Pub Date : 2016-08-01DOI: 10.1109/ICSESS.2016.7883175
Wenjun Zhang, Jincai Lin, Ning Jia
A dual-wavelength erbium-doped fiber laser (DW-EDFL) which can output double wavelengths of 1530nm, and 1550nm is proposed in this paper. The optimal condition for optimum output power of two wavelengths is extracted and demonstrated. When the length of EDFL is 4.13m the output power of the two wavelengths can reach 2mW. Additionally, two variable optical attenuators (VOA) are used to balance gain and loss of two signal lights in the ring resonator.
{"title":"A dual-wavelength erbium-doped fiber laser based on annular cavity","authors":"Wenjun Zhang, Jincai Lin, Ning Jia","doi":"10.1109/ICSESS.2016.7883175","DOIUrl":"https://doi.org/10.1109/ICSESS.2016.7883175","url":null,"abstract":"A dual-wavelength erbium-doped fiber laser (DW-EDFL) which can output double wavelengths of 1530nm, and 1550nm is proposed in this paper. The optimal condition for optimum output power of two wavelengths is extracted and demonstrated. When the length of EDFL is 4.13m the output power of the two wavelengths can reach 2mW. Additionally, two variable optical attenuators (VOA) are used to balance gain and loss of two signal lights in the ring resonator.","PeriodicalId":175933,"journal":{"name":"2016 7th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124404493","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 : 2016-08-01DOI: 10.1109/ICSESS.2016.7883022
Zhao Yang, Rongjing Hu, Ruisheng Zhang
human life is more and more dependent on the safety, reliability and effective operation of a variety of complex networks; however, most of networks are sparse, which means the network data is incomplete. To solve the problem, various link prediction methods have been proposed to find missing links in given networks. Among these methods, similarity-based methods are effective, however, still imperfect. In order to improve the predicting results, we combined local and global information of the network and then proposed a method based on one of similarity-based methods with community information. Experiments results show that the inclusion of community information improves the accuracy of results of predicting missing links.
{"title":"An improved link prediction algorithm based on common neighbors index with community membership information","authors":"Zhao Yang, Rongjing Hu, Ruisheng Zhang","doi":"10.1109/ICSESS.2016.7883022","DOIUrl":"https://doi.org/10.1109/ICSESS.2016.7883022","url":null,"abstract":"human life is more and more dependent on the safety, reliability and effective operation of a variety of complex networks; however, most of networks are sparse, which means the network data is incomplete. To solve the problem, various link prediction methods have been proposed to find missing links in given networks. Among these methods, similarity-based methods are effective, however, still imperfect. In order to improve the predicting results, we combined local and global information of the network and then proposed a method based on one of similarity-based methods with community information. Experiments results show that the inclusion of community information improves the accuracy of results of predicting missing links.","PeriodicalId":175933,"journal":{"name":"2016 7th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127925628","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}
With the rapid development of regional economy in Shandong Province, the demand of electric power increases rapidly. So, the development of the substation construction and its status information detection system has led to the massive power equipment status information data, which needs to be sorted out and standardized work. In this paper, the MapReduce technology is used for the degradation processing of monitor information according to the station control layer, bay layer and process layer; meanwhile, the voltage level of substation is used as the breakthrough point, and the similar or same monitoring information is combined and processed. Compared with the traditional method of processing power equipment monitoring information on cluster computer platform, the MapReduce technique can be verified to achieve monitoring data simplification, recursive and transplantation in substation monitoring and control information cloud platform. It could improve work efficiency in the three aspects of utility value, completion time and load balance.
{"title":"Optimized design of hierarchical substation monitoring information based on MapReduce technology","authors":"Shaoxiao Han, Xianghua Pan, Chen Li, Shengyuan Gao","doi":"10.1109/ICSESS.2016.7883204","DOIUrl":"https://doi.org/10.1109/ICSESS.2016.7883204","url":null,"abstract":"With the rapid development of regional economy in Shandong Province, the demand of electric power increases rapidly. So, the development of the substation construction and its status information detection system has led to the massive power equipment status information data, which needs to be sorted out and standardized work. In this paper, the MapReduce technology is used for the degradation processing of monitor information according to the station control layer, bay layer and process layer; meanwhile, the voltage level of substation is used as the breakthrough point, and the similar or same monitoring information is combined and processed. Compared with the traditional method of processing power equipment monitoring information on cluster computer platform, the MapReduce technique can be verified to achieve monitoring data simplification, recursive and transplantation in substation monitoring and control information cloud platform. It could improve work efficiency in the three aspects of utility value, completion time and load balance.","PeriodicalId":175933,"journal":{"name":"2016 7th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114893905","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 : 2016-08-01DOI: 10.1109/ICSESS.2016.7883135
Z. Chunsheng, Li Yan
Visual data mining techniques can display the process of data mining and results to the user graphically, which makes the user more perceptual and easy to understand the meaning of the mining process and its results and moreover it is very important in data mining. However, most of the visual data mining now is progressed with the result of visualization. At the same time, it is not suitable for the graphical display to the visualization processing of the association rule. In view of the above shortcomings, in this paper, the whole mining process of Apriori association rule is visually conducted under the natural language by the way of the natural language processing method, including data preprocessing, mining process and the visualization display of mining results which provides an integrate set of schemes for the user with characteristics of being more perceptual and more easy to understand.
{"title":"The visual mining method of Apriori association rule based on natural language","authors":"Z. Chunsheng, Li Yan","doi":"10.1109/ICSESS.2016.7883135","DOIUrl":"https://doi.org/10.1109/ICSESS.2016.7883135","url":null,"abstract":"Visual data mining techniques can display the process of data mining and results to the user graphically, which makes the user more perceptual and easy to understand the meaning of the mining process and its results and moreover it is very important in data mining. However, most of the visual data mining now is progressed with the result of visualization. At the same time, it is not suitable for the graphical display to the visualization processing of the association rule. In view of the above shortcomings, in this paper, the whole mining process of Apriori association rule is visually conducted under the natural language by the way of the natural language processing method, including data preprocessing, mining process and the visualization display of mining results which provides an integrate set of schemes for the user with characteristics of being more perceptual and more easy to understand.","PeriodicalId":175933,"journal":{"name":"2016 7th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130814020","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 : 2016-08-01DOI: 10.1109/ICSESS.2016.7883232
Yao Zhong-hua, Wu Lingda
Visual analysis on network security is a new area, it consists methods and technology of visualization and network security analysis, which has new challenges. Researchers on network security visualization have done certain extent research and accumulated much. Especially with the rapid development of visual analysis, visual network security analysis achieved rich results in recent years. However, there is less study on basic research framework and principle of security visualization analysis, this dissertation summarizes concerned problems in the field of security analysis, data sources, visual analysis techniques and related overview of visual analysis system. Through analysis of these systems, network security visualization on the research questions can be tested and directions for future research can be provided.
{"title":"Summary on network security visual analysis","authors":"Yao Zhong-hua, Wu Lingda","doi":"10.1109/ICSESS.2016.7883232","DOIUrl":"https://doi.org/10.1109/ICSESS.2016.7883232","url":null,"abstract":"Visual analysis on network security is a new area, it consists methods and technology of visualization and network security analysis, which has new challenges. Researchers on network security visualization have done certain extent research and accumulated much. Especially with the rapid development of visual analysis, visual network security analysis achieved rich results in recent years. However, there is less study on basic research framework and principle of security visualization analysis, this dissertation summarizes concerned problems in the field of security analysis, data sources, visual analysis techniques and related overview of visual analysis system. Through analysis of these systems, network security visualization on the research questions can be tested and directions for future research can be provided.","PeriodicalId":175933,"journal":{"name":"2016 7th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"121 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130827089","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 : 2016-08-01DOI: 10.1109/ICSESS.2016.7883031
Hamdi A. Al-Jamimi
Software defect prediction is a discipline that predicts the defects proneness of future modules. Software metrics are used for this kind of predication. However, the predication metrics are associated with uncertainty, thus the metrics need to be expressed in linguistic terms to overcome ambiguity and uncertainty. Two types of knowledge are utilized as input to the prediction models: software metrics and expert's opinions. This paper proposes a framework for developing fuzzy logic-based software predication model using different set of software metrics. It aims to provide a generic set of metrics to be used for software defects prediction. The performance of the proposed Fuzzy-based models has been validated using real software projects data where Takagi-Sugeno fuzzy inference engine is used to predict software defects. Validation results are satisfactory.
{"title":"Toward comprehensible software defect prediction models using fuzzy logic","authors":"Hamdi A. Al-Jamimi","doi":"10.1109/ICSESS.2016.7883031","DOIUrl":"https://doi.org/10.1109/ICSESS.2016.7883031","url":null,"abstract":"Software defect prediction is a discipline that predicts the defects proneness of future modules. Software metrics are used for this kind of predication. However, the predication metrics are associated with uncertainty, thus the metrics need to be expressed in linguistic terms to overcome ambiguity and uncertainty. Two types of knowledge are utilized as input to the prediction models: software metrics and expert's opinions. This paper proposes a framework for developing fuzzy logic-based software predication model using different set of software metrics. It aims to provide a generic set of metrics to be used for software defects prediction. The performance of the proposed Fuzzy-based models has been validated using real software projects data where Takagi-Sugeno fuzzy inference engine is used to predict software defects. Validation results are satisfactory.","PeriodicalId":175933,"journal":{"name":"2016 7th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131245862","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 : 2016-08-01DOI: 10.1109/ICSESS.2016.7883193
Xue Li, Jiagang Zhu
The existing consistency checking methods for component-based software designs are unable to check the semantics consistency and the interface consistency because the protocols themselves do not contain these information. Li order to enable the consistency checking method to check semantics consistency and interface consistency besides protocol consistency, we propose a consistency checking method by introducing the idea of method semantics into scenario-based specifications. The semantic extended interface automata (SIA) model is utilized to describe the semantics, interface and protocol information of components. The scenario-based specifications are specified by interaction overview diagrams with semantic constrains. Then according to the analysis of the behaviors of SIA model and interaction overview diagrams with semantic constrains, we developed an algorithm to check the consistency between component-based designs and the scenario-based semantic specifications. Our algorithm not only can check the protocol consistency but also the method semantic consistency which includes the type and semantics of methods.
{"title":"A consistency verification method with semantics for component-based software designs","authors":"Xue Li, Jiagang Zhu","doi":"10.1109/ICSESS.2016.7883193","DOIUrl":"https://doi.org/10.1109/ICSESS.2016.7883193","url":null,"abstract":"The existing consistency checking methods for component-based software designs are unable to check the semantics consistency and the interface consistency because the protocols themselves do not contain these information. Li order to enable the consistency checking method to check semantics consistency and interface consistency besides protocol consistency, we propose a consistency checking method by introducing the idea of method semantics into scenario-based specifications. The semantic extended interface automata (SIA) model is utilized to describe the semantics, interface and protocol information of components. The scenario-based specifications are specified by interaction overview diagrams with semantic constrains. Then according to the analysis of the behaviors of SIA model and interaction overview diagrams with semantic constrains, we developed an algorithm to check the consistency between component-based designs and the scenario-based semantic specifications. Our algorithm not only can check the protocol consistency but also the method semantic consistency which includes the type and semantics of methods.","PeriodicalId":175933,"journal":{"name":"2016 7th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128359769","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 : 2016-08-01DOI: 10.1109/ICSESS.2016.7883256
M. Babu, M. Ramjee, Somesh Katta, S. K.
Cluster Analysis methods are very important, popular data summarization techniques applied in diverse environments. These techniques retrieve the hidden patterns in large datasets in the form of characterized patterns which can be interpreted further in different contexts. Widespread use of medical information systems and explosive growth of medical databases require traditional manual data analysis coupled with efficient computer assisted analysis. Medical Diagnosis is a difficult process which needs proficiency as well as experience to cope with a disease. Data segmentation is an application in medical domain used to analyze patient records, disease trends and health care resource utilization, which in turn assist a physician in Medical Diagnosis. In the present paper a technique based on classification techniques is proposed to predict liver disorders accurately. The main objective is to examine whether the proposed method can obtain better prediction accuracy to traditional classification algorithms. The classification results using the proposed method are found to be very promising and accurate.
{"title":"Implementation of partitional clustering on ILPD dataset to predict liver disorders","authors":"M. Babu, M. Ramjee, Somesh Katta, S. K.","doi":"10.1109/ICSESS.2016.7883256","DOIUrl":"https://doi.org/10.1109/ICSESS.2016.7883256","url":null,"abstract":"Cluster Analysis methods are very important, popular data summarization techniques applied in diverse environments. These techniques retrieve the hidden patterns in large datasets in the form of characterized patterns which can be interpreted further in different contexts. Widespread use of medical information systems and explosive growth of medical databases require traditional manual data analysis coupled with efficient computer assisted analysis. Medical Diagnosis is a difficult process which needs proficiency as well as experience to cope with a disease. Data segmentation is an application in medical domain used to analyze patient records, disease trends and health care resource utilization, which in turn assist a physician in Medical Diagnosis. In the present paper a technique based on classification techniques is proposed to predict liver disorders accurately. The main objective is to examine whether the proposed method can obtain better prediction accuracy to traditional classification algorithms. The classification results using the proposed method are found to be very promising and accurate.","PeriodicalId":175933,"journal":{"name":"2016 7th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134410553","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 : 2016-08-01DOI: 10.1109/ICSESS.2016.7883199
Zhibo Liu, Qiang Li
Kad is the most popular P2P file sharing system. It is very difficult to capture all the users' lookup traffic because of its full distributed feature. Previous work could only monitors a subset of the lookup traffic. In this paper, we propose a lightweight method to monitor the global lookup traffic by inserting two ‘nearest neighbor’ peers into the peer at the last iteration of Kad lookup path. Since one of the inserted peer is closer than the last peer definitely, the user's search request would be redirected to the trap node. The experiment performed on eMule0.50a shows that this approach could capture most lookup traffic.
{"title":"Capture global Kad lookup traffic","authors":"Zhibo Liu, Qiang Li","doi":"10.1109/ICSESS.2016.7883199","DOIUrl":"https://doi.org/10.1109/ICSESS.2016.7883199","url":null,"abstract":"Kad is the most popular P2P file sharing system. It is very difficult to capture all the users' lookup traffic because of its full distributed feature. Previous work could only monitors a subset of the lookup traffic. In this paper, we propose a lightweight method to monitor the global lookup traffic by inserting two ‘nearest neighbor’ peers into the peer at the last iteration of Kad lookup path. Since one of the inserted peer is closer than the last peer definitely, the user's search request would be redirected to the trap node. The experiment performed on eMule0.50a shows that this approach could capture most lookup traffic.","PeriodicalId":175933,"journal":{"name":"2016 7th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133229705","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 : 2016-08-01DOI: 10.1109/ICSESS.2016.7883070
Qing Wang
Recommender system is to establish the relationship between the user and the information products, to use the existing selection habits and the similarity of each user's potential interest in the object, and then personalized recommendation. It is one of the effective ways to solve the information overload in the Internet age. But in practical application, because of the large number of products and the number of users, the traditional recommendation system is usually run on the single machine, which has been far from meeting the needs of such big data. In this paper, we design and implement a network recommendation algorithm based on Hadoop platform, which is based on the theory of Hadoop and Map/Reduce programming.
{"title":"Design and implementation of recommender system based on Hadoop","authors":"Qing Wang","doi":"10.1109/ICSESS.2016.7883070","DOIUrl":"https://doi.org/10.1109/ICSESS.2016.7883070","url":null,"abstract":"Recommender system is to establish the relationship between the user and the information products, to use the existing selection habits and the similarity of each user's potential interest in the object, and then personalized recommendation. It is one of the effective ways to solve the information overload in the Internet age. But in practical application, because of the large number of products and the number of users, the traditional recommendation system is usually run on the single machine, which has been far from meeting the needs of such big data. In this paper, we design and implement a network recommendation algorithm based on Hadoop platform, which is based on the theory of Hadoop and Map/Reduce programming.","PeriodicalId":175933,"journal":{"name":"2016 7th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123877110","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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