2017 18th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)最新文献
Pub Date : 2017-06-26DOI: 10.1109/SNPD.2017.8332383
Parinya Wichawong, P. Chongstitvatana
Hard disk failure is a serious problem in term of product quality and credibility to customers. All hard disk drive companies need to be aware and address how to get rid of failure and prevent the repeat of the problem in their products. The quality of failure analysis process depends on the person who has most experience. It would not be so efficient if the company has no experienced person to perform the analysis. A knowledge management system can store the knowledge of experienced engineers. It can help new engineers to learn the craft. It would reduce a knowledge gap issues and bring up efficiency for failure solving process. This paper presents a design and implementation of knowledge management system for failure analysis in hard disk with case-based reasoning. The existing cases are stored and a new case can be compared to the existing one in order to retrieve the relevant existing knowledge to help the analysis. Once the new case is solved, it can be stored to aid the future cases. A prototype of the system has been implemented and the assessment of user satisfaction shows that it can improve the failure analysis process effectively.
{"title":"Knowledge management system for failure analysis in hard disk using case-based reasoning","authors":"Parinya Wichawong, P. Chongstitvatana","doi":"10.1109/SNPD.2017.8332383","DOIUrl":"https://doi.org/10.1109/SNPD.2017.8332383","url":null,"abstract":"Hard disk failure is a serious problem in term of product quality and credibility to customers. All hard disk drive companies need to be aware and address how to get rid of failure and prevent the repeat of the problem in their products. The quality of failure analysis process depends on the person who has most experience. It would not be so efficient if the company has no experienced person to perform the analysis. A knowledge management system can store the knowledge of experienced engineers. It can help new engineers to learn the craft. It would reduce a knowledge gap issues and bring up efficiency for failure solving process. This paper presents a design and implementation of knowledge management system for failure analysis in hard disk with case-based reasoning. The existing cases are stored and a new case can be compared to the existing one in order to retrieve the relevant existing knowledge to help the analysis. Once the new case is solved, it can be stored to aid the future cases. A prototype of the system has been implemented and the assessment of user satisfaction shows that it can improve the failure analysis process effectively.","PeriodicalId":186094,"journal":{"name":"2017 18th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126476017","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 : 2017-06-26DOI: 10.1109/SNPD.2017.8022768
Yuusuke Kataoka, Takashi Matsubara, K. Uehara
Many comic books are now published as digital books, which easily provide color contents compared to the physical books. The motivation of automatic colorization of comic books now arises. Previous studies colorize sketches without other clues or with spatial color annotations. They are expected to reduce workloads of comic artists but still require spatial color annotations for desirable colorizations. This study introduces a color style information and combines it with conditional adversarially learned inference. The experimental results demonstrate that the objects are painted with colors depending on the color style information and that the color style information extracted from a color image supports to painting an object with a desirable color.
{"title":"Automatic manga colorization with color style by generative adversarial nets","authors":"Yuusuke Kataoka, Takashi Matsubara, K. Uehara","doi":"10.1109/SNPD.2017.8022768","DOIUrl":"https://doi.org/10.1109/SNPD.2017.8022768","url":null,"abstract":"Many comic books are now published as digital books, which easily provide color contents compared to the physical books. The motivation of automatic colorization of comic books now arises. Previous studies colorize sketches without other clues or with spatial color annotations. They are expected to reduce workloads of comic artists but still require spatial color annotations for desirable colorizations. This study introduces a color style information and combines it with conditional adversarially learned inference. The experimental results demonstrate that the objects are painted with colors depending on the color style information and that the color style information extracted from a color image supports to painting an object with a desirable color.","PeriodicalId":186094,"journal":{"name":"2017 18th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125375260","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 : 2017-06-26DOI: 10.1109/SNPD.2017.8022758
Ning Sun, H. Bai, Yuxia Geng, Huizhu Shi
With the rapid growth of the number of private cars and the development of the second-hand car market, second-hand cars have become the main choice when people buy cars. The online second-hand car platform provides both buyers and sellers the chance of online P2P trade. In such systems, the accuracy of second-hand car price evaluation largely determines whether the seller and the buyer can get more efficient trading experience. In this paper, the price evaluation model based on big data analysis is proposed, which takes advantage of widely circulated vehicle data and a large number of vehicle transaction data to analyze the price data for each type of vehicles by using the optimized BP neural network algorithm. It aims to establish a second-hand car price evaluation model to get the price that best matches the car. In this paper, the optimized BP neural network algorithm is used to select the optimal number of hidden neurons in BP neural network, which improves the convergence speed of the network topology and the accuracy of the prediction model. Through the sampling simulation experiments, the fitting curve of the prediction price is compared with the real transaction price derived from the optimized model. As a result, the fitting of the optimized model is better as well as the accuracy is higher.
{"title":"Price evaluation model in second-hand car system based on BP neural network theory","authors":"Ning Sun, H. Bai, Yuxia Geng, Huizhu Shi","doi":"10.1109/SNPD.2017.8022758","DOIUrl":"https://doi.org/10.1109/SNPD.2017.8022758","url":null,"abstract":"With the rapid growth of the number of private cars and the development of the second-hand car market, second-hand cars have become the main choice when people buy cars. The online second-hand car platform provides both buyers and sellers the chance of online P2P trade. In such systems, the accuracy of second-hand car price evaluation largely determines whether the seller and the buyer can get more efficient trading experience. In this paper, the price evaluation model based on big data analysis is proposed, which takes advantage of widely circulated vehicle data and a large number of vehicle transaction data to analyze the price data for each type of vehicles by using the optimized BP neural network algorithm. It aims to establish a second-hand car price evaluation model to get the price that best matches the car. In this paper, the optimized BP neural network algorithm is used to select the optimal number of hidden neurons in BP neural network, which improves the convergence speed of the network topology and the accuracy of the prediction model. Through the sampling simulation experiments, the fitting curve of the prediction price is compared with the real transaction price derived from the optimized model. As a result, the fitting of the optimized model is better as well as the accuracy is higher.","PeriodicalId":186094,"journal":{"name":"2017 18th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132081834","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 : 2017-06-26DOI: 10.1109/SNPD.2017.8022653
Amarita Ritthipakdee, A. Thammano
In primate life, there are a number of various social behavior, such as communication among members in a group, and food sharing, which are vital to maintain their survival. Similar to those of Swarm Intelligence, such as ant colony optimization, the behavior of primates motivates us to develop an algorithm with the aim of solving continuous problems. Our algorithm is inspired by the behavior of the primate. The communication among them is studied and is also a key part in their food finding strategy. Our proposed algorithm developed upon the behavior is tested with twelve standard benchmark functions and most of which converged to the optimal value.
{"title":"Primate swarm algorithm for continuous optimization problems","authors":"Amarita Ritthipakdee, A. Thammano","doi":"10.1109/SNPD.2017.8022653","DOIUrl":"https://doi.org/10.1109/SNPD.2017.8022653","url":null,"abstract":"In primate life, there are a number of various social behavior, such as communication among members in a group, and food sharing, which are vital to maintain their survival. Similar to those of Swarm Intelligence, such as ant colony optimization, the behavior of primates motivates us to develop an algorithm with the aim of solving continuous problems. Our algorithm is inspired by the behavior of the primate. The communication among them is studied and is also a key part in their food finding strategy. Our proposed algorithm developed upon the behavior is tested with twelve standard benchmark functions and most of which converged to the optimal value.","PeriodicalId":186094,"journal":{"name":"2017 18th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","volume":"405 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126681217","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 : 2017-06-26DOI: 10.1109/SNPD.2017.8022786
Matthew J. Bailey, Connor Collins, Matthew Sinda, Gongzhu Hu
This paper investigates the continued need for intrusion detection systems (IDS) in computer networks. It explores some of the ways that data mining techniques can be used to improve IDS, and looks at how others have implemented those techniques. It then highlights a method for developing an intrusion detection model using DBSCAN clustering and presents the results of the clustering algorithm as applied to a real-world data set. Finally, the paper concludes that clustering as an intrusion detection technique produces accurate results, but that special considerations must be made both with regard to outliers and the type of traffic flowing across the network.
{"title":"Intrusion detection using clustering of network traffic flows","authors":"Matthew J. Bailey, Connor Collins, Matthew Sinda, Gongzhu Hu","doi":"10.1109/SNPD.2017.8022786","DOIUrl":"https://doi.org/10.1109/SNPD.2017.8022786","url":null,"abstract":"This paper investigates the continued need for intrusion detection systems (IDS) in computer networks. It explores some of the ways that data mining techniques can be used to improve IDS, and looks at how others have implemented those techniques. It then highlights a method for developing an intrusion detection model using DBSCAN clustering and presents the results of the clustering algorithm as applied to a real-world data set. Finally, the paper concludes that clustering as an intrusion detection technique produces accurate results, but that special considerations must be made both with regard to outliers and the type of traffic flowing across the network.","PeriodicalId":186094,"journal":{"name":"2017 18th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115847330","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 : 2017-06-26DOI: 10.1109/SNPD.2017.8022699
Wannaporn Teekeng, Pornkid Unkaw
This paper presents a new hybrid HPSO-DE classification algorithm that combines the advantages of particle swarm optimization algorithm and differential evolution algorithm. Major improvements achieved by this combination are 1) flight improvement — flight behaviors are more and better diversified because each of the top 3 particles gets put into 3 different groups of the rest and then each group is mutated with a different operator and 2) particle improvement — members of a succeeding generation are composed of more of better particles than those of the current generation because better particles are allowed to produce more offspring. HPSO-DE and several other classification models were performance tested with 8 benchmarking datasets, and HPSO-DE was found to outperform them on 6 out of the 8.
{"title":"A new hybrid model of PSO and DE algorithm for data classification","authors":"Wannaporn Teekeng, Pornkid Unkaw","doi":"10.1109/SNPD.2017.8022699","DOIUrl":"https://doi.org/10.1109/SNPD.2017.8022699","url":null,"abstract":"This paper presents a new hybrid HPSO-DE classification algorithm that combines the advantages of particle swarm optimization algorithm and differential evolution algorithm. Major improvements achieved by this combination are 1) flight improvement — flight behaviors are more and better diversified because each of the top 3 particles gets put into 3 different groups of the rest and then each group is mutated with a different operator and 2) particle improvement — members of a succeeding generation are composed of more of better particles than those of the current generation because better particles are allowed to produce more offspring. HPSO-DE and several other classification models were performance tested with 8 benchmarking datasets, and HPSO-DE was found to outperform them on 6 out of the 8.","PeriodicalId":186094,"journal":{"name":"2017 18th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","volume":"135 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132459695","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 : 2017-06-01DOI: 10.1109/SNPD.2017.8022751
Du Chunye, Song Wei, Wu Jianhua
With the rapid development of mobile terminal, mobile applications are gradually penetrated into all aspects of people's life and work. Mobile games, mobile streaming media, location services, mobile Internet news, instant messaging, mobile music and other rich and colorful information era are changing the social life. In view of this, we propose the application software performance test based on the mobile terminal, and analyze the performance test technology and method of the mobile application. Experimental results show that the performance test of the application system can predict the pressure in real environment, the system will be applied in the problems exposed, through the analysis of the data of the test, it will provide help for performance optimization of application system.
{"title":"Based on the analysis of mobile terminal application software performance test","authors":"Du Chunye, Song Wei, Wu Jianhua","doi":"10.1109/SNPD.2017.8022751","DOIUrl":"https://doi.org/10.1109/SNPD.2017.8022751","url":null,"abstract":"With the rapid development of mobile terminal, mobile applications are gradually penetrated into all aspects of people's life and work. Mobile games, mobile streaming media, location services, mobile Internet news, instant messaging, mobile music and other rich and colorful information era are changing the social life. In view of this, we propose the application software performance test based on the mobile terminal, and analyze the performance test technology and method of the mobile application. Experimental results show that the performance test of the application system can predict the pressure in real environment, the system will be applied in the problems exposed, through the analysis of the data of the test, it will provide help for performance optimization of application system.","PeriodicalId":186094,"journal":{"name":"2017 18th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114976095","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}
More and more on-line experiments have been done in E-Commerce in order to understand the behavior of users or customers and then apply the data analysis technique to provide business guidance. One of the techniques is A/B testing. However, there is not clear guidance on the sample size in order for us to have valuable, trustable discovery. The purpose of this work is to find out a way to group customers in the data sample in order to achieve an optimal difference between the buckets. Based on the analysis result of real data collected during joining an industry project, we think the problem is complex and the meaningful conclusions have to be drawn with caution from business experiments such as A/B testing, due to the vast variation in the data. Moreover, if we don't allocate enough samples in the treatment group, the experiment could be inconclusive even if the testing lasts for a longer enough time, such as one month.
{"title":"Issues with conducting controlled on-line experiments for E-Commerce","authors":"Dapeng Liu, Shaochun Xu, Brian Zhang, Chunlin Wang, Chunqing Li, Feng Zhou","doi":"10.1109/SNPD.2017.8022721","DOIUrl":"https://doi.org/10.1109/SNPD.2017.8022721","url":null,"abstract":"More and more on-line experiments have been done in E-Commerce in order to understand the behavior of users or customers and then apply the data analysis technique to provide business guidance. One of the techniques is A/B testing. However, there is not clear guidance on the sample size in order for us to have valuable, trustable discovery. The purpose of this work is to find out a way to group customers in the data sample in order to achieve an optimal difference between the buckets. Based on the analysis result of real data collected during joining an industry project, we think the problem is complex and the meaningful conclusions have to be drawn with caution from business experiments such as A/B testing, due to the vast variation in the data. Moreover, if we don't allocate enough samples in the treatment group, the experiment could be inconclusive even if the testing lasts for a longer enough time, such as one month.","PeriodicalId":186094,"journal":{"name":"2017 18th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121054468","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 : 2017-06-01DOI: 10.1109/SNPD.2017.8022752
Hongliang Liang, Shirun Liu, Yini Zhang, Meilin Wang
To improve the accuracy of analysis results is one of the hard challenges for static analysis. Especially, static analyzers generally analyze all paths of a program, including infeasible paths, which undoubtedly decreases the analysis accuracy. To mitigate the issue, we design and implement a static analyzer, called ABAZER-SE, which is based on the meta-compilation and the GCC abstract syntax tree. ABAZER-SE combines symbolic execution and static analysis techniques to detect bugs in the source code. In addition, it allows users to write a custom checker for a specific bug.
{"title":"Improving the precision of static analysis: Symbolic execution based on GCC abstract syntax tree","authors":"Hongliang Liang, Shirun Liu, Yini Zhang, Meilin Wang","doi":"10.1109/SNPD.2017.8022752","DOIUrl":"https://doi.org/10.1109/SNPD.2017.8022752","url":null,"abstract":"To improve the accuracy of analysis results is one of the hard challenges for static analysis. Especially, static analyzers generally analyze all paths of a program, including infeasible paths, which undoubtedly decreases the analysis accuracy. To mitigate the issue, we design and implement a static analyzer, called ABAZER-SE, which is based on the meta-compilation and the GCC abstract syntax tree. ABAZER-SE combines symbolic execution and static analysis techniques to detect bugs in the source code. In addition, it allows users to write a custom checker for a specific bug.","PeriodicalId":186094,"journal":{"name":"2017 18th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121910780","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 : 2017-06-01DOI: 10.1109/SNPD.2017.8022652
Duangjai Jitkongchuen, Warattha Sukpongthai, A. Thammano
The proposed algorithm presents a solution to improve the grey wolf optimizer performance using weighted distance and immigration operation. The weight distance is used for the omega wolves movement is defined from fitness value of each leader (alpha, beta and delta). The traditional grey wolf algorithm has only one pack and has opportunity to trap in local optimum so the wolves in our proposed algorithm have more pack and have migrated between them. When the amount of pack has more than to predefine some pack will be eliminated. The experimental results are evaluated by a comparative with the traditional grey wolf optimizer (GWO) algorithm, particle swarm optimization (PSO) and differential evolution (DE) algorithm on 9 well-known benchmark functions. The experimental results showed that the proposed algorithm is capable of efficiently to solving complex optimization problems.
{"title":"Weighted distance grey wolf optimization with immigration operation for global optimization problems","authors":"Duangjai Jitkongchuen, Warattha Sukpongthai, A. Thammano","doi":"10.1109/SNPD.2017.8022652","DOIUrl":"https://doi.org/10.1109/SNPD.2017.8022652","url":null,"abstract":"The proposed algorithm presents a solution to improve the grey wolf optimizer performance using weighted distance and immigration operation. The weight distance is used for the omega wolves movement is defined from fitness value of each leader (alpha, beta and delta). The traditional grey wolf algorithm has only one pack and has opportunity to trap in local optimum so the wolves in our proposed algorithm have more pack and have migrated between them. When the amount of pack has more than to predefine some pack will be eliminated. The experimental results are evaluated by a comparative with the traditional grey wolf optimizer (GWO) algorithm, particle swarm optimization (PSO) and differential evolution (DE) algorithm on 9 well-known benchmark functions. The experimental results showed that the proposed algorithm is capable of efficiently to solving complex optimization problems.","PeriodicalId":186094,"journal":{"name":"2017 18th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128497679","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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