The objective of preparing and presenting financial statements is to provide information about the financial position and performance of an entity, which is useful to a wide range of users of financial statements for business decisions. If information presented in the financial statements is not full disclosure and/or is incorrect, the presented image of the business entity will be wrong, as well as business decisions made on the basis of such financial statements. Unfortunately, many entities knowingly manipulate revenues and expenses to manage earnings in a way that suits the entity management. Detecting frauds in financial statements is the primary task of forensic accountants. This paper analyzes the possibilities of applying Benford’s law in the forensic analysis of income statements of economic entities in Bosnia and Herzegovina, to detect possible earnings manipulation. The results of the research confirm that the positions of revenues and expenses in the income statements of economic entities in Bosnia and Herzegovina generally follow Benford’s law, but also stress the need to increase attention and conduct additional forensic investigations for certain items as indicators of financial statement manipulation.

Advanced signal detectors pose a lot of technical challenges for designing signal detection methods in orthogonal frequency division multiplexing (OFDM) with index modulation (IM). Traditional signal detection methods such as maximum likelihood have an excessive complexity, and existing deep learning (DL) based detection methods can reduce the complexity significantly. To further improve the detection performance, in this paper, we propose a complex deep neural network (C-DNN) and a complex convolution neural network (C-CNN) based intelligent signal detection method for OFDM-IM. Specifically, the proposed intelligent signal detection method is designed by C-DNN and C-CNN. The proposed signal detection methods for OFDM-IM use pilots to achieve semi-blind channel estimation, and to reconstruct the transmitted symbols based on channel state information (CSI). Simulation results are given to confirm the performance of the proposed signal detection method in terms of bit error rate and convergence speed.

Money laundering, in its almost 90-year-long history, has attracted the attention of the scientific, professional, but also the general public. Throughout the entire period, the manifestations of this criminal phenomenon, its typology, etiological factors, etc., have changed, but the essence has remained the same: the transformation of illegally acquired money into legal financial flows. Emerging markets are particularly burdened, which is the subject of this paper: identifying, monitoring and proving the process of money laundering with the aim to reduce it in developing countries. In addition, what can be observed in these markets is that money laundering operations are mainly related to those activities where most of the payments are made in cash. Their specificity, that is, the basic motive for execution, is not just a profit, but the aspiration to introduce “dirty” money into legal flows. The aim of this paper is to use the method of description to explain and describe scientifically the money laundering process and to combat this phenomenon with a focus on the characteristics of the money laundering process. In addition, the paper describes the models and weaknesses of this process, while at the same time it respects the standards and specifics of business operations in emerging markets. The result of the paper is that it provides an overview of money laundering in the 21st century in small and open economies, including proposals to prevent and combat this negative phenomenon.

The paper aims to investigate the influencing factors for the choice of accounting specialization by students at ten public higher education institutions in Bosnia and Herzegovina (BiH). In addition to the above, the paper also explores the gender structure of the students, the type of secondary education, the time of making the decision to choose the field of accounting, and planned future training in accounting. The research sample consisted of 253 respondents, and data collection was performed by electronic survey through distance learning platforms. To identify the key factors in choosing to study accounting, we used the multivariate method of factor analysis of major components. The results of the research point to the existence of four key influencing factors in the selection of accounting specialization: achievement, job fulfillment, the influence of authorities in the field of science and profession, and the influence of parents and friends. Over 77 percent of the students are women, and the students have mostly completed general high schools (gymnasiums) or high schools of economics (92 percent). More than 98 percent of the students plan to continue their training in the field of accounting. The results of the research have practical use in terms of preparation and presentation of accounting policies at public higher education institutions in BiH, given that the reduced number of students has resulted in rival positions among different study areas. The results of the research can also be useful to professional groups in the field of accounting in terms of achieving their strategic goals.

Concrete is one of the most used materials in the world, second only to water. One of the key advantages of this versatile material is its workability in the early stages before setting. Here, we use in situ underwater Raman microspectroscopy to investigate and visualize the early hydration kinetics of ordinary Portland cement (OPC) with submicron spatial and high temporal resolution. First, the spectral features of the C-S-H gel were analyzed in the hydroxyl stretching region to confirm the coexistence of Ca-OH and Si-OH bonds in a highly disordered C-S-H gel. Second, the disordered calcium hydroxide (Ca(OH)2) is experimentally identified for the first time in the mixture before setting, suggesting that Ca(OH)2 crystallization and growth are essential in the setting of cement paste. Finally, the phase transformations of clinker, C-S-H, and Ca(OH)2 are spatially and temporally resolved, and the hydration kinetics are studied by analyzing the spatial relationships of these phases using two-point correlation functions. The results quantitatively validate that the setting occurs as a percolation process, wherein the hydration products intersect and form an interconnected network. This time-space-resolved characterization method can map and quantitatively analyze the heterogeneous reaction of the cementitious colloidal system and thus provide potential application value in the field of cement chemistry and materials design more broadly.

Specific emitter identification (SEI) is a promising technology to discriminate the individual emitter and enhance the security of various wireless communication systems. SEI is generally based on radio frequency fingerprinting (RFF) originated from the imperfection of emitter’s hardware, which is difficult to forge. SEI is generally modeled as a classification task and deep learning (DL), which exhibits powerful classification capability, has been introduced into SEI for better identification performance. In the recent years, a novel DL model, named as complex-valued neural network (CVNN), has been applied into SEI methods for directly processing complex baseband signal and improving identification performance, but it also brings high model complexity and large model size, which is not conducive to the deployment of SEI, especially in Internet-of-things (IoT) scenarios. Thus, we propose an efficient SEI method based on CVNN and network compression, and the former is for performance improvement, while the latter is to reduce model complexity and size with ensuring satisfactory identification performance. Simulation results demonstrated that our proposed CVNN-based SEI method is superior to the existing DL-based methods in both identification performance and convergence speed, and the identification accuracy of CVNN can reach up to nearly 100% at high signal-to-noise ratios (SNRs). In addition, SlimCVNN just has 10% $\sim 30$ % model sizes of the basic CVNN, and its computing complexity has different degrees of decline at different SNRs; there is almost no performance gap between SlimCVNN and CVNN. These results demonstrated the feasibility and potential of CVNN and model compression.

Majority of new technologies in electrical engineering nowadays belong to the field of smart grids. Smart grids master programs are being implemented in the Western Balkans countries through the EU funded project ELEMEND. Within smart grids curriculum, practice-oriented teaching is crucial to teach students practical skills needed on the job market. This paper presents the practice-oriented approach of the team from the Public Electric Utility Elektroprivreda of Bosnia and Herzegovina d.d. - Sarajevo, being taught at the International Burch University within three courses from the Smart Grids in Electrical Distribution Systems master program. Apart from the basic theoretical knowledge, students are given projects with real-life problems and real data. Students are being trained to do projects using two commercial software tools. Projects are often on some of the challenging topics of smart grids and the final results of the project are therefore often published in international and national journals and conferences. Also, excursions and site visits to real-life visits of some of the smart grid technologies are organized, as well as internships for some of the students. Therefore, students are at the end trained and qualified for smart grid related jobs on the job market.

Swallowing physiology includes numerous biomechanical events including displacement of the hyoid bone, which is a crucial component of airway protection and opening of the proximal esophagus. The objective of this study was to evaluate the potential relations between the trajectory of hyoid bone movement and the risk of airway penetration and aspiration during a videofluoroscopic swallowing study. Two hundred sixty-five patients were involved in this study, producing a total of 1433 swallows of various volumes consisting of thin liquid, nectar-thick liquid, and solids during a fluoroscopic exam. The anterior and posterior landmarks of the body of the hyoid bone were manually marked in each frame of each fluoroscopic video. Generalized estimation equations were applied to evaluate the relationship between penetration–aspiration scores and mathematical features extracted from the hyoid bone trajectories, while also considering the influence of other independent variables such as age, bolus volume, and viscosity. Our results indicated that penetration–aspiration scores showed a significant relation to age. The maximum anterior (horizontal) displacement of the anterior hyoid bone landmark was significantly associated with the penetration–aspiration scores. Differences in the displacement of the hyoid bone are useful observations in airway protection. In this work, the potential relations between the trajectory of hyoid bone movement and the risk of airway penetration and aspiration during a videofluoroscopic swallowing study were evaluated. We extracted features from the hyoid bone trajectories and applied generalized estimation equations to investigate their relationship to penetration–aspiration scales. The results showed that the maximum anterior (horizontal) displacement of the anterior hyoid bone landmark was significantly associated with the penetration–aspiration scales. In this work, the potential relations between the trajectory of hyoid bone movement and the risk of airway penetration and aspiration during a videofluoroscopic swallowing study were evaluated. We extracted features from the hyoid bone trajectories and applied generalized estimation equations to investigate their relationship to penetration–aspiration scales. The results showed that the maximum anterior (horizontal) displacement of the anterior hyoid bone landmark was significantly associated with the penetration–aspiration scales.

The activities related to medical device market can be divided into pre-market and post-market surveillance. Pre-market processes have been defined by Medical Device Directives since 1992. These directives define all aspects of medical device design, production, testing, approval and certification. Appropriate standards have been adopted to support these activities. The CE mark issued by European Notified Bodies confirms that the medical device complies with safety and performance standards related to its class and that is therefore safe for intended usage. Post-market surveillance is not as well defined, so the new Medical Device Regulation addresses the identified gap and emphasizes the importance of standardizing and harmonizing the system for surveillance of medical devices already in use. The MDRs require stakeholders to monitor the quality, performance and safety of a device throughout its life cycle and to take corrective or preventive action when necessary. In this paper, we discuss the possibility of using artificial intelligence on Big Data structures resulting from the comprehensive methodology of post-market surveillance.

The fast pace of scientific and technological developments and the pressing need for a flexible skilled workforce and innovative products in the more competitive than ever world markets require robust but flexible mechanisms for the development, implementation, monitoring and assessment of undergraduate and graduate curricula and courses. In our research, we focus on the quality assurance process designed to achieve the desired Learning Outcomes (LOs) for new courses and education programs. We propose tools and techniques used to determine the extent to which the stated learning outcomes are achieved. More specifically, we present the Quality Assurance approach developed in the ERASMUS+ CBHE project Electrical Energy Markets and Engineering Education (ELEMEND). The approach for developing the LOs is based on the European Qualification Framework (EQF) which defines professional levels in terms of learning outcomes, i.e. knowledge, skills and autonomy-responsibility, and the ENQA European Standards and Guidelines for determining the quality assurance procedures and metrics. As a case study, the methodology is applied to the LOs of ELEMEND courses and the results are discussed. Additionally, this paper reflects the unique experience of collaboration between EU universities, HEIs of West Balkans, enterprises, and professional associations in order to create up to date curricula in smart grid related topics with sustainable links to the related industry and businesses.

Neonatal Jaundice (NJ) is a worldwide and commonly known issue with known treatment and preventions. However, in low-resource settings (LRSs), the solution to treatment is far from trivial. This paper aims to address the issues and causes for insufficient NJ phototherapy on a global scale, presenting the design, test and development of a first prototype of a vest, with embedded fibre optics and sensors for autonomous phototherapy treatment of new born jaundice in LRSs. Specifically, this paper evaluates and reports on the feasibility of such a device to be a means of delivering complete and effective phototherapy treatment to jaundiced neonates in LRSs. Among the main innovations included in our design, are garmented jaundice treatment, accessibility in LRSs, and integrated diagnostics for a closed loop control. The scope will hopefully facilitate at-home treatment in an effort to fulfil the global unmet need for phototherapy, typically occurring in rural and LRSs. In particular, this paper focuses on how the results of the needs assessment were cascaded into an innovative product design specification.

The goal of this paper is to determine the injury frequency rate in professional football players in leagues and national competitions by analyzing existing papers. We have chosen 21 articles according to the PRISMA method from the Google Scholar, ResearchGate Scopus, and Web of Science databases that fit both inclusion and exclusion criteria. We have discussed the following four segments based on the content of the selected papers: 1) An analysis of the injury frequency rate on the level of national teams, 2) An analysis of the injury frequency rate in club leagues, 3) A comparison of the injury frequency rate in matches and in practice, and 4) An analysis of the injury frequency rate in male versus female football players. The paper concludes that major national team tournaments have the highest injury frequency rate and that the probability of injury is four to five times higher in a match than in practice. The injury frequency rate in female players is lower than in male players regardless of the type of competition (national teams or leagues).