Iskanje po katalogu digitalne knjižnice

Opis: This paper aims to assess and compare the relative efficiency of commercial banks in six Western Balkan developing countries (North Macedonia, Serbia, Montenegro, Bosnia and Herzegovina (B&H), Kosovo1, and Albania), using the leading nonparametric methodology Data Envelopment Analysis (DEA) for the period 2016-2020, and investigating the impact of the COVID-19 pandemics on the performance of banking systems in these countries. The outputoriented DEA model has been implemented with interest expenses and noninterest expenses as inputs and interest revenue and non-interest revenue as outputs. Our findings show that the average efficiency of the six Western Balkan banking systems differs, and Kosovo’s banking system has noted the highest average efficiency in the whole observed period (2016–2020). In contrast, the banking system in Bosnia and Herzegovina noted the lowest average efficiency. The COVID-19 pandemic decreased the relative efficiency of the banking sectors in all six of the Western Balkan countries observed, except Kosovo. However, additional research that includes all pandemic years is recommended to assess the impact of the COVID-19 pandemic on the banking systems in the Western Balkans. This study provides invaluable insights for academic members, banking management and regulatory bodies, governments, and the interested public. It is the first empirical study that includes a glimpse of the first impact of the COVID-19 pandemic on banking systems in the developing countries of the Western Balkans.
Ključne besede: banking sector, data envelopment analysis, COVID-19, Western Balkans
Objavljeno v DKUM: 05.09.2023; Ogledov: 262; Prenosov: 7
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Opis: Depression is a prevalent comorbidity in patients with severe physical disorders, such as cancer, stroke, and coronary diseases. Although it can significantly impact the course of the primary disease, the signs of depression are often underestimated and overlooked. The aim of this paper was to review algorithms for the automatic, uniform, and multimodal classification of signs of depression from human conversations and to evaluate their accuracy. For the scoping review, the PRISMA guidelines for scoping reviews were followed. In the scoping review, the search yielded 1095 papers, out of which 20 papers (8.26%) included more than two modalities, and 3 of those papers provided codes. Within the scope of this review, supported vector machine (SVM), random forest (RF), and long short-term memory network (LSTM; with gated and non-gated recurrent units) models, as well as different combinations of features, were identified as the most widely researched techniques. We tested the models using the DAIC-WOZ dataset (original training dataset) and using the SymptomMedia dataset to further assess their reliability and dependency on the nature of the training datasets. The best performance was obtained by the LSTM with gated recurrent units (F1-score of 0.64 for the DAIC-WOZ dataset). However, with a drop to an F1-score of 0.56 for the SymptomMedia dataset, the method also appears to be the most data-dependent.
Ključne besede: multimodal depression classification, scoping review, real-world data, mental health
Objavljeno v DKUM: 11.08.2023; Ogledov: 529; Prenosov: 64
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Opis: In the fast-paced business landscape, unexpected events can pose significant challenges for companies. A lot of times, business intelligence presents a solution for companies in dealing with changes and improving organizational efficiency. As part of this master’s thesis, we have developed a business intelligence system that assists in the planning of new releases of smartphone components. We have simulated data and created reports, which can help the stakeholders to plan and analyze important milestones easily. We have tested two different data structures and showed how star schema is the most beneficial data structure for our BI system. We achieved this by restructuring data into a star schema model at different stages of migration and then compared the size of data and responsiveness of operations.
Ključne besede: business intelligence, star schema, data modeling
Objavljeno v DKUM: 27.06.2023; Ogledov: 414; Prenosov: 53
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Ključne besede: FDI, economic growth, sectoral data, manufacturing
Objavljeno v DKUM: 19.06.2023; Ogledov: 435; Prenosov: 4
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Opis: This handbook is a product of the Erasmus+ Strategic Partnership between the partners Université Polytéchnique Hauts-de-France, Politechnika Poznanska, Brandenburgische Technische Universität Cottbus-Senftenberg and the coordinator University of Maribor. Contentuous contribution were made by staff of University of Maribor and Politechnika Poznanska, evaluations by staff of the other two partners. The handbooks handles virtual learning environments in the international education and research area and exposure of the systems to cybercrime. Besides introductory contributions on legal aspects of challenges in the fields of human rights, European regulations of data security, civil law and criminal law aspects of caber security of virtual learning environments and methodologies of their introduction w8ithin organisations, the handbook also gives useful instructions for elaboration of virtual courses within virtual learning environments relevant for the internationalised research and education not only since the Covid-19 pandemic. The handbook is dedicated to use on the internet within the Moodle system.
Ključne besede: cyber security, virtual learning environment, data security, cyber crime, systems
Objavljeno v DKUM: 13.04.2023; Ogledov: 554; Prenosov: 40
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