Journals Published by Vilnius Tech
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Constitutive memory equations for auxetic materials
Get PDFIn this note we suggest a set of constitutive equations for anelastic materials whose internal structure can present anomalous variations resulting from external effects of tension/compression, as in auxetic media. For these problems we require of a new function related with the variation of internal structure, which allows us to define a threshold separating the internal structure media from the classic ones. The equations are formulated in the case of static problems but also when the material has memory or plastic properties in addition to auxetic ones. In order to limit the complexity of the formulae, the discussion is limited to the case where the perturbation is one dimensional, which however does not limit the significance of the results
Development of a method of surface water content research using ultraviolet rays
Get PDFIt is known that the process of water treatment in surface water bodies requires the development of advanced and effective technologies for the destruction of harmful microorganisms and viruses. The aim of the present study is to develop a method for the investigation of surface water content. As a result of the study, the electronic circuit of the purification device using ultraviolet rays was developed. The energy and spectral characteristics were experimentally investigated and the economic efficiency of the ultraviolet ray device was determined, taking into account the basic sanitary and hygienic requirements for the organisation of ultraviolet water disinfection. It is substantiated, that the developed scheme provides safety of conditions of work of the personnel with the equipment
Landscape management for disaster-prone cities: disaster resilient park proposal
Get PDFElazığ is a disaster-prone city due to its geological structure, proximity to fault lines, and similar reasons. As part of the study, a disaster-resilient green space model applicable to the city has been developed. The study examines how green spaces should be planned and designed to be used in disaster situations. The methodology of the study consists of three phases. (1) The city of Elazığ was analyzed in terms of disasters. (2) UAV and GPS CORS devices were used to collect data in the area designated as the disaster park and three-dimensional spatial analysis was performed. (3) The disaster park was designed according to the data obtained. The results show that Elazığ is frequently affected by disasters. Therefore, it is understood that the city needs a disaster-resistant green system. Suggestions for the design of disaster parks and their inclusion in the landscape management of disaster-prone cities have been developed
Bibliometric and visualized analysis of work engagement in business management
Get PDFWithin business management, the growing interest in work engagement stems from its recognised role in mitigating employee well-being, bolstering job satisfaction, and optimising organisational outcomes. This review comprehensively explores the knowledge structure of work engagement in business management, analysing 563 publications from the Scopus database spanning 2005 to 2023 through performance analysis, co-citation analysis, co-authorship analysis, keyword co-occurrence analysis, and content analysis. This review outlines prevailing trends and identifies influential scholars, articles, institutions, and leading countries. It illuminates the current state of scientific collaboration, providing a rationale for developing countries to seek academic cooperation with developed countries. Additionally, it delves into six current themes and four future directions, providing a robust theoretical framework for future research endeavours
Uncertain new technologies – economics of ground effect vehicle operator
Get PDFNew technologies and vehicle types have become available for transportation and logistics in the recent decade. One of the such is Ground Effect Vehicle (GEV), which in new reinvented form is using electric propulsion, new lighter materials and could be without onboard pilots. These could be used in coastal and archipelago types of areas, where distances are relatively short. In this research is introduced economic and business case evaluation of GEV in the context of Canary Islands. Aim is to build understanding from financial success of GEV. Simulation model incorporates number of uncertainties, like usage life-cycle of fleet, fleet investment cost, interest rates, lower cargo volume development in the early years and possibility for passenger transports. Analysis shows that success depends quite much on cargo pricing, and the interest of customers to pay premiums from faster delivery. Being operator of GEV offers possibility for profitability, but if most of uncertainties take place, then investments might increase too much and result on significant losses. Research provides added value on discipline development and better alternative on spreadsheet and cost focused models
Leveraging IT use in healthcare records management: impact on customer satisfaction and financial performance through knowledge transfer and absorptive capacity
Get PDFThis research looks at how IT use in managing healthcare records benefits organizational performance. This paper addresses a critical research gap by examining how the implementation of IT affects performance through organized learning mechanisms, absorptive capacity and knowledge transfer effectiveness, two under researched components from prior healthcare IT literature. Based on organizational learning theory, the study proposes internal capabilities mediate the relationship between the use of IT and organizational performance. A quantitative survey of 304 healthcare professionals was conducted, with data analysed using structural equation modelling and SmartPLS. The findings indicate that IT use has a substantial impact on knowledge transfer, and that knowledge transfer mediating the relationship between absorptive capacity and both customer satisfaction and financial performance. This study theoretically extends the discourse on IT enabled organizational performance by focusing on the role of organizational learning in the IT performance relationship. In practice, it provides operational ramifications for health-care leaders by emphasizing the need to align digital investments of that organization with its learning strategy to increase its sustainable performance improvement. The theoretical and empirical contributions conferred by this research are one of providing an integrated framework integrating IT use, organizational learning mechanisms, and performance outcomes in healthcare settings
Enhancing land use classification with hybrid machine learning and satellite imagery
Get PDFThe growing accessibility of satellite imagery and the rapid evolution of machine learning (ML) techniques have significantly advanced land use classification for environmental monitoring. However, challenges such as cloud coverage, varying image resolutions, and seasonal changes continue to hinder classification accuracy and consistency. This study aims to improve land use classification by proposing an integrated cloud interpolation, vegetation indices and ML based approach for classification of Sentinel-2 (S2) satellite data across the Baltic States. Specifically, a spatiotemporal interpolation module is introduced that reconstructs cloud-obscured pixels using multi-temporal coherence and derives optimized vegetation-index composites to enhance class separability under varying seasonal conditions. In order to achieve this aim and to choose the best ML algorithm for land use classification, we compare the performance of three classification algorithms, i.e., Random Forest (RF), K-Nearest Neighbours (KNN), and Support Vector Machines (SVM), and evaluate their effectiveness in handling noisy and incomplete data. Our experimental results show that all three methods achieve strong classification accuracy, with RF exceeding 90%, while KNN and SVM also demonstrate competitive results. These methodological enhancements have been demonstrated to reduce cloud-induced misclassification and provide a scalable, transferable framework for operational land-use mapping in challenging atmospheric and seasonal contexts. These findings highlight the robustness of the proposed approach and provide valuable insights for future applications of ML in land use classification and environmental analysis.
Optimizing aircraft maintenance tasks allocation using mixed integer linear programming
Get PDFThis study addresses the optimization of aircraft maintenance task allocation for small fleets using Mixed-Integer Linear Programming (MILP). The research integrates manpower efficiency, regulatory compliance, and workload balancing to minimize downtime and enhance resource utilization. A mathematical model is formulated to account for task durations, skill levels, and sequential/parallel task constraints, validated via MATLAB implementation. Results from a simulated 50-hour Cessna 172 maintenance check demonstrate a 25% reduction in completion time compared to average manual scheduling. The model balances workloads by assigning tasks based on manpower expertise, highlighting the critical role of human factors in reducing errors and improving efficiency. Practical implications include a cost-effective alternative to commercial software for small operators, enabling optimized planning without high-cost tools. This work bridges a gap in maintenance literature by explicitly incorporating manpower efficiency into MILP frameworks, offering actionable insights for regulators and operators to avoid maintenance congestions and enhance operational resilience
The impact of industrialization and self-renewing energy utilization on carbon discharges in the country economics
Get PDFIndustrialization has been pivotal in driving economic development. The research problem is the negative impact of industrialization to global warming and climate change. The relevance – enabling the use of renewable energy and green solutions to decrease CO₂ emissions. This research aims to evaluate the impact of short and long-term of industrialization, consumption of renewable energy, trade openness and economic growth on carbon emissions per capita in Indonesia. This research analyses [2000–2023] data, applying econometric ARDL approach and diagnostic tools. The Breusch-Godfrey Serial Correlation (BGSC) results revealed no consistent correlations, when Breusch-Pagan-Godfrey (BPG) test heteroscedasticity was confirmed. Ramsey RESET test (RRT) showed that the model is perfectly specified and significant; CUSUMSQ and CUSUM tools proved the stability of the model, when the VIF multicollinearity results indicated that no multicollinearity exists between the variables. Research findings show: trade openness and the consumption of renewable energy demonstrate a favourable effect for carbon output per capita in Indonesia as outcomes of economic progress, while industrialization has an adverse relationship with emissions of carbon per capita. The research originality – complex evaluation of the relationship between mentioned variables interplay. This publication provides recommendations for policymakers to improve the quality of environment
Climate change as a socio-economic challenge for the tourism sector: an econometric analysis of countries with the highest economic losses
Get PDFThe issue of climate change, and in particular the economic losses caused by natural disasters, is a significant problem for the tourism sector and its development. The research conducted aims to address the following research question: Does climate change, quantified by the economic losses attributed to extreme weather events, influence the development of the tourism sector, as measured by tourism’s contribution to GDP? Furthermore, the study explores the role of insurance as a financial instrument for mitigating the effects of climate change on tourism. An important part of the research is an in-depth regional analysis of climate change losses. It was carried out both on a continental level and for the countries studied. Statistical and econometric techniques were employed to investigate the research question. The analysis focused on a selection of countries identified by the Swiss Re Institute as having experienced the highest economic losses due to climate change. Thirteen countries were surveyed, ensuring representation for each continent. The research period spans the years 2014–2023, and the data analysis was conducted using Statistica 13 and Gretl software. The findings indicate that economic losses resulting from natural disasters show an increasing trend, both in absolute terms and as a percentage of national GDP. These losses represent a significant constraint on economic growth, particularly limiting the development of tourism. Furthermore, the survey shows that the negative effects of climate change are more challenging for less economically developed countries. These countries are in addition to being more exposed to climate-related damages because of their natural conditions, but also struggle with underdeveloped insurance sectors. Reduced access to insurance compounds the disruptive impact of climate change on tourism. An analysis of the relationship between the weather damage load on a country’s economy and the insurance gap identifies three countries – the USA and China – as being especially at risk. Investigating the impact of the effects of natural disasters on the development of the tourism sector in countries with the greatest economic losses from climate change fills a research gap in this area and contributes to the development of knowledge on the effects of climate change on the competitiveness and sustainability of tourism. The research should be considered original in its subject coverage. No studies of this scope have been found in the literature. Investigating the impact of insurance on climate change mitigation for the tourism sector should also be considered innovative. The results of the research can be used to shape tourism policy in the countries studied, as well as globally