Pub Date : 2018-06-01DOI: 10.1109/ICIST.2018.8426179
Mohamed Lamine Bouibed, H. Nemmour, Y. Chibani
In order to take advantage from collections of digitized handwritten documents, effective indexing and retrieval techniques are required. This work focuses on automatic writer retrieval, which is the task of finding in a dataset, all documents written by the same person. Contrary to conventional writer retrieval techniques that are based on dissimilarity measures, we propose to use the SVM classifier to perform the retrieval task. First, local gradient features are used to generate handwritten features. Then, dissimilarities calculated between intra-writer and inter-writer documents are used to train a SVM to allow an automatic retrieval of all the writers documents. Experiments are conducted on CVL and ICDAR 2011 datasets. The performance evaluation of the proposed system is carried out comparatively to the cosine similarity. Results obtained evince a significant improvement offered by SVM, which gives comparable and sometimes better scores than the state of the art.
{"title":"Evaluation of Gradient Descriptors and Dissimilarity Learning for Writer Retrieval","authors":"Mohamed Lamine Bouibed, H. Nemmour, Y. Chibani","doi":"10.1109/ICIST.2018.8426179","DOIUrl":"https://doi.org/10.1109/ICIST.2018.8426179","url":null,"abstract":"In order to take advantage from collections of digitized handwritten documents, effective indexing and retrieval techniques are required. This work focuses on automatic writer retrieval, which is the task of finding in a dataset, all documents written by the same person. Contrary to conventional writer retrieval techniques that are based on dissimilarity measures, we propose to use the SVM classifier to perform the retrieval task. First, local gradient features are used to generate handwritten features. Then, dissimilarities calculated between intra-writer and inter-writer documents are used to train a SVM to allow an automatic retrieval of all the writers documents. Experiments are conducted on CVL and ICDAR 2011 datasets. The performance evaluation of the proposed system is carried out comparatively to the cosine similarity. Results obtained evince a significant improvement offered by SVM, which gives comparable and sometimes better scores than the state of the art.","PeriodicalId":331555,"journal":{"name":"2018 Eighth International Conference on Information Science and Technology (ICIST)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127486194","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/ICIST.2018.8426110
Yu-Hung Lu, Chung-Chih Lin
The rapid aging of the global population has become a topic valued by all countries. At the same time, it also makes the issue of elderly care increasingly important. This paper focuses on elderly care institutions and proposes four care indicators. The four indicators are physiological function tracking, activity domain monitoring, fall prevention, and emergency help. This paper mainly uses smart clothes, BLE components and indoor positioning algorithm for smart elderly care system to collect the data from the residents in their daily life. After collecting the data, we will analyze the data to figure out the indicators we mention above. BLE components also have wearable detection, low power and signal loss warnings from preventing the device problem. Currently, this smart elderly care system is already imported to Taiwan's long-term care institutions.
{"title":"The Study of Smart Elderly Care System","authors":"Yu-Hung Lu, Chung-Chih Lin","doi":"10.1109/ICIST.2018.8426110","DOIUrl":"https://doi.org/10.1109/ICIST.2018.8426110","url":null,"abstract":"The rapid aging of the global population has become a topic valued by all countries. At the same time, it also makes the issue of elderly care increasingly important. This paper focuses on elderly care institutions and proposes four care indicators. The four indicators are physiological function tracking, activity domain monitoring, fall prevention, and emergency help. This paper mainly uses smart clothes, BLE components and indoor positioning algorithm for smart elderly care system to collect the data from the residents in their daily life. After collecting the data, we will analyze the data to figure out the indicators we mention above. BLE components also have wearable detection, low power and signal loss warnings from preventing the device problem. Currently, this smart elderly care system is already imported to Taiwan's long-term care institutions.","PeriodicalId":331555,"journal":{"name":"2018 Eighth International Conference on Information Science and Technology (ICIST)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114168086","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/ICIST.2018.8426157
Saran Chen, Tao Wang, Yanzhe Feng, Zhong Liu, Jincai Huang
Previous studies believe that the individuals who have great social influence play an important role in the collaborative activity. However, in Human Flesh Search (HFS), which is a typical collaborative activity originated from Chinese online social networks, we do not obtain the same conclusion but find that the correlation between social influence and collaborative influence is weak. Specifically, we first construct two networks from the crawling data, i.e., the social network and collaborative network of HFS participants, and quantify social influence and collaborative influence separately. Then we calculate the correlation between social influence and collaborative influence. Furthermore, we obtain three different types of participants by using BIC measure and k-means++ clustering algorithm and calculate the correlation between social influence and collaborative influence among different types. Although there exist differences in different types, all the results show that the correlation between social influence and collaborative influence is weak.
{"title":"Comparing Social Influence with Collaborative Influence in Human Flesh Search","authors":"Saran Chen, Tao Wang, Yanzhe Feng, Zhong Liu, Jincai Huang","doi":"10.1109/ICIST.2018.8426157","DOIUrl":"https://doi.org/10.1109/ICIST.2018.8426157","url":null,"abstract":"Previous studies believe that the individuals who have great social influence play an important role in the collaborative activity. However, in Human Flesh Search (HFS), which is a typical collaborative activity originated from Chinese online social networks, we do not obtain the same conclusion but find that the correlation between social influence and collaborative influence is weak. Specifically, we first construct two networks from the crawling data, i.e., the social network and collaborative network of HFS participants, and quantify social influence and collaborative influence separately. Then we calculate the correlation between social influence and collaborative influence. Furthermore, we obtain three different types of participants by using BIC measure and k-means++ clustering algorithm and calculate the correlation between social influence and collaborative influence among different types. Although there exist differences in different types, all the results show that the correlation between social influence and collaborative influence is weak.","PeriodicalId":331555,"journal":{"name":"2018 Eighth International Conference on Information Science and Technology (ICIST)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121820752","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/ICIST.2018.8426176
Shuai Yuan, B. de Schutter, S. Baldi
This paper studies model reference adaptive control for switched linear systems with large parametric uncertainties. An aggregate leakage approach is proposed to develop a novel adaptive law, which overcomes the state-of-the-art assumption of knowing the upper and lower bounds of the parameter uncertainty. In addition, a switching law is developed based on mode-dependent average dwell time scheme, which exploits the information of the known reference model for every subsystem, i.e., average dwell time is realized in a subsystem sense. Based on the proposed time-constraint scheme, switching signals that are less conservative than those based on dwell time and average dwell time can be designed. Global uniform ultimate boundedness of the closed-loop adaptive switched system is guaranteed. Furthermore, the tracking error is shown to be upper bounded and also an ultimate bound is presented. Simulations using NASA GTM aircraft illustrate the proposed method.
{"title":"Adaptive Tracking Control of Switched Linear Systems Using Mode-Dependent Average Dwell Time","authors":"Shuai Yuan, B. de Schutter, S. Baldi","doi":"10.1109/ICIST.2018.8426176","DOIUrl":"https://doi.org/10.1109/ICIST.2018.8426176","url":null,"abstract":"This paper studies model reference adaptive control for switched linear systems with large parametric uncertainties. An aggregate leakage approach is proposed to develop a novel adaptive law, which overcomes the state-of-the-art assumption of knowing the upper and lower bounds of the parameter uncertainty. In addition, a switching law is developed based on mode-dependent average dwell time scheme, which exploits the information of the known reference model for every subsystem, i.e., average dwell time is realized in a subsystem sense. Based on the proposed time-constraint scheme, switching signals that are less conservative than those based on dwell time and average dwell time can be designed. Global uniform ultimate boundedness of the closed-loop adaptive switched system is guaranteed. Furthermore, the tracking error is shown to be upper bounded and also an ultimate bound is presented. Simulations using NASA GTM aircraft illustrate the proposed method.","PeriodicalId":331555,"journal":{"name":"2018 Eighth International Conference on Information Science and Technology (ICIST)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116822369","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/ICIST.2018.8426188
H. V. Khang, S. Kandukuri, W. Pawlus, K. Robbersmyr
Prediction of machines' faulty parts is important in industrial applications in order to reduce productivity losses. As far as electrical machines are considered, a model-based fault diagnosis approach is usually used for this purpose. The model is derived from the modified winding function theory and hence, it requires a considerable amount of parameters at various operating conditions in order to be successfully used. However, the complete set of parameters is difficult to be obtained, as manufacturers of electric machines normally provide only the parameters that describe simple motor models (e.g. T-equivalent circuit at rated conditions). Therefore, the current work presents a method that can be used to estimate more detailed motor parameters. In addition, these parameters are then used in an expanded induction motor model which, in turn, is applied to study severity of a broken bar fault in an induction machine.
{"title":"Parameter Identification of a Winding Function Based Model for Fault Detection of Induction Machines","authors":"H. V. Khang, S. Kandukuri, W. Pawlus, K. Robbersmyr","doi":"10.1109/ICIST.2018.8426188","DOIUrl":"https://doi.org/10.1109/ICIST.2018.8426188","url":null,"abstract":"Prediction of machines' faulty parts is important in industrial applications in order to reduce productivity losses. As far as electrical machines are considered, a model-based fault diagnosis approach is usually used for this purpose. The model is derived from the modified winding function theory and hence, it requires a considerable amount of parameters at various operating conditions in order to be successfully used. However, the complete set of parameters is difficult to be obtained, as manufacturers of electric machines normally provide only the parameters that describe simple motor models (e.g. T-equivalent circuit at rated conditions). Therefore, the current work presents a method that can be used to estimate more detailed motor parameters. In addition, these parameters are then used in an expanded induction motor model which, in turn, is applied to study severity of a broken bar fault in an induction machine.","PeriodicalId":331555,"journal":{"name":"2018 Eighth International Conference on Information Science and Technology (ICIST)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123445313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/ICIST.2018.8426082
Gaosheng Zhang, Qichao Ma, Jiahu Qin, Yu Kang, W. Zheng
This paper investigates the fault tolerant consensus problem for a class of nonlinear multi-agent systems with actuator faults. The dynamics of the multi-agent systems are unknown nonlinear and nonidentical. The types of actuator fault include partial loss of effectiveness fault and biased fault. The main idea of the fault tolerant control adopted in this paper is the adaptive control. The control method used is a neural network based adaptive control which has a better adaptability than the traditional adaptive control. The developed adaptive neural network consensus protocol is proved to perform well with respect to the system nonlinear dynamics and actuator faults of the agent. Finally, numerical simulation on multi-agent system of four Chen's chaotic systems is performed to illustrate the effectiveness of the investigated adaptive neural network consensus protocol.
{"title":"Adaptive Neural Network Control for Consensus of Nonlinear Multi-Agent Systems with Actuator Faults","authors":"Gaosheng Zhang, Qichao Ma, Jiahu Qin, Yu Kang, W. Zheng","doi":"10.1109/ICIST.2018.8426082","DOIUrl":"https://doi.org/10.1109/ICIST.2018.8426082","url":null,"abstract":"This paper investigates the fault tolerant consensus problem for a class of nonlinear multi-agent systems with actuator faults. The dynamics of the multi-agent systems are unknown nonlinear and nonidentical. The types of actuator fault include partial loss of effectiveness fault and biased fault. The main idea of the fault tolerant control adopted in this paper is the adaptive control. The control method used is a neural network based adaptive control which has a better adaptability than the traditional adaptive control. The developed adaptive neural network consensus protocol is proved to perform well with respect to the system nonlinear dynamics and actuator faults of the agent. Finally, numerical simulation on multi-agent system of four Chen's chaotic systems is performed to illustrate the effectiveness of the investigated adaptive neural network consensus protocol.","PeriodicalId":331555,"journal":{"name":"2018 Eighth International Conference on Information Science and Technology (ICIST)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115805330","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/ICIST.2018.8426168
Shuquan Ye, Zhiwen Yu, Jiaying Lin, Kaixiang Yang, Dan Dai, Zhi-hui Zhan, Wei-neng Chen, Jun Zhang
Random forest (RF) is a competitive machine learning theorem, while one of the big challenges for it is imbalanced real-world data. A Two-dimensional-reduction RF (2DRRF) is presented in this paper, which is optimized based on traditional RF and three innovation points as follows. To improve RF in terms of performance on imbalanced data, a two-dimensional-reduction approach is created. Then, a modified T-link is proposed focusing on detecting and reducing safe samples. Moreover, a biased sampling manner is employed to build up optimal training datasets. Across 13 imbalanced datasets from KEEL-dataset with imbalance-ratio ranging from 6.38 to 129.44, experiments are carried out indicating that 2DRRF steadily holds advantages over the other two relevant implementations of RF in terms of accuracy, recall, precision and F-value.
{"title":"Two-Dimensional-Reduction Random Forest","authors":"Shuquan Ye, Zhiwen Yu, Jiaying Lin, Kaixiang Yang, Dan Dai, Zhi-hui Zhan, Wei-neng Chen, Jun Zhang","doi":"10.1109/ICIST.2018.8426168","DOIUrl":"https://doi.org/10.1109/ICIST.2018.8426168","url":null,"abstract":"Random forest (RF) is a competitive machine learning theorem, while one of the big challenges for it is imbalanced real-world data. A Two-dimensional-reduction RF (2DRRF) is presented in this paper, which is optimized based on traditional RF and three innovation points as follows. To improve RF in terms of performance on imbalanced data, a two-dimensional-reduction approach is created. Then, a modified T-link is proposed focusing on detecting and reducing safe samples. Moreover, a biased sampling manner is employed to build up optimal training datasets. Across 13 imbalanced datasets from KEEL-dataset with imbalance-ratio ranging from 6.38 to 129.44, experiments are carried out indicating that 2DRRF steadily holds advantages over the other two relevant implementations of RF in terms of accuracy, recall, precision and F-value.","PeriodicalId":331555,"journal":{"name":"2018 Eighth International Conference on Information Science and Technology (ICIST)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125895292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/ICIST.2018.8426119
Yi Huang, Rui Hu, Z. Zeng
Although the Capsule Network (CapsNet) has a better proven performance for the recognition of overlapping digits than Convolutional Neural Networks (CNNs), a large number of matrix-vector multiplications between lower-level and higher-level capsules impede efficient implementation of the CapsNet on conventional hardware platforms. Since three-dimensional (3-D) memristor crossbars provide a compact and parallel hardware implementation of neural networks, this paper provides an architecture design to accelerate convolutional and matrix operations of the CapsNet. By using 3-D memristor crossbars, the PrimaryCaps, DigitCaps, and convolutional layers of a CapsNet perform the matrix-vector multiplications in a highly parallel way. Simulations are conducted to recognize digits from the USPS database and to analyse the work efficiency of the proposed circuits. The proposed design provides a new approach to implement the CapsNet on memristor-based circuits.
{"title":"Three-Dimensional Memristor-Based Crossbar Architecture for Capsule Network Implementation","authors":"Yi Huang, Rui Hu, Z. Zeng","doi":"10.1109/ICIST.2018.8426119","DOIUrl":"https://doi.org/10.1109/ICIST.2018.8426119","url":null,"abstract":"Although the Capsule Network (CapsNet) has a better proven performance for the recognition of overlapping digits than Convolutional Neural Networks (CNNs), a large number of matrix-vector multiplications between lower-level and higher-level capsules impede efficient implementation of the CapsNet on conventional hardware platforms. Since three-dimensional (3-D) memristor crossbars provide a compact and parallel hardware implementation of neural networks, this paper provides an architecture design to accelerate convolutional and matrix operations of the CapsNet. By using 3-D memristor crossbars, the PrimaryCaps, DigitCaps, and convolutional layers of a CapsNet perform the matrix-vector multiplications in a highly parallel way. Simulations are conducted to recognize digits from the USPS database and to analyse the work efficiency of the proposed circuits. The proposed design provides a new approach to implement the CapsNet on memristor-based circuits.","PeriodicalId":331555,"journal":{"name":"2018 Eighth International Conference on Information Science and Technology (ICIST)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130775490","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2018-06-01DOI: 10.1109/ICIST.2018.8426182
Xinming Shi, Z. Zeng
Adaptive firing rate of neuron plays an indispensable role in stabilizing the neural system, which means that the firing rate of neuron could be adjusted adaptively within an inherent range. In this paper, two aspects of implementing the adaptive firing rate are proposed at the circuit level. First, a memristor model is used in the neuron circuit to represent membrane sensitivity. Second, the threshold voltage of neuron circuit can be adjusted adaptively to change the firing rate. Combined these two methods, the adaptive firing rate of neuron circuit is realized effectively, which is in accordance with its biological counterpart. Furthermore, the proposed neuron circuit is applied in the spiking neural network to verify its functionality, where pattern recognition could be realized. All the simulations are carried out on PSPICE.
{"title":"Memristor-Based Neuron Circuit with Adaptive Firing Rate","authors":"Xinming Shi, Z. Zeng","doi":"10.1109/ICIST.2018.8426182","DOIUrl":"https://doi.org/10.1109/ICIST.2018.8426182","url":null,"abstract":"Adaptive firing rate of neuron plays an indispensable role in stabilizing the neural system, which means that the firing rate of neuron could be adjusted adaptively within an inherent range. In this paper, two aspects of implementing the adaptive firing rate are proposed at the circuit level. First, a memristor model is used in the neuron circuit to represent membrane sensitivity. Second, the threshold voltage of neuron circuit can be adjusted adaptively to change the firing rate. Combined these two methods, the adaptive firing rate of neuron circuit is realized effectively, which is in accordance with its biological counterpart. Furthermore, the proposed neuron circuit is applied in the spiking neural network to verify its functionality, where pattern recognition could be realized. All the simulations are carried out on PSPICE.","PeriodicalId":331555,"journal":{"name":"2018 Eighth International Conference on Information Science and Technology (ICIST)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132615345","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}
This paper is concerned with the issues of weighted H∞ performance of a class of stochastic switched affine nonlinear systems. The stochastic system considered in the literature is with state dependent noise. The switching strategy is about mode-dependent average dwell time (MDADT) approach, which is more general than the average dwell time (ADT) approach by considering each subsystem with its own ADT. A sufficient condition is obtained to guarantee the considered system with all stable subsystems achieve the exponential stability in mean square sense and a weighted H∞ performance. Finally, some remarks concludes this paper.
{"title":"Weighted H∞ Performance Analysis of Nonlinear Stochastic Switched Systems with State Dependent Noise: A Mode-Dependent Average Dwell Time Method","authors":"Xiushan Jiang, Senping Tian, Tianliang Zhang, Weihai Zhang","doi":"10.1109/ICIST.2018.8426073","DOIUrl":"https://doi.org/10.1109/ICIST.2018.8426073","url":null,"abstract":"This paper is concerned with the issues of weighted H∞ performance of a class of stochastic switched affine nonlinear systems. The stochastic system considered in the literature is with state dependent noise. The switching strategy is about mode-dependent average dwell time (MDADT) approach, which is more general than the average dwell time (ADT) approach by considering each subsystem with its own ADT. A sufficient condition is obtained to guarantee the considered system with all stable subsystems achieve the exponential stability in mean square sense and a weighted H∞ performance. Finally, some remarks concludes this paper.","PeriodicalId":331555,"journal":{"name":"2018 Eighth International Conference on Information Science and Technology (ICIST)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2018-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133219340","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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