Enterprise resource planning (ERP) is widely used to boost the total market power of businesses. The wrong selection is one of the key reasons why ERP installations fail. Due to the complexity of the business environment and the range of ERP systems, choosing an ERP system is a complex and time-consuming procedure. ERP alternatives may be assessed using several criteria, so the ERP selection process may be considered a multi-criteria decision-making (MCDM) problem. In this study, the rough best worst method (BWM) was used to determine criteria weights, while the newly developed rough integrated simple weighted sum product (WISP) was used to rank ERP alternatives. Results suggest that the SFT-4 coded software is regarded as the best option, followed by SFT-5, SFT-6, SFT-2, SFT-3, and SFT-1. Results of the newly developed rough WISP method are compared to those of existing rough techniques in the sensitivity analysis. The differences between them have been found to be negligible. The outcomes show how effectively developed rough BWM and WISP integrated method performs in terms of ERP selection with usability, accuracy, ease of use, and consistency. This study will help decision-makers in a context where ERP is implemented choose the best ERP software for different sectors.

We examine the class of finite paragraded groups which we will denote by $\mathcal{P}.$ After observing that the class $\mathcal{P}$ is closed with respect to subgroups and direct products (\cite{7}), we define the notion of a pro-$\mathcal{P}$ group and consider the completion of such a group.   2000 Mathematics Subject Classification. 08A05, 16W50, 20L05, 20E18, 20-99

This paper introduces a novel chaotic strategy for controlling the acceleration coefficients within the particle swarm optimization (PSO) algorithm. The PSO algorithm with chaotic exponential-based acceleration coefficients is developed to enhance the exploration of the search space and avoid premature convergence, a common issue associated with the standard PSO algorithm. The PSO algorithm with chaotic exponential-based acceleration coefficients is applied to multilevel image thresholding. The attained experimental results demonstrate that the PSO algorithm utilizing the chaotic strategy to control the cognitive and social acceleration coefficients can be successfully utilized for the selection of image thresholds across a variety of images.

This paper deals with the development and testing of an intelligent vibration damping system that can real-time analyze the vibration of the system, of which it is an integral part, and acting on vibration decreasing. Damping system is based on the pendulum tuned mass damper. The system can determine combinations of changes in mechanical properties and introduce additional disturbances to achieve optimal reduction of induced vibrations. The system's performances were evaluated through experiments conducted on an experimental model. The experiment involved variations in pendulum to observe the system's response for initial perturbance. The embedded system was implemented using an Arduino controller and accompanying components such as an actuator, data acquisition device, accelerometer, and PC. The paper also discusses a proposed adaptive pendulum mass damper with real-time tuning capability for controlling structural vibrations. Combining experimental and simulation results, the paper demonstrates the effectiveness of the developed system and the adaptive pendulum mass damper in actively damping vibrations in structures.

Single axis trackers have their application in the efficiency improvement process of photovoltaic systems. In spite of large investment costs, their application is necessary in the areas with a low amount of available solar irradiation. This is applicable only if it is required to exploit all available energy sources at any cost. With optimization and improvement of these systems it is possible to increase their efficiency, reduce energy usage for their movement and improve system reliability. Motion parameters are significant for the optimization of the system. It is necessary to set and monitor the right parameters as a prerequisite for system optimization. The process of calibration of single axis tracker prototype is shown in this paper. It is shown that proper calibration and system adjustment could improve efficiency of the system.

The political systems of Bosnia and Herzegovina, Cyprus, and Lebanon are defined by ethnic or religious divides that have historical roots in their Ottoman and European colonial past. This paper aims to investigate the impact of these historical legacies on popular representation and institutional structures. The Ottomans and European colonizers created institutions that allowed subjects to elect their representatives, shaping these countries' initial experiences with modernity. This paper employs historical institutionalism as a theoretical approach, and path dependency as a methodology to explore how historical legacies have shaped the political institutions and power‐sharing arrangements in Bosnia and Herzegovina, Cyprus, and Lebanon.

Energy production is one of the most crucial scientific, technological, economic, and political challenges in today's world. In response to the increasing demands of the European Union for reducing CO2 emissions and mitigating climate change, countries are obligated to align their national energy plans with clearly defined objectives, aiming for climate neutrality by 2050. This paper explores the location potential and optimal implementation of biomass power plants in Bosnia and Herzegovina. Biomass power plants, particularly those utilizing wood and plant biomass, are a promising solution for simultaneously reducing pollution, addressing unnecessary waste, and improving the energy efficiency of the systems where they are installed. The paper concludes that the potential of wood and plant biomass in Bosnia and Herzegovina remains underutilized. From an eco-perspective, the paper will also examine the reuse of large degraded areas in mines, where the fast-growing energy crops like Miscanthus could be planted.

In this paper we deal with sheaves of the category of paragraded rings with the same set of grades $\Delta,$ in short, the category of paragraded rings of type $\Delta,$ denoted by $R^P_\Delta.$ The definition of a sheaf of category $R^P_\Delta$ is the same as for any other category, but we are interested in the paragraded structure sheaf, as we named it here, and so, in some way we introduce the theory of paragraded structures into algebraic geometry. For this purpose we need to deal with homogeneous ideals, particularly, we need to introduce the prime spectrum of $R\in\mathrm{obj}(R^P_\Delta)$ and to analyze the localization of $R$.   2010 Mathematics Subject Classification. 16S60, 16S85, 16W99

The Teacher Efficacy for Inclusive Practices (TEIP) scale is a widely used instrument for assessing teachers' effectiveness in implementing inclusive practices. The TEIP has not been validated in Bosnia and Herzegovina (BIH). The goal of the present study was to conduct a confirmatory factor analysis (CFA) of the TEIP in a sample of teachers in BIH. The sample consisted of 239 elementary school teachers (204 females, 35 males; mean age‐ 43.5 years, SD‐ 8.3 years). The results of the CFA found that the original TEIP structure was not a good fit for our data. However, through some modifications on the item level, we created a satisfactory model that retained the same structure as the original TEIC. The composite reliability and construct maximal reliability were well above the recommended cut point of 0.70 for all factors. Our findings suggest that the modified version of the TEIP has the potential to be an effective and useful instrument for assessing teachers' efficacy in inclusive practices in BIH. This study represents an important step towards the cultural adaptation and validation of the TEIP in BIH, highlighting areas for future research and application in diverse educational contexts.

With the move towards 6G and associated technology deployment in higher frequency bands, measurements of directionally-resolved channels and sounders capable of performing such measurements are a necessity. In this paper, we present a new concept of channel sounding based on a Redirecting Rotating Mirror Arrangement (ReRoMA), capable of performing double-directional channel measurements at millimeter wave frequencies by mechanical beam steering orders of magnitude faster than existing rotating-horn arrangements. We present this new concept, describe a prototype operating at 60 GHz, and use it to perform, as proof-of-principle, a dynamic cart-to-cart channel measurements at a T-intersection scenario. We show that this sounding principle works and allows the directional evaluation of the channel. We visualize the different resolvable propagation paths in terms of dynamic angular and delay power spectrum, and relate them to the environmental geometry.

One of the key factors critical to the advancements of IoT systems in remote areas today are energy-efficient IoT deployment and the integration with IoT /edge/continuum. An energy-efficient IoT deployment requires finding adequate solutions for applications that require remote area devices and the related replacement and charging of batteries. On the other hand, an efficient integration of different communication technologies spanning the IoT, edge and cloud continuum that at the same time can integrate energy harvesting devices in remote areas is still an open challenge. In this paper, we integrate energy harvesting with wearable remote IoT devices on freely roaming farm animals within the edge/cloud continuum along its powerful application layer protocols, MQTT and AMQP. We experimentally investigate the performance of kinetic energy harvester used to power a LoRa module to send application layer messages from IoT to cloud. From the functional system testing perspective, we show that these messages can be successfully forwarded for further processing and evaluation in the edge and cloud setting even from the remote areas. We engineered an inexpensive and first open-source multi-protocol MQTT based communication gateway, as an alternative to today's proprietary and expensive gateway solutions, and we built a system that can not only power the capturing of animal movement patterns outdoors, but also the related application-layer protocol messages.

This paper explores the contribution of custom-trained Large Language Models (LLMs) to developing Open Education Resources (OERs) in higher education. Our empirical analysis is based on the case of a custom LLM specialized for teaching business management in higher education. This custom LLM has been conceptualized as a virtual teaching companion, aimed to serve as an OER, and trained using the authors’ licensed educational materials. It has been designed without coding or specialized machine learning tools using the commercially available ChatGPT Plus tool and a third-party Artificial Intelligence (AI) chatbot delivery service. This new breed of AI tools has the potential for wide implementation, as they can be designed by faculty using only conventional LLM prompting techniques in plain English. This paper focuses on the opportunities for custom-trained LLMs to create Open Educational Resources (OERs) and democratize academic teaching and learning. Our approach to AI chatbot evaluation is based on a mixed-mode approach, combining a qualitative analysis of expert opinions with a subsequent (quantitative) student survey. We have collected and analyzed responses from four subject experts and 204 business students at the Faculty of Economics, Business and Tourism Split (Croatia) and Faculty of Economics Mostar (Bosnia and Herzegovina). We used thematic analysis in the qualitative segment of our research. In the quantitative segment of empirical research, we used statistical methods and the SPSS 25 software package to analyze student responses to the modified BUS-15 questionnaire. Research results show that students positively evaluate the business management learning chatbot and consider it useful and responsive. However, interviewed experts raised concerns about the adequacy of chatbot answers to complex queries. They suggested that the custom-trained LLM lags behind the generic LLMs (such as ChatGPT, Gemini, and others). These findings suggest that custom LLMs might be useful tools for developing OERs in higher education. However, their training data, conversational capabilities, technical execution, and response speed must be monitored and improved. Since this research presents a novelty in the extant literature on AI in education, it requires further research on custom GPTs in education, including their use in multiple academic disciplines and contexts.

Heuristic search is often used for motion planning and pathfinding problems, for finding the shortest path in a graph while also promising completeness and optimal efficiency. The drawback is it's space complexity, specifically storing all expanded child nodes in memory and sorting large lists of active nodes, which can be a problem in real-time scenarios with limited on-board computation. To combat this, we present the Search with Learned Optimal Pruning-based Expansion (SLOPE), which, learns the distance of a node from a possible optimal path, unlike other approaches that learn a cost-to-go value. The unfavored nodes are then pruned according to the said distance, which in turn reduces the size of the open list. This ensures that the search explores only the region close to optimal paths while lowering memory and computational costs. Unlike traditional learning methods, our approach is orthogonal to estimating cost-to-go heuristics, offering a complementary strategy for improving search efficiency. We demonstrate the effectiveness of our approach evaluating it as a standalone search method and in conjunction with learned heuristic functions, achieving comparable-or-better node expansion metrics, while lowering the number of child nodes in the open list. Our code is available at https://github.com/dbokan1/SLOPE.

Introduction Between 2021 and 2023, a project was funded in order to explore the mortality burden (YLL–Years of Life Lost, excess mortality) of COVID-19 in Southern and Eastern Europe, and Central Asia. Methods For each national or sub-national region, data on COVID-19 deaths and population data were collected for the period March 2020 to December 2021. Unstandardized and age-standardised YLL rates were calculated according to standard burden of disease methodology. In addition, all-cause mortality data for the period 2015–2019 were collected and used as a baseline to estimate excess mortality in each national or sub-national region in the years 2020 and 2021. Results On average, 15–30 years of life were lost per death in the various countries and regions. Generally, YLL rates per 100,000 were higher in countries and regions in Southern and Eastern Europe compared to Central Asia. However, there were differences in how countries and regions defined and counted COVID-19 deaths. In most countries and sub-national regions, YLL rates per 100,000 (both age-standardised and unstandardized) were higher in 2021 compared to 2020, and higher amongst men compared to women. Some countries showed high excess mortality rates, suggesting under-diagnosis or under-reporting of COVID-19 deaths, and/or relatively large numbers of deaths due to indirect effects of the pandemic. Conclusion Our results suggest that the COVID-19 mortality burden was greater in many countries and regions in Southern and Eastern Europe compared to Central Asia. However, heterogeneity in the data (differences in the definitions and counting of COVID-19 deaths) may have influenced our results. Understanding possible reasons for the differences was difficult, as many factors are likely to play a role (e.g., differences in the extent of public health and social measures to control the spread of COVID-19, differences in testing strategies and/or vaccination rates). Future cross-country analyses should try to develop structured approaches in an attempt to understand the relative importance of such factors. Furthermore, in order to improve the robustness and comparability of burden of disease indicators, efforts should be made to harmonise case definitions and reporting for COVID-19 deaths across countries.