Journals Published by Vilnius Tech
Not a member yet
12596 research outputs found
Sort by
Fixed point approximation of contractive-like mappings using a stable iterative family and its dynamics via quadratic polynomials
Get PDFThis study aims at presenting a novel bi-parametric family of iterative methods for computing the fixed points of a contractive-like mapping. We thoroughly analyze the strong and stable convergence of the proposed technique and explore its applicability across various problem domains. Regarding convergence, it is proven that for several operators, the Mann iteration is analogous to the proposed multi-step class, and vice-versa. Moreover, numerical tests demonstrate the superior performance of the new procedures compared to existing three-step schemes. We further examine the dynamic behavior of several fixed-point iterative techniques when applied to quadratic polynomials. Based on the outcomes of these experiments, it can be concluded that the proposed family demonstrates both validity and effectiveness
A joint discrete limit theorem for Epstein and Hurwitz zeta-functions
Get PDFIn the paper, we obtain a joint limit theorem on weak convergence for probability measure defined by discrete shifts of the Epstein and Hurwitz zeta-functions. The limit measure is explicitly given. For the proof, some linear independence restriction is required. The proved theorem extends and continues Bohr–Jessen’s classical results on probabilistic characterization of value distribution for the Riemann zeta-function
Enhancing blood glucose control through the fixed point theorem
Get PDFDiabetes is a chronic condition that poses significant health risks globally, arising from the body’s inability to effectively utilize insulin produced by the pancreas or insufficient insulin production. This paper proposes a novel approach to diabetes management by focusing on optimal control strategies aimed at regulating blood glucose levels to achieve desired targets. We integrate concepts of output controllability into a discrete-time model that captures the dynamics of glucose and insulin interactions. Applying fixed-point theorems, we define permissible control mechanisms for dealing with the challenge of keeping glucose concentrations within optimal ranges. The theoretical framework is supported by numerical simulations that demonstrate the efficacy of the suggested optimal control method in minimizing blood glucose fluctuations. Our findings shed light on the development of advanced blood glucose control systems, eventually leading to enhanced diabetes management and improved quality of life for individuals impacted by the disease
Spatiotemporal patterns and prediction of multi-region house prices via functional mixed effects model
Get PDFHouse prices have always been a popular indicator for real estate market monitoring. This study explores the spatiotemporal patterns of house prices at the community level in San Francisco from January 2009 to April 2024. A functional spatiotemporal semiparametric mixed effects (FST-SM) model was proposed to analyze the Zillow Home Value Index (ZHVI), considering spatiotemporal variations. This response is associated with known influences and unknown latent random effects. The random-effects component was expanded using functional principal components. The conditional autoregressive (CAR) structure of the principal component scores was adopted to analyze nonparametric time trends and spatiotemporal correlations. The proposed model was compared with other time-series models in terms of spatiotemporal prediction. The results show that the prediction accuracy of the proposed model is higher than that of other regular models. In summary, a functional mixed effects model was proposed to describe spatiotemporal patterns and forecast house prices. This study can provide valuable references for decision-making by local governments, real estate suppliers, and house buyers
Impact of financial market development on housing prices: Evidence from China
Get PDFHousing prices in cities of China had soared by 70% from 2012 to 2021, attracting increasing public concern. Financial market development may suppress housing prices by allowing speculators to channel capital into financial markets rather than merely into the property sector, whereby it plays a critical role in shaping housing prices theoretically. This study aims to investigate the impact of financial market development on housing prices with a sample of 261 cities in China from 2011 to 2021, concluding that financial market development is negatively related to housing prices based on the GMM model. Correspondingly, a potential policy to decrease housing prices is to promote financial market development
Forecasting pandemic-induced changes in real estate market values through machine learning approaches
Get PDFIn this study, a new temporal segmentation method is used to forecasting the real estate market based on the structural and spatial attributes of 676 houses in Niğde, Türkiye, from the years 2019 to 2022. Artificial Neural Networks (ANN), Random Forest (RF), Decision Tree (DT), and K-Nearest Neighbours (KNN) were employed for model development and comparative performance analysis. According to the results, the ANN model that used temporal variables showed the most successful performance by achieving the highest R2 for 2019 (1. period: 0.979, 2. period: 0.990, 3. period: 0.914, 4. period: 0.831) and 2022 (1. period: 0.971, 2. period: 0.975, 3. period: 0.586, 4. period: 0.896) scores. Additionally, the COD values (5%–10%) and PRD values (0.98 to 1.03) remained within the acceptable range, further validating the model’s reliability. RF model showed more effective performance than other models by achieving the highest R2: 0.510 for 2019 and R2: 0.509 for 2022 when temporal variables were excluded. These findings highlight the importance of integrating time-sensitive parameters into valuation models to improve forecast accuracy and robustness. The study offers a replicable, flexible methodology for crisis-responsive valuation, providing valuable insights for policymakers, investors, and urban planners aiming to mitigate risks and enhance resilience in real estate market decision-making
Unknown interiors of ancient Egypt: producing by artificial intelligence in the context of light-space relationship
Get PDFThis study presents a design method aimed at visualizing cultural heritage through the architecture of ancient Egypt using modern technologies. With the deepening of the digital age, the use of digital technology and artificial intelligence in cultural heritage research has become an important tool for renewing and disseminating period architecture. The reason for choosing the interior spaces of ancient Egypt as a sample in this study is that, in addition to leaving a rich heritage in the field of architecture, ancient Egypt offers distinct period architecture in terms of space-light relationship. As a result of literature review, keywords related to architecture and the relationship between space and light in the Ancient Period were identified, and the study was visualized using the state-of-the-art artificial intelligence technology of today, namely human-computer interaction combined with text-to-image technology. The motivation and aim of this study is to demonstrate the role of reanimating cultural heritage like ancient period architectures in the computer environment based on interpretation, contributing to architectural sustainability, and spreading to future periods
Perspectives concerning leadership research in the framework of corporate sustainability
Get PDFThe main purpose of this paper is to explore current perspectives on the approach to the concept of leadership in relation to sustainability. The research question is focused on the importance of leadership and its contribution as a driver of change, in the organizational sustainability context. The methodology of research has as main framework the bibliometric analysis approach. This quantitative research method allowed achieving some specific objectives, such as: determining the scientific interest in the studied topic and the main authors in the field, identifying the key concepts that interfered with leadership and sustainability and highlighting the main leadership style that facilitates the transition to sustainability. It is thus intended to make a valuable and up-to-date contribution to 2024 on the main trends manifested in leadership research as theory and practice. Among the main findings obtained, it is highlighted that, after 2020, the top three leadership styles that have created links in correlation with other concepts, thus generating organizational change, are: transformational leadership, ethical leadership and authentic leadership. Of these, transformational leadership stands out as a key factor in driving innovation and sustainable performance, this fact being valuable to managers and researchers
Does digital payments reduce the risk of money laundering? The role of financial sector development
Get PDFThis study examines how financial sector development mediates the relationship between digital payments and money laundering. The current study relies on a sample of 120 countries, including both developed and developing economies, for the years 2014, 2017, and 2021. The findings reveal that digital payments, the rule of law, and political stability reduce the risk of money laundering, indicating that the increased use of digital payments helps reduce the risk of money laundering. This suggests that digital transactions, being more traceable and transparent than cash transactions, can help authorities monitor and prevent illicit financial activities more effectively. Regarding the mediation effect of financial sector development, the results show that financial sector development and the rule of law positively affect the density of digital payment transactions. In addition, it revealed that money-laundering risk is lower when the financial system develops and compliance with laws and political stability. These findings provide actionable insights for policymakers, regulators, and financial institutions committed to strengthening anti-money laundering efforts
Accessibility of public transport for people with disabilities: a systematic literature review
No full textThe use of public transport is a facilitator for the development of people′s abilities and a channel for their participation in society. Mobility limitations are a cause of social exclusion and people with disabilities is one of the groups most likely to suffer from it. Problems using public transportation are among the main causes for this exclusion. The aim of this research is to conduct a systematic review of the published literature on to public transport accessibility for people with disabilities. We have found articles published in peer-reviewed scientific journals between 2010 and 2022, searching in Web of Science Core Collection (WoS) and Scopus databases implementing the Systematic Literature Review (SLR) methodology and applying Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines. Of the 2224 documents found during the initial search, we selected 65 articles according to the criteria used, more than 60% of them published in the last 4 years. Despite the growing literature on public transport and disability, there is still little research into this area, with the urban bus being the most studied mode of transport; and physical disability the most analysed in the articles identified