VGTU Journals (Vilnius Gediminas Technical University - Vilnius Tech)
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Health status assessment and fault warning methods for aircraft engines under time varying operating conditions
No full textWith the growth of the aviation transportation industry, aircraft engines, as the core components of flight safety, are facing increasingly severe challenges in health status assessment and fault warning technology. To achieve accurate evaluation and fault warning of engine status, this study proposes a new method using improved multi-channel network and hybrid network models. The new method can achieve life prediction and evaluation of engine health status in different time-varying scenarios by improving the multi-channel network. Meanwhile, the method achieves early warning of operational faults by using a hybrid network model for real-time analysis of aircraft engine operation data. The results demonstrated that the new method had root mean square errors of only 12.35 and 12.84 on different datasets, significantly better than other models. The score of the new model has also significantly decreased, with accuracy rates of 91.5% and 93.4% on different datasets, far exceeding other models. Moreover, although the new model had a large number of parameters, it had short training time, low latency, small memory usage, and excellent system performance. The new method can significantly improve the health status assessment and fault warning of engines, which has good guiding significance for achieving stable operation of aircraft engines
Drawbacks of demand accuracy assessment models on the example of slow-moving spare parts in civil aviation
No full textLots of researchers worldwide use a big variety of forecast models to predict demand. After running the forecast model, researcher always has a question if received prediction was accurate or not. To do so, a number of methods exist to assess model accuracy. Application of accuracy assessment models itself is not complex. The most difficult part for researcher: interpretation of the result and the understanding of information to take the right decisions. Companies who do demand forecast in 95% of cases use only one accuracy assessment method for their forecast model. In case, companies do it for fast moving items and the business doesn’t have any special requirement for the result level, it could be accepted. But in case slow-moving inventory is used and the company requires a certain service level, then there is a space for potential mistakes when running one model only. This work figures out the drawbacks of the current approaches towards forecast accuracy assessment of spare parts with little transaction history and proposes approaches to choose right accuracy assessment models. Experiment on data of existing company A that does aircraft maintenance was run to study the results of various forecast accuracy assessment models
Multiple Normalization Rating Analysis (MUNRA) and its application to digital supplier selection in the textile industry
No full textThe rapid development of digital technologies – such as IoT, AI, blockchain, and digital twins – has transformed supply chains into interconnected ecosystems, making digital supplier selection both critical and complex. For the first time, this study proposes a novel multi-criteria decision-making (MCDM) method, Multiple Normalization Rating Analysis (MUNRA), for ranking alternatives. It integrates linear, vector, and non-linear normalization to improve robustness, reduce rank reversal, and enhance decision accuracy. A case study of digital supplier selection in the textile industry is considered for a real-life application of the method. Results highlight technology integration, flexibility, and technological capability as the most influential criteria for selecting digital suppliers. Moreover, the final ranking of the six digital suppliers is as follows: DS5, DS4, DS2, DS6, DS1, and DS3. Validation through comparative MCDM methods, Spearman correlation, and sensitivity analyses confirms the credibility of the method. It is also shown that it is free from the rank reversal phenomenon. The research presents a computationally efficient and rigorous method for evaluating digital suppliers, offering strategic insights for digital supply chain management. The application of MUNRA to a larger decision-making problem further illustrates its scalability and cross-domain applicability
Effectiveness of a mindfulness-based training program to improve creative self-efficacy among a sample of secondary school students
No full textTo motivating creativity among students, creative self-efficacy is one of the most important indicators, as it refers to individuals’ beliefs about their creative abilities, their motivation towards creativity, and possession of the necessary knowledge for creativity. The main objective of this study is to identify the effectiveness of a training program based on mindfulness, in improving creative self-efficacy. 30 eighth grade students, experimental and control groups included 15 students. The training program experimental group received a training program of 13 sessions, while the control group was not included. Assessment using the creative self-efficacy scale showed that the experimental group students scored higher on the creative self-efficacy table and its subscales than the students in the control group, and showed a positive effect of the mindfulness-based training program in improving creative self-efficacy among a group of secondary school students
The creative processes in the cities: the case of Turkish literature
No full textUtilizing a four-stage model of the creative process, this article explores the creative process of experiencing and representing the city in a selection of modern Turkish literature and illuminates how the creative process aligns with and informs writings on the Turkish city. The analysis is focused on the inspiration, dreaming, reflecting, and imagining procedures of the creative process incumbent upon writing the Turkish city; concepts that condition stages of creativity. This paper’s approach is in significant part a response to the theoretical problem of how the author situates the Turkish city, particularly regarding the capital Ankara, that is understood in the context of singularity and Istanbul, that is situated within a multiplicity of realities. This Ankara–Istanbul relationship is further referenced in the context of a discourse that is centered on the novel idea of an intersection of four tracts or a double chiasm. Several writers are referenced, especially the Turkish authors Ahmet Hamdi Tanpınar, Elif Shafak, and Orhan Pamuk
Learning creative interpretation in the music classroom: the possibilities of the emotional expression method
No full textThe article discusses the problems of interpretation of a piece of music and presents a part of an extensive research on 26 filmed lessons, where the emotional expression method is used to reveal innovative possibilities for encouraging creative interpretation. The emotional expression method is used here as a way of stimulating musicality and musical, including interpretative, skills, and self-expression, by expressing the content of a work’s emotional intonations, or the experiences of a “fictional hero”, evoked by the integration with non-musical art forms. In this one alternative empirical experiment we used Emery Schubert and Dorottya Fabian’s taxonomy of expressive features in music performance, which was developed in 2014 and focuses on expressivity in music performance, defines the specificity of interpretations, determines the differences between performances, and allows to identify the style of the various different interpretations. The participants (19 female and 7 male students) were selected for the experiment by means of representative case sampling. The main aims of the 26 experimental lessons were to stimulate the pupil to develop a personal relationship with the piece being performed, its “fictional hero”, to improve the pupil’s interpretation of the piece, and to stimulate the discussion of moral values by asking specific questions focused on the fulfilment of the goals of emotional and ethical education. The results of the study were evaluated by four experts – teachers of different specialisations in the subject of the instrument. The evaluation procedure was based on the review of the experimental filmed lessons and the filling in of templates of evaluation protocols (104 in total) prepared in advance by the researchers. The study revealed the positive impact of emotional expression method on harmonising the music-making process, where traditional teaching makes it challenging to quickly achieve changes in sound quality, dynamics, phrasing, expressiveness, or stylistics; it helped to develop the student’s emotional competence and reduce stage anxiety. However, there were also necessary conditions for the application of emotional expression method: the pupil must have a good knowledge of the text of the piece of music, so that the “technical” difficulties do not interfere with the expression of the experiences of the “fictional hero” used in the method
Explainable AI-based mass appraisal: Insights from machine learning applications in Korea’s residential property market
No full textMass appraisal plays a pivotal role in real estate management, facilitating property tax assessments, mortgage evaluations, and urban planning across large geographical areas. In regions like Korea, where real estate markets are rapidly evolving, valuation models based on multiple linear regression are valued for their simplicity and interpretability but often fall short in capturing complex market dynamics. In contrast, machine learning (ML) models, while addressing non-linear relationships between property characteristics and market values and offering superior predictive performance, are often criticized for their “black-box” nature, which raises concerns over interpretability in transparency-critical domains like property tax assessments and policy planning. To address these concerns, this study investigates the application of Explainable AI (XAI) techniques in the mass appraisal of residential properties in Korea, integrating XAI methods with both multiple linear regression and random forest models. Using SHAP (SHapley Additive exPlanations) and PFI (Permutation Feature Importance) values, the study analyzes feature importance and predictive contributions, offering insights into the factors driving property valuations. Additionally, a temporal analysis was conducted by segmenting the data into time intervals to examine how feature importance and predictive contributions evolve over time. By combining high predictive performance with transparent and interpretable insights, the findings demonstrate that XAI can enhance the usability of both traditional and advanced automated valuation models (AVMs) for real-world decision-making in the Korean real estate sector
Sustainability, risk, and social responsibility: The new triad in real estate management
No full textThe increasing importance of sustainability, risk, and social responsibility in real estate management reflects evolving societal demands, regulatory pressures, and market dynamics. Motivated by the need to align real estate practices with environmental goals and social equity, this study explores how these three pillars can be systematically integrated into property management. The aim is to develop a holistic framework that transforms risks into opportunities and promotes long-term value creation. Using a mixed-methods approach, including literature analysis and semi-structured expert interviews conducted within the Romanian real estate sector, this study investigates how ESG criteria and digital technologies are currently applied in practice. Key findings reveal that tools such as BIM, digital twins, and ESG reporting enhance transparency, operational efficiency, and stakeholder engagement. The research concludes that integrating the sustainability–risk–responsibility triad provides strategic advantages, enhances resilience, and strengthens the role of real estate management in advancing sustainable development
East-West risk connectedness in the European banking sector
No full textThis study examines the risk spillover dynamics between banks in Central and Eastern Europe (CEE) and Western Europe (WE) across 30 banking groups from 2014 to 2023, segmented into three distinct periods: pre-COVID-19, during COVID-19, and the Russo-Ukrainian conflict. The key contribution of the paper lies in combining a cross-regional perspective with a longer time horizon, covering major shocks. Utilizing the Diebold-Yilmaz interconnectedness index model, we analyze volatilities derived from daily stock prices to identify key players in the transmission and absorption of financial shocks. Our findings, supported by existing literature, reveal a strong interconnectedness between the two parts of Europe. WE banks are more likely to be shock transmitters, while CEE banks play the role of shock receivers. However, during the Russo-Ukrainian war, CEE banks appeared more among the net transmitting banks. Although one of the main features of the CEE financial system is its dependence on WE, a bank nationalism has also emerged in some countries. This may nuance the dynamics of CEE financial stability: reducing the magnitude of WE shock, but in the case of CEE-specific shocks, the possibility of risk transfer (dispersion) is also weakened
A Vieta–Lucas collocation and non-standard finite difference technique for solving space-time fractional-order Fisher equation
No full textThe purpose of the article is to analyze an accurate numerical technique to solve a space-time fractional-order Fisher equation in the Caputo sense. For this purpose, the spectral collocation technique is used, which is based on the Vieta–Lucas approximation. By using the properties of Vieta–Lucas polynomials, this technique reduces the nonlinear equations into a system of ordinary differential equations (ODEs). The non-standard finite difference (NSFD) method converts this system of ODEs into algebraic equations which have been solved numerically. Moreover, the error estimate is investigated for the proposed method. To show the accuracy and efficiency of the technique, the obtained numerical results are compared with the analytical results and existing results of the particular forms of the considered fractional order models through error analysis. The important feature of this article is the exhibition of variations of the field variable for various values of spatial and temporal fractional order parameters for different particular cases