This study analyzes financial literacy in Bosnia and Herzegovina by considering three areas: interest, inflation, and diversification, with financial literacy as a multi-dimensional construct consisting of financial knowledge and financial skills. Using a cross-sectional questionnaire-based survey, 638 valid responses were collected from working-age individuals (18-65 years old). Financial knowledge and skills were analyzed through a prism of several demographic factors, including age, education, household income, and gender. Welch's F tests, ANOVA with Brown-Forsythe, LSD post hoc tests, and Welch's t-tests were performed to test the hypotheses. The findings provide evidence of moderate financial literacy. Similarly to previous studies, financial knowledge and skills partially depend on the respondent's age, education, household income, and gender. The study contributes to the current literature by taking a much-needed non-functional approach to examining financial literacy, focusing not only on financial knowledge but also on often neglected financial skills and providing insight into the unique context of Bosnia and Herzegovina.

Diabetes is a widespread disease, suffered by millions, including children. Treatment of diabetes type 1 and sometimes even type 2, entails multiple blood glucose checks and insulin injections per day, and can thus be extremely exhausting, especially for very young children. Open-loop systems of insulin delivery, insulin pumps, used today commercially, require human interaction which can lead to low blood glucose control due to human mistakes. Fully automated closed-loop systems of artificial pancreas, as one-hormone as well as dual-hormone systems, are being developed. This paper is the literature survey of the latest research on the automated closed-loop artificial pancreas. The objective of this paper is to explore the development of devices and techniques to facilitate the daily life of diabetic patients with emphasis on the latest research on the topic. From so-called pens to open-loop systems of insulin pumps, closed-loop systems with user interaction -hybrid closed-loop, to the latest fully automatized closed-loop -artificial pancreas. In total 300 articles are reviewed from which 150 articles are retained for the literature survey and 50 are analysed in this literature review.

The purpose of this study was to compare attitudes toward sexting using vignettes. Participants were 49 university students (ages 19-26) who participated in five online focus group discussions and responded to five written vignettes describing sexting. The five vignettes about sexting were composed of five types of sexting experiences: 1) sexting under intimate partner pressure, 2) revenge sexting, 3) consensual sexting with intimate partner, 4) sexting under peer pressure, and 5) sexting to flirt with others. Students gave their opinions on the vignettes presented. Revenge sexting was perceived as a behaviour more negative than any other type of sexting experience. The vignette that depicted sexting with an intimate partner in a long-distance relationship was perceived as the least negative of all types of sexting. The results of this study aim to inspire future studies to use vignettes as a methodological tool to determine youths' attitudes, beliefs, and opinions about sexting.

Understanding physical effects occurring, for example, in the electromagnetic field, can be challenging. To ease the learning experience, it is beneficial to visualize and encourage interaction with the physical field. Augmented Reality (AR) can serve as a tool to visualize naturally invisible fields to help students understand physical effects. In this paper, we present a workflow to incorporate field results stemming from a FEM tool or simple analytical solutions into an augmented reality (AR) experience. We focus on providing a simple framework for educators to integrate this tool into school or university teaching. We present a workflow to process simulation results for AR and provide source material through a template and a guide so that educators can quickly translate their projects into (augmented) reality. The basis for this project is the game engine Unity, which can be used free of charge for educators. Combined with other free or open-source programs for visualization and preparation like openCFS and Paraview, this setup can be used freely by anybody for education.

The aim of this work is to optimize the design of a sensor-actuator measurement system for identifying local variations in the magnetic permeability of cut steel sheets. Before the identification problem, i.e. finding the material parameters causing the measurement data, is solved, the design of the measurement setup should first be improved in order to increase the identifiability of the material distribution. For the objective function of the design optimization the Fisher information matrix (FIM) is used, which allows to quantity the amount of information that the measurements carry about the unknown parameters. To evaluate the magnetic field values depending on various design parameters and material distributions, a 2D magneto-static problem is solved by the finite element method. Due to the high numerical effort arising with evaluating the FIM and thus calculating the forward model many times within the optimization procedure, a surrogate model of the sensor-actuator system has been trained in advance and is used to predict the magnetic flux densities.

Software processes consist of a complex set of activities required to deliver software products within predicted quality, costs, and deadlines. To accomplish such goals, a software organization needs a quality and mature software process as a prerequisite for success. Adopting Software Capability Maturity Model Integration (CMMI) represents a well-known path in the pursuit of mature software processes. However, its implementation is a subject of a permanent effort that implies different approaches and methods, and often leads to unsuccessful or limited success, though. This is especially emphasized in small software companies given the dynamic environment influenced by different factors, including insufficient resources, changes in technology, and staff turnover. In this paper, a case study of a small software company implementing software process improvement is presented. In a tailored approach to process improvement, a specific method using the balanced scorecard as input into the IDEAL model has been designed, enabling a narrow link between business goals and specific improvement goals. The results show that the software process and selected performance indicators were improved, and suggest the potential of the proposed approach in small organizations.

In the aftermath of the recent pandemic, organizations around the world had the opportunity to assess the benefits and drawbacks of allowing the bulk of their employees to work from home (WFH). As a result, many organizations realize that by using technology, it is possible to shift a significant percentage of their workforce to permanently function from any location without being physically present at a designated workplace. Although the economic benefits for organizations that allow WFH seem to be clear, how factors related to perceptions of employees such as their work motivation (WM) and their work-life balance (WLB) caused by blurred boundaries between work and family at home are not clearly understood. Therefore, the primary goal of this study is to determine how WFH impacts WLB through the possible mediating effects of work-family conflict (WFC) and WM. A cross-sectional survey instrument was developed using Likert type measurement scales that were adopted from top-tier journals. The data was collected through convenient sampling from 249 managerial and non-managerial employees in Omani business organizations. The relationships were tested through structural equation modeling. The results indicate that WFH increases WFC and WM, while the relationship between WFH and WLB is mediated by WFC, but not by WM. The findings of this study have implications for both theory and practice.

To assess the prevalence, clinical characteristics, and outcomes of patients with heart failure (HF) with or without moderate to severe aortic valve disease (AVD) (aortic stenosis [AS], aortic regurgitation [AR], mixed AVD [MAVD]).

Key account management (KAM) is a strategic approach that focuses on developing and retaining long-term relationships with key customers. In today’s business world, where competition is fierce and disruption is the norm, KAM has become increasingly important for companies looking to maintain a competitive edge. In Bosnia and Herzegovina, many companies are beginning to recognize the value of KAM and are implementing KAM strategies to improve their financial performance. To better understand the impact of KAM on financial performance in Bosnia and Herzegovina, ongoing research is being conducted to identify the influence of key account management orientation on company financial performance in different industry sectors. The research has collected data from several companies in various industries, with each company being considered as a unit of analysis. To ensure the reliability and validity of the research instrumentation, a validated and reliable questionnaire was used, and item total reliability and confirmatory factor analysis were employed to test the reliability and validity of the constructs. The analysis of the data collected will be done using the structural equation modeling (SEM) technique, which will allow the researchers to identify the effects of key account management orientation on the company’s financial performance. The researchers expect to find statistically significant evidence supporting the impact of KAM orientation on the financial performance of companies in Bosnia and Herzegovina. The findings of this research could have important implications for companies looking to improve their financial performance through the implementation of KAM strategies. By demonstrating the impact of KAM on financial performance, the research could encourage more companies in Bosnia and Herzegovina to adopt KAM strategies and help them gain a competitive edge in their respective industries.

The Internet of things (IoT) is getting more and more intrusive into our lives until the day comes when everything becomes connected to the Internet. Due to the limited resources and heterogeneous Internet of Things (IoT) devices, the traditional means of protection are useless and cannot be used to protect these devices. The most important security risks, their causes and the consequences of their occurrence have been listed, scheduled and categorized. The study concluded that there are real security risks that cannot be ignored, and they need to find innovative solutions to eliminate them or reduce their damage to a minimum. This paper showed the main risks addressed in previews research, and outlined the gaps in this field of technology, also producing a brief summary information about the most important solution to avoid many threats against the IoT field.

The Transport & Logistics (T&L) industry directly employs around 10 million people and accounts for 5% of the Gross Domestic Product (GDP) of the European Union (EU). Effective T&L systems are fundamental for the ability of European companies to compete in the world economy. With the advent of 5G with the data rates of up to 20Gbps, its end-to-end latencies down to 5ms, and its very high reliability (99,999%), there is a significant opportunity to bring innovations to the T&L vertical, and why the T&L sector is expected to be one of the key adopters of 5G technology. In this paper, we define a 5G testbed tailored to T&L vertical services, which are designed and developed using the concept of 5G-based Edge Network Applications defined within the European project VITAL-5G. In addition to the testbed, we also describe the interaction with the testbed and its accessibility via the VITAL-5G platform, which supports T&L actors to experiment and validate their services within the real-life 5G-based T&L environment (e.g., sea ports, river ports, and warehouses).

Accurate prediction of cellular link performance represents a corner stone for many adaptive applications, such as video streaming. State-of-the-art solutions focus on distributed device-based methods relying on historic throughput and PHY metrics obtained through device APIs. In this paper, we study the impact of centralised solutions that integrate information collected from other network nodes. Specifically, we develop and compare machine learning inference engines for both distributed and centralised approaches to predict the LTE physical resource blocks using ns3-simulation. Our results illustrate that network load represents the most important feature in the centralised approaches resulting in halving the RB prediction error to 14% in comparison to 28 % for the distributed case.

COVID-19 is a contagious disease caused by a virus, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The first known case was identified in Wuhan, China, in December 2019. The disease quickly spread worldwide, resulting in the COVID-19 pandemic. The outburst of COVID-19 pandemic had tremendous effect on the whole world and analysis of the data can be meaningful in many ways to better understand the effect it had in our society. This paper aims in the direction of analysis of COVID-19 daily information based on country and continent level in terms of understanding the number of cases and deaths and their relationship, besides this is aims to better understand the vaccination number by country and effect of cases/death how they have affected these numbers. The solution was created on analysis of a dataset that contains daily information on each country, and using MySQL, SQL and PowerBi to generate the results for this work in way of query results which have been transformed to visuals using PowerBi for better understanding for further research work on this topic.

Premature ventricular complex (PVC) is seen in most individuals. It has been shown that the kinetics‐tracking index or Kawasaki‐Tanaka index (KT index) strongly predicts pulmonary capillary wedge pressure (PCWP) by noninvasively. KT index was defined as log10 (active LAEF/minimum LAV index). We goaled to assess PCWP non‐invasively in patients with frequent PVCs with normal left ventricular systolic functions and to evaluate whether there is an increase in PCWP before systolic and diastolic functions are impaired.