The purpose of this paper is to examine the current state of rural tourism in Republic of Srpska as well as to provide guidance and recommendations for the development of this form of tourism. The used model approach expert opinion and, on this occasion, the DEX method of multicriteria decision-making was used. With this model, an assessment of rural tourist capacities is carried out on a random sample of four tourist facilities. The reason for the results obtained in this way is that the observed facilities have adequately used the natural resources available to Republic of Srpska. In addition, recommendations and guidelines are given in order to further develop this type of tourism in Republic of Srpska. The presented model offers an innovative approach in the assessment of current and potential tourist facilities. For this reason, it should be used in future research.

The aim of the research in the paper is to evaluate the state of rural settlements in Brčko District with regard to the development of rural tourism. Together with the Tourism Department of the Brčko District, five experts from the field of tourism were selected and they evaluated the current state of rural settlements in this part of Bosnia and Herzegovina. The evaluations were processed using the fuzzy approach with the SWARA (Stepwise Weight Assessment Ratio Analysis) multi-criteria decision-making method. Using this method, the weights of the used criteria were determined, representing the degree of development of conditions in rural settlements. The results showed that "rural facilities and services" are the best developed in rural settlements, while the criteria related to feelings and experiences are the least developed. Based on this research, it is possible to implement measures to strengthen certain criteria that have not been adequately developed in order to further improve rural tourism in Brčko District.

Changes in the market, caused by globalization, have led to the fact that many companies needed to adapt their operations. In response to these changes, the concept of supply chain was developed to help companies from procurement to sales of products. This paper examines the effects of supply chains on competitiveness using the example of agro-food companies from the Republic of Croatia. The research was conducted through a questionnaire which included 188 agribusiness companies. The responses were systematized and statistically processed using descriptive statistics, correlation analysis and multivariate regression analysis. The results showed that the effects of supply chains play a major role in determining the competitiveness of agro-food companies. Therefore, it is necessary to improve the effects of the supply chain in these companies in order to improve competitiveness and achieve better results of these companies on the market.

Meat inspection is an important part of education for every veterinary student. However, traditional teaching methods require the sacrifice of living animals, and are thus considered expensive, inadequate and inhumane. Development of novel technologies has provided opportunities for new, improved ways of education. Smart 3D Meat Inspection (S3DMI) is an elearning tool that allows veterinary medicine students to acquire required skills using virtual 3D models of animal organs and carcasses. These models can be manipulated and “cut” just like real organs, allowing students to learn this essential skill without the need for animal carcasses. Students are allowed to practice any part of meat inspection as many times necessary, at their own pace, without time, place or resources limitations. This type of education is considered superior to traditional methods. There is no need for sacrification of animals for educational purposes and the cost of education is greatly reduced, while the educational quality is uninterrupted. Models developed for S3DMI can also be adjusted for courses like animal anatomy and pathology, which also require the use of real animal cadavers. S3DMI is still in its developmental stages, but it has a great potential to minimalize the need for animal sacrifice in the education of future veterinarians, while ensuring the quality improvement.

— Cause-effect graphing is a commonly used black-box technique with many applications in practice. It is important to be able to create accurate cause-effect graph specifications from system requirements before converting them to test case tables used for black-box testing. In this paper, a new graphical software tool for creating cause-effect graph specifications is presented. The tool uses standardized graphical notation for describing different types of nodes, logical relations and constraints, resulting in a visual representation of the desired cause-effect graph which can be exported for later usage and imported in the tool. The purpose of this work is to make the cause-effect graph specification process easier for users in order to solve some of the problems which arise due to the insufficient amount of understanding of cause-effect graph elements. The proposed tool was successfully used for creating cause-effect graph specifications for small, medium and large graphs. It was also successfully used for performing different types of tasks by users without any prior knowledge of the functionalities of the tool, indicating that the tool is easy to use, helpful and intuitive. The results indicate that the usage of standardized notation is easier to understand than non-standardized approaches from other tools.

Cause-effect graphs are a popular black-box testing technique. The most commonly used approach for generating test cases from cause-effect graph specifications uses backward-propagation of forced effect activations through the graph in order to get the values of causes for the desired test case. Many drawbacks have been identified when using this approach for different testing requirements. Several algorithms for automatically generating test case suites from cause-effect graph specifications have been proposed. However, many of these algorithms do not solve the main drawbacks of the initial back-propagation approach and offer only minor improvements for specific purposes. This work proposes two new algorithms for deriving test cases from cause-effect graph representations. Forward-propagation of cause values is used for generating the full feasible test case suite, whereas multiple effect activations are taken into account for reducing the feasible test case suite size. Evaluation of the test case suites generated by using the proposed algorithms was performed by using the newly introduced test effect coverage and fault detection rate effectiveness metrics. The evaluation shows that the proposed algorithms work in real time even for a very large number of cause nodes. The results also indicate that the proposed algorithm for generating all feasible test cases generates a larger test case suite, whereas the proposed algorithm for test case suite minimization generates a smaller test case subset than the originally proposed approaches while ensuring the maximum effect coverage, fault detection rate effectiveness and a better test effect coverage ratio.