Információ Technológia Tanszék Publikációk

A tanszék tagjainak publikációi áttekinthetőek az iDEa Tudóstér oldalán.

Válogatás az elmúlt év publikációiból

Bátfai, N., Jeszenszky, P., Mamenyák, A., Halász, B., Besenczi, R., Komzsik, J., Kóti, B., Kövér, G., Smajda, M., Székelyhídi, C., Takács, T., Róka, G., Ispány, M.: Competitive programming: A case study for developing a simulation-based decision support system. Infocommun. J 8 (1), 24-38., 2016.

  • FootballAvatar is an experimental industrial research and development subproject of the project 'SziMe3D?3D technological innovation in tourism, education and sport'. FootballAvatar aims to produce a novel decision support information system based on simulations for professional football clubs. This paper establishes the notion of football avatar in the sense of information technology, though it has a strong mathematical background. However, we would like to apply it in several analytic and simulation software tools developed in our project. The main question is that how this notion could be implemented and used in several software environments including C++, Java, and R,or from an architectural viewpoint, on desktops, smart phones, and tablets, while the kinds of uses and the base definitions have often changed during the R&D phases. This changing of the precise interpretation of the notion of "football avatar" has a direct impact on selecting the software process model. For this reason, we have developed an own software methodology called Competitive Programming, which will be presented in detail, as a main result in the present paper.

Biró, P., Csernoch, M., Abari, K., Máth, J.: First Year Students' Algorithmic Skills in Tertiary Computer Science Education. Knowledge, Information and Creativity Support Systems Selected Papers from KICSS'2014 - 9th International Conference, held in Limassol, Cyprus, on November 6-8, 2014 351-358. -, 2016.

  • Faculties of Informatics are facing the problem in Hungary that students starting their tertiary education in Computer Sciences do not have a satisfactory level of algorithmic skills, their knowledge seems superficial, and the dropout rate is extremely high in these courses. We have launched a project to test how students’ algorithmic skills have been developed in their primary and secondary education, how students evaluate their knowledge. The test proved that an extremely high percentage of the students arrive at the Faculty of Informatics with underdeveloped algorithmic skills, with unreliable knowledge, and they do not consider the recently emerged, non-traditional environments as programming tools and facilities for developing algorithmic skills.

Csernoch, M., Biró, P.: Introduction to Classroom Sprego. Acta Didact. Napocensia 9 (1), 1-14., 2016.

  • Sprego is programming with spreadsheet functions. The present paper provides introductory Sprego examples which have so far only been available in Hungarian. Spreadsheet environments offer both a programming tool which best serves beginner and end-user programmers' interest, and an approach which lightens the burden of coding and language details. Sprego programming utilizes these tools and offers a real world problem solving method based on authentic tables with various contents. The examples selected for the paper show how Sprego programming can be introduced into programming and/or spreadsheet classes.

Biró, P., Csernoch, M.: Sprego-programozás hatékonyságvizsgálata. In: Interdiszciplináris pedagógia és az oktatási rendszer újraformálása : A IX. Kiss Árpád Emlékkonferencia előadásainak szerkesztettváltozata : Debrecen, 2015. szeptember 25-26. / Buda András, Kiss Endre, DE Neveléstudományok Intézete, Debrecen, 117-126, 2016.

  • A Sprego módszert - Spreadsheet Lego, programozás táblázatkezelői környezetben, funkcionális programozási nyelven - a projekt kezdetén olyan középiskolás diákok számára fejlesztettük ki, akik nehézkesen kezelték a táblázatkezelő programok grafikus felületét, annak ellenére, hogy nagyon jól teljesítettek az informatika más területein. Táblázatkezelői környezetben nem tudtak hatékonyan dolgozni, nem voltak képesek az itt felmerülő problémák hatékony megoldására. A módszer gyakorlati alkalmazása azonban bebizonyította, hogy lényegesen szélesebb körben is alkalmazható, valamint szolgálhat bevezető nyelvként más magas szintű programozási nyelvekhez.

Bourguignon, M., Vasconcellos, K., Reisen, V., Ispány, M.: A Poisson INAR(1) process with a seasonal structure. J. Stat. Comput. Simul 86 (2), 373-387., 2016.

  • This paper introduces a non-negative integer-valued autoregressive (INAR) process with seasonal structureof first order, which is an extension of the standard INAR(1) model proposed by Al-Osh and Alzaid [First-order integer-valued autoregressive (INAR(1)) process. J Time Ser Anal. 1987;8:261-275]. The main properties of the model are derived such as its stationarity and autocorrelation function (ACF),among others. The conditional least squares and conditional maximum likelihood estimators of the model parameters are studied and their asymptotic properties are established. Some detailed discussion is dedicated to the case where the marginal distribution of the process is Poisson. A Monte Carlo experiment is conducted to evaluate and compare the performances of these estimators for finite sample sizes. The standard Yule-Walker approach is also considered for comparison purposes. The empirical results indicate that, in general, the conditional maximum likelihood estimator presents much better performance in terms of bias and mean square error. The model is illustrated using a real data set.

Vágner, A.: The GridOPTICS clustering algorithm. Intelligent data analysis "Accepted by Publisher" 2016.

  • The OPTICS algorithm is a hierarchical density-based clustering method. It creates reachability plots to identify all clusters in the point set. Nevertheless, it has limitation, namely it is very slow for large data sets. We introduce the GridOPTICS algorithm, which builds a grid structure to reduce the number of data points, then it applies the OPTICS clustering algorithm on the grid structure. In order to get the clusters, the algorithm uses the reachability plots of the grid structure, then it determines to which cluster the original input points belong. The experimental results show that our new algorithm is faster than the OPTICS, the speed-up can be one or two orders of magnitude or more, which depends mainly on the (tau) parameter of the GridOPTICS algorithm. At the end of the article, we give some advice to which point set you can apply the GridOPTICS algorithm.

Frissítés dátuma: 2018.02.27.


Tisztelt Felhasználó!

 

A Debreceni Egyetem kiemelt fontosságúnak tartja a rendelkezésére bocsátott, illetve birtokába jutott személyes adatok védelmét. Ezúton tájékoztatjuk Önt, hogy a Debreceni Egyetem a 2018. május 25. napján hatályba lépett Általános Adatvédelmi Rendelet alapján felülvizsgálta folyamatait és beépítette a GDPR előírásait az adatkezelési és adatvédelmi tevékenységébe. A felhasználók személyes adatait a Debreceni Egyetem korábban is teljes körültekintéssel kezelte, megfelelve az érvényben lévő adatkezelési szabályozásoknak. A GDPR előírásait követve frissítettük Adatvédelmi Tájékoztatónkat, amelyet az alábbi linkre kattintva olvashat el: Adatkezelési tájékoztató. DE Kancellária VIR Központ