2018 59th International Scientific Conference on Information Technology and Management Science of Riga Technical University (ITMS)最新文献

{"title":"59th International Scientific Conference on Information Technology and Management Science of Riga Technical University (ITMS)","authors":"J. Grabis, A. Romānovs, G. Kuleshova","doi":"10.1109/itms.2018.8552969","DOIUrl":"https://doi.org/10.1109/itms.2018.8552969","url":null,"abstract":"","PeriodicalId":367060,"journal":{"name":"2018 59th International Scientific Conference on Information Technology and Management Science of Riga Technical University (ITMS)","volume":"41 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123863640","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}

{"title":"Approximation of Distribution of Log-returns with Normal Inverse Gaussian Process","authors":"O. Rubenis, Andrejs Matvejevs","doi":"10.1109/ITMS.2018.8552949","DOIUrl":"https://doi.org/10.1109/ITMS.2018.8552949","url":null,"abstract":"Normal inverse Gaussian (NIG) distribution is a quit a new distribution introduced in 1997. This is distribution, which describes evolution of NIG process. It appears that in many cases NIG distribution describes log-returns of stock prices with a high accuracy. Unlike normal distribution, it has higher kurtosis, which is necessary to fit many historical returns. This gives the opportunity to construct precise algorithms for hedging risks of options. The aim of this work is to evaluate how good NIG distribution can reproduce stock price dynamics and to illuminate future fields of applications.","PeriodicalId":367060,"journal":{"name":"2018 59th International Scientific Conference on Information Technology and Management Science of Riga Technical University (ITMS)","volume":"238 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132164135","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}

{"title":"Using Data Analytics for Customers Segmentation: Experimental Study at a Financial Institution","authors":"Pavels Goncarovs","doi":"10.1109/ITMS.2018.8552951","DOIUrl":"https://doi.org/10.1109/ITMS.2018.8552951","url":null,"abstract":"The customer segmentation divides customers into groups according to a range of different characteristics. It is necessary to understand the customers from different angles. The paper describes a five steps customer segmentation method consisting of gathering of quantitative information; creating specific microsegments; sorting microsegments; creating final customer segments; and linking the segments to marketing. The method is used for customer segmentation at a financial institution. The experimental studies conducted specifically focus on interactions between customer area-specific micro segmentations and final all-round customer segmentation. The final segmentation results are integrated in business intelligence applications for utilization in marketing operations.","PeriodicalId":367060,"journal":{"name":"2018 59th International Scientific Conference on Information Technology and Management Science of Riga Technical University (ITMS)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125546861","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}

{"title":"Hospital Information System (HIS) Performance in the Post-implementation Stage","authors":"Hossein Ahmadi, F sadoughi, Tania Azadi, L. Shahmoradi","doi":"10.1109/ITMS.2018.8552966","DOIUrl":"https://doi.org/10.1109/ITMS.2018.8552966","url":null,"abstract":"Hospital Information Systems (HIS) have been used widely in different healthcare settings and yet not many of them can gain the expected benefits of it. Despite the initial successful adoption, many evidences suggest that hospitals are not able to fully utilize the advantages of HIS in post-implementation stage. This paper aims to discover the influential dimension and their respective factors affecting HIS performance in the post-implementation stage. A quantitative study of Iranian public hospitals was performed to determine the influential dimensions as organization, technology and continuous process improvement and their respective factors including user participation, efficiency, user training, competency of HIS internal team, and inter-department collaboration/communication. Potential dimensional factors describing the successful use of HIS to improve hospital performance in the post-implementation stage was proposed and tested through administration of a questionnaire in 16 public hospitals affiliated to Tehran University of Medical Sciences. Data were analyzed using the Statistical Package for the Social Sciences (SPSS) version 22 with data scored in Likert Scale (score 1–5). The results show that there are two influential dimensions including HIS use and continuous process improvement having positive effect on successful performance of HIS in post-implementation stage. Findings of this study reveal how HIS is exploited in Iranian hospitals and giving added values to their users. Despite the focus of many HIS literature on system adoption, this paper discovers the post-implementation stage and tries to shed light on the actual use of HIS and its performance under the influence of its predominant factors.","PeriodicalId":367060,"journal":{"name":"2018 59th International Scientific Conference on Information Technology and Management Science of Riga Technical University (ITMS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128962056","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}

{"title":"Establishing Supply Chain process framework based on SCOR model: case study","authors":"Andrejs Girjatovičs, Laila Māra Pesoa, O. Kuzņecova","doi":"10.1109/ITMS.2018.8552963","DOIUrl":"https://doi.org/10.1109/ITMS.2018.8552963","url":null,"abstract":"Business process frameworks are now usually used as commonplace to support companies in embracing enterprise architectures and working out how all business processes fit together. There are different methodologies and frameworks available for achieving this goal. The paper presents the case study of the implementation of the Supply Chain SCOR framework in Retail Company.","PeriodicalId":367060,"journal":{"name":"2018 59th International Scientific Conference on Information Technology and Management Science of Riga Technical University (ITMS)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128349912","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}

{"title":"Process Improvement in Furniture Manufacturing: A Case Study","authors":"Filiz Ersoz, T. Ersoz, Hamza Peker","doi":"10.1109/ITMS.2018.8552968","DOIUrl":"https://doi.org/10.1109/ITMS.2018.8552968","url":null,"abstract":"Today, with the increasing competition, enterprises are working to increase the product quality in order to meet the demands of the customers and increase the market share. The Six Sigma philosophy that emerged in the 1970s is a study to reduce the costs of poor quality in the production and service process. In this study, Six Sigma philosophy was applied in order to reduce the cycle time of the diamond sofa product produced by a furniture enterprise. Firstly, the production line was examined in detail by SIPOC analysis method and the cycle times of the processes were collected by chronometry method. Then, statistical methods such as proj ect identification document, Pareto diagram, Fishbone diagram were used. The control of the change in cycle time in the production of diamond sofa was calculated by ARENA 9.0 simulation program.","PeriodicalId":367060,"journal":{"name":"2018 59th International Scientific Conference on Information Technology and Management Science of Riga Technical University (ITMS)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128738712","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}

{"title":"Investigation of network intrusion detection using data visualization methods","authors":"V. Bulavas","doi":"10.1109/ITMS.2018.8552977","DOIUrl":"https://doi.org/10.1109/ITMS.2018.8552977","url":null,"abstract":"There are numerous sources of network intrusion detection data, for example, network traffic, system host logs, user activity, such as mail or browsing, use of smart devices and similar. All these data come in big volume, velocity and variety. Analysis of such data is essential for making anomaly detection and intrusion prevention decisions. Common data processing steps, following the acquisition of data and pre-processing, are data reduction and projection. These steps help to reduce the number of dimensions, and visualization, which enables observation of distinct features in real time. Projection and visualisation, further discussed in this paper are required for better understanding of contained intrusion phenomena, such as data theft, malware activity or hacking attempts. Machine learning enables reduction of data complexity, supports discovery of anomalies and speedups related decision-making. Visualization helps further understand data by elaborating the well-hidden data properties and features. Numerous methods of multidimensional data visualization are currently available to assist data scientist or information security analyst in the broad landscape of intrusion data analysis. For simplicity, visualization methods in this paper are categorized as direct, linear projection, non-linear projection and other. Attention is drawn to linear projection, in particular principal components analysis, helping to select the most informative dimensions of the data. Principal Component analysis provide indication of anomalies of network traffic. Decision Tree method is utilized to provide decision criteria for anomaly recognition as an intrusion. Investigation in this research demonstrates that combination of PCA and Decision Tree methods allows classification of intrusions such as Smurf, Satan, Neptune, Portsweep, Ppsweep with probabilities higher than 95% with depth of tree set to 4 and number of PCA components set to 10. Nevertheless, Nmap and Teardrop intrusions are classified purely, therefore deeper Decision Tree is needed to increase classification accuracy.","PeriodicalId":367060,"journal":{"name":"2018 59th International Scientific Conference on Information Technology and Management Science of Riga Technical University (ITMS)","volume":"120 1‐2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120853117","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}

{"title":"[Copyright notice]","authors":"","doi":"10.1109/itms.2018.8552971","DOIUrl":"https://doi.org/10.1109/itms.2018.8552971","url":null,"abstract":"","PeriodicalId":367060,"journal":{"name":"2018 59th International Scientific Conference on Information Technology and Management Science of Riga Technical University (ITMS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116689595","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}

{"title":"SQL query construction from database concepts","authors":"Henrihs Gorskis","doi":"10.1109/ITMS.2018.8552953","DOIUrl":"https://doi.org/10.1109/ITMS.2018.8552953","url":null,"abstract":"The paper extends on previously proposed database concepts and their use as mapping point to a database in a domain ontology. It describes the process of constructing SQL queries from them. The proposed database concepts allow for the mapping of domain concept to the sources of data from a database. The paper describes the process of traversing the class hierarchy in an ontology. This is done to gather database concepts and to construct a SQL query. The purpose of the constructed SQL query is to obtain data from a database and to populate the ontology. It is populated with instances related to the selected ontology concept. The described process begins with the selection of one ontology concept, continues with obtaining all directly related concepts from the ontology, filtering and collecting database concepts, and y finishes with constructing the SQL query.","PeriodicalId":367060,"journal":{"name":"2018 59th International Scientific Conference on Information Technology and Management Science of Riga Technical University (ITMS)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122122583","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}

{"title":"Multiplicative aggregation for ERP upgrade decision making","authors":"Maksim Goman, S. Koch","doi":"10.1109/ITMS.2018.8552962","DOIUrl":"https://doi.org/10.1109/ITMS.2018.8552962","url":null,"abstract":"This paper introduces an alternative multiplicative performance measure for the aggregation of different criteria estimates for decision making. The application to a decision problem of upgrading enterprise resource planning (ERP) system is considered for illustration.","PeriodicalId":367060,"journal":{"name":"2018 59th International Scientific Conference on Information Technology and Management Science of Riga Technical University (ITMS)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128152049","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}