1. Advancing intelligent toolpath generation: A systematic review of CAD–CAM integration in Industry 4.0 and 5.0Marko Simonič, Iztok Palčič, Simon Klančnik, 2025, izvirni znanstveni članek Opis: This systematic literature review investigates advancements in intelligent computer-aided design and computer-aided manufacturing (CAD–CAM) integration and toolpath generation, analyzing their evolution across Industry 4.0 and emerging Industry 5.0 (I5.0) paradigms. Using the theory–contextcharacteristics–methodology framework, the study synthesizes 51 peer-reviewed studies (from 2000 to 2025) to map theoretical foundations, industrial applications, technical innovations, and methodological trends. Findings reveal that artificial intelligence (AI) and machine learning dominate research, driving breakthroughs in feature recognition, adaptive toolpath optimization, and predictive maintenance. However, human-centric frameworks central to I5.0, such as socio-technical collaboration, remain underexplored. High-precision sectors (aerospace, biomedical) lead adoption, while small and medium enterprises (SMEs) lag due to resource constraints. Technologically, AI-driven automation and STEP-NC standards show promise, yet interoperability gaps persist due to fragmented data models and legacy systems. Methodologically, AI-based modeling prevails (49 % of studies), but experimental validation and socio-technical frameworks are sparse. Key gaps include limited real-time adaptability, insufficient AI training datasets, and slow adoption of sustainable practices. The review highlights the urgent need for standardized data exchange protocols, scalable solutions for SMEs, and human-AI collaboration models to align CAD–CAM integration with I5.0’s
Ključne besede: CAD–CAM integration, Industry 4.0, Industry 5.0, toolpath optimization, AI, theory–context–characteristics–methodology (TCCM)
Objavljeno v DKUM: 09.12.2025; Ogledov: 0; Prenosov: 4
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3. Do Kahoot! games enhance vocabulary learning?Caroline V. Katemba, Joshua H. L. Tobing, Talitha A. Putri, 2022, izvirni znanstveni članek Opis: Many educators are considering using online games for learning vocabulary. Among the existing online games is Kahoot. This study aimed to determine if male and female students learn vocabulary the same way using Kahoot! Games. The study examined whether there was any significant difference among the female and male groups in their vocabulary enhancement. This quantitative research study used a pre-test and a posttest administered to sixty-eight seventh-grade students. Findings revealed a significant difference in vocabulary enhancement between female and male students, thus supporting the use of Kahoot! games as an effective method for teaching vocabulary.
Ključne besede: technology & vocabulary, male vs. female, smartphone, EFL context
Objavljeno v DKUM: 25.07.2025; Ogledov: 0; Prenosov: 5
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4. Enhancing self-regulated learning in higher educationBarbara Šteh, Marjeta Šarić, 2020, izvirni znanstveni članek Opis: A key task of higher education is empowering students for in-depth learning, critical thinking, and assuming responsibility for learning and their future professional work. To attain these goals, it is crucial for students to acquire the ability to regulate their learning. This article presents the concept of self-regulated learning, together with the learning models and factors that contribute to the adequate application of self-regulating strategies. The latter depend on both students’ individual characteristics and contextual factors. The processes of self-regulated learning can be learnt and lead students to more meaningful learning, greater satisfaction in studying, and better learning outcomes.
Ključne besede: higher education, selfregulated learning, enhancing self-regulated learning, students’ characteristics, learning context
Objavljeno v DKUM: 26.06.2025; Ogledov: 0; Prenosov: 11
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5. From theory to practice : incentives for managers and professionalsBranka Zolak Poljašević, Nemanja Berber, 2024, izvirni znanstveni članek Opis: Although, in theory, a considerable amount of literature emphasizes the significance of employee incentive pay, there is not much empirical research indicating their dispersion in practice. The primary purpose of this study is to explore the level of implementation of various incentives in three countries: Slovenia, Serbia, Bosnia and Herzegovina. The research was conducted on a sample of 321 companies. Data for this study were extracted from the CRANET dataset. The latest data collection cycle was conducted in 2021-2022. In addition to descriptive statistics, the Pearson Chi-Square Test and Cramer's V test were used to test hypotheses. The research results indicate a statistically significant difference in using most observed compensation elements among the observed countries. The study contributes to compensation management literature by presenting empirical data regarding the degree of implementation of various compensation instruments in three observed countries.
Ključne besede: incentives, compensations, country context, managers, professionals
Objavljeno v DKUM: 28.05.2025; Ogledov: 0; Prenosov: 102
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6. RNGSGLR: generalization of the context-aware scanning architecture for all character-level context-free languagesŽiga Leber, Matej Črepinšek, Marjan Mernik, Tomaž Kosar, 2022, izvirni znanstveni članek Opis: The limitations of traditional parsing architecture are well known. Even when paired with
parsing methods that accept all context-free grammars (CFGs), the resulting combination for any
given CFG accepts only a limited subset of corresponding character-level context-free languages
(CFL). We present a novel scanner-based architecture that for any given CFG accepts all corresponding
character-level CFLs. It can directly parse all possible specifications consisting of a grammar and
regular definitions. The architecture is based on right-nulled generalized LR (RNGLR) parsing and
is a generalization of the context-aware scanning architecture. Our architecture does not require
any disambiguation rules to resolve lexical conflicts, it conceptually has an unbounded parser and
scanner lookahead and it is streaming. The added robustness and flexibility allow for easier grammar
development and modification.
Ključne besede: context-aware scanning, pseudo-scannerless parsing, scanner conflict resolution, generalized LR (GLR), right-nulled GLR (RNGLR), scannerless GLR (SGLR)
Objavljeno v DKUM: 28.03.2025; Ogledov: 0; Prenosov: 11
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7. Assessing the situation of micro, small, and medium-sized enterprises in the emerging markets of Egypt under COVID-19 implicationsNourhan Ahmed Saad, Sonja Mlaker Kač, Sara El Gazzar, 2023, izvirni znanstveni članek Opis: Micro, Small, and Medium-sized Enterprises (MSMEs) play a vital role in emerging economies, thus this research aims at assessing the current situation of Egyptian MSMEs under COVID-19 pandemic and identifying the role of Egyptian MSMEs in economic growth and development. This research adopted qualitative design; 24 semi-structured interviews were conducted with different eco-system stakeholders and MSMEs’ managers using content analysis to analyse collected data based on NVivo software. The findings revealed the importance of MSMEs sector in the emerging markets as well as global ones. Additionally, MSMEs play a significant role in enhancing country’s economic growth and development, particularly in GDP, job opportunities, domestic products/services, national income, sub-contractor, and individual/society welfare. Furthermore, the findings identify the main challenges that face Egyptian MSMEs under COVID-19 implications through analysing the four main strategic factors and concluded by policy recommendations that could be implemented by MSMEs’ owners to take full advantage in the Egyptian context and their contribution on country’s economic growth.
Ključne besede: MSMEs sector, COVID-19, economic growth, egyptian context, policy action
Objavljeno v DKUM: 17.07.2024; Ogledov: 127; Prenosov: 24
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8. On parsing programming languages with Turing-complete parserBoštjan Slivnik, Marjan Mernik, 2023, izvirni znanstveni članek Opis: A new parsing method based on the semi-Thue system is described. Similar to, but with more efficient implementation than Markov normal algorithms, it can be used for parsing any recursively enumerable language. Despite its computational power, it is meant to be used primarily for parsing programming and domain-specific languages. It enables a straightforward simulation of a number of existing parsing algorithms based on context-free grammars. The list includes both top-down shift-produce methods (such as SLL and LL) and bottom-up shift-reduce methods (such as LALR and LR), as well as mixed top-down-and-bottom-up methods such as LLLR. To justify the use of the new parsing method, the paper provides numerous examples of how a parser can actually be made in practice. It is advised that the main part of the parser is based on some simple well-established approach, e.g., SLL(1), while syntactically more complicated phrases can be parsed by exploiting the full power of the new parser. These phrases may either be extensions to the original language or some embedded domain-specific language. In all such and similar cases, no part of the language is restricted to be context-free. In fact, context-sensitive languages can be handled quite efficiently.
Ključne besede: Turing-complete parsing, context-sensitive, error recovery
Objavljeno v DKUM: 14.02.2024; Ogledov: 325; Prenosov: 26
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9. The influence of non-formal artistic and creative activities in multicultural educational contextsFernando Pérez-Martin, 2017, izvirni znanstveni članek Opis: Our schools are becoming more and more multicultural every year. It is no longer uncommon to have in the same classroom students from over a dozen nationalities, with diverse backgrounds, beliefs and ways of seeing the world. This article is an invitation to reflect on the role that non-formal artistic and creative activities can play in multicultural educational settings. To this end, an excerpt from a Case Study carried out in one of Canada%s most multicultural schools is presented, showcasing some of the activities developed there and analysing the positive influences they have in its educational community.
Ključne besede: non-formal art, music education, Case Study research, creativity, multicultural education, Educational context
Objavljeno v DKUM: 16.11.2017; Ogledov: 1338; Prenosov: 361
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10. Context-dependent factored language modelsGregor Donaj, Zdravko Kačič, 2017, izvirni znanstveni članek Opis: The incorporation of grammatical information into speech recognition systems is often used to increase performance in morphologically rich languages. However, this introduces demands for sufficiently large training corpora and proper methods of using the additional information. In this paper, we present a method for building factored language models that use data obtained by morphosyntactic tagging. The models use only relevant factors that help to increase performance and ignore data from other factors, thus also reducing the need for large morphosyntactically tagged training corpora. Which data is relevant is determined at run-time, based on the current text segment being estimated, i.e., the context. We show that using a context-dependent model in a two-pass recognition algorithm, the overall speech recognition accuracy in a Broadcast News application improved by 1.73% relatively, while simpler models using the same data achieved only 0.07% improvement. We also present a more detailed error analysis based on lexical features, comparing first-pass and second-pass results.
Ključne besede: speech recognition, factored language model, dynamic backoff path, word context, inflectional language, morphosyntactic tags
Objavljeno v DKUM: 26.06.2017; Ogledov: 1829; Prenosov: 383
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