• Cover Page
• Editorial Board and Information for Authors
• Aims and Scope
• Contents
Contents
Special section
Mészáros A., Papp J. and Telek M.
Fitting traffic traces with discrete canonical phase type distributions and Markov arrival processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .453
Atencia I.
A discrete-time system with service control and repairs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 471
Kim C., Dudin A., Dudin S. and Dudina O.
Analysis of an MMAP/PH1, PH2/N/∞ queueing system operating in a random environment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .485
Zeifman A., Satin Y., Korolev V. and Shorgin S.
On truncations for weakly ergodic inhomogeneous birth and
death processes . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .503
Gaidamaka Y., Pechinkin A., Razumchik R., Samouylov K. and Sopin E.
Analysis of an M|G|1|R queue with batch arrivals and two hysteretic overload control policies . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 519
Zhao J., Mhedheb Y., Tao J., Jrad F., Liu Q. and Streit A.
Using a vision cognitive algorithm to schedule
virtualmachines . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .535
Dębski R.
High-performance simulation-based algorithms for an alpine ski racer’s trajectory optimization in heterogeneous computer systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .551
Regular section
Yuan L., Liu J. and Tang X.
Multiple-instance learning with pairwise instance similarity . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .567
Cichosz P. and Pawełczak Ł.
Imitation learning of car driving skills with decision trees and random forests . . . . . . . . . . . . . . . .579
Kowalski M., Kaczmarek P., Kabaciński R., Matuszczak M., Tranbowicz K. and Sobkowiak R.
A simultaneous localization and trackingmethod for a wormtracking system. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 599
Chen G. and Yang Z.Z.
Methods for estimating vehicle queues at a marine terminal: A computational comparison . . . . . . . . . . 611
Helmi B.H., Rahmani A.T. and Pelikan M.
A factor graph based genetic algorithm. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .621
Ding D., Ma Q. and Ding X.
An unconditionally positive and global stability preserving NSFD scheme for an epidemic model with vaccination . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .635
Tran H.L., Pham V.N. and Vuong H.N.
Multiple neural network integration using a binary decision tree to improve the ECG signal recognition accuracy. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 647
Muszyński M. and Osowski S.
Data mining methods for gene selection on the basis of gene expression arrays . . . . . . . . . . . .657
Kumar D.T., Soleimani H. and Kannan G.
Forecasting return products in an integrated forward/reverse supply chain utilizing an ANFIS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 669
Vukašinović V., Šilc J. and Škrekovski R.
Modeling acquaintance networks based on balance theory . . . . . . . . . . . . . . . . . 683
Domańska J., Domański A., Augustyn D.R. and Klamka J.
A RED modified weighted moving average for soft real-time application . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .697