Pub Date : 2016-08-01DOI: 10.1109/ICSESS.2016.7883081
Shuai Zhao, Yunhai Tong, Xiangfeng Meng, Xianglin Yang, Shaohua Tan
In the stock market, return reversal happens when investors sell overbought stocks and buy oversold stocks, making the trends of the stocks' prices reverse. While existing studies mainly focused on developing theories to explain the cause of return reversal, we aim at predicting return reversal by proposing a two-stage method in this paper. In the first stage, we employ dynamical Bayesian factor graph (DBFG) to select key factors correlating with return reversal closely from a comprehensive set of economic factors. In the second stage, we input the key factors into artificial neural network (ANN), support vector machine (SVM) and hidden Markov model (HMM) respectively, to accomplish the prediction of return reversal. Through extensive experiments on the US stock market, we establish that the key factors influencing return reversal generally change from year to year, yet factors related to the economic theory of liquidity effect consistently emerge as part of the key factors. Besides, DBFG-ANN achieves the most accurate prediction among the models, leading to precisions above 60%.
{"title":"Predicting return reversal through a two-stage method","authors":"Shuai Zhao, Yunhai Tong, Xiangfeng Meng, Xianglin Yang, Shaohua Tan","doi":"10.1109/ICSESS.2016.7883081","DOIUrl":"https://doi.org/10.1109/ICSESS.2016.7883081","url":null,"abstract":"In the stock market, return reversal happens when investors sell overbought stocks and buy oversold stocks, making the trends of the stocks' prices reverse. While existing studies mainly focused on developing theories to explain the cause of return reversal, we aim at predicting return reversal by proposing a two-stage method in this paper. In the first stage, we employ dynamical Bayesian factor graph (DBFG) to select key factors correlating with return reversal closely from a comprehensive set of economic factors. In the second stage, we input the key factors into artificial neural network (ANN), support vector machine (SVM) and hidden Markov model (HMM) respectively, to accomplish the prediction of return reversal. Through extensive experiments on the US stock market, we establish that the key factors influencing return reversal generally change from year to year, yet factors related to the economic theory of liquidity effect consistently emerge as part of the key factors. Besides, DBFG-ANN achieves the most accurate prediction among the models, leading to precisions above 60%.","PeriodicalId":175933,"journal":{"name":"2016 7th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"14 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":"129646384","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.2016.7883176
He Panfeng, Cheng Naiping, Ni Shuyan
Affected by the stratosphere winds, the swing of high altitude platform station seriously affected the performance of the communication system. This paper described and analyzed the swing state of the platform, established the swing state of high altitude platform multi beam antenna coverage model. The expression of coverage geometry, received power and carrier interference ratio was derived. In the swing state, the performance of multi beam antenna is simulated and analyzed, which provides a theoretical reference for the future design of multi beam cell.
{"title":"Coverage model of multi beam antenna from high altitude platform in the swing state","authors":"He Panfeng, Cheng Naiping, Ni Shuyan","doi":"10.1109/ICSESS.2016.7883176","DOIUrl":"https://doi.org/10.1109/ICSESS.2016.7883176","url":null,"abstract":"Affected by the stratosphere winds, the swing of high altitude platform station seriously affected the performance of the communication system. This paper described and analyzed the swing state of the platform, established the swing state of high altitude platform multi beam antenna coverage model. The expression of coverage geometry, received power and carrier interference ratio was derived. In the swing state, the performance of multi beam antenna is simulated and analyzed, which provides a theoretical reference for the future design of multi beam cell.","PeriodicalId":175933,"journal":{"name":"2016 7th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"24 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":"126355726","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.2016.7883160
Yu Zhao, Fenglian Liu, Riwei Wang
In order to solve existed accumulative error and SLAM problem for dead reckoning, this paper was proposed a positioning method combining with the known structured environment based on Extended Kalman Filter algorithm (EKF). This method quickly extracts the information of border and corner. According to the feature mapping relationships between world coordinate system and local coordinate system, calculate the robot's position and orientation space in the scene by matching the modeled environmental information. This method that we proposed achieved a better accuracy, timeliness and correctness.
{"title":"Location technology of indoor robot based on laser sensor","authors":"Yu Zhao, Fenglian Liu, Riwei Wang","doi":"10.1109/ICSESS.2016.7883160","DOIUrl":"https://doi.org/10.1109/ICSESS.2016.7883160","url":null,"abstract":"In order to solve existed accumulative error and SLAM problem for dead reckoning, this paper was proposed a positioning method combining with the known structured environment based on Extended Kalman Filter algorithm (EKF). This method quickly extracts the information of border and corner. According to the feature mapping relationships between world coordinate system and local coordinate system, calculate the robot's position and orientation space in the scene by matching the modeled environmental information. This method that we proposed achieved a better accuracy, timeliness and correctness.","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":"126428068","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.2016.7883220
M. H. Khanam, Md.A. Khudhus, M. Babu
In this paper, we depict hybrid approach, i.e., combination of rule based approach and machine learning techniques, i.e Conditional Random Fields (CRF) for Named Entity Recognition (NER). The main objective of Named Entity Recognition is to categorize all Named Entities (NE) in a document into predefined classes like Person name, Location name, Organization name. This paper first outlines the Named Entity Recognizer using rule based approach. In this approach we prepared Gazette lists for names of persons, locations and organizations, some suffix and prefix features and dictionary consist of 200000 words to recognize the category of names entities. Further, we used Machine learning technique, i.e., CRF in order to improve the accuracy of the system.
{"title":"Named Entity Recognition using Machine learning techniques for Telugu language","authors":"M. H. Khanam, Md.A. Khudhus, M. Babu","doi":"10.1109/ICSESS.2016.7883220","DOIUrl":"https://doi.org/10.1109/ICSESS.2016.7883220","url":null,"abstract":"In this paper, we depict hybrid approach, i.e., combination of rule based approach and machine learning techniques, i.e Conditional Random Fields (CRF) for Named Entity Recognition (NER). The main objective of Named Entity Recognition is to categorize all Named Entities (NE) in a document into predefined classes like Person name, Location name, Organization name. This paper first outlines the Named Entity Recognizer using rule based approach. In this approach we prepared Gazette lists for names of persons, locations and organizations, some suffix and prefix features and dictionary consist of 200000 words to recognize the category of names entities. Further, we used Machine learning technique, i.e., CRF in order to improve the accuracy of the system.","PeriodicalId":175933,"journal":{"name":"2016 7th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"30 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":"121143989","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.2016.7883212
Yu Litao, Han Aoyang, Wang Li, Jia Xu, Zhang Zhisheng
The paper presents a short-term load forecasting model for metro power supply system based on echo state neural network. Echo state neural network composed of input layer, reserve pool, the output layer. Reserve pool as a dynamic network is connected by a large number of random sparse of neurons. Reserve pool is used to overcome the slow convergence speed and avoid neural network into the local minimum. Using the actual historical data of the metro power supply system to simulate, the simulation results show that the short-term load forecasting model for metro power supply system based on echo state neural network has good prediction accuracy.
{"title":"Short-term load forecasting model for metro power supply system based on echo state neural network","authors":"Yu Litao, Han Aoyang, Wang Li, Jia Xu, Zhang Zhisheng","doi":"10.1109/ICSESS.2016.7883212","DOIUrl":"https://doi.org/10.1109/ICSESS.2016.7883212","url":null,"abstract":"The paper presents a short-term load forecasting model for metro power supply system based on echo state neural network. Echo state neural network composed of input layer, reserve pool, the output layer. Reserve pool as a dynamic network is connected by a large number of random sparse of neurons. Reserve pool is used to overcome the slow convergence speed and avoid neural network into the local minimum. Using the actual historical data of the metro power supply system to simulate, the simulation results show that the short-term load forecasting model for metro power supply system based on echo state neural network has good prediction accuracy.","PeriodicalId":175933,"journal":{"name":"2016 7th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"30 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":"121212655","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.2016.7883042
Huihong He, Yan Li, Yanfei Lv, Yong Wang
Nowadays Spark has been widely adopted as a sharp blade in solving big data problems by pipelining tasks of jobs on each node of cluster. In order to improve cluster resource utilization, lots of Spark performance-tuning advices have been proposed both by Spark and researchers. However, we notice that most of these advices focus tuning configuration items in isolation without considering job characteristics. In this paper, we try to explore the impact of executor quota allocation for Spark job in consideration of job stages and size of input. Dozens of carefully designed experiments reveal that execution time among job stages varies in probability as executor quota changes and thus the job execution time varies. We believe this conclusion helps to shed light on allocating executor resource quota regarding to job characteristics.
{"title":"Exploring the power of resource allocation for Spark executor","authors":"Huihong He, Yan Li, Yanfei Lv, Yong Wang","doi":"10.1109/ICSESS.2016.7883042","DOIUrl":"https://doi.org/10.1109/ICSESS.2016.7883042","url":null,"abstract":"Nowadays Spark has been widely adopted as a sharp blade in solving big data problems by pipelining tasks of jobs on each node of cluster. In order to improve cluster resource utilization, lots of Spark performance-tuning advices have been proposed both by Spark and researchers. However, we notice that most of these advices focus tuning configuration items in isolation without considering job characteristics. In this paper, we try to explore the impact of executor quota allocation for Spark job in consideration of job stages and size of input. Dozens of carefully designed experiments reveal that execution time among job stages varies in probability as executor quota changes and thus the job execution time varies. We believe this conclusion helps to shed light on allocating executor resource quota regarding to job characteristics.","PeriodicalId":175933,"journal":{"name":"2016 7th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"264 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":"123285389","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.2016.7883189
Y. Liu
In view of the present cloud security problem which has been becoming one of the major obstacles hindering the development of the cloud increasingly, put forward a kind of technology implementation of memory security isolation based on Xen. And based on the Xen virtual machine monitor system, analysis the implementation approach of memory virtualization in the model, using Xen virtualization system memory's super calls and authorization table mechanism, design the security memory isolation system with the basics of virtual machine manager internal implementation of access control module (ACM). Experiments show that the system can effectively isolate the memory data between different customer domain OS illegal access.
{"title":"Design and implement a safe method for isolating memory based on Xen cloud environment","authors":"Y. Liu","doi":"10.1109/ICSESS.2016.7883189","DOIUrl":"https://doi.org/10.1109/ICSESS.2016.7883189","url":null,"abstract":"In view of the present cloud security problem which has been becoming one of the major obstacles hindering the development of the cloud increasingly, put forward a kind of technology implementation of memory security isolation based on Xen. And based on the Xen virtual machine monitor system, analysis the implementation approach of memory virtualization in the model, using Xen virtualization system memory's super calls and authorization table mechanism, design the security memory isolation system with the basics of virtual machine manager internal implementation of access control module (ACM). Experiments show that the system can effectively isolate the memory data between different customer domain OS illegal access.","PeriodicalId":175933,"journal":{"name":"2016 7th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"24 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":"115434927","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.2016.7883017
Amro Louay Al-Bajjari, Ling Yuan
This paper mainly focus on designing and implementing a web security model in order to protect the network from any potential threats and attacks. When the email and information exchange between two parties over insecure channels, a web security model with optimized zero knowledge protocol can be used to identify the authentication between two parties. The proposed security model can achieve the authentication property implemented by using Zero Knowledge Protocol (ZKP), the integrity property implemented by using HMAC, and the confidentiality property implemented by using AES. The web security model can demonstrate to handle the man-in-the-middle attack.
{"title":"Research of web security model based on Zero Knowledge Protocol","authors":"Amro Louay Al-Bajjari, Ling Yuan","doi":"10.1109/ICSESS.2016.7883017","DOIUrl":"https://doi.org/10.1109/ICSESS.2016.7883017","url":null,"abstract":"This paper mainly focus on designing and implementing a web security model in order to protect the network from any potential threats and attacks. When the email and information exchange between two parties over insecure channels, a web security model with optimized zero knowledge protocol can be used to identify the authentication between two parties. The proposed security model can achieve the authentication property implemented by using Zero Knowledge Protocol (ZKP), the integrity property implemented by using HMAC, and the confidentiality property implemented by using AES. The web security model can demonstrate to handle the man-in-the-middle attack.","PeriodicalId":175933,"journal":{"name":"2016 7th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"324 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":"115844187","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.2016.7883062
Jie Hu, Guoshi Wu, Pengfei Sun, Qiu Xiong
Bayesian network (BN), an important machine learning technique, has been widely used in modeling relationships among random variables. BN is considered to be suitable for tasks like prediction, classification and cause analysis. In fact, Bayesian network model often preforms better precision than other commonly used algorithm models in classification and prediction. Meanwhile, taking Max-Min-Hill-Climbing as an example, many BN structure learning algorithms are heuristic, which means the time algorithm needs to converge can grow intensively when dealing with massive calculation. This paper aims at lessening time cost of learning BN structure process. We proposed an approach combining MapReduce with MMHC method. After splitting the training data set, several sub Bayesian network structures are learned simultaneously on Hadoop. To easily integrate prediction results from all those subnets, we employed boosting method to manage classification task. Our experiment results show good precision as well as better time performance in real distributed environment.
贝叶斯网络是一种重要的机器学习技术，广泛应用于随机变量之间的关系建模。BN被认为适用于预测、分类和原因分析等任务。事实上，贝叶斯网络模型在分类和预测方面往往比其他常用的算法模型具有更好的精度。同时，以max - min - hill - climb为例，许多BN结构学习算法是启发式的，这意味着在处理大量计算时，算法需要收敛的时间会急剧增长。本文旨在减少学习BN结构过程的时间成本。我们提出了一种MapReduce与MMHC相结合的方法。将训练数据集分割后，在Hadoop上同时学习多个子贝叶斯网络结构。为了方便地整合所有子网的预测结果，我们采用提升方法来管理分类任务。实验结果表明，该方法在真实的分布式环境下具有良好的精度和时间性能。
{"title":"A parallel Bayesian network learning algorithm for classification","authors":"Jie Hu, Guoshi Wu, Pengfei Sun, Qiu Xiong","doi":"10.1109/ICSESS.2016.7883062","DOIUrl":"https://doi.org/10.1109/ICSESS.2016.7883062","url":null,"abstract":"Bayesian network (BN), an important machine learning technique, has been widely used in modeling relationships among random variables. BN is considered to be suitable for tasks like prediction, classification and cause analysis. In fact, Bayesian network model often preforms better precision than other commonly used algorithm models in classification and prediction. Meanwhile, taking Max-Min-Hill-Climbing as an example, many BN structure learning algorithms are heuristic, which means the time algorithm needs to converge can grow intensively when dealing with massive calculation. This paper aims at lessening time cost of learning BN structure process. We proposed an approach combining MapReduce with MMHC method. After splitting the training data set, several sub Bayesian network structures are learned simultaneously on Hadoop. To easily integrate prediction results from all those subnets, we employed boosting method to manage classification task. Our experiment results show good precision as well as better time performance in real distributed environment.","PeriodicalId":175933,"journal":{"name":"2016 7th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"128 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":"128468991","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.2016.7883087
Boang Feng, Jianwei Liu
In this paper, we propose an Identity-Based encryption (IBE) scheme and corresponding signature scheme with the feature of transmission route assurance. And then, we put forward a reforming method to make them more efficient and lightweight with the end-to-end feature, encouraging a broader range of application in ad-hoc networks. Based on these schemes, we present a new identity-based authentication protocol for ad-hoc networks. Through analysis and contrast, we show the fulfillment and feasibility of our protocol with respect to the security and efficiency goals.
{"title":"Practical Identity-Based authentication protocol for ad-hoc networks","authors":"Boang Feng, Jianwei Liu","doi":"10.1109/ICSESS.2016.7883087","DOIUrl":"https://doi.org/10.1109/ICSESS.2016.7883087","url":null,"abstract":"In this paper, we propose an Identity-Based encryption (IBE) scheme and corresponding signature scheme with the feature of transmission route assurance. And then, we put forward a reforming method to make them more efficient and lightweight with the end-to-end feature, encouraging a broader range of application in ad-hoc networks. Based on these schemes, we present a new identity-based authentication protocol for ad-hoc networks. Through analysis and contrast, we show the fulfillment and feasibility of our protocol with respect to the security and efficiency goals.","PeriodicalId":175933,"journal":{"name":"2016 7th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"6 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":"128750532","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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