Routing is a very challenging task in opportunistic networks due to the lack of continuous end-to-end path between nodes. To improve the routing performance, a type of community-based routing protocol is presented. This routing generally turns to the social attributes of nodes to construct the community, and utilizes community characteristics (nodes within the same community come in contact with each other more frequently) to select the relay nodes and make the forwarding decisions. Unfortunately, this routing has a problem of transmission bottleneck between communities. To address this issue, we propose an enhanced community-based routing assisted by ferry in opportunistic networks. This routing resorts to some super-nodes as ferry nodes to ferry messages between communities in order to overcome the network division. The simulation results demonstrate the efficiency and effectiveness of the proposed scheme by comparing it with existing routing schemes.
{"title":"An Enhanced Community-Based Routing with Ferry in Opportunistic Networks","authors":"Weimin Chen, Zhigang Chen, Wenjia Li, Feng Zeng","doi":"10.1109/IIKI.2016.8","DOIUrl":"https://doi.org/10.1109/IIKI.2016.8","url":null,"abstract":"Routing is a very challenging task in opportunistic networks due to the lack of continuous end-to-end path between nodes. To improve the routing performance, a type of community-based routing protocol is presented. This routing generally turns to the social attributes of nodes to construct the community, and utilizes community characteristics (nodes within the same community come in contact with each other more frequently) to select the relay nodes and make the forwarding decisions. Unfortunately, this routing has a problem of transmission bottleneck between communities. To address this issue, we propose an enhanced community-based routing assisted by ferry in opportunistic networks. This routing resorts to some super-nodes as ferry nodes to ferry messages between communities in order to overcome the network division. The simulation results demonstrate the efficiency and effectiveness of the proposed scheme by comparing it with existing routing schemes.","PeriodicalId":371106,"journal":{"name":"2016 International Conference on Identification, Information and Knowledge in the Internet of Things (IIKI)","volume":"34 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":"115716795","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}
Kun Li, Junsheng Zhang, Changqing Yao, Chongde Shi
Relation extraction is an important task for understanding text. In the big data era, automatic relation extraction from unstructured texts is urgently needed for structured information organization and information analysis. In this paper, we survey the automatic relation extraction methods, especially the traditional machine learning on closed data set and open information environment such as Web, including supervised and semi-supervised methods. And then, we discuss the applications based on relation extraction such as event extraction and QA systems.
{"title":"Automatic Relation Extraction from Text: A Survey","authors":"Kun Li, Junsheng Zhang, Changqing Yao, Chongde Shi","doi":"10.1109/IIKI.2016.58","DOIUrl":"https://doi.org/10.1109/IIKI.2016.58","url":null,"abstract":"Relation extraction is an important task for understanding text. In the big data era, automatic relation extraction from unstructured texts is urgently needed for structured information organization and information analysis. In this paper, we survey the automatic relation extraction methods, especially the traditional machine learning on closed data set and open information environment such as Web, including supervised and semi-supervised methods. And then, we discuss the applications based on relation extraction such as event extraction and QA systems.","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":"126304034","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 introduces the imaging formula in bistatic radar cross section (RCS) measurement at first. Then the bistatic angle’s impact on imaging performance and the features of two typical bistatic RCS measurement modes are explored based on the shape of the corresponding Fourier transform spectrum domain (k-space). Finally simulation data of ideal points is used to verify our conclusions.
{"title":"Study of Bistatic Angle's Impact on Imaging Performance in Bistatic RCS Measurement","authors":"Ming Lyu, Chao Gao","doi":"10.1109/IIKI.2016.105","DOIUrl":"https://doi.org/10.1109/IIKI.2016.105","url":null,"abstract":"This paper introduces the imaging formula in bistatic radar cross section (RCS) measurement at first. Then the bistatic angle’s impact on imaging performance and the features of two typical bistatic RCS measurement modes are explored based on the shape of the corresponding Fourier transform spectrum domain (k-space). Finally simulation data of ideal points is used to verify our conclusions.","PeriodicalId":371106,"journal":{"name":"2016 International Conference on Identification, Information and Knowledge in the Internet of Things (IIKI)","volume":"2 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":"125223463","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}
As the amount of target characteristics data increasing rapidly, the tradition methods cannot satisfy the need of the storage and management of those data. According to the features of those data, a new storage system is proposed base on RDBMS and Hadoop. The structured data and the metadata of unstructured data is stored in the RDBMS under certain schema, while the large amount of unstructured one allocated among numbers of nodes in the hadoop cluster. In order to maximize the superiority of storage, the HBase is used for storing massive small-size unstructured data and the HDFS is applied for holding the large-scale ones. Meanwhile, the access control and the multi-thread upload and download approach combined with load balancing and caching mechanism is applied for improving the efficiency of data transmission. Experiment results show that the proposed storage system is reasonable and practicable.
{"title":"Research of Target Characteristics Storage Based on RDBMS and Hadoop","authors":"Yanqi Wang, Yusheng Jia, Xiaodan Xie","doi":"10.1109/IIKI.2016.33","DOIUrl":"https://doi.org/10.1109/IIKI.2016.33","url":null,"abstract":"As the amount of target characteristics data increasing rapidly, the tradition methods cannot satisfy the need of the storage and management of those data. According to the features of those data, a new storage system is proposed base on RDBMS and Hadoop. The structured data and the metadata of unstructured data is stored in the RDBMS under certain schema, while the large amount of unstructured one allocated among numbers of nodes in the hadoop cluster. In order to maximize the superiority of storage, the HBase is used for storing massive small-size unstructured data and the HDFS is applied for holding the large-scale ones. Meanwhile, the access control and the multi-thread upload and download approach combined with load balancing and caching mechanism is applied for improving the efficiency of data transmission. Experiment results show that the proposed storage system is reasonable and practicable.","PeriodicalId":371106,"journal":{"name":"2016 International Conference on Identification, Information and Knowledge in the Internet of Things (IIKI)","volume":"42 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":"134128619","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}
Zhongqiu Ji, Huihui Wang, Guiping Jiang, Xulong Li, Lin Li
The test system was to study balance control strategy during an unexpected slip and the adaptive change to balance perturbation. This study performed slip tests on 10 healthy male students (age: 20.0±1.6 years, height: 1.72±0.05 m, mass: 64.67±9.81 kg) using the test system, Kinematics and kinetic date analyses using the Ariel video analysis system and Kistler force platform were performed. When the subject encountering an unexpected backward slip during sit-to-stand, people will take a backward recovery step and increase the maximum rising velocity of the hip joint by strong support against a backward slip. After balance perturbation training, similar to balance perturbation intensity, the amplitude of the balance adjustment decreased significantly. People can maintain their balance by swinging their trunk and arm.
{"title":"A Computer Simulation System Used for Analyzing Balance Control Strategy during an Unexpected Slip","authors":"Zhongqiu Ji, Huihui Wang, Guiping Jiang, Xulong Li, Lin Li","doi":"10.1109/IIKI.2016.40","DOIUrl":"https://doi.org/10.1109/IIKI.2016.40","url":null,"abstract":"The test system was to study balance control strategy during an unexpected slip and the adaptive change to balance perturbation. This study performed slip tests on 10 healthy male students (age: 20.0±1.6 years, height: 1.72±0.05 m, mass: 64.67±9.81 kg) using the test system, Kinematics and kinetic date analyses using the Ariel video analysis system and Kistler force platform were performed. When the subject encountering an unexpected backward slip during sit-to-stand, people will take a backward recovery step and increase the maximum rising velocity of the hip joint by strong support against a backward slip. After balance perturbation training, similar to balance perturbation intensity, the amplitude of the balance adjustment decreased significantly. People can maintain their balance by swinging their trunk and arm.","PeriodicalId":371106,"journal":{"name":"2016 International Conference on Identification, Information and Knowledge in the Internet of Things (IIKI)","volume":"18 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":"115092206","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}
Shuaijing Xu, Guangzhi Zhang, R. Bie, Wenshuang Liang, Cheonshik Kim, Dongkyoo Shin
Rapid development of computer and network technology has greatly promoted the biological information science. People have made satisfactory achievements in the study of high-throughput interaction map and pathogenic gene identification, and have been able to verify the candidate associations between genes and disease. However, a large amount of implicit knowledge between diseases, symptoms and genes have not been discovered. With the arrival of the age of big data, the number and variety of biomedical data sets have had a huge breakthrough. The rapid growth of biomedical big data provides the possibility of discovering biomedical implied relationship and assessing the strength association between entities. This paper puts forward an implicit association mining algorithm combining Monte Carlo method with the Newton's law of cooling. The algorithm synthesizes path, known-correlation intensity and dynamic changes of associated network topology. It can effectively find out potential and meaningful association between biomedical entities, and can evaluate the strength of the association based on probability.
{"title":"Implicit Correlation Intensity Mining Based on the Monte Carlo Method with Attenuation","authors":"Shuaijing Xu, Guangzhi Zhang, R. Bie, Wenshuang Liang, Cheonshik Kim, Dongkyoo Shin","doi":"10.1109/IIKI.2016.23","DOIUrl":"https://doi.org/10.1109/IIKI.2016.23","url":null,"abstract":"Rapid development of computer and network technology has greatly promoted the biological information science. People have made satisfactory achievements in the study of high-throughput interaction map and pathogenic gene identification, and have been able to verify the candidate associations between genes and disease. However, a large amount of implicit knowledge between diseases, symptoms and genes have not been discovered. With the arrival of the age of big data, the number and variety of biomedical data sets have had a huge breakthrough. The rapid growth of biomedical big data provides the possibility of discovering biomedical implied relationship and assessing the strength association between entities. This paper puts forward an implicit association mining algorithm combining Monte Carlo method with the Newton's law of cooling. The algorithm synthesizes path, known-correlation intensity and dynamic changes of associated network topology. It can effectively find out potential and meaningful association between biomedical entities, and can evaluate the strength of the association based on probability.","PeriodicalId":371106,"journal":{"name":"2016 International Conference on Identification, Information and Knowledge in the Internet of Things (IIKI)","volume":"29 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":"114259314","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}
Recommender systems have been applied by E-commerce or other application sites to recommend their produces that customers might be interested in. This paper refines a bipartite graph to a two-layer graph model by adding the similarity information between consumers and products, the related metric is presented to measure the relationship among them, and the shortest path algorithm is introduced to obtain suitable recommendations.
{"title":"An Algorithm Based on Two-Layer Graph Model for E-Commerce Recommendation","authors":"Li Pan, Xiaosha Xu, Zhimeng Tan, Xin Peng","doi":"10.1109/IIKI.2016.53","DOIUrl":"https://doi.org/10.1109/IIKI.2016.53","url":null,"abstract":"Recommender systems have been applied by E-commerce or other application sites to recommend their produces that customers might be interested in. This paper refines a bipartite graph to a two-layer graph model by adding the similarity information between consumers and products, the related metric is presented to measure the relationship among them, and the shortest path algorithm is introduced to obtain suitable recommendations.","PeriodicalId":371106,"journal":{"name":"2016 International Conference on Identification, Information and Knowledge in the Internet of Things (IIKI)","volume":"56 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":"124749875","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}
Jie Zhang, Zhiyuan Li, Yidou You, R. Huang, Jin Liu, Xu Chen
AsterixDB Big Data Management System isone of the non-relational databases, developed and researched by researcher in UC Irvine, UC Riverside, andUC San Diego. One of the basic storage structures of AsterixDB is a log structured merge tree, and the log structured merge tree cannot get away from merging operations. When we research in this project closely, we foundthat a better merge policy helps improve the CURD performance of log structured merge tree in a great level. The existing merging policies show a lot of drawbackswhen data size gets bigger and bigger. Our method aimsat optimizing merge policy utilizing a new scheduler–Level Scheduler which was proposed in [6]. Experimentsshow that our merge algorithm is much more efficient.
{"title":"Optimization of Merge Policy in AsterixDB Big Data Management System","authors":"Jie Zhang, Zhiyuan Li, Yidou You, R. Huang, Jin Liu, Xu Chen","doi":"10.1109/IIKI.2016.29","DOIUrl":"https://doi.org/10.1109/IIKI.2016.29","url":null,"abstract":"AsterixDB Big Data Management System isone of the non-relational databases, developed and researched by researcher in UC Irvine, UC Riverside, andUC San Diego. One of the basic storage structures of AsterixDB is a log structured merge tree, and the log structured merge tree cannot get away from merging operations. When we research in this project closely, we foundthat a better merge policy helps improve the CURD performance of log structured merge tree in a great level. The existing merging policies show a lot of drawbackswhen data size gets bigger and bigger. Our method aimsat optimizing merge policy utilizing a new scheduler–Level Scheduler which was proposed in [6]. Experimentsshow that our merge algorithm is much more efficient.","PeriodicalId":371106,"journal":{"name":"2016 International Conference on Identification, Information and Knowledge in the Internet of Things (IIKI)","volume":"27 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":"123708759","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 with the correlation between two different stocks, the model of Stock Social Network (SSN) is proposed to represent and analyze the intrinsic complex relationship. We choose 313 stocks from 9 industries to build an evolution model of SSN, which predicted that some stocks clusters are isolated and the nodes and edges in SSN are decreasing distinctly step by step with the change of threshold δ from 0.7, 0.75 and 0.8, respectively. Meanwhile, the coverage rate of nodes in SSN arrives 0.2076 at δ = 0.8, in reverse, the 79.24% nodes is trimmed during the process of evolution of SSN. Based on these results, we design a new portfolio strategy based on new index, named CSSNI, to optimize the asset pricing model. The results show that the ratio of return is 0.92666 based on the CSSNI, which is much better than the result by traditional strategy.
{"title":"Social Network-Based Stock Correlation Analysis and Prediction","authors":"Y. Rao, Xuhui Zhong, Shumin Lu","doi":"10.1109/IIKI.2016.102","DOIUrl":"https://doi.org/10.1109/IIKI.2016.102","url":null,"abstract":"In order to forecast the price movement with the correlation between two different stocks, the model of Stock Social Network (SSN) is proposed to represent and analyze the intrinsic complex relationship. We choose 313 stocks from 9 industries to build an evolution model of SSN, which predicted that some stocks clusters are isolated and the nodes and edges in SSN are decreasing distinctly step by step with the change of threshold δ from 0.7, 0.75 and 0.8, respectively. Meanwhile, the coverage rate of nodes in SSN arrives 0.2076 at δ = 0.8, in reverse, the 79.24% nodes is trimmed during the process of evolution of SSN. Based on these results, we design a new portfolio strategy based on new index, named CSSNI, to optimize the asset pricing model. The results show that the ratio of return is 0.92666 based on the CSSNI, which is much better than the result by traditional strategy.","PeriodicalId":371106,"journal":{"name":"2016 International Conference on Identification, Information and Knowledge in the Internet of Things (IIKI)","volume":"273 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":"130594373","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}
Mobile opportunistic networks can effectively improve network resource utilities and system performance. In this paper, we propose a cooperation-based routing algorithm to achieve mobile opportunistic communications. To this end, mobile agent nodes are designed to attain information sensitivity and remaining energy of the cluster nodes. For the neighbor cluster nodes with remaining energy and information sensitivity being best among other neighbor cluster nodes, we select them as the next cluster nodes acting as mobile agent nodes. Through the cooperation, the information about node's remaining energy and information sensitivity is shared among nodes. In this way, the optimal multi-hop forwarding routing can be established to adapt to the locally changing network topology. At the same time, network nodes can have more opportunities to access networks. Simulation results show that our approach is effective.
{"title":"A Cooperation-Based Routing Algorithm in Mobile Opportunistic Networks","authors":"Yao Fu, Dingde Jiang, Deyu Zhang, Houbing Song, Hongyuan Wang, Xiaoping Zhou","doi":"10.1109/IIKI.2016.1","DOIUrl":"https://doi.org/10.1109/IIKI.2016.1","url":null,"abstract":"Mobile opportunistic networks can effectively improve network resource utilities and system performance. In this paper, we propose a cooperation-based routing algorithm to achieve mobile opportunistic communications. To this end, mobile agent nodes are designed to attain information sensitivity and remaining energy of the cluster nodes. For the neighbor cluster nodes with remaining energy and information sensitivity being best among other neighbor cluster nodes, we select them as the next cluster nodes acting as mobile agent nodes. Through the cooperation, the information about node's remaining energy and information sensitivity is shared among nodes. In this way, the optimal multi-hop forwarding routing can be established to adapt to the locally changing network topology. At the same time, network nodes can have more opportunities to access networks. Simulation results show that our approach is effective.","PeriodicalId":371106,"journal":{"name":"2016 International Conference on Identification, Information and Knowledge in the Internet of Things (IIKI)","volume":"3 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":"127902366","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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