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Found 6374 publications

A work in progress - accreditation of forensic DNA laboratories as a part of the, European Forensic Science Area 2020 (EFSA 2020)” concept

Mónika Nogel Andras Czebe Gabor Kovacs Zsolt Pádár

Publication Name: Forensic Science International Genetics Supplement Series

Publication Date: 2019-12-01

Volume: 7

Issue: 1

Page Range: 836-837

Description:

As 2020 is approaching, various stakeholders and EU Member States are currently implementing some elements of the EFSA2020 concept. EFSA2020 offers Europe the chance to raise the quality level of its forensic science and in doing so, improve the public's confidence in the administration of justice. However, there is plenty of opportunity for further progress in creating the common forensic area. The paper will focus on accreditation of forensic DNA laboratories in V4 countries.

Open Access: Yes

DOI: 10.1016/j.fsigss.2019.10.195

Developing a macroscopic model based on fuzzy cognitive map for road traffic flow simulation

Miklós F. Hatwágner Gergely Cs Mikulai Mehran Amini Laszlo T. Koczy

Publication Name: Infocommunications Journal

Publication Date: 2021-01-01

Volume: 13

Issue: 3

Page Range: 14-23

Description:

Fuzzy cognitive maps (FCM) have been broadly employed to analyze complex and decidedly uncertain systems in modeling, forecasting, decision making, etc. Road traffic flow is also notoriously known as a highly uncertain nonlinear and complex system. Even though applications of FCM in risk analysis have been presented in various engineering fields, this research aims at modeling road traffic flow based on macroscopic characteristics through FCM. Therefore, a simulation of variables involved with road traffic flow carried out through FCM reasoning on historical data collected from the e-toll dataset of Hungarian networks of freeways. The proposed FCM model is developed based on 58 selected freeway segments as the “concepts” of the FCM; moreover, a new inference rule for employing in FCM reasoning process along with its algorithms have been presented. The results illustrate FCM representation and computation of the real segments with their main road traffic-related characteristics that have reached an equilibrium point. Furthermore, a simulation of the road traffic flow by performing the analysis of customized scenarios is presented, through which macroscopic modeling objectives such as predicting future road traffic flow state, route guidance in various scenarios, freeway geometric characteristics indication, and effectual mobility can be evaluated.

Open Access: Yes

DOI: 10.36244/ICJ.2021.3.2

Spatiotemporal prediction of soil moisture content at various depths in three soil types using machine learning algorithms

A. Széles Omar Hijazi Nour Ali Tarek Alahmad A. Nyéki M. Neményi

Publication Name: Frontiers in Soil Science

Publication Date: 2025-01-01

Volume: 5

Issue: Unknown

Page Range: Unknown

Description:

Introduction: Accurate prediction of soil moisture content (SMC) is crucial for agricultural systems as it affects hydrological cycles, crop growth, and resource management. Considering the challenges with prediction accuracy and determining the effect of soil texture, depth, and meteorological data on SMC variation and prediction capability of the used models, this research has been conducted. Methods: Three machine learning (ML) models—random forest regression (RFR), eXtreme gradient boosting (XGBoost), and long short-term memory (LSTM)—were developed to predict SMC in three soil types (loam, sandy loam, and silt loam) at five depths of 5, 20, 40, 60, and 80 cm. The dataset was collected during the maize season in 2023, encompassing meteorological parameters collected using Internet of Things (IoT)-based sensors and SMC data calculated using the gravimetric method. Results: The results showed variations in SMC in all studied soil types and depths, with silt loam exhibiting the highest variation in SMC. RFR demonstrated high accuracy at different depths and soil types, particularly in loam soil, at a depth of 80 with a root mean square error (RMSE) value of 0.89 and a mean absolute error (MAE) value of 0.74, and in silt loam at 40 cm depth with an RMSE value of 0.498 and an MAE of 0.416. LSTM performed effectively at shallower and moderate depths (60 and 20 cm) with RMSE values of 0.391 and 0.804 and MAE values of 0.335 and 0.793, respectively. In sandy loam soil at 5 cm depth, XGBoost displayed minimal errors and robust performance at the same depths with higher accuracy, achieving an RMSE of 0.025 and an MAE of 0.159. Analysis of training and validation loss revealed that the LSTM model stabilized and improved with more epochs, showing a more consistent decrease in MSE, while RFR and XGBoost exhibited higher performance with increased model complexity, shown in low MSE and RMSE values. Comparisons between measured and predicted SMC% values demonstrated the models’ effectiveness in capturing soil moisture dynamics. Furthermore, feature importance analysis revealed that solar radiation and precipitation were the most influential predictors across all models, offering critical insights into dominant environmental drivers of soil moisture variability. Discussion: By providing precise SMC predictions across different spatial and temporal scales, this study underscores the value of ML models for SMC prediction, which could have implications for improving irrigation scheduling, reducing water wastages, and enhancing sustainability.

Open Access: Yes

DOI: 10.3389/fsoil.2025.1612908

Intelligent production of the future - first results of a survey

No authors available

Publication Name: 17th IMEKO TC 10 and EUROLAB Virtual Conference "Global Trends in Testing, Diagnostics and Inspection for 2030"

Publication Date: 2020-01-01

Volume:

Issue:

Page Range: 402-407

Description:

Witnessing the unprecedented scale and speed of industry transformation due to digitization in general and the emergence of smart solutions in all aspects of manufacturing in particular, it is well justified to deal with the question of what production of the future will look like. How intelligent will it be when the hard challenges and disruptive effects of the changes will be overcome, and what are the chances to meet the critical requirements of collaboration and cooperation, flexibility and competitiveness? What are the technological and management tools to avoid being stuck in the so-called pilot purgatory? These issues are addressed in an international survey based on a questionnaire specifically tailored to conclude to viable options and recommendations for industrial companies. The results that are mostly in conformity with those published in the literature show that there is yet a lot to do to facilitate a definite turn in the mindset of the actors and to make them realize the relevance of simultaneous and continuous cultural and technological development.

Open Access: No

DOI: DOI not available

Taxonomic analysis of the diversity in the level of wind energy development in european union countries

Laszlo Vasa Tomasz Pisula Mirosław Liana Katarzyna Chudy-Laskowska

Publication Name: Energies

Publication Date: 2020-09-01

Volume: 13

Issue: 17

Page Range: Unknown

Description:

In this paper, the development of the wind energy sector in 28 European Union countries in 2017 is described. By means of taxonomic methods-i.e., Ward's method and the Wroclaw taxonomic methods-clusters of countries similar in terms of their potential and level of development of the wind energy sector in the EU are distinguished. The main purpose of the paper is to separate and cluster EU countries due to the current development potential of the wind energy sector and determinants stimulating the development of this sector. By means of the ranking methods of linear ordering (Technique for Order of Preference by Similarity to Ideal Solution-TOPSIS method), a ranking of EU countries that defines their position in the development of this very important wind energy sector was determined. The results show that the research hypothesis of a great diversity of EU countries considering the development potential of the wind energy sector is justified. The countries of the former European Union, which have focused for a long time on the development of wind energy in their energy policy and have had favorable climate and natural conditions, as well as a large social acceptance of programs supporting the acquisition of energy from renewable sources, have primacy in the development ranking of the energy sector. Additionally, new members of the union, in spite of some delays associated with the development of "green"energy, are trying to increase their energy potential in this area. The research may be extended to include further analyses regarding other renewable energy sources and take into account other European and world countries.

Open Access: Yes

DOI: 10.3390/en13174371

Computer aided formulation design based on molecular dynamics simulation: Detergents with fragrance

Lei Zhang Haiqiu Tang Yan Qi Lifeng Zhao Rafiqul Gani

Publication Name: Computers and Chemical Engineering

Publication Date: 2025-01-01

Volume: 192

Issue: Unknown

Page Range: Unknown

Description:

Computer-aided formulation design is a methodology that utilizes domain knowledge and selected methods and tools suitable for computer-based applications to assist in formulation (product) design. In this paper, molecular dynamics simulation and Bayesian neural network algorithms are combined with well-known engineering models to help accelerate the development and optimization of formulation-based detergent products with a view to improve product quality and performance. In particular, the mechanism of the behavior of polymers (an active ingredient in the product) to improve the product quality in terms of the fragrance and its residence time is highlighted. Results from molecular dynamic simulation applied to study the molecular interaction mechanism show that the polymers have an attraction effect with fragrance molecules and could adsorb more to make them to stay on the surface of clothes. In addition, the polymer attenuates the diffusion of the fragrance molecules, lengthening the entire process of fragrance diffusion, which is the essence of the ability of the polymer to slow down the release of the fragrance. A Quantitative Structure-Property Relationship (QSPR) model between component proportions and fragrance diffusion is established through Bayesian Neural Network (BNN) and the product formulation is optimized based on this model. Keeping polymer and perfume ingredients unchanged, the surfactant amounts are optimized to provide improved product quality.

Open Access: Yes

DOI: 10.1016/j.compchemeng.2024.108919

The Use Of Payment Cards In Kazakhstan: Analysis And Forecast

Laszlo Vasa Olga V. Koshkina Anna Kredina Olga V. Koshkina

Publication Name: Economy Strategy and Practice

Publication Date: 2021-01-01

Volume: 16

Issue: 3

Page Range: 106-116

Description:

The aim of the study is to analyze and forecast the use of payment cards for making non-cash payments through national payment systems in Kazakhstan. Based on this goal, a hypothesis was put forward that in Kazakhstan, there is a relationship between the number of payment cards and the volume of non-cash payments. This hypothesis was confirmed because of the study. The information base of the study was the data on payment cards, which were taken from the Statistical Bulletin of the National Bank of the Republic of Kazakhstan. Hypothesis testing was carried out using correlation analysis for three periods: 2009, 2016, 2020. The method of finding Pearson’s correlation in the SPSS program was used. The results showed a downward change in the relationship between the selected indicators and the amount of funds transferred over time. Also, in this study, a forecast was made for 2021-2023 for the indicators under consideration. To make a forecast for the indicators under consideration, a graphical method (polynomial trend line) was used. The resulting forecast shows the growth of cardholders and, consequently, the spread of the number of payment cards among the population in 2021-2023. The practical significance of this study is that the proposed methodology can help predict the dynamics of payment cards in any country in the world. Recommendations are also given for further improving the financial system, since increasing the transparency of monetary circulation in small-and-medium sized businesses will lead to a positive result in the implementation of the program for universal declaration of income in 2025.

Open Access: Yes

DOI: 10.51176/1997-9967-2021-3-106-116

New data on terrestrial gastropods (Gastropoda: Cyclophoroidea) from mid-Cretaceous Burmese amber, with descriptions of two new species in the genus Euthema (Diplommatinidae)

J. M. Bichain Barna Páll-Gergely Imre Szenti M. Szabó None Kokavecz

Publication Name: Zoosystematica Rossica

Publication Date: 2025-01-01

Volume: 34

Issue: 2

Page Range: 336-353

Description:

Mid-Cretaceous Burmese amber preserves an exceptionally diverse assemblage of operculate land snails. Here, two new diplommatinid species are described: Euthema convexispira Bichain et Páll-Gergely, sp. nov. and Eu. torokzselenszkyi Páll-Gergely et Szabó, sp. nov. Newly found specimens of two previously known species, Hirsuticyclus canaliculatus Yu, 2022 and Cretadiostoma caperatum Yu, Zhuo et Páll-Gergely, 2023, are described and illustrated; the specimen of the former is characterised by a distinctive spiral operculum, while that of the latter provides additional data on the morphology of the aperture and the proportions of the shell whorls. Furthermore, the article reports three specimens that are tentatively attributed here to the species Euthema cf. annae Balashov, 2021 and to the genera Euthema Yu, Wang et Pan, 2018 and Pulchraspira Yu, Salvador et Jarzembowski, 2021.

Open Access: Yes

DOI: 10.31610/ZSR/2025.34.2.336

Assessing the influence of financial repression on Bangladesh's financial development

Jewel Kumar Roy Md Yousuf Kamal Hossain Mohammad Bin Amin Mohammod Ullah Sayeed Bin Kamal Chowdhury

Publication Name: Multidisciplinary Science Journal

Publication Date: 2026-07-08

Volume: 8

Issue: 3

Page Range: Unknown

Description:

We investigate how financial repression affects financial development of Bangladesh over the period 1980-2022. Employing VECM, we find that repression policies negatively affect financial development, meaning that controlling the financial sector counteracts financial progress. Following the results, we recommend some policies. To accelerate financial progress, policymakers need to rethink on these restrictive policy instruments. For emerging nations like Bangladesh, this paper offers the first empirical data on the connection between financial repression and financial development.

Open Access: Yes

DOI: 10.31893/multiscience.2026140