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Publications - 6374

Development of the financial situation of Hungarian food industry enterprises - changes between 2017 and 2021

Károly Kacz Szabolcs Troján Judit Hegyi Anita Miklósné Varga

Publication Name: Economic and Regional Studies Studia Ekonomiczne I Regionalne

Publication Date: 2023-09-01

Volume: 16

Issue: 3

Page Range: 348-366

Description:

Subject and purpose of work:: The aim of the study is to analyse how the main financial data of d ouble-entry b ookkeeping f ood p rocessing e nterprises r eflect t he e ffects o f t he i ndicated economic environment. Materials and methods:: The evaluation was fundamentally based on ratios calculated on the basis of the statement of financial position and the income statement as well as trend analysis and financial indicators. Results:: The number of Hungarian food processing enterprises has been gradually decreasing over the period under review. Both turnover and expenditure show linear growth at current prices, with increases in the various result categories. The asset structure is stable, and profitability is improving. Conclusions:: The number of companies and the employment in the sector have been steadily declining in recent years, while efficiency is increasing. The increase in profits in the food industry is remarkable for all branches of the economy. The sector is adapting well to the negative effects of the changing economic environment.

Open Access: Yes

DOI: 10.2478/ers-2023-0022

A comparative study of various evolutionary algorithms used for fuzzy rule-based inference and learning systems

Krisztián Balázs Zs Dányádi Ĺaszĺo T. Ḱoczy

Publication Name: Iccc Conti 2010 IEEE International Joint Conferences on Computational Cybernetics and Technical Informatics Proceedings

Publication Date: 2010-08-06

Volume: Unknown

Issue: Unknown

Page Range: 49-54

Description:

The goal of this paper is to provide an overview of a variety of evolutionary algorithms, comparing their efficiency on fuzzy rule-based inference and learning. Fuzzy rule-based inference can be used to model a desirable outward behavior of a system when given a specific input, which, in the case of this comparative study, is determined by a set of samples, generated by sufficiently complex objective functions. Optimizing a fuzzy rule-based inference system is a matter of finding a rule base that is as close to imitating the desired behavior as possible. While the specific applications of evolutionary methods are endless, the objective functions used here remain general in nature. © 2010 IEEE.

Open Access: Yes

DOI: 10.1109/ICCCYB.2010.5491228

Analysis of morphology changes of heat treated metallization of compound semiconductors by the fast wavelet-transform based on B-Spline

K. A. Demcu M. Schusztera László Dobos Imre Mojzes Szilvia Nagy

Publication Name: Journal of Optoelectronics and Advanced Materials

Publication Date: 2007-01-01

Volume: 9

Issue: 7

Page Range: 2241-2244

Description:

Heat treatment of metallized compound semiconductors results in generation of Ohmic contacts. The morphology changes of the surface during the thermal treatment can be observed by scanning electron microscope. According to our previous results these patterns show fractal character. The fractal dimension of a self-similar object can be calculated using the toolbox of fast wavelet-transform. A method is presented for analyzing the electron microscopic images of the heat treated samples by a fast wavelet-transform based algorithm using the filter coefficients of the two dimensional B-Spline functions. A connection between the dimension values of the patterns and the temperatures of the heat treating are shown.

Open Access: Yes

DOI: DOI not available

Comparison between Ramberg-Osgood and Hardin-Drnevich soil models in Midas GTS NX

Majd Ahmad R. P. Ray

Publication Name: Pollack Periodica

Publication Date: 2021-12-31

Volume: 16

Issue: 3

Page Range: 52-57

Description:

This paper studies the two widely used material models for predicting the dynamic behavior of soils, the Ramberg-Osgood and Hadrin-Drnevich models. Resonant column and torsional simple shear test results on dry sand were used to calibrate and evaluate the model built in the finite element software Midas GTS NX. Both material models are already implemented by the software. This study estimates the ability and efficiency of both soil models coupled with the Masing criteria to predict the behavior of soil when subjected to irregular loading patterns, (e.g., earthquakes), and measure the two most important dynamic properties, the dynamic shear modulus, and the damping ratio.

Open Access: Yes

DOI: 10.1556/606.2021.00353

Fuzzy Linguistic Signatures

Nour Ammar Ĺaszĺo T. Ḱoczy

Publication Name: Infocommunications Journal

Publication Date: 2026-01-01

Volume: 18

Issue: 1

Page Range: 43-52

Description:

Fuzzy Linguistic Signatures (FLS) extend the concept of Fuzzy Signatures (FSigs) by introducing linguistic variables as qualitative descriptors within a hierarchical fuzzy structure. Although fuzzy signatures have been successfully applied in various domains, their reliance on numerical membership degrees limits their ability to model subjective or linguistically defined information. This paper establishes a formal mathematical framework for FLS by defining a family of fuzzy linguistic signatures equipped with suitable linguistic aggregation operators and a partial ordering relation among linguistic values. Furthermore, meet-and-join operators are introduced to demonstrate that FLS satisfies the properties of a lattice as an algebraic structure. Consequently, fuzzy linguistic signatures provide an expressive representational framework capable of handling qualitative, human-like reasoning.

Open Access: Yes

DOI: 10.36244/ICJ.2026.1.5

Cumulative and Rolling Horizon Prediction of Overall Equipment Effectiveness (OEE) with Machine Learning

János Jósvai Péter Dobra

Publication Name: Big Data and Cognitive Computing

Publication Date: 2023-09-01

Volume: 7

Issue: 3

Page Range: Unknown

Description:

Nowadays, one of the important and indispensable conditions for the effectiveness and competitiveness of industrial companies is the high efficiency of manufacturing and assembly. These enterprises based on different methods and tools systematically monitor their efficiency metrics with Key Performance Indicators (KPIs). One of these most frequently used metrics is Overall Equipment Effectiveness (OEE), the product of availability, performance and quality. In addition to monitoring, it is also necessary to predict efficiency, which can be implemented with the support of machine learning techniques. This paper presents and compares several supervised machine learning techniques amongst other polynomial regression, lasso regression, ridge regression and gradient boost regression. The aim of this article is to determine the best estimation method for semiautomatic assembly line and large batch size. The case study presented with a real industrial example gives the answer as to which of the cumulative or rolling horizon prediction methods is more accurate.

Open Access: Yes

DOI: 10.3390/bdcc7030138

Impact assessment between the city and the company reputation

Eva Happ Petra Jakab

Publication Name: Economics and Sociology

Publication Date: 2017-01-01

Volume: 10

Issue: 1

Page Range: 279-289

Description:

Since there’s a race for customers on the market of the consumer goods, cities of the 21st century compete for the inhabitants, tourists, investors and companies. In this competition the image and good reputation of the city, their conscious framing is one of the biggest feats of arms. The economy of the dynamically developing city, Győr is based after several system changes on the automobile industry. Its main leg is the important international company with headquarter in Győr since 1993, the Audi Hungaria Zrt. (AH). As results of the research analysing the marketing communicational print and film tools of the company and the city, the author tried to figure out, how the AH and the city interact in their corporate communication, in their reputation.

Open Access: Yes

DOI: 10.14254/2071-789X.2017/10-1/20

Comparison of square-wave and sinusoidal signal injection in sensorless polarity detection for PMSMs

Krisztian Enisz Istvan Szalay Denes Fodor

Publication Name: 2022 IEEE 20th International Power Electronics and Motion Control Conference Pemc 2022

Publication Date: 2022-01-01

Volume: Unknown

Issue: Unknown

Page Range: 583-589

Description:

This paper compares the non-modulated square-wave voltage injection-based and sinusoidal voltage injection-based polarity detection methods applicable in sensorless PMSM drives. A quadratic PMSM model extension is presented that serves as a basis for the polarity detection techniques. The comparison includes the polarity-dependent current components produced by the injected signals, the design parameters related to the injected signal features and their effect on the probability of correct polarity detection. The performance differences and possible application areas are also discussed.

Open Access: Yes

DOI: 10.1109/PEMC51159.2022.9962876

A Hybrid Discrete Memetic Algorithm for Solving Flow-Shop Scheduling Problems

Olivér Hornyák Károly Nehéz Boldizsar Tuu-Szabo Levente Fazekas Ĺaszĺo T. Ḱoczy

Publication Name: Algorithms

Publication Date: 2023-09-01

Volume: 16

Issue: 9

Page Range: Unknown

Description:

Flow-shop scheduling problems are classic examples of multi-resource and multi-operation scheduling problems where the objective is to minimize the makespan. Because of the high complexity and intractability of the problem, apart from some exceptional cases, there are no explicit algorithms for finding the optimal permutation in multi-machine environments. Therefore, different heuristic approaches, including evolutionary and memetic algorithms, are used to obtain the solution—or at least, a close enough approximation of the optimum. This paper proposes a novel approach: a novel combination of two rather efficient such heuristics, the discrete bacterial memetic evolutionary algorithm (DBMEA) proposed earlier by our group, and a conveniently modified heuristics, the Monte Carlo tree method. By their nested combination a new algorithm was obtained: the hybrid discrete bacterial memetic evolutionary algorithm (HDBMEA), which was extensively tested on the Taillard benchmark data set. Our results have been compared against all important other approaches published in the literature, and we found that this novel compound method produces good results overall and, in some cases, even better approximations of the optimum than any of the so far proposed solutions.

Open Access: Yes

DOI: 10.3390/a16090406