Pub Date : 2010-09-02DOI: 10.1109/ICEIE.2010.5559827
Meiling Zhuang, Xiaofeng Zhang, Jianan Fang
Functional dividing lines are designed according to the Gauss Curvature of each node on undeveloped triangled 3-D body surface. Robert Hooke Law and Young's Modulus are applied to set up energy model based on the edges change before and after each triangle is flattened. To improve the practicability for flattened surface is the emphasis. In combination with the energy model, the algorithm is designed and optimized to minimize the unused energy after the triangles being flattened. At last the graphics of flattened 2D planes along dividing lines and corresponding energy distributing are got. The flattened 2D planes with longitude and weft direction are more fitted for fabrics cutting which will be laid on it.
{"title":"The optimum flattening for undeveloped 3-D body surface based on energy","authors":"Meiling Zhuang, Xiaofeng Zhang, Jianan Fang","doi":"10.1109/ICEIE.2010.5559827","DOIUrl":"https://doi.org/10.1109/ICEIE.2010.5559827","url":null,"abstract":"Functional dividing lines are designed according to the Gauss Curvature of each node on undeveloped triangled 3-D body surface. Robert Hooke Law and Young's Modulus are applied to set up energy model based on the edges change before and after each triangle is flattened. To improve the practicability for flattened surface is the emphasis. In combination with the energy model, the algorithm is designed and optimized to minimize the unused energy after the triangles being flattened. At last the graphics of flattened 2D planes along dividing lines and corresponding energy distributing are got. The flattened 2D planes with longitude and weft direction are more fitted for fabrics cutting which will be laid on it.","PeriodicalId":211301,"journal":{"name":"2010 International Conference on Electronics and Information Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2010-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132652584","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 : 2010-09-02DOI: 10.1109/ICEIE.2010.5559858
Jia Wu, Z. Cai, Zhechao Gao
K-Nearest-Neighbor (KNN) as an important classification method based on closest training examples has been widely used in data mining due to its simplicity, effectiveness, and robustness. However, the class probability estimation, the neighborhood size and the type of distance function confronting KNN may affect its classification accuracy. Many researchers have been focused on improving the accuracy of KNN via distance weighted, attribute weighted, and dynamically selected methods et al. In this paper, we first reviewed some improved algorithms of KNN in three categories mentioned above. Then, we singled out an improved algorithm called dynamic k-nearest-neighbor with distance and attribute weighted, simply DKNDAW. In DKNDAW, we mixed dynamic selected, distance weighted and attribute weighted methods. We experimentally tested our new algorithm in Weka system, using the whole 36 standard UCI data sets which are downloaded from the main website of Weka. In our experiment, we compared it to KNN, WAKNN, KNNDW, KNNDAW, and DKNN. The experimental results show that DKNDAW significantly outperforms KNN, WAKNN, KNNDW, KNNDAW, and DKNN in terms of the classification accuracy.
{"title":"Dynamic K-Nearest-Neighbor with Distance and attribute weighted for classification","authors":"Jia Wu, Z. Cai, Zhechao Gao","doi":"10.1109/ICEIE.2010.5559858","DOIUrl":"https://doi.org/10.1109/ICEIE.2010.5559858","url":null,"abstract":"K-Nearest-Neighbor (KNN) as an important classification method based on closest training examples has been widely used in data mining due to its simplicity, effectiveness, and robustness. However, the class probability estimation, the neighborhood size and the type of distance function confronting KNN may affect its classification accuracy. Many researchers have been focused on improving the accuracy of KNN via distance weighted, attribute weighted, and dynamically selected methods et al. In this paper, we first reviewed some improved algorithms of KNN in three categories mentioned above. Then, we singled out an improved algorithm called dynamic k-nearest-neighbor with distance and attribute weighted, simply DKNDAW. In DKNDAW, we mixed dynamic selected, distance weighted and attribute weighted methods. We experimentally tested our new algorithm in Weka system, using the whole 36 standard UCI data sets which are downloaded from the main website of Weka. In our experiment, we compared it to KNN, WAKNN, KNNDW, KNNDAW, and DKNN. The experimental results show that DKNDAW significantly outperforms KNN, WAKNN, KNNDW, KNNDAW, and DKNN in terms of the classification accuracy.","PeriodicalId":211301,"journal":{"name":"2010 International Conference on Electronics and Information Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2010-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131860237","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 : 2010-09-02DOI: 10.1109/ICEIE.2010.5559796
F. Anifowose, A. Abdulraheem
This paper presents a hybrid model consisting of a fusion of Functional Networks and Type-2 Fuzzy Logic. The model capitalizes on the capability of Functional Networks, using its least square fitting algorithm, to reduce the dimensionality of the input data by selecting the most relevant variables for the prediction of porosity and permeability of oil and gas reservoirs. It also attempts to improve the performance of Type-2 Fuzzy Logic whose complexity is increased and performance degraded with increased dimensionality of input data. The Functional Networks block was used to select the dominant variables from six datasets. The dimensionally-reduced datasets were then divided into training and testing subsets using the stratified sampling approach. Hence, the Type-2 Fuzzy Logic block is trained and tested with the best and dimensionally-reduced variables from the input data. The results showed that the hybrid model performed better in terms of training and testing with higher correlation coefficients, lower root mean square errors and reduced execution times than the original Type-2 Fuzzy Logic system. This work has confirmed the possibility and bright prospect for more hybrid models with better performance indices.
{"title":"A fusion of Functional Networks and Type-2 Fuzzy Logic for the characterization of oil and gas reservoirs","authors":"F. Anifowose, A. Abdulraheem","doi":"10.1109/ICEIE.2010.5559796","DOIUrl":"https://doi.org/10.1109/ICEIE.2010.5559796","url":null,"abstract":"This paper presents a hybrid model consisting of a fusion of Functional Networks and Type-2 Fuzzy Logic. The model capitalizes on the capability of Functional Networks, using its least square fitting algorithm, to reduce the dimensionality of the input data by selecting the most relevant variables for the prediction of porosity and permeability of oil and gas reservoirs. It also attempts to improve the performance of Type-2 Fuzzy Logic whose complexity is increased and performance degraded with increased dimensionality of input data. The Functional Networks block was used to select the dominant variables from six datasets. The dimensionally-reduced datasets were then divided into training and testing subsets using the stratified sampling approach. Hence, the Type-2 Fuzzy Logic block is trained and tested with the best and dimensionally-reduced variables from the input data. The results showed that the hybrid model performed better in terms of training and testing with higher correlation coefficients, lower root mean square errors and reduced execution times than the original Type-2 Fuzzy Logic system. This work has confirmed the possibility and bright prospect for more hybrid models with better performance indices.","PeriodicalId":211301,"journal":{"name":"2010 International Conference on Electronics and Information Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2010-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134590406","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 : 2010-09-02DOI: 10.1109/ICEIE.2010.5559810
Feng Xu, Liang Zhou, H. Wen, Chen Huang, Qian Zhao
With iterative decoding, most LDPC codes have a weakness known as error floor. In this work, we propose a fixed bits LDPC decoding scheme to improve the ability of LDPC transmission. The method is universal as it can be applied to any code/channel model/decoding algorithm and it improves performance greatly, without losing the code regularity, without changing the decoding algorithm. Simulation results show that the error floor performance also can be significantly improved with this decoding scheme.
{"title":"A fixed bits LDPC decoder","authors":"Feng Xu, Liang Zhou, H. Wen, Chen Huang, Qian Zhao","doi":"10.1109/ICEIE.2010.5559810","DOIUrl":"https://doi.org/10.1109/ICEIE.2010.5559810","url":null,"abstract":"With iterative decoding, most LDPC codes have a weakness known as error floor. In this work, we propose a fixed bits LDPC decoding scheme to improve the ability of LDPC transmission. The method is universal as it can be applied to any code/channel model/decoding algorithm and it improves performance greatly, without losing the code regularity, without changing the decoding algorithm. Simulation results show that the error floor performance also can be significantly improved with this decoding scheme.","PeriodicalId":211301,"journal":{"name":"2010 International Conference on Electronics and Information Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2010-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133110000","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 : 2010-09-02DOI: 10.1109/ICEIE.2010.5559907
C. Pornpanomchai, Naret Chantharangsikul
Currently in the rubber factories employ many experts or scientists to grade the Ribbed Smoked Sheet (RSS). They grade the RSS by using their eyes and experience. The objective of this research is to build a computer system that can help rubber experts to grade the RSS. This system is called “Ribbed Smoked Sheet Grading System (RSSGS)”. The system consists of 4 main components, which are 1) Image Acquisition, 2) Image Preprocessing, 3) RSS Grading, and 4) Display of Result. In the image acquisition component, we use a digital camera to take an RSS image in a controlled environment box. In the image preprocessing component, we apply several image processing methods to prepare a suitable RSS image for a grading process. In the RSS grading component, we apply the k-Mean Clustering and the Euclidean Distance method to classify the RSS into five grades, which are RSS1, RSS2, RSS3 RSS4 and RSS5. In the Result Display component, we create a graphic user interface (GUI) for displaying results of the RSS grading. We test the system by using 398 RSS images for a training dataset and another 322 RSS images for an un-training dataset. The precision rates of our RSSGS are 80.90 percent for an untraining dataset. The average access time for the RSSGS is around 10.88 seconds per RSS image.
{"title":"Ribbed Smoked Sheet Grading System (RSSGS)","authors":"C. Pornpanomchai, Naret Chantharangsikul","doi":"10.1109/ICEIE.2010.5559907","DOIUrl":"https://doi.org/10.1109/ICEIE.2010.5559907","url":null,"abstract":"Currently in the rubber factories employ many experts or scientists to grade the Ribbed Smoked Sheet (RSS). They grade the RSS by using their eyes and experience. The objective of this research is to build a computer system that can help rubber experts to grade the RSS. This system is called “Ribbed Smoked Sheet Grading System (RSSGS)”. The system consists of 4 main components, which are 1) Image Acquisition, 2) Image Preprocessing, 3) RSS Grading, and 4) Display of Result. In the image acquisition component, we use a digital camera to take an RSS image in a controlled environment box. In the image preprocessing component, we apply several image processing methods to prepare a suitable RSS image for a grading process. In the RSS grading component, we apply the k-Mean Clustering and the Euclidean Distance method to classify the RSS into five grades, which are RSS1, RSS2, RSS3 RSS4 and RSS5. In the Result Display component, we create a graphic user interface (GUI) for displaying results of the RSS grading. We test the system by using 398 RSS images for a training dataset and another 322 RSS images for an un-training dataset. The precision rates of our RSSGS are 80.90 percent for an untraining dataset. The average access time for the RSSGS is around 10.88 seconds per RSS image.","PeriodicalId":211301,"journal":{"name":"2010 International Conference on Electronics and Information Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2010-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133789006","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 : 2010-09-02DOI: 10.1109/ICEIE.2010.5559739
Mingyue Jiang, Zuohua Ding, Q. Ge
Testing is the last step to check the correctness of a software system. However, due to its incompleteness, we still do not know if the implementation behavior matches the design behavior. In this paper, we provide a new solution for web applications. Since web application has special navigation character, we can get rich information in the log file after testing. From such log file, we extract the Petri net based behavior of the web application. The behavior is then checked by SPIN. Market Information System has been adopted as the case study.
{"title":"Behavior checking of web applications after testing","authors":"Mingyue Jiang, Zuohua Ding, Q. Ge","doi":"10.1109/ICEIE.2010.5559739","DOIUrl":"https://doi.org/10.1109/ICEIE.2010.5559739","url":null,"abstract":"Testing is the last step to check the correctness of a software system. However, due to its incompleteness, we still do not know if the implementation behavior matches the design behavior. In this paper, we provide a new solution for web applications. Since web application has special navigation character, we can get rich information in the log file after testing. From such log file, we extract the Petri net based behavior of the web application. The behavior is then checked by SPIN. Market Information System has been adopted as the case study.","PeriodicalId":211301,"journal":{"name":"2010 International Conference on Electronics and Information Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2010-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116072061","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}
Due to the rapid development of the modern world, the stress is rapid increasing to the human being. For the patients of panic disorder who suffer from hyperventilation syndrome. This study proposes a portable system to monitor the oxygen concentration in the blood, and then provides proper advices for releasing. This system would make the patients feel better when they are in the shadow of panic disorder.
{"title":"A biofeedback portable system for panic disorder","authors":"Ching-Yi Chen, Chekmarev LIu, Ya-Ling Chang, Chih-Yuan Wang, Shih-Tsang Tang, Jiun-Hung Lin","doi":"10.1109/ICEIE.2010.5559840","DOIUrl":"https://doi.org/10.1109/ICEIE.2010.5559840","url":null,"abstract":"Due to the rapid development of the modern world, the stress is rapid increasing to the human being. For the patients of panic disorder who suffer from hyperventilation syndrome. This study proposes a portable system to monitor the oxygen concentration in the blood, and then provides proper advices for releasing. This system would make the patients feel better when they are in the shadow of panic disorder.","PeriodicalId":211301,"journal":{"name":"2010 International Conference on Electronics and Information Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2010-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116172531","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 : 2010-09-02DOI: 10.1109/ICEIE.2010.5559716
Taehee Kim, Jung-Hun Kim, Hee Jeong, M. Lee
In Wireless Sensor Networks (WSNs), each node performs multiple roles, such as sensor, router, and storage. It gathers data from an environment and does not only transfer the data to destinations such as sinks but also store the data in its storage. Therefore, just one node failure can cause malfunctions of various facilities of a WSN. So far, many schemes are proposed to overcome such malfunctions, however, most of them give less consideration to storage-role of nodes, that is, to reserve data safely. Besides, even schemes paying attention to storage-role of nodes are based on impractical assumptions or are suitable to particular cases. In this paper, first, we investigate the data preserving methods of existing schemes and their limitations. Then, we suggest a backup scheme as a solution to overcome such limitations and considering factors for developing a new backup scheme. The considering factors include the followings; the number of backup data, the location of backup data, and data recovery method. Finally, we propose the backup scheme reflecting the considering factors. The proposed scheme can safely preserves data in spite of node failures and consumes reasonable energy. Furthermore, it is suitable well to common WSNs and does not need any impractical assumptions.
{"title":"Fault-tolerant data storage in Wireless Sensor Networks","authors":"Taehee Kim, Jung-Hun Kim, Hee Jeong, M. Lee","doi":"10.1109/ICEIE.2010.5559716","DOIUrl":"https://doi.org/10.1109/ICEIE.2010.5559716","url":null,"abstract":"In Wireless Sensor Networks (WSNs), each node performs multiple roles, such as sensor, router, and storage. It gathers data from an environment and does not only transfer the data to destinations such as sinks but also store the data in its storage. Therefore, just one node failure can cause malfunctions of various facilities of a WSN. So far, many schemes are proposed to overcome such malfunctions, however, most of them give less consideration to storage-role of nodes, that is, to reserve data safely. Besides, even schemes paying attention to storage-role of nodes are based on impractical assumptions or are suitable to particular cases. In this paper, first, we investigate the data preserving methods of existing schemes and their limitations. Then, we suggest a backup scheme as a solution to overcome such limitations and considering factors for developing a new backup scheme. The considering factors include the followings; the number of backup data, the location of backup data, and data recovery method. Finally, we propose the backup scheme reflecting the considering factors. The proposed scheme can safely preserves data in spite of node failures and consumes reasonable energy. Furthermore, it is suitable well to common WSNs and does not need any impractical assumptions.","PeriodicalId":211301,"journal":{"name":"2010 International Conference on Electronics and Information Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2010-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121708129","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}
Anger is a normal, healthy emotion. But when anger gets out of control, it can cause problems in daily life. Anger status can be determined basing on the HRV spectrum, which reflects the interaction of sympathetic and parasympathetic nervous systems. This study developed a portable system for real-time reflecting the user's anger status, which would facilitate the conscious of anger. Moreover help to control the anger release, which would further effectively improve the personal health and life quality.
{"title":"A real-time portable analyzer for anger emotion","authors":"Aibing. Lin, Fan-Yun Yen, Mu-Hui Sun, Feng-Shuo Shang, Shih-Tsang Tang, Jiun-Hung Lin","doi":"10.1109/ICEIE.2010.5559845","DOIUrl":"https://doi.org/10.1109/ICEIE.2010.5559845","url":null,"abstract":"Anger is a normal, healthy emotion. But when anger gets out of control, it can cause problems in daily life. Anger status can be determined basing on the HRV spectrum, which reflects the interaction of sympathetic and parasympathetic nervous systems. This study developed a portable system for real-time reflecting the user's anger status, which would facilitate the conscious of anger. Moreover help to control the anger release, which would further effectively improve the personal health and life quality.","PeriodicalId":211301,"journal":{"name":"2010 International Conference on Electronics and Information Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2010-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123848780","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 : 2010-09-02DOI: 10.1109/ICEIE.2010.5559887
S. Jadhav, S. Nalbalwar, A. Ghatol
In this paper we proposed a automated Artificial Neural Network (ANN) based classification system for cardiac arrhythmia using standard 12 lead ECG recordings. In this study, we are mainly interested in producing high confident arrhythmia classification results to be applicable in diagnostic decision support systems. In arrhythmia analysis, it is unavoidable that some attribute values of a person would be missing. Therefore we have replaced these missing attributes by closest column value of the concern class. Multilayer percepron (MLP) feedforward neural network model with static backpropagation algorithm is used to classify arrhythmia cases into normal and abnormal classes. Networks models are trained and tested for UCI ECG arrhythmia data set. This data set is a good environment to test classifiers as it is incomplete and ambiguous bio-signal data collected from total 452 patient cases. The classification performance is evaluated using six measures; sensitivity, specificity, classification accuracy, mean squared error (MSE), receiver operating characteristics (ROC) and area under curve (AUC). Our experimental results give 86.67% testing classification accuracy.
{"title":"Artificial Neural Network based cardiac arrhythmia classification using ECG signal data","authors":"S. Jadhav, S. Nalbalwar, A. Ghatol","doi":"10.1109/ICEIE.2010.5559887","DOIUrl":"https://doi.org/10.1109/ICEIE.2010.5559887","url":null,"abstract":"In this paper we proposed a automated Artificial Neural Network (ANN) based classification system for cardiac arrhythmia using standard 12 lead ECG recordings. In this study, we are mainly interested in producing high confident arrhythmia classification results to be applicable in diagnostic decision support systems. In arrhythmia analysis, it is unavoidable that some attribute values of a person would be missing. Therefore we have replaced these missing attributes by closest column value of the concern class. Multilayer percepron (MLP) feedforward neural network model with static backpropagation algorithm is used to classify arrhythmia cases into normal and abnormal classes. Networks models are trained and tested for UCI ECG arrhythmia data set. This data set is a good environment to test classifiers as it is incomplete and ambiguous bio-signal data collected from total 452 patient cases. The classification performance is evaluated using six measures; sensitivity, specificity, classification accuracy, mean squared error (MSE), receiver operating characteristics (ROC) and area under curve (AUC). Our experimental results give 86.67% testing classification accuracy.","PeriodicalId":211301,"journal":{"name":"2010 International Conference on Electronics and Information Engineering","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2010-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125194105","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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