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2017 8th IEEE International Conference on Software Engineering and Service Science (ICSESS)最新文献

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Short-term traffic flow prediction based on wavelet function and extreme learning machine 基于小波函数和极限学习机的短期交通流预测
2017 8th IEEE International Conference on Software Engineering and Service Science (ICSESS) Pub Date : 2017-11-01 DOI: 10.1109/ICSESS.2017.8342971
W. Feng, Hong Chen, Zhaojin Zhang
{"title":"Short-term traffic flow prediction based on wavelet function and extreme learning machine","authors":"W. Feng, Hong Chen, Zhaojin Zhang","doi":"10.1109/ICSESS.2017.8342971","DOIUrl":"https://doi.org/10.1109/ICSESS.2017.8342971","url":null,"abstract":"As the traffic flow has the characteristics of non-linear and strong interference, it has different features in different time-frequency domain. The traditional short-term traffic flow forecasting methods have the disadvantages of lower prediction accuracy, harder parameter determination and poorer adaptability. Aiming at above problems, we proposed a short — term traffic flow forecasting algorithm based on the wavelet function and the Extreme Learning Machine (ELM) to optimize the short — term traffic flow forecasting method. Firstly, the activation function of hidden layer neurons in the prediction model of the ELM is optimized according to the denoising principle of the wavelet function. Secondly, the short-term traffic volume prediction model of the ELM is established, and the traffic volume during the evening peak hours of the Canadian Whitemud Drive highway is forecasted. Finally, the results of this paper are compared with ones that predicted by BP neural network model Compared the R2 value of 0.7 in this method with the one of 0.5331 in BP neural network, the results show that the proposed method in this paper has better generalization ability and more proper stability than BP neural network has. The prediction results are in good agreement with the desired short — term traffic volume, and the short-term traffic flow can be predicted more efficiently.","PeriodicalId":179815,"journal":{"name":"2017 8th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126488093","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}
引用次数: 10
A dimensional model of service design toward utilizing public transportation open data 面向公共交通开放数据的服务设计维度模型
2017 8th IEEE International Conference on Software Engineering and Service Science (ICSESS) Pub Date : 2017-11-01 DOI: 10.1109/ICSESS.2017.8343060
T. Yamakami
{"title":"A dimensional model of service design toward utilizing public transportation open data","authors":"T. Yamakami","doi":"10.1109/ICSESS.2017.8343060","DOIUrl":"https://doi.org/10.1109/ICSESS.2017.8343060","url":null,"abstract":"Public transportation open data is increasingly available to leverage third-party value-added applications to improve transport experience. Despite of increase of open data, service design methodologies are under-explored. Ad hoc service design leads to under-utilization of available open data. The author presents a dimensional model of service design of public transportation open data. Then the author presents a layered software framework to accommodate the proposed model. Finally, the author presents examples of new services derived from the dimensional guidance.","PeriodicalId":179815,"journal":{"name":"2017 8th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127927460","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}
引用次数: 0
An information security risk assessment method based on conduct effect and dynamic threat 基于行为效应和动态威胁的信息安全风险评估方法
2017 8th IEEE International Conference on Software Engineering and Service Science (ICSESS) Pub Date : 2017-11-01 DOI: 10.1109/ICSESS.2017.8343029
Qiao Hong, Tian Jianwei, Tian Zheng, Qi Wenhui, L. Xi, Zhu Hongyu, Chen Shengsheng
{"title":"An information security risk assessment method based on conduct effect and dynamic threat","authors":"Qiao Hong, Tian Jianwei, Tian Zheng, Qi Wenhui, L. Xi, Zhu Hongyu, Chen Shengsheng","doi":"10.1109/ICSESS.2017.8343029","DOIUrl":"https://doi.org/10.1109/ICSESS.2017.8343029","url":null,"abstract":"Traditional Information Security Risk Assessment method did not consider the dynamic characteristic and risk conduct effect among assets, which makes the assessment result inaccurately. To solve this problem, this paper proposes a novel Information Security Risk Assessment method based on Conduct effect and Dynamic threat (ISRACD). ISRACD adopts DTC (Dynamic Threat Calculation) method to calculate threat degree more objectively. Besides, ISRACD proposes ACEC (Asset Conduct Effect Calculation) method to describe the conduct effect among assets and quantify the conduct value. Based on the two methods, ISRACD can obtain the security level more precisely.","PeriodicalId":179815,"journal":{"name":"2017 8th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131351775","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}
引用次数: 3
Stock market forecast based on wavelet neural network optimized by Cuckoo search 基于布谷鸟搜索优化的小波神经网络股票市场预测
2017 8th IEEE International Conference on Software Engineering and Service Science (ICSESS) Pub Date : 2017-11-01 DOI: 10.1109/ICSESS.2017.8342977
Hua Zhi, Jinghua Zhang, Zhengbo Xue, Yan Zhang
{"title":"Stock market forecast based on wavelet neural network optimized by Cuckoo search","authors":"Hua Zhi, Jinghua Zhang, Zhengbo Xue, Yan Zhang","doi":"10.1109/ICSESS.2017.8342977","DOIUrl":"https://doi.org/10.1109/ICSESS.2017.8342977","url":null,"abstract":"As a typical nonlinear deterministic dynamical system, stock market can be predicted by Wavelet Neural Network. Since Cuckoo Search is a new heuristic bionic group intelligent optimization algorithm, it can be widely used in various optimization problems. In this paper, we use Cuckoo Search (CS) to optimize the initial parameters of wavelet neural network. Results of the experiment show that the optimized CS-WNN has higher prediction accuracy than the traditional WNN in stock market forecast.","PeriodicalId":179815,"journal":{"name":"2017 8th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"219 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131930563","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}
引用次数: 1
Method of license compliance of open source software governance 开源软件治理的许可遵从性方法
2017 8th IEEE International Conference on Software Engineering and Service Science (ICSESS) Pub Date : 2017-11-01 DOI: 10.1109/icsess.2017.8342869
H. Yun, Y. Joe, D. Shin
{"title":"Method of license compliance of open source software governance","authors":"H. Yun, Y. Joe, D. Shin","doi":"10.1109/icsess.2017.8342869","DOIUrl":"https://doi.org/10.1109/icsess.2017.8342869","url":null,"abstract":"When someone use Open Source Software(OSS), an user must obligate the license which is specified by developer of the OSS. Also, developing and redistributing software with two or more OSS could lead license violation. Violator may disclose/modify/rewrite their code, change its redistribution license, and forgive their patent because of the violation. Therefore, we suggest the process for governance OSS in developing software to avoid intellectual property litigation. The main processes are license file inspection from OSS project files and automated OSS license compatibility checking.","PeriodicalId":179815,"journal":{"name":"2017 8th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130191615","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}
引用次数: 2
Transforming context-aware application development model into a testing model 将上下文感知的应用程序开发模型转换为测试模型
2017 8th IEEE International Conference on Software Engineering and Service Science (ICSESS) Pub Date : 2017-11-01 DOI: 10.1109/ICSESS.2017.8342891
Mirza Aamir Mehmood, M. Khan, W. Afzal
{"title":"Transforming context-aware application development model into a testing model","authors":"Mirza Aamir Mehmood, M. Khan, W. Afzal","doi":"10.1109/ICSESS.2017.8342891","DOIUrl":"https://doi.org/10.1109/ICSESS.2017.8342891","url":null,"abstract":"Software testing aims at ensuring the quality of a software product. Context-aware applications are emerging applications that are capable to sense their environment and adapt to situational context to provide better user experience. Context-aware applications pose many challenges for software testing such as defining test adequacy criteria, generating test data, developing context-aware test cases etc. Test case generation process for context-aware applications can be automated using a model based testing technique. To attain this goal with maximum degree of automation, it is required to transform development model into a test model automatically. In this study, we propose a typecast of activity node of UML activity diagram, called Context-Aware Activity for modelling context-aware applications. We have also developed an approach for automatic transformation of the development model i.e., UML activity diagram with Context-aware Activity typecast into a testing model i.e. function nets. This testing model is used to automate test case generation and we have illustrated how to generate context-aware test cases using our proposed approach.","PeriodicalId":179815,"journal":{"name":"2017 8th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134033281","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}
引用次数: 4
A novel algorithm for detecting GSMem attacks 一种检测GSMem攻击的新算法
2017 8th IEEE International Conference on Software Engineering and Service Science (ICSESS) Pub Date : 2017-11-01 DOI: 10.1109/ICSESS.2017.8343045
Weijun Zhu, Kai Nie, ShaoHuan Ban, Yongwen Fan, Jianwei Wang
{"title":"A novel algorithm for detecting GSMem attacks","authors":"Weijun Zhu, Kai Nie, ShaoHuan Ban, Yongwen Fan, Jianwei Wang","doi":"10.1109/ICSESS.2017.8343045","DOIUrl":"https://doi.org/10.1109/ICSESS.2017.8343045","url":null,"abstract":"GSMem is a malware which is against air-gapped computers. Up to now, no method can detect it. To this end, this paper puts forward an algorithm for detecting GSMem. At first, the new algorithm detects whether or not there exists a thread in memory, which periodically calls the MOVNTDQ instruction. If such a thread occurs, a binary character string which is generated from the periodical call, will be matched with another binary character string which expresses some confidential information. And the new algorithm determines whether a GSMem attack occurs or not according to the result of the match. The simulation results show that the new algorithm can detect a GSMem in air-gapped networks in principle. The complexity analysis demonstrates that the new algorithm can complete its task within polynomial time.","PeriodicalId":179815,"journal":{"name":"2017 8th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131010588","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}
引用次数: 1
Porcelain image classification based on semi-supervised mean shift clustering 基于半监督均值移位聚类的瓷器图像分类
2017 8th IEEE International Conference on Software Engineering and Service Science (ICSESS) Pub Date : 2017-11-01 DOI: 10.1109/ICSESS.2017.8343031
Pengbo Zhou, Kegang Wang
{"title":"Porcelain image classification based on semi-supervised mean shift clustering","authors":"Pengbo Zhou, Kegang Wang","doi":"10.1109/ICSESS.2017.8343031","DOIUrl":"https://doi.org/10.1109/ICSESS.2017.8343031","url":null,"abstract":"This paper puts forward a method of constructing efficient clustering model using sample constraints at the problem of porcelain image classification. The method is based on the mean-shift clustering algorithm, the mapping kernel transformation matrix is computed by using the sample constraint, and defined using the Intra-class consistency measure and Inter-class sample difference in distribution measurement, the method of determining the best clustering bandwidth parameters is achieved, and an effective semi-supervised clustering model is obtained. The experimental results show that compared to the common fuzzy mean clustering, kernel fuzzy mean clustering and some improved algorithms based on it, This method has been greatly improved in the clustering effect, the classification method is applied to the porcelain image, to achieve a more accurate classification with individual image tiles effectively.","PeriodicalId":179815,"journal":{"name":"2017 8th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130739036","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}
引用次数: 1
Feature selecting based on fourier series fitting 基于傅立叶级数拟合的特征选择
2017 8th IEEE International Conference on Software Engineering and Service Science (ICSESS) Pub Date : 2017-11-01 DOI: 10.1109/ICSESS.2017.8342905
Huanyu Chen, Chongyang Wang, Tong Chen, Xingcong Zhao
{"title":"Feature selecting based on fourier series fitting","authors":"Huanyu Chen, Chongyang Wang, Tong Chen, Xingcong Zhao","doi":"10.1109/ICSESS.2017.8342905","DOIUrl":"https://doi.org/10.1109/ICSESS.2017.8342905","url":null,"abstract":"In spectral quantitative analysis, the accuracy and complexity of the designed prediction model will be negatively affected by enormous data volume and noise of the original spectrum. This paper presents a dimensionality reduction and noise decreasing method for original spectrum analysis based on Fourier series fitting (FSF). By extracting features using FSF, the original spectrum data will be mapped into Fourier series, and a regression prediction model using partial least squares (PLS) is established. The experimental analysis suggests that FSF method, compared with PLS, discrete fourier transform (DFT), artificial neural networks (ANNs) and genetic algorithm with PLS (GA-PLS), can produce better results considering the running time, the number of input variables and prediction accuracy.","PeriodicalId":179815,"journal":{"name":"2017 8th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"124 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133271763","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}
引用次数: 4
Hybrid software reliability prediction model based on residual errors 基于残差的混合软件可靠性预测模型
2017 8th IEEE International Conference on Software Engineering and Service Science (ICSESS) Pub Date : 2017-11-01 DOI: 10.1109/ICSESS.2017.8342959
Gul Jabeen, Xi Yang, Luo Ping, Sabit Rahim, Gul Sahar, A. A. Shah
{"title":"Hybrid software reliability prediction model based on residual errors","authors":"Gul Jabeen, Xi Yang, Luo Ping, Sabit Rahim, Gul Sahar, A. A. Shah","doi":"10.1109/ICSESS.2017.8342959","DOIUrl":"https://doi.org/10.1109/ICSESS.2017.8342959","url":null,"abstract":"Software reliability is one of the key features of software quality assurance. It is primarily associated with the defects of software, which indicates a major factor in software development. Software has become an indispensable investment for an organization. The users are more concerned about accurate and efficient failure prediction model. Early fault prediction model can reduce the cost of the test, increase reliability and improve the quality of software. Precise prediction is desired from the every model but no model has proved to be successful at efficiently and accurately developing software reliability model. In this paper, the authors have combined two most popular reliability prediction models and get the most accurate output from them by using Markov method based on their residual errors. Furthermore, experiment analysis and comparison carried out on U.S. Navy Tactical Data System, which shows the accuracy of the hybrid approach.","PeriodicalId":179815,"journal":{"name":"2017 8th IEEE International Conference on Software Engineering and Service Science (ICSESS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128882027","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}
引用次数: 3
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