed on Lombardini diesel engine upper hose radiator LDW1404. This experiment produces a maximum voltage of 2.05 volts, with the current strength of 68.4 mA (0.064 A) and the power generated is 140.22 mA (0.14 A) with a difference in heat sink temperature from the heat side of 17, 8°C
提高发动机性能效率的汽车技术竞赛日益激烈，其中之一就是在汽车散热器中使用热能。这是除了减少引擎的工作量。它也能产生电能。本实验采用四台TEC1-12706热电发生器(TEG)串联布置，散热器结构与流体流动方向一致，安装在TEG夹具正上方。TEG夹具将安装在Lombardini柴油机上部软管散热器LDW1404上。本实验产生的最大电压为2.05伏，电流强度为68.4 mA (0.064 a)，产生的功率为140.22 mA (0.14 a)，散热侧温度差为17.8℃
{"title":"Experimental Study: Design of Thermoelectric Generator (TEG) Fixture for Harvesting an Automobile Electricity","authors":"Awria Awria, Muhammad Hasan Albana, Rahman Hakim","doi":"10.1109/INCAE.2018.8579151","DOIUrl":"https://doi.org/10.1109/INCAE.2018.8579151","url":null,"abstract":"The automotive technology race to improve the efficiency of engine performance is increasing, one of which is the use of heat energy in car radiators. This is in addition to reducing the workload of the engine. It can also produce electrical energy. This experiment uses four pieces of TEC1-12706 thermoelectric generators (TEG) which are arranged in series with heat sink construction in the direction of the fluid flow mounted directly above the TEG fixture. TEG Fixture will be installed on Lombardini diesel engine upper hose radiator LDW1404. This experiment produces a maximum voltage of 2.05 volts, with the current strength of 68.4 mA (0.064 A) and the power generated is 140.22 mA (0.14 A) with a difference in heat sink temperature from the heat side of 17, 8°C","PeriodicalId":387859,"journal":{"name":"2018 International Conference on Applied Engineering (ICAE)","volume":"93 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":"131342863","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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