{"title":"Incremental Rerouting Algorithm for single-vehicle VRPPD","authors":"R. Guralnik","doi":"10.1145/3134302.3134326","DOIUrl":"https://doi.org/10.1145/3134302.3134326","url":null,"abstract":"Transportation of goods and transportation of persons routing algorithms are extensively studied since early 80's as a subtype of a Traveling Salesman Problem. This subtype includes VRPPD (Vehicle Routing Problem with Pickup and Delivery), courier systems and DARP (dial-a-ride problem). But for these systems to be effective in real world situations, they have to react quickly and efficiently to unexpected circumstances like dense traffic or road closing. With this in mind we developed an incremental rerouting algorithm which modifies initial solution route according to the new traffic conditions.","PeriodicalId":131196,"journal":{"name":"Proceedings of the 18th International Conference on Computer Systems and Technologies","volume":"1997 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134166122","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":"Requirements Management in Students' Software Development Projects","authors":"Pekka Mäkiaho, T. Poranen, Zheying Zhang","doi":"10.1145/3134302.3134340","DOIUrl":"https://doi.org/10.1145/3134302.3134340","url":null,"abstract":"In this paper, we study requirements management practices in students' software development projects. The 12 projects studied applied iterative development models and agile practices. We analyze tools usage, methods, processes, common problems, risks, and challenges in requirements management. We also research changes in requirements statuses and conduct a more detailed analysis for status changes in three projects. As a result, we propose guidelines and suggestions to teachers and project managers based on our findings.","PeriodicalId":131196,"journal":{"name":"Proceedings of the 18th International Conference on Computer Systems and Technologies","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133155342","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}
A. Ivanov, S. Deleva, Milena Georgieva, D. Orozova
{"title":"A Conceptual Model of a Virtual Collaboration Space for Bat Scientists","authors":"A. Ivanov, S. Deleva, Milena Georgieva, D. Orozova","doi":"10.1145/3134302.3134308","DOIUrl":"https://doi.org/10.1145/3134302.3134308","url":null,"abstract":"The paper presents a conceptual model for development of a Virtual Collaboration Space for field scientists who research bats. The Space is designed as a Cloud Environment incorporating intelligent data structures where the Semantic Web concepts are applied. Agent-Oriented Programming Paradigm is used as a base and BDI Intelligent Software Assistants as an additional abstraction layer of communication between the Collaboration Space and the users. Furthermore, a data science algorithms would be applied in order to support the scientist on daily basis for their \"on field\" tasks.","PeriodicalId":131196,"journal":{"name":"Proceedings of the 18th International Conference on Computer Systems and Technologies","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131531318","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}
Oskari Jahkola, A. Happonen, Antti Knutas, J. Ikonen
{"title":"What Should Application Developers Understand about Mobile Phone Position Data","authors":"Oskari Jahkola, A. Happonen, Antti Knutas, J. Ikonen","doi":"10.1145/3134302.3134346","DOIUrl":"https://doi.org/10.1145/3134302.3134346","url":null,"abstract":"The paper presents a study of GPS location data provided by smartphones for the purpose of understanding what kind of physical location based issues software developers should consider while designing position aware applications. The study consists of a set of experiments, where GPS data provided by smartphones is evaluated in different setups, differentiated from each other based on signal reception environments. From the experiments, we deduct and present guidelines for the developers.","PeriodicalId":131196,"journal":{"name":"Proceedings of the 18th International Conference on Computer Systems and Technologies","volume":"126 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116089812","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":"Neural Network Application in Financial Area","authors":"R. Trifonov, D. Budakova, G. Pavlova","doi":"10.1145/3134302.3134336","DOIUrl":"https://doi.org/10.1145/3134302.3134336","url":null,"abstract":"Forecasting financial data is an extremely important issue and it is a good opportunity to demonstrate the capabilities of the neural networks. The objective of this study is to develop a neural network model for forecasting the direction of movement of financial data one step forward. The architecture of a neural network uses four different technical indicators, which are based on the raw data and the current day of the week. The training method is algorithm with back propagation of the error. The program realization and experimental results are considered in this article.","PeriodicalId":131196,"journal":{"name":"Proceedings of the 18th International Conference on Computer Systems and Technologies","volume":"310 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122782446","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}