The protection and preservation of the privacy of personal data are one of the main requirements when it comes to an application dealing with the processing of such data. It is no different when it comes to information systems that store and process data about students in higher education systems. The public presentation of such data represents a serious threat to the safety of students as well as their status within the higher education system. For this reason, it is necessary to use the possibility of advanced technologies in order to raise data security to the highest level. One such technology that is able to provide transparency, security and data protection at a high level is blockchain technology. In this work, the Hyperledger Fabric distributed ledger private blockchain network was analyzed and its usability in terms of user rights management in higher education system was evaluated. Experimental analysis showed that such a platform has the ability to take advantage of private blockchain technologies in terms of user rights management and to provide security, flexibility and scalability of the system.

Maintaining and establishing transparency, security and privacy, when the data that should be included as part of documents that should serve as public educational documents in the labor market, are a challenging task, especially nowadays when we have more frequent cyber-attacks on public institutions. Setting up the security mechanisms of information systems that should store, process and show this type of data can be a very demanding job. For this reason, the introduction of new technologies in this area, such as blockchain technology, leads to considerable system and implementation relief. In this paper, private blockchain platforms are analyzed from the point of view of processing digital certificates or diplomas in the higher education system. An overview of the most popular platforms of this type is given. The most appropriate solution for these needs are discussed and proposed.

Mycotoxins have become a serious issue in the animal feed industry and have also affected the aquaculture industry. Mycotoxins can create serious health problems in aquatic and terrestrial animals, and their presence in agricultural products may result in significant economic losses. To reduce the impact of mycotoxins on Nile tilapia fry, two commercially available products—Organically Modified Clinoptilolite (OMC) and multi-component mycotoxin detoxifying agent (MMDA)—were used in this study. Six diets as treatments (T1 = Control (C); T2 = Control + OMC 2 g/kg (OMC); T3 = Control + MMDA 2 g/kg (MMDA); T4 = AFB1 0.5 mg/kg (AF); T5 = AFB1 0.5 mg/kg + 2 g/kg OMC (AFOMC); T6 = AFB1 0.5 mg/kg + MMDA 2 g/kg (AFMMDA)) with similar crude protein levels (35.75 ± 0.35%) were formulated and fed to Nile tilapia fry (1.97 ± 0.1 g) for a period of 84 days. These fish were housed in 18 aquaria (100 L) at a density of 50 fish/aquarium. The results from this study showed that MMDA significantly (p < 0.05) improved the survival of fish by 16% as compared to the control group. Nevertheless, growth parameters were not affected among the treatments. These results also indicated that protein intake was significantly higher in the control and OMC diet (T2) compared to aflatoxin B1-fed tilapia. The protein efficiency ratio (PER) was significantly higher in the AFMMDA as compared to the control and MMDA. A 14-day bacterial challenge test with Aeromonas hydrophila demonstrated that diets containing MMDA or OMC improved survival when AFB1 was present in the diet. Therefore, the supplementation of feed with MMDA or OMC is recommended to ameliorate the negative effects of AFB1 in Nile Tilapia feeds.

The increase in the number of wind farms and their share in the total electrical energy generation leads to the need for a different approach to this source in cases where the stability of the power system is potentially impaired. With the development of different types of wind power plants, equipped with power electronics devices, there is the possibility of quick power management and injection, in conditions when it is needed, where a huge amount of accumulated kinetic energy can also be used. This paper presents the influence of a wind power plant equipped with a full-scale converter on the transient stability in cases of close and distant short circuits, during the outage of a heavily loaded line. Special attention was paid to the Rate of Change of Frequency (RoCoF) in the power system in cases with and without a wind farm where fast power injections were possible.

The contribution of renewable energy sources to the power system stability will have to be greater in the future. The problem will arise if the share of wind power plants in total production increases and large failures occur. Then, wind farms, which are often called inertia-less sources in the literature, will have to help maintain the frequency in a normal amount by changing the management method and based on fast PMU measurements. This can be done by using the synthetic inertia size, which is defined for sources that are derived from the system via energy converters and which do not participate in defining the total inertia of the system. This paper provides a better insight into the understanding of the concept of synthetic inertia, as well as insight into the current development of management and the application of synthetic inertia in maintaining the stability of the power system.

When students enroll at universities, various datasets can be available to managers and teachers. Clustering techniques can be applied in order to divide the instances within those datasets into natural groups. In this paper, one clustering-based approach combined with attribute selection methods for identifying specific input dataset variables meaningful for the disjunction of distinct students' profiles has been proposed. Also, an analysis of the descriptive students' model obtained by the proposed methodology is performed.

New forms of communication are created as a result of the advancement of information and communication technologies, particularly the Internet and the WWW. These technologies introduce technological solutions as a response to ongoing difficulties. Relying on the predominant written form, besides its semantics, content on WWW must convey additional information like its structure, formatting, and relationships between its parts. Markup languages were born. Although markup languages addressed the issue at hand, they also raised several new issues, one of which is how to exchange material between disparate markup languages. In this paper, creating a meta-model of the two most commonly used markup languages, Markdown and HTML, is shown. The meta-model is created using the Eclipse Modeling Framework (EMF) ECore model, which relies on grammar obtained from markup languages. This meta-model simplifies comprehension of the relationship between markup language content and its model, which represents the first step towards the automatic transformation between models, i.e., the interchange of their content.

In research to determine the degree of interest in enrolling students in certain high schools, predictive analysis and comparison models are rarely used when classifying and processing different data. All this leads to large fluctuations in enrolment in secondary schools, where certain schools are unable to enrol numerous students who show an interest in a particular field. On the other hand, students lose interest in certain schools, which leads to the discontinuation of certain courses necessary for the needs of today's labour market. Institutions responsible for organizing the educational process do not sufficiently compare and connect teaching and non-teaching activities when analysing the talents and interests of elementary school students from different fields. The goal of this work is to predict the enrolment of students in secondary schools, using the classifiers of programming languages, based on the results that students express during regular classes in elementary schools.The results show that the accuracy of the data during the training of the Random Forest predictor is 52%, while in Wolfram Alpha it is 62%

The paper presents the most recent achievements in developing AMADEOS - the first online web-based tool aimed at business process model-driven database design. The preexisting AMADEOS was able only to derive an initial conceptual database model automatically, while other design phases were not supported. The most recent development efforts resulted in the complete coverage of the database design process, from conceptual model to physical database, by using the standard UML notation.

The idea of this paper is the proposal of a low-cost control device based on the concept of IoT, which will have many functionalities integrated. A large number of integrated functionalities make it possible to satisfy a large number of different users. The proposed control device solution could be used both for controlling the operation of devices and machines in industrial plants and for training engineers.

Embedded systems are widely used in different spheres of everyday life. Implementation of web server into these systems enable remote access to processed data. Web server implementation should be suitable for limited resources of these systems. In this paper, web server implementation in system for air parameter monitoring will be presented. This implementation is done using LwIP stack and enables remote access to measurement results within local network. Operation principle of web server and whole system will be discussed.

The Internet of Things (IoT) is considered a new paradigm that aims to connect a large number of devices. IoT is increasingly present in domains such as healthcare, transport, agriculture, and other industrial branches. An increasing number of IoT devices, as well as the amount of data, leads to increased energy consumption and a negative impact on the environment. Therefore, researchers are focusing on the concept of Green IoT that aims to increase energy efficiency and create a safe environment. The focus of this paper is on energy-efficient techniques within green data centers. Also, the performance evaluation of data centers was performed in the GreenCloud simulator for the optimal load of data centers in terms of energy efficiency and sustainability.

Introduction: Antimicrobial resistance and the rapid spread of multiresistant bacteria represent one of the main public health problem in limited resources countries. This issue is significantly worsening since the COVID-19 pandemic due to the unreasonably increased antibiotics prescription to patients with confirmed SARS-CoV-2 infection. The aim of this study was to examine whether COVID-19 pandemic (2020, 2021) was associated with increased antibiotic consumption in inpatient and outpatient settings in the middle size urban region (Republic of Srpska/Bosnia and Herzegovina) in comparison to period before the pandemic (2019). Additionally, we aimed to determine antimicrobial resistance and the presence of multiresistant bacteria in the regional hospital (“Saint Apostol Luka” Hospital Doboj) in 2021. Methodology: The consumption of antibiotics in inpatient was calculated as Defined Daily Dose per one hundred of patient-days. The consumption of antibiotics in outpatient was calculated as Defined Daily Dose per thousand inhabitants per day. Resistance of bacteria to antibiotics is expressed as a rates and density for each observed antibiotic. The rate of resistance was calculated as a percentage in relation to the total number of isolates of individual bacteria. The density of resistance of isolated bacteria against a specific antibiotic was expressed as the number of resistant pathogens/1000 patient days. Results: Antibiotic consumption in hospital setting registered during 2019, 2020 and 2021 was as follows: carbapenems (meropenem: 0.28; 1.91; 2.33 DDD/100 patient-days, respectively), glycopeptides (vancomycin: 0.14; 1.09, 1.54 DDD/100 patient-days, respectively), cephalosporins (ceftriaxone: 6.69; 14.7; 14.0 DDD/100 patient-days, respectively) and polymyxins (colistin: 0.04; 0.25; 0.35 DDD/100 bed-days, respectively). Consumption of azithromycin increased drastically in 2020, and dropped significantly in 2021 (0.48; 5.61; 0.93 DDD/100 patient-days). In outpatient setting, an increase in the consumption of oral forms of azithromycin, levofloxacin and cefixime, as well as parenteral forms of amoxicillin-clavulanic acid, ciprofloxacin and ceftriaxone, was recorded. In 2021, antimicrobial resistance to reserve antibiotics in hospital setting was as follows: Acinetobacter baumanii to meropenem 66.0%, Klebsiella spp to cefotaxime 67.14%, Pseudomonas to meropenem 25.7%. Conclusion: Recent COVID-19 pandemic was associated with increased antibiotic consumption in inpatient and outpatient settings, with characteristic change of pattern of azithromycin consumption. Also, high levels of antimicrobial resistance to reserve antibiotics were registered in hospital setting with low prevalence of identified pathogen-directed antimicrobial prescription. Strategies toward combat antimicrobial resistance in the Doboj region are urgently needed.

Since depletion of natural resources and the amount of construction and demolition waste have overcome the socially and environmentally acceptable level, the construction industry must address this issue and reduce its impact on the environment. A step towards sustainability in the construction industry is the application of recycled aggregates and supplementary cementitious materials as integral components of concretes, which provides conserving natural aggregates and waste reduction. This study adopts a holistic approach to producing green self-compacting concrete with the highest portion of recycled aggregate as a replacement for natural aggregate and fly ash as filler. Based on the particle packing density method, four series of self-compacting concrete were prepared: the first series was made with natural fine and coarse aggregate, the second series was made with fine natural aggregate and recycled coarse aggregate, the third with 50 % (by mass) of fine natural aggregate replaced by recycled fine aggregate and recycled coarse aggregate, and the fourth series completely with recycled fine and coarse aggregate. The content of fly ash remained constant. Regardless of the expected decrease of workability in a fresh state with the increase of the recycled aggregate content, all series exceeded the requirements set for the hardened structural concrete.

Objectives The addition of CT-derived fractional flow reserve (FFR-CT) increases the diagnostic accuracy of coronary CT angiography (CCTA). We assessed the impact of FFR-CT in routine clinical practice on clinical decision-making and patient prognosis in patients suspected of stable coronary artery disease (CAD). Methods This retrospective, single-center study compared a cohort that received CCTA with FFR-CT to a historical cohort that received CCTA before FFR-CT was available. We assessed the clinical management decisions after FFR-CT and CCTA and the rate of major adverse cardiac events (MACEs) during the 1-year follow-up using chi-square tests for independence. Kaplan–Meier curves were used to visualize the occurrence of safety outcomes over time. Results A total of 360 patients at low to intermediate risk of CAD were included, 224 in the CCTA only group, and 136 in the FFR-CT group. During follow-up, 13 MACE occurred in 12 patients, 9 (4.0%) in the CCTA group, and three (2.2%) in the FFR-CT group. Clinical management decisions differed significantly between both groups. After CCTA, 60 patients (26.5%) received optimal medical therapy (OMT) only, 115 (51.3%) invasive coronary angiography (ICA), and 49 (21.9%) single positron emission CT (SPECT). After FFR-CT, 106 patients (77.9%) received OMT only, 27 (19.9%) ICA, and three (2.2%) SPECT ( p  < 0.001 for all three options). The revascularization rate after ICA was similar between groups ( p  = 0.15). However, patients in the CCTA group more often underwent revascularization ( p  = 0.007). Conclusion Addition of FFR-CT to CCTA led to a reduction in (invasive) diagnostic testing and less revascularizations without observed difference in outcomes after 1 year. Key Points • Previous studies have shown that computed tomography–derived fractional flow reserve improves the accuracy of coronary computed tomography angiography without changes in acquisition protocols. • This study shows that use of computed tomography-derived fractional flow reserve as gatekeeper to invasive coronary angiography in patients suspected of stable coronary artery disease leads to less invasive testing and revascularization without observed difference in outcomes after 1 year. • This could lead to a significant reduction in costs, complications and (retrospectively unnecessary) usage of diagnostic testing capacity, and a significant increase in patient satisfaction.