RFOS - Repository of Faculty of Organizational Sciences Univ. of Belgrade
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A decision modeling approach for smart training environment with motor Imagery-based brain computer interface under neutrosophic cubic fuzzy set
No full textThe modeling of smart training environments (STEs) for motor imagery-based brain–computer interface (MI-BCI) falls under the multi-attribute decision analysis (MADA) due to three main concerns, namely, multiple evaluation attributes, data variation, and attribute prioritization. Despite the tremendous efforts over the last years, none of the developed STEs have met all of the essential smart attributes. Thus, modeling multiple STEs to determine the best one for MI-BCI is difficult. Literature reviews have evaluated and modeled the existing STE alternatives, but informational uncertainty remains an open issue. The earlier MADA solution also has some issues. Thus, this study extended fuzzy weighted with zero inconsistency (FWZIC) with neutrosophic cubic sets (NCSs) for modeling uncertainty to prioritize the smart attributes of STEs and estimate the weight values of each one. Then, the developed NCS–FWZIC method is integrated with multi-attributive border approximation area comparison (MABAC) method to model the STE alternatives. The findings revealed the following: (1) NCS–FWZIC had effectively prioritized and weighted the smart attributes of STEs with no inconsistency. Ease of use attribute was considered the most influential attribute because it earned the greatest weight value. (2) MABAC method produced stable and reliable modeling results. STE5 obtained the highest model among the 27 STEs. Sensitivity analysis and Spearman's rho, systematic modeling, and comparison analysis were conducted to test the stability and robustness of the results reported in this study
Evaluation of Cooperative Intelligent Transportation System scenarios for resilience in transportation using type-2 neutrosophic fuzzy VIKOR
No full textThere is a critical need for research in proactive and predictive management of the resilience of transportation systems implementing new technologies. Cooperative Intelligent Transportation System (C-ITS) uses wireless technology to allow vehicles and infrastructure to talk to each other in real-time. This makes it easier for people to work together on the road and makes it possible to make safer and more efficient traffic flows. Significant progress may be made in the transportation industry as a result of the incorporation of self-powered sensors into C-ITS providing resilience in transportation operation. One advantageous feature is that these sensors, which generate their power, could be deployed in a variety of C-ITS implementation scenarios. To assist decision-makers in making the most informed choice possible concerning investments and implementations, a type-2 neutrosophic number (T2NN) based VIKOR (VlseKriterijumska Optimizacija I Kompromisno Resenje) method is used to perform advantage prioritization. To accomplish this goal, a case study is carried out to determine which of the three alternatives is the most suitable based on a set of twelve criteria that is divided into four aspects. According to the findings, the applicability and short-term benefits are the most crucial factors in determining which option is the most advantageous for the use of self-powered sensors in C-ITS. This is because both of these factors have an immediate impact on the system
Are Future Project Managers Ready for a Digitalized World?
No full textThe Fourth Industrial Revolution has changed the way organizations do their business, resulting in highly digitalized business environment and making digital competences as one of most needed in the future. The purpose of the study was to establish the proficiency level of the future project managers' digital competences. The study design included using self-assessment tool and targeting undergrads and grads students in field of project management. The results showed that respondents are at advanced level of digital competences and that there is no difference between gender, level of education, previous field of study for grad students or academic achievements. The best results are in area of information and literacy, while most challenging is safety. Future research should include verification of the results using tools to examine digital competences specifically needed for project managers working in digitalized environment. The results of this study could be useful to both academics and practitioners, especially in upgrading current teaching program and developing skills which are needed in labor market
Embeddings for Automatic Short Answer Grading: A Scoping Review
No full textAutomatic grading of short answers is an important task in computer-assisted assessment (CAA). Recently, embeddings, as semantic-rich textual representations, have been increasingly used to represent short answers and predict the grade. Despite the recent trend of applying embeddings in automatic short answer grading (ASAG), there are no systematic reviews of literature reporting on their usage. Therefore, following the PRISMA-ScR guidelines, this scoping review summarises relevant literature on the use of embeddings in ASAG, and reports on the current state of the art in that research area and on the identified knowledge gaps. We searched seven research databases for the relevant journal, conference, and workshop papers published from 2016 to July 2021. The inclusion criteria were based on the type of publication, its venue ranking, study focus, and evaluation methods. Upon the full-text screening, 17 articles were included in the scoping review. Among these, most of the articles used word embeddings, mainly to estimate the similarity of student and model answers using the cosine similarity measure or to initialise a neural network-based classification model. The contribution of embeddings to the performance of ASAG models compared to non-embedding features is inconclusive. Models employing embeddings were mostly evaluated on four public ASAG datasets using earlier ASAG methods as baselines. We summarise the reported evaluation results and draw conclusions on the performance of the state-of-the-art ASAG models. IEE
Evaluation of metaverse integration alternatives of sharing economy in transportation using fuzzy Schweizer-Sklar based ordinal priority approach
No full textSharing economy transportation applications reduce car ownership and single-vehicle occupancy, contributing to the region's environmental sustainability. Metaverse is a promising new technology that combines sharing economy applications with transportation networks. By combining these two approaches, authorities can improve the sustainability of sharing economy applications. This study aims to assist decision-makers and authorities by developing a multi-criterion decision-making (MCDM) model that prioritizes three sharing economy-based metaverse integration alternatives, namely integrating safety measures, payment systems, and the optimization of operations in the metaverse. A novel multi-criteria framework, including fuzzy Schweizer-Sklar norms based on the Ordinal Priority Approach (OPA) to assess the metaverse integration alternatives, is developed. To rank the alternatives, non-linear processing of information based on the fuzzy Schweizer-Sklar weight assessment method (SWAS) is proposed. A case study is developed to provide a foundation for the experts' evaluations using twelve criteria, which are organized into four aspects namely, economic, user, operational, and advancement. Finally, the results indicate that the most favorable approach is optimized operations via the integration of the sharing economy into the metaverse
Maclaurin symmetric mean aggregation operators based on novel Frank T-norm and T-conorm for intuitionistic fuzzy multiple attribute group decision-making
No full textMulti-attribute group decision-making (MAGDM) is an interesting technique to find the most optimal alternative among comparative alternatives. Several authors put forward to MAGDM by introducing different fuzzy frameworks and also different tools to deal with fuzzy information. Intuitionistic fuzzy set (IFS) is the fuzzy framework that deals with the uncertainty in MAGDM. Due to their flexibility and generality, Frank t-norm (FTNM) and t-conorm (FTCNM) play an essential role in information fusion. Moreover, as the generalization of some mean operators, the Maclaurin symmetric mean (MSM) operator considers the relationship between multi-criteria arguments, especially in MAGDM. This article aims to develop some MSM aggregation operators (AOs) for the intuitionistic fuzzy set (IFS) based on FTNM and FTCNM and to apply newly developed AOs in the MAGDM. To utilize the MAGDM algorithm, first, we defined the MSM by using the FTNM and FTCNM in the environment of IFS. Then we proposed intuitionistic fuzzy (IF) Frank MSM (IFFMSM) and IF Frank weighted MSM (IFFWMSM) operators. Then, the fundamental properties of these AOs are stated and proved. Then, the strategy is given that accounts for the application of the newly developed family of AOs. Further, freshly defined operators are applied to the MAGDM problem with the help of an example where the risk factors of the construction industry are assessed. To cope with the significance, the proposed AOs are compared with some existing AOs. This study also addresses the variation of these AOs' behavior based on the interpretation of sensitive parameters
Multi-objective optimization model for uncertain crop production under neutrosophic fuzzy environment: A case study
No full textIn real world uncertainty exist in almost every problem. Decision-makers are often unable to describe the situation accurately or predict the outcome of potential solutions due to uncertainty. To resolve these complicated situations, which include uncertainty, we use expert descriptive knowledge which can be expressed as fuzzy data. Pakistan, a country with a key geographic and strategic position in South Asia, relies heavily on irrigation for its economy, which involves careful consideration of the limits. A variety of factors can affect yield, including the weather and water availability. Crop productivity from reservoirs and other sources is affected by climate change. The project aims to optimize Kharif and Rabbi crop output in canal-irrigated areas. The optimization model is designed to maximize net profit and crop output during cropping seasons. Canal-connected farmed areas are variables in the crop planning model. Seasonal crop area, crop cultivated area, crop water requirement, canal capacity, reservoir evaporation, minimum and maximum storage, and overflow limits affect the two goals. The uncertainties associated with the entire production planning are incorporated by considering suitable membership functions and solved using the Multi-Objective Neutrosophic Fuzzy Linear Programming Model (MONFLP). For the validity and effectiveness of the technique, the model is tested for the wheat and rice production in Pakistan. The study puts forth the advantages of neutrosophic fuzzy algorithm which has been proposed, and the analyses derived can be stated to deal with yield uncertainty in the neutrosophic environments more effectively by considering the parameters which are prone to abrupt changes characterized by unpredictability
UTICAJ INDIVIDUALNIH FAKTORA NA NAMERU STUDENATA DA KORISTE SISTEME E – UČENJA
No full textOsnovni cilj istraživanja predstavlja analizu uticaja grupe odabranih
individualnih varijabli (samoefikasnost, lična inovativnost i deljenje znanja) na nameru
za korišćenje sistema e – učenja od strane studenata. Budući da postoji širok spektar
faktora koji može definisati navedenu nameru, u ovom radu izdvojeni su lični faktori u
segmentu kompetencija i motivacije kao dominantne determinante opredeljenosti. Izbor
zavisne varijable zasnovan na njenom ključnom uticaju na samoefikasnost procesa
učenja u e – okruženju. Istraživanje je sprovedeno na uzorku od 800 studenata različitih
visokoškolskih institucija. Na osnovu rezultata sprovedenog istraživanja može se
zaključiti da je pretpostavka da postoji pozitivna korelaciona veza na nivou statističke
značajnosti između namere studenata za korišćenje sistema za e – učenje, kao zavisne
promenljive, i samoefikasnosti, lične inovativnosti i deljenja znanja, kao grupe
nezavisnih promenljivih, potvrđena
Capacity Building Across Higher Education and Rural Youth in WINnovators Space
No full textThis paper demonstrates the Design as a Hypothesis Framework for developing cross-university students and mentors, and rural youth (aged 18–30) and regional business ecosystems capacity building practice approaches to support sustainable development goals. We describe how a gamified learning and co-working WINnovators Space (https://winnovators-space.eu/) with e-learning materials for self-learning and mentored group work problem based challenges was developed to support university students’, mentors and the business partners’ engagement and building agency and capacity with regional rural young women. The Pilot study with the capacity building practice application validates the Design Hypothesis in three countries – Estonia (N = 35), Slovenia (N28), Serbia (N22) – involving young rural women, higher education students, academic and business mentors