The article presents research about the use of genetic algorithms in the analysis of the interrelation among curriculum courses in higher education. The authors used genetic algorithms as a method to analyse the influence that achieved grades in predictors' courses have on achieved grades in dependent courses as well as to observe whether the genetic algorithms can contribute to improving the curriculum. The research was based on a set of data related to the success of students from the Faculty of Information Technologies at the University 'Džemal Bijediae' in Mostar, Bosnia and Herzegovina. The aim was to anticipate students' grades based on the grades they obtained in previous semester's courses. This research should help educational institutions to evaluate the suitability of the sequence of courses within the curriculum in order to enable personalized learning paths, make the teaching processes more efficient, and promote a balanced curriculum. Namely, a good curriculum can attract new students, improve the success rate of enrolled students, and increase the quality and visibility of the institution. Since the genetic algorithm is search techniques for handling complex spaces, we can use it for the research at each stage of the educational process. Analyses of quantitative data using a genetic algorithm can help educational institutions improve the quality of teaching.

One of the rapidly growing additive technology for polymer-based products is Fused Deposition Modeling (FDM), which is used for prototypes, single-part production and also small series production. Today, this technology is increasingly used for engineering purposes, and it is of great importance to know the mechanical properties of materials used in FDM technology, which are commonly thermoplastic polymers. The mechanical properties of materials are obtained by standard mechanical testing, but problem is that there are no official standards that define the method of mechanical testing of FDM materials. The aim of this study is to analyse the influence of the strain rate on tensile properties. Three different materials, PLA, tough PLA and carbon PLA, are examined. Strain rate was varied from 0,5 mm/min to 100 mm/min. The test was performed according to ISO 527-2. All specimens are 3D printed with 100 % infill and same 3D printing parameters.

Additive manufacturing is technology that is widely used to produce good quality products with complex geometries. One of the most popular additive technology today is fused deposition modelling (FDM). Literature review is showing that many parameters have influence on mechanical properties of FDM printed materials. Influence of FDM 3D printer model on strength properties of printed PLA (polylactic acid) material with different infill density is presented in this paper. Testing specimens are printed with five different 3D printer models of the same manufacturer with the same material and 3D printing parameters. Aim was to investigate 3D printer model influence on strength properties of 3D printed PLA material. The results of this study could be useful for users and researchers in order to select appropriate printer model for particular purpose considering optimal relation of PLA material strength properties and FDM 3D printer model.

Existence of standardized materials and product standards for various products gives confidence in complete material selection process. In case of welded steel products, respective product standards clearly define requirements for design and fabrication. Among many properties, four are mostly considered: strength, ductility, toughness, and weldability. Nowadays products are more demanding than ever, and it is not possible to consider single property anymore, but two or even three of them. In such cases, selection charts are used, making material selection easier. This paper provides selection charts and corresponding design criteria defined in welded product standards for selected structural steel grades. Values presented in selection charts are acquired through own researches, as well as from available literature. Considered structural steels are grades with yield strength from 355 to 960 MPa, available in three mayor delivery conditions: normalized, thermo-mechanically treated, and quenched and tempered.