Pub Date : 2017-09-01DOI: 10.1109/IDAP.2017.8090218
A. Müngen, Mehmet Kaya
Word of epidemic is a very popular term in modern world which social media has affect almost all people along all over the world. Modern World's social networks are very sophisticated networks and learning information is very crucial for analyze user behaviors. Finding user's effect on other users/people is very interesting point in complex networks. Almost all related works only focus on finding and analyzing user behaviors for creating user profiles. However, in real life, all posts actually have different effect so have different influence values. Our proposed method that based on fuse motif analysis (FMA), focus on finding most effective posts for Instagram Social Network which one of the most popular social networks. Proposed method firstly calculate all posts influence values on other people. In our method, it is take into account variety of factors include users' other posts popularity, emotional based sentimental analyze on comments and tag frequency. It has been proposed that to create a model to predict most influencing posts including all determined factors. Proposed method applied and analyzed on Instagram data which gathered by us and share our experimental results in the paper.
{"title":"Influence analysis of posts in social networks by using quad-motifs","authors":"A. Müngen, Mehmet Kaya","doi":"10.1109/IDAP.2017.8090218","DOIUrl":"https://doi.org/10.1109/IDAP.2017.8090218","url":null,"abstract":"Word of epidemic is a very popular term in modern world which social media has affect almost all people along all over the world. Modern World's social networks are very sophisticated networks and learning information is very crucial for analyze user behaviors. Finding user's effect on other users/people is very interesting point in complex networks. Almost all related works only focus on finding and analyzing user behaviors for creating user profiles. However, in real life, all posts actually have different effect so have different influence values. Our proposed method that based on fuse motif analysis (FMA), focus on finding most effective posts for Instagram Social Network which one of the most popular social networks. Proposed method firstly calculate all posts influence values on other people. In our method, it is take into account variety of factors include users' other posts popularity, emotional based sentimental analyze on comments and tag frequency. It has been proposed that to create a model to predict most influencing posts including all determined factors. Proposed method applied and analyzed on Instagram data which gathered by us and share our experimental results in the paper.","PeriodicalId":111721,"journal":{"name":"2017 International Artificial Intelligence and Data Processing Symposium (IDAP)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120922120","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 : 2017-09-01DOI: 10.1109/IDAP.2017.8090284
Talha Kiliç, T. Tuncer
Wireless sensor networks consist of many sensors designed to provide information flow from a specific area. Sensors communicate with each other and receive information from the environment. The information obtained from the physical environment is carried into the network environment. In recent years, improvements in wireless sensor networks have necessitated the control, observation, data collection and storage of large physical areas. Especially in crowded cities, it is compulsory to collect and process data on physical infrastructure, air pollution, traffic and many similar issues. Therefore, cities become smart environments. The smart city structure aims to combine data from different sources for different purposes under a single point. In this article, we provide a framework that can instantly communicate park information to customers in different parts of the city. For this, parking information is stored in a database using cloud architecture through the sensors in the parking lot entrances. Customers can obtain parking information stored in the database with an improved mobile application. With smart parking system, it is possible to find suitable parking place, to prevent loss of customers time and to reduce costs.
{"title":"Smart city application: Android based smart parking system","authors":"Talha Kiliç, T. Tuncer","doi":"10.1109/IDAP.2017.8090284","DOIUrl":"https://doi.org/10.1109/IDAP.2017.8090284","url":null,"abstract":"Wireless sensor networks consist of many sensors designed to provide information flow from a specific area. Sensors communicate with each other and receive information from the environment. The information obtained from the physical environment is carried into the network environment. In recent years, improvements in wireless sensor networks have necessitated the control, observation, data collection and storage of large physical areas. Especially in crowded cities, it is compulsory to collect and process data on physical infrastructure, air pollution, traffic and many similar issues. Therefore, cities become smart environments. The smart city structure aims to combine data from different sources for different purposes under a single point. In this article, we provide a framework that can instantly communicate park information to customers in different parts of the city. For this, parking information is stored in a database using cloud architecture through the sensors in the parking lot entrances. Customers can obtain parking information stored in the database with an improved mobile application. With smart parking system, it is possible to find suitable parking place, to prevent loss of customers time and to reduce costs.","PeriodicalId":111721,"journal":{"name":"2017 International Artificial Intelligence and Data Processing Symposium (IDAP)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132626563","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 : 2017-09-01DOI: 10.1109/IDAP.2017.8090256
Furkan Oztemiz, Serdar Ethem Hamamci
Nowadays, increasing data sizes have grown at incredible levels. Many firms want to interpret their produced data and reach the useful information. In this study, by making customer basket analysis of a company operating in the retail sector, to organize suitable campaigns for the customers has been aimed and sales amounts of campaign items have been predicted before the campaign. The association rules for the items purchased by the customers has been obtained by using the Apriori algorithm. Sales amounts of associated items have been predicted with Artificial Neural Networks (ANN). For prediction process with ANN, MATLAB-NNTOOL toolbox has been used. With these prediction process, sales amounts of the campaign items offered to the customers have been determined and an idea about the success of campaign success has been obtained. In the study, 34 months sales data has been considered.
{"title":"Implementation of applied prediction with YSA for data groups with association rule","authors":"Furkan Oztemiz, Serdar Ethem Hamamci","doi":"10.1109/IDAP.2017.8090256","DOIUrl":"https://doi.org/10.1109/IDAP.2017.8090256","url":null,"abstract":"Nowadays, increasing data sizes have grown at incredible levels. Many firms want to interpret their produced data and reach the useful information. In this study, by making customer basket analysis of a company operating in the retail sector, to organize suitable campaigns for the customers has been aimed and sales amounts of campaign items have been predicted before the campaign. The association rules for the items purchased by the customers has been obtained by using the Apriori algorithm. Sales amounts of associated items have been predicted with Artificial Neural Networks (ANN). For prediction process with ANN, MATLAB-NNTOOL toolbox has been used. With these prediction process, sales amounts of the campaign items offered to the customers have been determined and an idea about the success of campaign success has been obtained. In the study, 34 months sales data has been considered.","PeriodicalId":111721,"journal":{"name":"2017 International Artificial Intelligence and Data Processing Symposium (IDAP)","volume":"151 9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131143280","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 : 2017-09-01DOI: 10.1109/IDAP.2017.8090195
Bircan Kamislioglu, Ayhan Akbal
This paper presents pilot symbol aided channel estimation in Filter Bank Multicarrier (FBMC). FBMC has been employed widespread in communication applications because of its good spectral behaviors. Unlike Orthogonal Frequency Division Multiplexing, FBMC structure avoids imaginary interference. So that auxiliary symbols are employed and decrease peak to power ratio and improve achievable capacity. OFDM and FBMC are compared about achievable of channel estimation with pilot symbols. The achievable capacity is increased with linear precoding by interference cancellation. Using two or three auxiliary pilot symbols instead of one is purposed and achievable capacity via Signal to Noise Ratio (SNR) is compared. OFDM and FBMC with coding and auxiliary symbols are discussed about capacity and numerical results are realized in Matlab.
{"title":"Pilot symbol based channel estimation and capacity evaluation in FBMC and OFDM","authors":"Bircan Kamislioglu, Ayhan Akbal","doi":"10.1109/IDAP.2017.8090195","DOIUrl":"https://doi.org/10.1109/IDAP.2017.8090195","url":null,"abstract":"This paper presents pilot symbol aided channel estimation in Filter Bank Multicarrier (FBMC). FBMC has been employed widespread in communication applications because of its good spectral behaviors. Unlike Orthogonal Frequency Division Multiplexing, FBMC structure avoids imaginary interference. So that auxiliary symbols are employed and decrease peak to power ratio and improve achievable capacity. OFDM and FBMC are compared about achievable of channel estimation with pilot symbols. The achievable capacity is increased with linear precoding by interference cancellation. Using two or three auxiliary pilot symbols instead of one is purposed and achievable capacity via Signal to Noise Ratio (SNR) is compared. OFDM and FBMC with coding and auxiliary symbols are discussed about capacity and numerical results are realized in Matlab.","PeriodicalId":111721,"journal":{"name":"2017 International Artificial Intelligence and Data Processing Symposium (IDAP)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127044461","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 : 2017-09-01DOI: 10.1109/IDAP.2017.8090248
Ali Fatih Gündüz, Mehmed Oguz Sen, A. Karcı, C. Yeroğlu
Human motion tracking, which requires both motion sensing hardware and algorithms based on computer vision, is an enjoyable and active research area with diverse applications. As a depth sensor device Kinect is a famous hardware component for this task. In this work, we studied using more than one Kinect camera to obtain better motion tracking which is applicable for motion capture. We synthetically created two camera data from one and then focused on de-noising and fusing these data in order to obtain more realistic skeleton joint coordinates. Artificial Immune System (AIS) optimization algorithm is suggested and used for this task. As a result we obtained 30% better fusion results from noisy synthetic data. Our results showed that AIS is a promising algorithm for obtaining optimal joint coordinates in the fusion of multiple Kinect skeleton data.
{"title":"Artificial immune system optimization based duplex kinect skeleton fusion","authors":"Ali Fatih Gündüz, Mehmed Oguz Sen, A. Karcı, C. Yeroğlu","doi":"10.1109/IDAP.2017.8090248","DOIUrl":"https://doi.org/10.1109/IDAP.2017.8090248","url":null,"abstract":"Human motion tracking, which requires both motion sensing hardware and algorithms based on computer vision, is an enjoyable and active research area with diverse applications. As a depth sensor device Kinect is a famous hardware component for this task. In this work, we studied using more than one Kinect camera to obtain better motion tracking which is applicable for motion capture. We synthetically created two camera data from one and then focused on de-noising and fusing these data in order to obtain more realistic skeleton joint coordinates. Artificial Immune System (AIS) optimization algorithm is suggested and used for this task. As a result we obtained 30% better fusion results from noisy synthetic data. Our results showed that AIS is a promising algorithm for obtaining optimal joint coordinates in the fusion of multiple Kinect skeleton data.","PeriodicalId":111721,"journal":{"name":"2017 International Artificial Intelligence and Data Processing Symposium (IDAP)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127205848","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 : 2017-09-01DOI: 10.1109/IDAP.2017.8090189
Ferhat Demirci, E. Karabudak, B. Ilgen
In this paper, we introduce our multi-document summarization system for Turkish news. The aim of the summarization system is to build a single document for multi document news that have been collected previously. The news were collected from several Turkish news sources via Real Simple Syndication (RSS). They were separated into clusters according to their topics. We utilized cosine similarity metric for the clustering process. Latent Semantic Analysis (LSA) has been used in the summarization phase. Multi-Document Summarization (MDS) differs from single document summarization in that the issues of compression, speed, redundancy and passage selection are essential inside the formation of ideal summaries. In this study, we utilized term frequency in document scoring which let us select the sentences with higher importance degree. We use ROUGE technique for evaluation of the system and our results show that the average of recall and precision percentage of this system is 43%. In the manual summarization phase, fifteen volunteers took part. The reason of low percentage is interpreted as getting texts randomly without any edit. It has been observed that the number of sentences and rate of summarization affect the accuracy rate.
{"title":"Multi-document summarization for Turkish news","authors":"Ferhat Demirci, E. Karabudak, B. Ilgen","doi":"10.1109/IDAP.2017.8090189","DOIUrl":"https://doi.org/10.1109/IDAP.2017.8090189","url":null,"abstract":"In this paper, we introduce our multi-document summarization system for Turkish news. The aim of the summarization system is to build a single document for multi document news that have been collected previously. The news were collected from several Turkish news sources via Real Simple Syndication (RSS). They were separated into clusters according to their topics. We utilized cosine similarity metric for the clustering process. Latent Semantic Analysis (LSA) has been used in the summarization phase. Multi-Document Summarization (MDS) differs from single document summarization in that the issues of compression, speed, redundancy and passage selection are essential inside the formation of ideal summaries. In this study, we utilized term frequency in document scoring which let us select the sentences with higher importance degree. We use ROUGE technique for evaluation of the system and our results show that the average of recall and precision percentage of this system is 43%. In the manual summarization phase, fifteen volunteers took part. The reason of low percentage is interpreted as getting texts randomly without any edit. It has been observed that the number of sentences and rate of summarization affect the accuracy rate.","PeriodicalId":111721,"journal":{"name":"2017 International Artificial Intelligence and Data Processing Symposium (IDAP)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125676061","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 : 2017-09-01DOI: 10.1109/IDAP.2017.8090205
Mahmut Dirik, A. F. Kocamaz, Emrah Dönmez
The presentation of the environment based on visual data is important for the mobile robot to do localization and orientation. Selection safe path for the path planning, it is necessary to locate the position of the mobile robot in surrounding environment. In this study, vision-based control system and fuzzy logic controller methods were used together to construct a collision free path environment. The experimental environment was monitored with an overhead camera and robot position information, obstacles and target positions were determined by visual processing techniques. A safe (non-collision) path plan between the robot and the target has been achieved using fuzzy decision sets. Six virtual sensor data were used to plan the robot orientation control. A graphical representation of the test results of applications made for different scenarios is demonstrated and commentated.
{"title":"Visual servoing based path planning for wheeled mobile robot in obstacle environments","authors":"Mahmut Dirik, A. F. Kocamaz, Emrah Dönmez","doi":"10.1109/IDAP.2017.8090205","DOIUrl":"https://doi.org/10.1109/IDAP.2017.8090205","url":null,"abstract":"The presentation of the environment based on visual data is important for the mobile robot to do localization and orientation. Selection safe path for the path planning, it is necessary to locate the position of the mobile robot in surrounding environment. In this study, vision-based control system and fuzzy logic controller methods were used together to construct a collision free path environment. The experimental environment was monitored with an overhead camera and robot position information, obstacles and target positions were determined by visual processing techniques. A safe (non-collision) path plan between the robot and the target has been achieved using fuzzy decision sets. Six virtual sensor data were used to plan the robot orientation control. A graphical representation of the test results of applications made for different scenarios is demonstrated and commentated.","PeriodicalId":111721,"journal":{"name":"2017 International Artificial Intelligence and Data Processing Symposium (IDAP)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126708748","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 : 2017-09-01DOI: 10.1109/IDAP.2017.8090214
Emrah Dönmez, A. F. Kocamaz, Mahmut Dirik
Path planning is the one of the most basic research areas in robotics. It simply concern about acquiring a safe path with admissible cost. In this study, we adapt bidirectional rapidly random exploring tree (Bi-RRT) path extraction to visual based configuration space map hosting obstacles and smooth result path with curve fitting models. Firstly, a map of the configuration space is created and robot, target positions are detected with threshold based object detection. There are two positions where two distinct RRT are launched on this map. These positions are robot initial position and target position. Both RRT try to reach target with random branches in each iterations. When one of these RRT branch intersect with other RRT branch, the algorithm is stopped. The acquired trajectory is the path between initial position and target position. But acquired path is generally close to the obstacles and unnecessary branches or jagged parts can be formed. Therefore, to provide safety object dilation over obstacles are used. Finally, the path is smoothed with curve fitting models. We conduct several experiments to evaluate Bi-RRT performance.
{"title":"Bi-RRT path extraction and curve fitting smooth with visual based configuration space mapping","authors":"Emrah Dönmez, A. F. Kocamaz, Mahmut Dirik","doi":"10.1109/IDAP.2017.8090214","DOIUrl":"https://doi.org/10.1109/IDAP.2017.8090214","url":null,"abstract":"Path planning is the one of the most basic research areas in robotics. It simply concern about acquiring a safe path with admissible cost. In this study, we adapt bidirectional rapidly random exploring tree (Bi-RRT) path extraction to visual based configuration space map hosting obstacles and smooth result path with curve fitting models. Firstly, a map of the configuration space is created and robot, target positions are detected with threshold based object detection. There are two positions where two distinct RRT are launched on this map. These positions are robot initial position and target position. Both RRT try to reach target with random branches in each iterations. When one of these RRT branch intersect with other RRT branch, the algorithm is stopped. The acquired trajectory is the path between initial position and target position. But acquired path is generally close to the obstacles and unnecessary branches or jagged parts can be formed. Therefore, to provide safety object dilation over obstacles are used. Finally, the path is smoothed with curve fitting models. We conduct several experiments to evaluate Bi-RRT performance.","PeriodicalId":111721,"journal":{"name":"2017 International Artificial Intelligence and Data Processing Symposium (IDAP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114386171","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 : 2017-09-01DOI: 10.1109/IDAP.2017.8090283
Mücahid Barstuğan, R. Ceylan
Dictionary Learning is a method used in signal and image processing. In this study, classification of mammogram images were realized by using dictionary learning and sparse representation algorithms. The attributes of the images were detected with Wavelet Transform and PCA, and the new dataset which was created by the obtained attributes were classified by Dictionary Learning. Moreover, the classification performance of the Dictionary Learning algorithm was evaluated by classifying the new dataset with SVM, Rotation Forest and AdaBoost algorithms. The best classification accuracy was obtained by PCA-Dictionary Learning algorithm as 98.89%.
{"title":"Classification of mammogram images by dictionary learning","authors":"Mücahid Barstuğan, R. Ceylan","doi":"10.1109/IDAP.2017.8090283","DOIUrl":"https://doi.org/10.1109/IDAP.2017.8090283","url":null,"abstract":"Dictionary Learning is a method used in signal and image processing. In this study, classification of mammogram images were realized by using dictionary learning and sparse representation algorithms. The attributes of the images were detected with Wavelet Transform and PCA, and the new dataset which was created by the obtained attributes were classified by Dictionary Learning. Moreover, the classification performance of the Dictionary Learning algorithm was evaluated by classifying the new dataset with SVM, Rotation Forest and AdaBoost algorithms. The best classification accuracy was obtained by PCA-Dictionary Learning algorithm as 98.89%.","PeriodicalId":111721,"journal":{"name":"2017 International Artificial Intelligence and Data Processing Symposium (IDAP)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114887955","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 : 2017-09-01DOI: 10.1109/IDAP.2017.8090280
Bora I. Kumova, Samuel Bacha Heye
Robotic agents consist of various compositions of properties that are found in their mechatronics, behavioural and cognitive architectures. Common properties of each architecture type serve as criteria for assessing the degree of intelligence of most embodied agent models. Although embodied intelligence has long been accepted for robotic agents, the literature is short on combined evaluations that discuss all properties of all architecture types in one framework. Here we provide a review of existing taxonomies for each type of architecture and attempt to combine them all in a single taxonomy for robotic agents.
{"title":"A survey of robotic agent architectures","authors":"Bora I. Kumova, Samuel Bacha Heye","doi":"10.1109/IDAP.2017.8090280","DOIUrl":"https://doi.org/10.1109/IDAP.2017.8090280","url":null,"abstract":"Robotic agents consist of various compositions of properties that are found in their mechatronics, behavioural and cognitive architectures. Common properties of each architecture type serve as criteria for assessing the degree of intelligence of most embodied agent models. Although embodied intelligence has long been accepted for robotic agents, the literature is short on combined evaluations that discuss all properties of all architecture types in one framework. Here we provide a review of existing taxonomies for each type of architecture and attempt to combine them all in a single taxonomy for robotic agents.","PeriodicalId":111721,"journal":{"name":"2017 International Artificial Intelligence and Data Processing Symposium (IDAP)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124278684","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：