Pub Date : 2019-07-31DOI: 10.14710/JTSISKOM.7.3.2019.109-115
Y. Yaddarabullah
The application of the Bellman-ford algorithm for finding the shortest path both weighted and unweighted graph has a weakness in determining the shortest path based on road conditions. This study modified the Bellman-Ford algorithm by adding the Technique for Order of Preference by Similarity to the Ideal Solution method to provide alternative road assessments based on its condition criteria including road density, road width, travel time, and distance. This modified Bellman-Ford has better performance in finding the alternative shortest path by choosing a road with smoother conditions, even though distance and travel time increase.
Bellman-ford算法在寻找加权和非加权图的最短路径时都存在一个缺点，即不能根据道路条件确定最短路径。本研究对Bellman-Ford算法进行了改进，在理想解决方法的基础上加入了相似偏好排序技术(Order of Preference by Similarity)，提供了基于道路密度、道路宽度、行驶时间和距离等条件标准的备选道路评估。改进后的Bellman-Ford在距离和行驶时间增加的情况下，通过选择条件更平坦的道路来寻找备选最短路径的性能更好。
{"title":"Modifikasi Algoritme Bellman-Ford Untuk Pencarian Rute Terpendek Berdasarkan Kondisi Jalan","authors":"Y. Yaddarabullah","doi":"10.14710/JTSISKOM.7.3.2019.109-115","DOIUrl":"https://doi.org/10.14710/JTSISKOM.7.3.2019.109-115","url":null,"abstract":"The application of the Bellman-ford algorithm for finding the shortest path both weighted and unweighted graph has a weakness in determining the shortest path based on road conditions. This study modified the Bellman-Ford algorithm by adding the Technique for Order of Preference by Similarity to the Ideal Solution method to provide alternative road assessments based on its condition criteria including road density, road width, travel time, and distance. This modified Bellman-Ford has better performance in finding the alternative shortest path by choosing a road with smoother conditions, even though distance and travel time increase.","PeriodicalId":56231,"journal":{"name":"Jurnal Teknologi dan Sistem Komputer","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46932965","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 : 2019-07-31DOI: 10.14710/JTSISKOM.7.3.2019.103-108
Ariefana Ria Riszky, M. Sadikin
The implementation of a marketing strategy requires a reference so that promotion can be on target, such as by looking for similarities between product items. This study examines the application of the association rule method and apriori algorithm to the purchase transaction dataset to assist in forming candidate combinations among product items for customer recommended product promotion. The purchase transaction dataset was collected in October and November 2018 with a total data of 1027. In the experiment, the minimum value of support is 85%, and the minimum confidence value is 90% by processing data using the Weka software 3.9 version. Apriori algorithm can form association rules as a reference in the promotion of company products and decision support in providing product recommendations to customers based on defined minimum support and confidence values.
{"title":"Data Mining Menggunakan Algoritma Apriori untuk Rekomendasi Produk bagi Pelanggan","authors":"Ariefana Ria Riszky, M. Sadikin","doi":"10.14710/JTSISKOM.7.3.2019.103-108","DOIUrl":"https://doi.org/10.14710/JTSISKOM.7.3.2019.103-108","url":null,"abstract":"The implementation of a marketing strategy requires a reference so that promotion can be on target, such as by looking for similarities between product items. This study examines the application of the association rule method and apriori algorithm to the purchase transaction dataset to assist in forming candidate combinations among product items for customer recommended product promotion. The purchase transaction dataset was collected in October and November 2018 with a total data of 1027. In the experiment, the minimum value of support is 85%, and the minimum confidence value is 90% by processing data using the Weka software 3.9 version. Apriori algorithm can form association rules as a reference in the promotion of company products and decision support in providing product recommendations to customers based on defined minimum support and confidence values.","PeriodicalId":56231,"journal":{"name":"Jurnal Teknologi dan Sistem Komputer","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44076636","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 : 2019-07-31DOI: 10.14710/jtsiskom.7.3.2019.116-120
Dwi Yuny Sylfania, F. P. Juniawan, Laurentinus Laurentinus, H. Pradana
In the campaign period of regional heads election, fraud can occur, such as money politics, blaming campaign facilities, campaign time violations, and black campaign. This study implemented a secure SMS application for election fraud complaints as a tool for the society to report all forms of election fraud that have occurred to the election supervisory department safely. The RSA algorithm was applied to encrypt the messages for sender privacy protection. The application was able to perform the message randomization function properly with a 10.44% avalanche effect. Brute force attack using a 16-bit key length needs 3.7 milliseconds for each try to find 32.768 possible private keys.
{"title":"SMS Security Improvement using RSA in Complaints Application on Regional Head Election’s Fraud","authors":"Dwi Yuny Sylfania, F. P. Juniawan, Laurentinus Laurentinus, H. Pradana","doi":"10.14710/jtsiskom.7.3.2019.116-120","DOIUrl":"https://doi.org/10.14710/jtsiskom.7.3.2019.116-120","url":null,"abstract":"In the campaign period of regional heads election, fraud can occur, such as money politics, blaming campaign facilities, campaign time violations, and black campaign. This study implemented a secure SMS application for election fraud complaints as a tool for the society to report all forms of election fraud that have occurred to the election supervisory department safely. The RSA algorithm was applied to encrypt the messages for sender privacy protection. The application was able to perform the message randomization function properly with a 10.44% avalanche effect. Brute force attack using a 16-bit key length needs 3.7 milliseconds for each try to find 32.768 possible private keys.","PeriodicalId":56231,"journal":{"name":"Jurnal Teknologi dan Sistem Komputer","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42390338","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 : 2019-07-31DOI: 10.14710/jtsiskom.7.3.2019.89-92
Doddy Teguh Yuwono, A. Fadlil, S. Sunardi
Data lost due to the fast format or system crash will remain in the media sector of storage. Digital forensics needs proof and techniques for retrieving data lost in storage. This research studied the performance comparison of open-source forensic software for data retrieval, namely Scalpel, Foremost, and Autopsy, using the National Institute of Standards Technology (NIST) forensic method. The testing process was carried out using the file carving technique. The carving file results are analyzed based on the success rate (accuracy) of the forensic tools used in returning the data. Scalpel performed the highest accuracy for file carving of 100% success rate for 20 document files in pdf and Docx format, and 90% for 10 image files in png and jpeg format.
{"title":"Performance Comparison of Forensic Software for Carving Files using NIST Method","authors":"Doddy Teguh Yuwono, A. Fadlil, S. Sunardi","doi":"10.14710/jtsiskom.7.3.2019.89-92","DOIUrl":"https://doi.org/10.14710/jtsiskom.7.3.2019.89-92","url":null,"abstract":"Data lost due to the fast format or system crash will remain in the media sector of storage. Digital forensics needs proof and techniques for retrieving data lost in storage. This research studied the performance comparison of open-source forensic software for data retrieval, namely Scalpel, Foremost, and Autopsy, using the National Institute of Standards Technology (NIST) forensic method. The testing process was carried out using the file carving technique. The carving file results are analyzed based on the success rate (accuracy) of the forensic tools used in returning the data. Scalpel performed the highest accuracy for file carving of 100% success rate for 20 document files in pdf and Docx format, and 90% for 10 image files in png and jpeg format.","PeriodicalId":56231,"journal":{"name":"Jurnal Teknologi dan Sistem Komputer","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47249952","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 : 2019-07-31DOI: 10.14710/JTSISKOM.7.3.2019.98-102
Agung Prakesakwa, Adhe Suryani, Rendra Gustriansyah
During the process of using containers by the importer, the shipping company as the owner of the container is often faced with the problem of those who must be responsible for handling containers that are damaged when shipping goods. This study examines the application of the Naïve Bayes method to help the container owner to make a decision in analyzing each case of objection from the importer. The analysis was carried out for each objection case submitted by the importer regarding subsidizing the cost of repairs to be given a FREE or PAID decision by considering 4 factors, which are the damaging side, the damage, the type of damage, and the cost of repairs. From 48 datasets collected and analyzed, the decision has an accuracy rate of 63.3% in subsidizing of container repair costs.
{"title":"Sistem Pendukung Keputusan untuk Subsidi Biaya Perbaikan Kerusakan Kontainer Menggunakan Naive Bayes","authors":"Agung Prakesakwa, Adhe Suryani, Rendra Gustriansyah","doi":"10.14710/JTSISKOM.7.3.2019.98-102","DOIUrl":"https://doi.org/10.14710/JTSISKOM.7.3.2019.98-102","url":null,"abstract":"During the process of using containers by the importer, the shipping company as the owner of the container is often faced with the problem of those who must be responsible for handling containers that are damaged when shipping goods. This study examines the application of the Naïve Bayes method to help the container owner to make a decision in analyzing each case of objection from the importer. The analysis was carried out for each objection case submitted by the importer regarding subsidizing the cost of repairs to be given a FREE or PAID decision by considering 4 factors, which are the damaging side, the damage, the type of damage, and the cost of repairs. From 48 datasets collected and analyzed, the decision has an accuracy rate of 63.3% in subsidizing of container repair costs.","PeriodicalId":56231,"journal":{"name":"Jurnal Teknologi dan Sistem Komputer","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48608852","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 : 2019-07-31DOI: 10.14710/jtsiskom.7.3.2019.%p
Doddy Teguh Yuwono, Abdul Fadlil, S. Sunardi
Data yang hilang karena format cepat atau sistem crash akan tetap ada di dalam sektor media penyimpanan. Forensik digital memerlukan bukti dan teknik pengembalian data yang tepat untuk mengembalikan data yang hilang dari media penyimpanan. Penelitian ini melakukan perbandingan performansi perangkat lunak forensik open source untuk mengembalikan data, yaitu Scalpel, Foremost dan Autopsy, menggunakan metode forensik National Institute of Standards Technology (NIST). Proses pengujian yang dilakukan menggunakan teknik file carving. Hasil file carving dianalisis dengan melihat tingkat keberhasilan (akurasi) alat forensik yang digunakan dalam pengembalian data. Scalpel menunjukkan akurasi file carving tertinggi dengan keberhasilan sebesar 100% untuk 20 file dokumen dalam format pdf dan Docx, dan 90% untuk file gambar dalam format png dan jpeg.
{"title":"Perbandingan Kinerja Perangkat Lunak Forensik untuk File Carving dengan Metode NIST","authors":"Doddy Teguh Yuwono, Abdul Fadlil, S. Sunardi","doi":"10.14710/jtsiskom.7.3.2019.%p","DOIUrl":"https://doi.org/10.14710/jtsiskom.7.3.2019.%p","url":null,"abstract":"Data yang hilang karena format cepat atau sistem crash akan tetap ada di dalam sektor media penyimpanan. Forensik digital memerlukan bukti dan teknik pengembalian data yang tepat untuk mengembalikan data yang hilang dari media penyimpanan. Penelitian ini melakukan perbandingan performansi perangkat lunak forensik open source untuk mengembalikan data, yaitu Scalpel, Foremost dan Autopsy, menggunakan metode forensik National Institute of Standards Technology (NIST). Proses pengujian yang dilakukan menggunakan teknik file carving. Hasil file carving dianalisis dengan melihat tingkat keberhasilan (akurasi) alat forensik yang digunakan dalam pengembalian data. Scalpel menunjukkan akurasi file carving tertinggi dengan keberhasilan sebesar 100% untuk 20 file dokumen dalam format pdf dan Docx, dan 90% untuk file gambar dalam format png dan jpeg.","PeriodicalId":56231,"journal":{"name":"Jurnal Teknologi dan Sistem Komputer","volume":"7 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-07-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45943110","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 : 2019-04-30DOI: 10.14710/JTSISKOM.7.2.2019.77-82
Nurajijah Nurajijah, Dwizah Riana
The decision on financing approval in sharia cooperatives has a high risk of the inability of customers to pay their credit obligations at maturity or referred to as bad credit. To maintain and minimize risk, an accurate method is needed to determine the financing agreement. The purpose of this study is to classify sharia cooperative loan history data using the Naïve Bayes algorithm, Decision Tree and SVM to predict the credibility of future customers. The results showed the accuracy of Naïve Bayes algorithm 77.29%, Decision Tree 89.02% and the highest Support Vector Machine (SVM) 89.86%.
{"title":"Algoritma Naïve Bayes, Decision Tree, dan SVM untuk Klasifikasi Persetujuan Pembiayaan Nasabah Koperasi Syariah","authors":"Nurajijah Nurajijah, Dwizah Riana","doi":"10.14710/JTSISKOM.7.2.2019.77-82","DOIUrl":"https://doi.org/10.14710/JTSISKOM.7.2.2019.77-82","url":null,"abstract":"The decision on financing approval in sharia cooperatives has a high risk of the inability of customers to pay their credit obligations at maturity or referred to as bad credit. To maintain and minimize risk, an accurate method is needed to determine the financing agreement. The purpose of this study is to classify sharia cooperative loan history data using the Naïve Bayes algorithm, Decision Tree and SVM to predict the credibility of future customers. The results showed the accuracy of Naïve Bayes algorithm 77.29%, Decision Tree 89.02% and the highest Support Vector Machine (SVM) 89.86%.","PeriodicalId":56231,"journal":{"name":"Jurnal Teknologi dan Sistem Komputer","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44874529","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 : 2019-04-30DOI: 10.14710/JTSISKOM.7.2.2019.47-55
Hadha Afrisal
Place recognition algorithm based-on visual sensor is crucial to be developed especially for an application of indoor robot navigation in which a Ground Positioning System (GPS) is not reliable to be utilized. This research compares the approach of place recognition of using learned-features from a model of Convolutional Neural Network (CNN) against conventional methods, such as Bag of Words (BoW) with SIFT features and Histogram of Oriented Uniform Patterns (HOUP) with its Local Binary Patterns (LBP). This research finding shows that the performance of our approach of using learned-features with transfer learning method from pre-trained CNN AlexNet is better than the conventional methods based-on handcrafted-features such as BoW and HOUP.
{"title":"Metode Pengenalan Tempat Secara Visual Berbasis Fitur CNN untuk Navigasi Robot di Dalam Gedung","authors":"Hadha Afrisal","doi":"10.14710/JTSISKOM.7.2.2019.47-55","DOIUrl":"https://doi.org/10.14710/JTSISKOM.7.2.2019.47-55","url":null,"abstract":"Place recognition algorithm based-on visual sensor is crucial to be developed especially for an application of indoor robot navigation in which a Ground Positioning System (GPS) is not reliable to be utilized. This research compares the approach of place recognition of using learned-features from a model of Convolutional Neural Network (CNN) against conventional methods, such as Bag of Words (BoW) with SIFT features and Histogram of Oriented Uniform Patterns (HOUP) with its Local Binary Patterns (LBP). This research finding shows that the performance of our approach of using learned-features with transfer learning method from pre-trained CNN AlexNet is better than the conventional methods based-on handcrafted-features such as BoW and HOUP.","PeriodicalId":56231,"journal":{"name":"Jurnal Teknologi dan Sistem Komputer","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46750721","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 : 2019-04-30DOI: 10.14710/JTSISKOM.7.2.2019.56-63
I. M. G. Sunarya, Tita Karlita, Joko Priambodo, Rika Rokhana, E. M. Yuniarno, T. A. Sardjono, I. Sunu, I. Purnama
Detection of vascular areas (blood vessels) using B-Mode ultrasound images is needed for automatic applications such as registration and navigation in medical operations. This study developed the detection of the carotid artery area using Convolution Neural Network Single Shot Network Multibox Detector (SSD) to determine the bounding box ROI of the carotid artery area in B-mode ultrasound images. The data used are B-Mode ultrasound images on the neck that contain the carotid artery area (primary data). SSD method result is 95% of accuracy which is higher than the Hough transformation method, Ellipse method, and Faster RCNN in detecting carotid artery area in the B-Mode ultrasound image. The use of image enhancement with Gaussian filter, histogram equalization, and Median filters in this method can increase detection accuracy. The best process time of the proposed method is 2.09 seconds so that it can be applied in a real-time system.
{"title":"Deteksi Arteri Karotis pada Citra Ultrasound B-Mode Berbasis Convolution Neural Network Single Shot Multibox Detector","authors":"I. M. G. Sunarya, Tita Karlita, Joko Priambodo, Rika Rokhana, E. M. Yuniarno, T. A. Sardjono, I. Sunu, I. Purnama","doi":"10.14710/JTSISKOM.7.2.2019.56-63","DOIUrl":"https://doi.org/10.14710/JTSISKOM.7.2.2019.56-63","url":null,"abstract":"Detection of vascular areas (blood vessels) using B-Mode ultrasound images is needed for automatic applications such as registration and navigation in medical operations. This study developed the detection of the carotid artery area using Convolution Neural Network Single Shot Network Multibox Detector (SSD) to determine the bounding box ROI of the carotid artery area in B-mode ultrasound images. The data used are B-Mode ultrasound images on the neck that contain the carotid artery area (primary data). SSD method result is 95% of accuracy which is higher than the Hough transformation method, Ellipse method, and Faster RCNN in detecting carotid artery area in the B-Mode ultrasound image. The use of image enhancement with Gaussian filter, histogram equalization, and Median filters in this method can increase detection accuracy. The best process time of the proposed method is 2.09 seconds so that it can be applied in a real-time system.","PeriodicalId":56231,"journal":{"name":"Jurnal Teknologi dan Sistem Komputer","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44484267","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 : 2019-04-30DOI: 10.14710/JTSISKOM.7.2.2019.83-88
T. Matulatan, M. Bettiza, Muhamad Radzi Rathomi, N. Ritha, N. Hayaty
Computer Assisted Testing (CAT) system in Indonesia has been commonly used but only to displaying random exam questions and unable to detect the maximum performance of the test participants. This research proposes a simple way with a good level of accuracy in identifying the maximum ability of test participants. By applying the Bayesian probabilistic in the selection of random questions with a weight of difficulties, the system can obtain optimal results from participants compared to sequential questions. The accuracy of the system measured on the choice of questions at the maximum level of the examinee alleged ability by the system, compared to the correct answer from participants gives an average accuracy of 75% compared to 33% sequentially. This technique allows tests to be carried out in a shorter time without repetition, which can affect the fatigue of the test participants in answering questions.
{"title":"Predictive Adaptive Test with Selective Weighted Bayesian Through Questions and Answers Patterns to Measure Student Competency Levels","authors":"T. Matulatan, M. Bettiza, Muhamad Radzi Rathomi, N. Ritha, N. Hayaty","doi":"10.14710/JTSISKOM.7.2.2019.83-88","DOIUrl":"https://doi.org/10.14710/JTSISKOM.7.2.2019.83-88","url":null,"abstract":"Computer Assisted Testing (CAT) system in Indonesia has been commonly used but only to displaying random exam questions and unable to detect the maximum performance of the test participants. This research proposes a simple way with a good level of accuracy in identifying the maximum ability of test participants. By applying the Bayesian probabilistic in the selection of random questions with a weight of difficulties, the system can obtain optimal results from participants compared to sequential questions. The accuracy of the system measured on the choice of questions at the maximum level of the examinee alleged ability by the system, compared to the correct answer from participants gives an average accuracy of 75% compared to 33% sequentially. This technique allows tests to be carried out in a shorter time without repetition, which can affect the fatigue of the test participants in answering questions.","PeriodicalId":56231,"journal":{"name":"Jurnal Teknologi dan Sistem Komputer","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-04-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43539613","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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