Journals Published by Vilnius Tech
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Harmonization of marine gravity data in Eastern Baltic
Get PDFMarine gravity datasets covering areas of state scale typically are made up of data that has been surveyed over multiple campaigns. These campaigns often take place many years apart, are of varying resolution and accuracy. This is due to ship-borne campaigns being much more expensive and time consuming than the ones on land; because of this, there is added value in validating and possibly correcting older data sets.
Over the course of recent BalMarGrav marine gravity project, dense, high quality gravity data was obtained covering most of the Latvian exclusive economic zone. The new data have been compared to campaigns, both as means of new data validation, and to check for possible biases among older data sets. Purpose of this research is to further the effort, to provide wider coverage of old marine gravity points, to test automated gravity point digitization, and to perform inter-campaign comparisons, using new, filtered and more precise data.
Data recovered during this research covers the previous data gaps between sets used in previous research. Using a more complete data coverage can improve new campaign data set validation and provide insights on inter-campaign biases within older data. Recovered data cover shallow coastal areas, where gravity mapping was not done over BalMarGrav project. Thus, by applying correctional values geoid errors can be minimized in the problematic transition zone between terrestrial and marine data.
Survey reports containing 20th century marine gravity point data were digitized, using optical character recognition. Gravity point values were transferred to sea surface and transformed to modern reference frames. Both modern and historic marine gravity data were filtered for gross errors and bias tracks. Data set robustness was checked, using leave-one-out cross validation. After processing, a comparison was made between old and new data.
Results present re-processed and filtered marine gravity datasets, and their comparison statistics. Comparison statistics before and after filtering reveal the increased accuracy and precision of filtered data. Mean comparison values reveal inter-campaign biases and provide correction values, which can increase data accuracy for use as input in future research and surface modelling
GIS based ground water assessment of Nilakkottai Taluk, Tamil Nadu, India: hydrogeochemistry and statistical perspective
Get PDFWater quality is imperative for drinking and agriculture purposes in order to meet the increasing requirements for water. The systematic assessment of groundwater quality in Nilakkottai Taluk, Dindigul District, Tamil Nadu, was performed. In order to ascertain the quality of the study area’s groundwater, various water quality indices, spatial distribution maps, multivariate statistical analysis, and hydrofacies diagrams have been contemplated. 40 samples were collected and analysed for 20 water quality parameters, using the standard techniques. The quality results of the irrigation analysis showed that the groundwater samples were satisfactory for agricultural use. The deduction of four principal components denotes that hydrogeochemical processes and anthropogenic inputs were the main controlling factors. The durov plot demonstrated the dominance of Ca-HCO3 type groundwater, indicating a weathering process through fresh water recharge. This study insisted that majority of the samples satisfactory for crop yield and need to be protected from further contamination
Reduction of food waste odors with probiotics and baking soda
No full textFood waste management is an important challenge for environmental protection, especially due to the unpleasant odors emitted. This study analyzes the effects of probiotics and baking soda on food waste odor reduction. The research was conducted using the dynamic olfactometry method, assessing odor concentration in different types of food waste: fish waste, dairy product waste, meat waste, and plant-based waste, i.e., fruit and vegetable waste. The experiment is carried out by placing 1 kilogram of food waste in 5-liter containers. The duration of the study is 7 days. The results showed that probiotics are more effective in reducing odors than baking soda, especially in fish and fruit and vegetable waste.
Article in Lithuanian.
Maisto atliekų išskiriamų kvapų mažinimas probiotikais ir valgomąja soda
Santrauka
Maisto atliekų tvarkymas yra svarbus aplinkos apsaugos iššūkis, o kartu ir iš atliekų skleidžiami nemalonūs kvapai. Šiame tyrime analizuojamas probiotikų ir valgomosios sodos poveikis maisto atliekų kvapų mažinimui. Tyrimas atliktas taikant dinaminės olfaktometrijos metodą, vertinant kvapo koncentraciją skirtingose maisto atliekų rūšyse: žuvies atliekose, pieno produktų atliekose, mėsos atliekose bei augalinės kilmės atliekose, t. y. vaisių ir daržovių atliekose. Eksperimentas atliktas maisto atliekas sudėjus po 1 kilogramą į 5 litrų talpyklas. Tyrimo trukmė 7 dienos. Gauti rezultatai parodė, kad probiotikai efektyviau sumažina kvapus nei valgomoji soda, ypač žuvies, vaisių ir daržovių atliekose.
Reikšminiai žodžiai: maisto atliekos, kvapų mažinimas, dinaminės olfaktometrijos metodas, probiotikai, valgomoji soda (NaHCO₃)
Enhancing prediction of ride-hailing fares using advanced deep learning techniques
Get PDFFare prediction is a critical component of online ride-hailing services, as it significantly influences consumer decision-making and enhances operational efficiency for service providers. Reliable fare prediction is especially important in dynamic pricing environments, where fares are affected by factors such as demand fluctuations, traffic conditions, and weather patterns. This study aims to enhance fare prediction in ride-hailing services by utilizing advanced deep learning models. Using a comprehensive dataset of Uber and Lyft fare data collected in Boston during the winter of 2018, we evaluated three deep learning architectures: Long Short-Term Memory (LSTM), Bidirectional LSTM (BiLSTM), and BiLSTM with an attention mechanism (BiLSTM + Attention). The results showed that the BiLSTM + Attention model achieved the highest prediction accuracy, making it the most effective approach for fare prediction. However, its longer training time poses limitations for time-sensitive applications. Conversely, the LSTM model provided a strong balance between predictive accuracy and computational efficiency, making it a suitable alternative for scenarios that require faster model deployment. Additionally, our analysis identified key factors influencing fare variability – such as trip distance, time of day, and weather conditions – highlighting the importance of feature selection in enhancing model performance. By improving fare prediction accuracy, this study offers valuable insights for optimizing dynamic pricing strategies, enhancing consumer satisfaction, and helping ride-hailing platforms better manage supply–demand imbalances. These findings provide a foundation for future research exploring hybrid models and real-time data integration to further improve predictive capabilities in ride-hailing services
Factors influencing technical competencies in digital marketing of MSMEs in wholesale and retail sectors: the mediating role of core competencies
Get PDFWhile technology is essential for the survival of micro, small, and medium-sized businesses (MSMEs), their ability to use digital marketing effectively, especially in the wholesale and retail sectors, remains unclear. The study aims to investigate the current state of digital marketing capabilities and the influence of behavioral competencies on technical competencies through the core competencies in digital marketing. The research approach included surveying a sample size of 400 MSMEs in the wholesale and retail sectors. The collected data was analysed using a combination of descriptive statistics and structural equation modelling approaches. This study highlights the crucial role of core competencies in digital marketing. It suggests that strong behavioral skills positively influence technical skills by first impacting core competencies. The findings of this research show that improving behavioral and core competencies has a substantial and positive impact on the technical competencies in digital marketing. Including, the primary goal of developing digital marketing abilities should be to hone behavioral and core competencies since they will contribute to a demonstrable enhancement in the technical competencies of digital marketing
Influence of transport air pollutants on climate change in EU: case of Lithuania
Get PDFThe purpose of the research paper is to observe and analyse how the motorization rate of EU countries influence climate change during the last decades in terms of inventory of emissions of air pollutants from transport, giving an example of Lithuania. Passenger cars are a major polluter, accounting for 61% of total CO2 emissions from EU road transport. EU approved directions to transitioning to fossil-free transport and reducing car use in future to make the European Union carbon neutral by 2050. Research methodology is statistical analysis of motorization rate growth and air pollution in the EU countries during the period of 2014–2024. In the research paper the quantitative analysis and comparison method are applied. Findings: research paper shows that in the EU countries motorization rate is growing very fast. However the consequences of this vary from country to country. Significant disparities arise from the age of the vehicles, the type of fuel utilized, and the turnover rate of passenger cars, resulting in the current fleet not achieving an adequate decrease in CO2 emissions. This research examines the correlation between motorization levels and CO2 emissions across several EU countries over recent decades and offers potential solutions to this issue
Spectral algorithm for fractional BVPs via novel modified Chebyshev polynomials fractional derivatives
Get PDFThis paper introduces a spectral algorithm tailored for solving fractional boundary value problems (BVPs) using the fractional derivatives of modified Chebyshev polynomials. Specifically, it addresses linear and non-linear BVPs and Bratu equations in one dimension via spectral methods. The approach employs basis functions derived from first-kind shifted polynomials that satisfy the homogeneous boundary conditions. The fractional derivatives are formulated to facilitate the solution process. The convergence analysis is studied for the suggested basis expansion; some numerical results are exhibited to verify the applicability and accuracy of the method
Modelling solutions for cost optimization in multimodal transports considering the operational risk variables
Get PDFThe general risk assessment usually has the potential of setting a viable ground for pursuing a complex mathematical model based on an objective function, defined by several variables and constraints, which can be further applied for the specific analysis of multimodal transport. In order to assess the operational risks in multimodal transports, the authors have formulated an objective function with the aim of minimizes the sum of total cost of transportation on route components depending on the risk variables, respectively for road, maritime and railway subsystems of multimodal transport, in different combinatorial perspectives. The main objective of this study is to provide a method to value the overall risk assessment based on the defined objective function, considering both the variables that may influence the cost effectiveness and the relevant probabilities for each route component of multimodal transport. In this perspective, the authors have sought to provide practical solutions for decision-making process in multimodal routing, to optimize the costs on different routes and to contribute for decision-making process in routing and transports mode selection. The main contribution is residing from the novelty of decision-making process approach, considering the risk variables in different combination, facile to be applied professional in multimodal transportation in routing process, when risks are to be considered as significant for process reliability.
First published online 19 January 2026
Extended security control and delay propagation in air cargo transport operations: implications for supply chain continuity
Get PDFPrior research on security controls in air cargo terminals has primarily focused on protecting passengers, crews, and airport infrastructure, while largely overlooking the maintenance of supply chain continuity. The present study addresses this gap by analysing how the configuration, spatial placement, and scheduling of screening procedures affect the stability of cargo flows, as well as the incidence and propagation of delays in air freight operations. Evidence was collected at 2 terminals – a regional facility in southern Poland and a large international terminal in southern Europe, which enabled a comparative assessment that accounts for organisational and structural differences. The analysis mapped screening procedures onto the operational timeline of cargo-handling. Standard screening consisted of radiographic inspection of palletised consignments using an X-ray system. A negative result triggered an extended screening path comprising, in sequence, canine inspection, chemical screening using reactive swabs, and manual inspection of the load unit after opening by a qualified specialist. The total delay was computed as the sum of the times associated with the additional screening steps and the waiting time for the substitute uplift. Findings for 2022–2024 indicate pronounced differences between terminals in both the scale and effectiveness of controls. At the regional terminal, 3…6% of shipments were routed to extended screening, the average duration of additional actions was 1…2 h, and the final delay was 14…20 h. At the international terminal, the corresponding values were 12…15%, 5…7 h, and 84…95 h. The most significant delays were generated by procedures requiring external specialists, such as crate-opening technicians, and by the organisation of replacement transport. Where specialist support was provided periodically, the waiting time for inspection could reach up to 7 days, whereas smaller facilities operated with near-immediate response times. Based on these results, several operational improvements are indicated. Recommended actions include maintaining specialists on-call, issuing immediate notifications of adverse X-ray outcomes to planning teams, and selectively automating repetitive steps. Implementing these measures is expected to reduce inspection-related delays, improve on-time delivery performance, and enhance the resilience of air cargo supply chains.
First published online 23 January 202
Statistical models for the utilization process of aviation radio equipment
Get PDFThe reliability of aviation equipment is a critical factor that directly influences the efficiency of tasks associated with flight operations. To assess reliability, various indicators are commonly employed, including mean time between failures, mean time between repairs, steady-state availability, availability function, downtime ratio, and utilization factor. However, in modern aviation, the operation of radio equipment often neglects considerations of economic impact, socio-political factors, and a comprehensive analysis of the efficiency of all components within the civil aviation infrastructure. Reliability indicators are typically stochastic in nature, necessitating the development of statistical models, the application of advanced statistical data processing methods, and the enhancement of decision-making technologies, including those leveraging artificial intelligence. External influences, operational conditions, degradation of electrical components, and instability in both autonomous and external power supplies often result in nonstationary trends across the range of parameters being monitored. These dynamic changes highlight the need for advancements in traditional data processing methods, particularly in areas such as dataset formation, classification, evaluation, and forecasting. This article focuses on the development of statistical models for the downtime ratio and utilization factor, specifically addressing scenarios characterized by nonstationary trends in diagnostic parameters