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Publications - 6374

Nutritional and functional aspects of European cereal-based fermented foods and beverages

Tolulope Joshua Ashaolu Babett Greff László Varga

Publication Name: Food Research International

Publication Date: 2025-05-01

Volume: 209

Issue: Unknown

Page Range: Unknown

Description:

European cereal-based fermented foods (ECBFFs) and alcoholic beverages have been fundamental components of regional diets for centuries, providing unique flavor profiles, essential nutrients, and a diverse array of health benefits. These foods, which encompass breads, beverages, and porridges, derive their functional and culinary properties from the activity of lactic acid bacteria and yeasts. This review examines the nutritional and functional characteristics of ECBFFs, with a focus on their microbial composition and fermentation processes. It highlights various ECBFFs and alcoholic beverages, including conventional and sourdough breads, tarhana, boza, kvass, and beers examining their health-promoting properties and potential for commercial expansion. Key findings from the literature show that certain ECBFFs are abundant in prebiotics and probiotics, primarily due to the fermentation processes involving lactic acid bacteria and yeasts. These microorganisms generate bioactive compounds such as organic acids, bacteriocins, and phenolic compounds, which exhibit antimicrobial, antioxidant, and anti-inflammatory activities. ECBFFs can also enhance digestibility, improve mineral bioavailability, and support gut health, thereby promoting overall well-being. From a commercial perspective, products like Yosa and Proviva demonstrate the feasibility of developing innovative ECBFFs that align with contemporary dietary preferences. The future of ECBFFs is promising, offering extensive opportunities for research, innovation, and large-scale commercialization to meet the increasing consumer demand for functional, plant-based foods.

Open Access: Yes

DOI: 10.1016/j.foodres.2025.116221

Special Issue on CogInfoCom-Supported Approaches, Models and Solutions in Surface Transportation

Attila Borsos Salvatore Cafiso Marian Tracz Péter Baranyi

Publication Name: Intelligent Decision Technologies

Publication Date: 2017-01-01

Volume: 11

Issue: 4

Page Range: 415

Description:

No description provided

Open Access: Yes

DOI: 10.3233/IDT-170311

Analyzing employee behavior related questionnaires by combined fuzzy signature model

Dalia Susniene Daiva Žostautienė Ojaras Purvinis Laszlo T. Koczy

Publication Name: Fuzzy Sets and Systems

Publication Date: 2020-09-15

Volume: 395

Issue: Unknown

Page Range: 254-272

Description:

The evaluation of data obtained from responses given to questionnaires in humanities and social sciences, such as management, linguistics, etc. is a complex task with the necessity of dealing with the inherent subjectivity and vagueness in such data. In this paper, a method based on fuzzy signatures (FSigs), suitable for analyzing questionnaires with hierarchically connected (partially) vague responses is proposed, and its applicability will be demonstrated by a real life problem; the partial analysis of an ongoing research examining employee behavior in various companies. The linkage of the factors hidden in the data bases obtained from the answers to the questionnaires, containing various factors interconnected in a more or less tight way, are represented by a hierarchical FSig system, allowing further evaluation and the discovery of emerging connections and deeper patterns among the responses, thus extending the idea of the original FSig model towards a more general, fuzzy-fuzzy signature approach. The method proposed here is a combination of some statistical elements with the Fuzzy Signature model, and it also uses Kohonen-maps in order to discover deeper structural components in the data pool. As FSigs are suitable to express hierarchically structured connections among vague and imprecise features of the individual data, the statistical analysis helps reveal the degrees of redundancies and the closeness of connectedness of the individual elements within the responses, and thus enable the construction of a relevant FSig tree graph for the data on hand, while further expert domain knowledge helps with determining the proper fuzzy aggregations in the intermediate nodes of the FSigs. The case study presented is based on data obtained from North Lithuanian companies. The results of the case study focusing on the analysis of the connection between OCB and CWB, and other factors, disclose some interesting and, partly unexpected, results. They indicate a strong and unambiguous relationship between career satisfaction and OCB, which is not very surprising. However, it is found that there is no relationship with gender, age, and actual position in the company, which are generally supposed to be determining factors. These results may be further validated by expert knowledge, and thus the new combined method for evaluating structured multicomponent data and internal dependencies is adequate.

Open Access: Yes

DOI: 10.1016/j.fss.2020.04.018

Kriging-Assisted Multi-Objective Optimization Framework for Electric Motors Using Predetermined Driving Strategy

Péter Korös György Istenes Zoltan Pusztai Ferenc Friedler Zoltán Horváth

Publication Name: Energies

Publication Date: 2023-06-01

Volume: 16

Issue: 12

Page Range: Unknown

Description:

In this paper, a multi-objective optimization framework for electric motors and its validation is presented. This framework is suitable for the optimization of design variables of electric motors based on a predetermined driving strategy using MATLAB R2019b and Ansys Maxwell 2019 R3 software. The framework is capable of managing a wide range of objective functions due to its modular structure. The optimization can also be easily parallelized and enhanced with surrogate models to reduce the runtime. The framework is validated by manufacturing and measuring the optimized electric motor. The method’s applicability for solving electric motor design problems is demonstrated via the validation process. A test application is also presented, in which the operating points of a predetermined driving strategy provide the input for the optimization. The kriging surrogate model is used in the framework to reduce the runtime. The results of the optimization and the framework’s benefits and drawbacks are discussed through the provided examples, in addition to displaying the properly applicable design processes. The optimization framework provides a ready-to-use tool for optimizing electric motors based on the driving strategy for single- or multi-objective purposes. The applicability of the framework is demonstrated by optimizing the electric motor of a world recorder energy-efficient race vehicle. In this application, the optimization framework achieved a 2% improvement in energy consumption and a 9% increase in speed at a rated DC voltage, allowing the motor to operate at desired working points even with low battery voltage.

Open Access: Yes

DOI: 10.3390/en16124713

Evaluating AI-driven credit scoring models versus traditional statistical techniques

Neha Parashar Jewel Kumar Roy Pradip Sanatkumar Padhye Varsha Shriram Nerlekar Sushil Kumar Gupta Dipak Santram Vakrani

Publication Name: Discover Artificial Intelligence

Publication Date: 2026-12-01

Volume: 6

Issue: 1

Page Range: Unknown

Description:

This study evaluates AI credit-scoring models against standard statistical models using a real-life data set with 1000 loan applications. The main research question is about whether machine-learning methods are more valuable in terms of predictive accuracy, interpretability and stability to changes in the process of macroeconomic deterioration as compared to traditional methods. The four model variants were developed: the logistic regression and decision tree as examples of the classical ones, and XGBoost gradient-boosting ensemble and multilayer perceptron neural networks as examples of AI-based alternatives. The methodological engine was R (v4.3.1), which established a 70:30 train-test strata union, inner cross-validation and harmony spatial search to tune the hyperparameter. The findings show that XGBoost produces an optimal balanced accuracy cumulative gain curve (cumulative gain, CGC: 0.89; area under the receiver operating characteristic, AUC: 0.89) that is trumped by the neural network (CGC: 0.87; AUC: 0.87) and succeeded by the logistic regression (CGC: 0.76; AUC: 0.76). The SHAP analysis shows that the amount of credit, duration of loan, and age are central predictors. During stress-test simulation, XGBoost is stable in making predictions (AUC = 0.83) compared to a severe decline in logistic-regression results (AUC = 0.68). The results therefore justify the claim that the state-of-the-art AI tools have better predictive potential and robust interpretability, thus rising as viable alternatives to the systems in vogue in modern finance organisations.

Open Access: Yes

DOI: 10.1007/s44163-025-00772-1

An Approach for Hierarchical Clustering of Road Vehicle Vibration Spectrums

Peter Foldesi László Róbert Hári

Publication Name: Lecture Notes in Mechanical Engineering

Publication Date: 2023-01-01

Volume: Unknown

Issue: Unknown

Page Range: 799-811

Description:

Research on the non-stationary nature of road vehicle vibrations (RVV) led to advances in simulating such processes. Contemporary methods introduced for the analysis of RVV primarily aimed at partitioning the signal in the time- or time − frequency domain, providing differing segments of a signal. However, a degree of dissimilarity, or conversely similarity, is still challenging to find. Hereunder we argue that in some cases, merely a statement of dissimilarity between neighbouring segments within a signal might be well-enough, though from a broader perspective, the assessment of the similarity of discrete Fourier transforms (DFT) may be the next practical step forward. For this reason, the current paper presents the hierarchical clustering of elements of the short-time Fourier transform (STFT) plane from an RVV measurement; secondly, it introduces a clustering validation metric to arrive at an optimum distance metric and a threshold to use in binary hierarchical clusters.

Open Access: Yes

DOI: 10.1007/978-3-031-15211-5_66

Optimization and finite element analysis of 3-pole magnetic bearing with nonlinear material

Miklós Kuczmann Daniel Marcsa

Publication Name: Przeglad Elektrotechniczny

Publication Date: 2010-12-20

Volume: 86

Issue: 12

Page Range: 91-94

Description:

This paper deals with the design and numerical simulation of a radial active magnetic bearing. This bearing is a Y-shaped three-pole magnetic bearing fed by two amplifiers. The geometry design is based on the analytical computation and numerical optimization based on nonlinear finite element analysis. The nonlinearity has been handled by the Newton-Raphson method.

Open Access: Yes

DOI: DOI not available

Development of Magnetic Hysteresis Loop Measurement System for Characterization of 3D-Printed Magnetic Cores

Tamas Orosz Miklos CSIZMADIA Tamás Horváth

Publication Name: Electronics Switzerland

Publication Date: 2025-06-01

Volume: 14

Issue: 11

Page Range: Unknown

Description:

Today, numerous advanced options exist for analyzing and measuring magnetic hysteresis loops and core loss across a broad spectrum of applications. Most of these systems are compact and ready to use, fulfilling the measurement and data processing requirements for laminated iron cores according to the standards. However, modeling newly developed materials with complex structures or the high-frequency behavior of iron cores, and the computation of dynamic hysteresis properties’ temperature dependence, are still challenging problems in the field. Moreover, these standardized measurement tools are relatively expensive, and most of them represent a black box that impedes research and further development. This paper presents the development of a cheap and accessible measurement system that is explicitly designed for recording the hysteresis properties of 3D-printed iron cores. The paper presents a comprehensive overview of the design process, components, circuitry, and simulations integral to this project. The paper presents a completed circuit simulation conducted using LTspice and validation of the prototype’s measurement performance. The measurements obtained with the proposed system show good agreement with those of the reference setup, demonstrating its accuracy and practical applicability.

Open Access: Yes

DOI: 10.3390/electronics14112235

Residual Stresses in Carburised, Carbonitrided and Case-hardened Components (Part 1)

Tamás Réti

Publication Name: Heat Treatment of Metals

Publication Date: 2003-12-08

Volume: 30

Issue: 4

Page Range: 83-96

Description:

The assesment of residual stress effects in carburised, carbonitride and case-hardened components was discussed. The development of computational models and procedures, which were applied to the simulation of the stress-evolution processes during heat treatment was also discussed. Shot peening, the most versatile method of producing residual stresses was studied. The influence of microstructure and residual stresses on crack initiation and propagation was discussed.

Open Access: Yes

DOI: DOI not available