Songde Hu, Huansheng Ning, Yang Xu, L. Mao, Youzhong Li, Lijun Zhang
Silicon physical unclonable function (PUF) is a special circuit that can reflect the uncontrollable intrinsic variation of integrated circuits (ICs) manufacturing process. These PUFs can be used as hardware security in security fields, such as authentication of devices and key generation in security applications. In order to know how the PUF circuits express the physical characteristics due to manufacturing process variations and provide a reference for researchers in the field of security, we briefly introduce the arbiter-based PUF and analyze the arbiter-based PUF in depth as it is a typical one of the silicon PUFs. Instead of paying attention to the whole PUF circuit which most studies do, we just focus on the stages so we can determine a demand of the arbiter. Monte Carlo simulation has been used to simulate the manufacturing process variations and the simulation is based on 40nm and 65nm technology libraries. Finally, a Monte Carlo-based statistical analysis has demonstrated that advanced technologies can enlarge intrinsic variation.
{"title":"Statistical Analysis of Process Variations on the Delay-Based PUF","authors":"Songde Hu, Huansheng Ning, Yang Xu, L. Mao, Youzhong Li, Lijun Zhang","doi":"10.1109/IIKI.2016.104","DOIUrl":"https://doi.org/10.1109/IIKI.2016.104","url":null,"abstract":"Silicon physical unclonable function (PUF) is a special circuit that can reflect the uncontrollable intrinsic variation of integrated circuits (ICs) manufacturing process. These PUFs can be used as hardware security in security fields, such as authentication of devices and key generation in security applications. In order to know how the PUF circuits express the physical characteristics due to manufacturing process variations and provide a reference for researchers in the field of security, we briefly introduce the arbiter-based PUF and analyze the arbiter-based PUF in depth as it is a typical one of the silicon PUFs. Instead of paying attention to the whole PUF circuit which most studies do, we just focus on the stages so we can determine a demand of the arbiter. Monte Carlo simulation has been used to simulate the manufacturing process variations and the simulation is based on 40nm and 65nm technology libraries. Finally, a Monte Carlo-based statistical analysis has demonstrated that advanced technologies can enlarge intrinsic variation.","PeriodicalId":371106,"journal":{"name":"2016 International Conference on Identification, Information and Knowledge in the Internet of Things (IIKI)","volume":"87 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131189856","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}
The user evaluation of shopping websites always has huge amounts of data which is a waste of manpower and material resources. Aiming at this problem, this paper puts forward a model based on LSTM and word vectors [1]. LSTM can be a very good solution because of the long distance learning of the neural nodes to forward neural nodes of declining awareness, thus LSTM neural network model can be better to finish the task of user sentiment analysis.
{"title":"LSTM Based on the Classification of Emotion about User Evaluation on Shopping Site","authors":"Rong Xiao, Xiaohui Cui, Peipei Zhou, Wanfeng Ge","doi":"10.1109/IIKI.2016.77","DOIUrl":"https://doi.org/10.1109/IIKI.2016.77","url":null,"abstract":"The user evaluation of shopping websites always has huge amounts of data which is a waste of manpower and material resources. Aiming at this problem, this paper puts forward a model based on LSTM and word vectors [1]. LSTM can be a very good solution because of the long distance learning of the neural nodes to forward neural nodes of declining awareness, thus LSTM neural network model can be better to finish the task of user sentiment analysis.","PeriodicalId":371106,"journal":{"name":"2016 International Conference on Identification, Information and Knowledge in the Internet of Things (IIKI)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128034289","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}
In a lot of microwave system development process, we often need to test antenna pattern be loaded in the system and provide support to carry out the relevant system design and testing. This article focuses on the issue during the millimeter wave antenna pattern test encountered and the measures taken.
{"title":"Problems and Solutions Encountered in the Measurement of Millimeter Wave Antenna Pattern","authors":"Yonglei Li, Hongmei Tang, Xin Liu, Tiexing Wang","doi":"10.1109/IIKI.2016.32","DOIUrl":"https://doi.org/10.1109/IIKI.2016.32","url":null,"abstract":"In a lot of microwave system development process, we often need to test antenna pattern be loaded in the system and provide support to carry out the relevant system design and testing. This article focuses on the issue during the millimeter wave antenna pattern test encountered and the measures taken.","PeriodicalId":371106,"journal":{"name":"2016 International Conference on Identification, Information and Knowledge in the Internet of Things (IIKI)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133652474","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}
C. Duanmu, Di Zhao, Dingde Jiang, Houbing Song, Jiping Xiong
In the applications of the internet of things (IOT), the nodes in the network usually has power limits and storage space limits. Thus, the images over the IOT are usually low-resolution images. However, the customer usually want high-resolution images. To satisfy these needs, the solution of super-resolution methods comes. In this paper, a new algorithm for super-resolution is proposed, where the three dimensional discrete cosine transform (3D-DCT) is employed to extract the features of the image blocks. Then, the low frequency coefficients in the 3D-DCT are set with large weight values, and the high frequency coefficients are set with relatively small weight values. The 3D-DCT coefficients are then multiplied with the corresponding weights, and a reverse 3D-DCT is carried out. A bi-cubic transform is employed to get a high resolution block. The difference between that block and the actual high resolution block is saved in the training set with the 3D-DCT blocks. A new difference measure is proposed in the online phase to obtain the similarity between a candidate block and the blocks in the training set. After this, several training blocks are selected and the neighbor embedding method is employed to reconstruct the high resolution blocks. To reduce the computational complexity of the algorithm, the revised K-means algorithm is employed. The experimental results show that the proposed algorithm performs much better than the traditional neighbor embedding algorithm and the bi-cubic interpolation algorithm.
{"title":"A Three Dimension Super-Resolution Algorithm through Neighbor Embedding Based on Weighted Coefficient Values for Internet of Things","authors":"C. Duanmu, Di Zhao, Dingde Jiang, Houbing Song, Jiping Xiong","doi":"10.1109/IIKI.2016.52","DOIUrl":"https://doi.org/10.1109/IIKI.2016.52","url":null,"abstract":"In the applications of the internet of things (IOT), the nodes in the network usually has power limits and storage space limits. Thus, the images over the IOT are usually low-resolution images. However, the customer usually want high-resolution images. To satisfy these needs, the solution of super-resolution methods comes. In this paper, a new algorithm for super-resolution is proposed, where the three dimensional discrete cosine transform (3D-DCT) is employed to extract the features of the image blocks. Then, the low frequency coefficients in the 3D-DCT are set with large weight values, and the high frequency coefficients are set with relatively small weight values. The 3D-DCT coefficients are then multiplied with the corresponding weights, and a reverse 3D-DCT is carried out. A bi-cubic transform is employed to get a high resolution block. The difference between that block and the actual high resolution block is saved in the training set with the 3D-DCT blocks. A new difference measure is proposed in the online phase to obtain the similarity between a candidate block and the blocks in the training set. After this, several training blocks are selected and the neighbor embedding method is employed to reconstruct the high resolution blocks. To reduce the computational complexity of the algorithm, the revised K-means algorithm is employed. The experimental results show that the proposed algorithm performs much better than the traditional neighbor embedding algorithm and the bi-cubic interpolation algorithm.","PeriodicalId":371106,"journal":{"name":"2016 International Conference on Identification, Information and Knowledge in the Internet of Things (IIKI)","volume":"174 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114471344","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}
In the traditional Chinese medicine (TCM) wrist pulse diagnosis plays a major role in detecting the health status of an individual. It depends strongly on the doctors' long-term experience as well as on their different inferences. Being subjective and based on long-term experience, pulse detection methods are difficult to standardize. Kim pulse diagnosis (KPD), established by Wei Jin, is an efficient method validated by both traditional Chinese medicine and in recent years also by western medicine. The key step to automatic implementation of KPD, using signal processing and analysis, is the developed KPD signal acquisition device. However, the raw wrist pulse signal acquired from KPD device includes a significant amount of noise. This paper proposes several preprocessing algorithms for pulse diagnosis, that includes wavelet transform and Gaussian filter to remove noise and the iterative sliding window (ISW) algorithm to remove the baseline wander and split the continuous signal into single periods. Experimental results show, that the algorithm for baseline wander removal is efficient and that the segmented signal matches the signal described in KPD.
{"title":"KPD Based Signal Preprocessing Algorithm for Pulse Diagnosis","authors":"Zhichao Zhang, Yuan Zhang, W. Jin, A. Kos","doi":"10.1109/IIKI.2016.75","DOIUrl":"https://doi.org/10.1109/IIKI.2016.75","url":null,"abstract":"In the traditional Chinese medicine (TCM) wrist pulse diagnosis plays a major role in detecting the health status of an individual. It depends strongly on the doctors' long-term experience as well as on their different inferences. Being subjective and based on long-term experience, pulse detection methods are difficult to standardize. Kim pulse diagnosis (KPD), established by Wei Jin, is an efficient method validated by both traditional Chinese medicine and in recent years also by western medicine. The key step to automatic implementation of KPD, using signal processing and analysis, is the developed KPD signal acquisition device. However, the raw wrist pulse signal acquired from KPD device includes a significant amount of noise. This paper proposes several preprocessing algorithms for pulse diagnosis, that includes wavelet transform and Gaussian filter to remove noise and the iterative sliding window (ISW) algorithm to remove the baseline wander and split the continuous signal into single periods. Experimental results show, that the algorithm for baseline wander removal is efficient and that the segmented signal matches the signal described in KPD.","PeriodicalId":371106,"journal":{"name":"2016 International Conference on Identification, Information and Knowledge in the Internet of Things (IIKI)","volume":"293 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116095856","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}
In order to enhance the performance of E-Commerce recommendation, a hybrid filtering approach based on the taxonomy of E-Commerce platform is put forward. The classification tree of products is used to find the users with similar shopping intention. The sparsity of user ratings, major problem for collaborative filtering, is overcome. A two-granularity user profile is built to reflect the customer's shopping interests. User profile is firstly described as a set of leaf nodes of the classification tree. Then, each category of the user profile is refined by the theory of fuzzy set. Fuzzy sets make user profile and item representation more accurate. At the same time, tags instead of key words extracted from item content, are used for the building of user profiles and representation of items. It overcomes the analysis difficulty and large calculation problems for content-based filtering.
{"title":"Improve E-Commerce Recommendation by Classification Tree and Fuzzy Sets","authors":"Lianhong Ding, Yanhong Zheng","doi":"10.1109/IIKI.2016.73","DOIUrl":"https://doi.org/10.1109/IIKI.2016.73","url":null,"abstract":"In order to enhance the performance of E-Commerce recommendation, a hybrid filtering approach based on the taxonomy of E-Commerce platform is put forward. The classification tree of products is used to find the users with similar shopping intention. The sparsity of user ratings, major problem for collaborative filtering, is overcome. A two-granularity user profile is built to reflect the customer's shopping interests. User profile is firstly described as a set of leaf nodes of the classification tree. Then, each category of the user profile is refined by the theory of fuzzy set. Fuzzy sets make user profile and item representation more accurate. At the same time, tags instead of key words extracted from item content, are used for the building of user profiles and representation of items. It overcomes the analysis difficulty and large calculation problems for content-based filtering.","PeriodicalId":371106,"journal":{"name":"2016 International Conference on Identification, Information and Knowledge in the Internet of Things (IIKI)","volume":"524 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123352761","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}
Smart sport equipment is being increasingly used in highly competitive (professional) sport. By definition, smart equipment employs various sensors for detecting its state and actions. The correct choice of the most appropriate sensor(s) is of paramount importance. When integrated into the equipment, ideal sensors are unobstructive, and do not change the functionality of the equipment. The article focuses on identification and selection of sensors suitable for the integration into a golf club. We used two orthogonally affixed strain gage sensors, a 3-axis accelerometer, and a 3-axis gyroscope. The responses of strain gage sensors are used for measuring golf club flex. They are calibrated and validated in the laboratory environment by the highly accurate optical tracking system Qualisys Track Manager (QTM). Accelerometer and gyroscope are used to measure golf club acceleration and angular speed. Field tests are performed without QTM, only with the sensors affixed to the golf club. The first set of results show that the strain gage sensors complement the inertial sensors. For some golf swing tracking and error detection applications strain gage sensors could be the only type of sensors needed. Our final goal is to be able to acquire and analyze as many parameters of a golf club in real time during the entire swing. Such information would make the identification and selection of the most appropriate sensors to be applicable for a defined task easier.
{"title":"Identification and Selection of Sensors Suitable for Integration into Sport Equipment: Smart Golf Club","authors":"A. Kos, A. Umek, S. Tomažič","doi":"10.1109/IIKI.2016.71","DOIUrl":"https://doi.org/10.1109/IIKI.2016.71","url":null,"abstract":"Smart sport equipment is being increasingly used in highly competitive (professional) sport. By definition, smart equipment employs various sensors for detecting its state and actions. The correct choice of the most appropriate sensor(s) is of paramount importance. When integrated into the equipment, ideal sensors are unobstructive, and do not change the functionality of the equipment. The article focuses on identification and selection of sensors suitable for the integration into a golf club. We used two orthogonally affixed strain gage sensors, a 3-axis accelerometer, and a 3-axis gyroscope. The responses of strain gage sensors are used for measuring golf club flex. They are calibrated and validated in the laboratory environment by the highly accurate optical tracking system Qualisys Track Manager (QTM). Accelerometer and gyroscope are used to measure golf club acceleration and angular speed. Field tests are performed without QTM, only with the sensors affixed to the golf club. The first set of results show that the strain gage sensors complement the inertial sensors. For some golf swing tracking and error detection applications strain gage sensors could be the only type of sensors needed. Our final goal is to be able to acquire and analyze as many parameters of a golf club in real time during the entire swing. Such information would make the identification and selection of the most appropriate sensors to be applicable for a defined task easier.","PeriodicalId":371106,"journal":{"name":"2016 International Conference on Identification, Information and Knowledge in the Internet of Things (IIKI)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124693852","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}
In order to forecast the price movement of stock with the correlated news events, an enhanced Topic-driven model with the positional weight of feature words and label of stocks, named LP-LDA model, is proposed to represent and analyze the intrinsic mechanism in financial market. The experiment results show that LP-LDA has a better performance than traditional LDA model. Especially, when the number of topics are increasing, the running time of LP-LDA model are 0.69s, 0.78 s and 1.15s at 100, 200 and 300 topics, respectively, which are better than LDA. Furthermore, Degree of Influence (DoI) is defined to describe the considerable influence about the news events on the price movement of certain stock, which provides a new mechanism to measure the fluctuating price. The experiment results shown that the coefficient of correlation between news topic and return rate of stock is 0.9137, which is much higher than other results of experiment.
{"title":"Research on News Topic-Driven Market Flucatuation and Predication","authors":"Y. Rao, Xuhui Zhong, Shumin Lu","doi":"10.1109/IIKI.2016.93","DOIUrl":"https://doi.org/10.1109/IIKI.2016.93","url":null,"abstract":"In order to forecast the price movement of stock with the correlated news events, an enhanced Topic-driven model with the positional weight of feature words and label of stocks, named LP-LDA model, is proposed to represent and analyze the intrinsic mechanism in financial market. The experiment results show that LP-LDA has a better performance than traditional LDA model. Especially, when the number of topics are increasing, the running time of LP-LDA model are 0.69s, 0.78 s and 1.15s at 100, 200 and 300 topics, respectively, which are better than LDA. Furthermore, Degree of Influence (DoI) is defined to describe the considerable influence about the news events on the price movement of certain stock, which provides a new mechanism to measure the fluctuating price. The experiment results shown that the coefficient of correlation between news topic and return rate of stock is 0.9137, which is much higher than other results of experiment.","PeriodicalId":371106,"journal":{"name":"2016 International Conference on Identification, Information and Knowledge in the Internet of Things (IIKI)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124892457","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}
Yuqi Yang, Guangzhi Zhang, R. Bie, Sungjoong Kim, Dongil Shin
Health is closely related to everyone. Integrating different medical data sets will bring tremendous value for human. Basing on Chinese and English disease medical term, we use text mining technique in terms of two dimensions of the disease from the name and text description of the semantic clustering to achieve initial alignment disease terminology. First, we translate the Chinese data set through the API translation. Then we assign weights for each feature item to obtain feature vector for each disease node disease. Finally, we calculate the similarity of diseases and K-means clustering. We conduct experiments to evaluate the method on real-world and authoritative dataset, and the results prove that it has better rationality and superiority. The method can be extended to the initial alignment of multilingual texts with the same concept after improving.
{"title":"Key Techniques of Cross-Language Medical Term Alignment","authors":"Yuqi Yang, Guangzhi Zhang, R. Bie, Sungjoong Kim, Dongil Shin","doi":"10.1109/IIKI.2016.26","DOIUrl":"https://doi.org/10.1109/IIKI.2016.26","url":null,"abstract":"Health is closely related to everyone. Integrating different medical data sets will bring tremendous value for human. Basing on Chinese and English disease medical term, we use text mining technique in terms of two dimensions of the disease from the name and text description of the semantic clustering to achieve initial alignment disease terminology. First, we translate the Chinese data set through the API translation. Then we assign weights for each feature item to obtain feature vector for each disease node disease. Finally, we calculate the similarity of diseases and K-means clustering. We conduct experiments to evaluate the method on real-world and authoritative dataset, and the results prove that it has better rationality and superiority. The method can be extended to the initial alignment of multilingual texts with the same concept after improving.","PeriodicalId":371106,"journal":{"name":"2016 International Conference on Identification, Information and Knowledge in the Internet of Things (IIKI)","volume":"116 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126310884","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}
While location based services (LBS) are facilitating our daily life, the privacy issues including location privacy and query privacy are also arising. Existing efforts aiming to preserving query privacy rely on third party servers or fail to provide guaranteed privacy degree. In this paper we combine the concepts of differential privacy and k-anonymity to establish a novel notion of differentially private k-anonymity (DPkA) for query privacy in LBS. The sufficient and necessary condition for the availability of 0-DPkA is recognized and a mechanism M0 to achieve 0-DPkA is given. For other cases that 0-DPkA is impossible, this paper presents an algorithm to achieve ε-DPkA with bounded ε.
{"title":"Differentially Private k-Anonymity: Achieving Query Privacy in Location-Based Services","authors":"Jinbao Wang, Zhipeng Cai, Chunyu Ai, Donghua Yang, Hong Gao, Xiuzhen Cheng","doi":"10.1109/IIKI.2016.67","DOIUrl":"https://doi.org/10.1109/IIKI.2016.67","url":null,"abstract":"While location based services (LBS) are facilitating our daily life, the privacy issues including location privacy and query privacy are also arising. Existing efforts aiming to preserving query privacy rely on third party servers or fail to provide guaranteed privacy degree. In this paper we combine the concepts of differential privacy and k-anonymity to establish a novel notion of differentially private k-anonymity (DPkA) for query privacy in LBS. The sufficient and necessary condition for the availability of 0-DPkA is recognized and a mechanism M0 to achieve 0-DPkA is given. For other cases that 0-DPkA is impossible, this paper presents an algorithm to achieve ε-DPkA with bounded ε.","PeriodicalId":371106,"journal":{"name":"2016 International Conference on Identification, Information and Knowledge in the Internet of Things (IIKI)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129332774","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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