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Found 6423 publications

Systematic approach to software related tasks in electric fuel-efficiency vehicle development

Erno Horváth Péter Korös

Publication Name: Ines 2015 IEEE 19th International Conference on Intelligent Engineering Systems Proceedings

Publication Date: 2015-11-13

Volume: Unknown

Issue: Unknown

Page Range: 375-378

Description:

Nowadays software related tasks in experimental vehicle development are getting more and more attention. These tasks not only include the final product related software solutions such as the motor and the vehicle control algorithm or the telemetry system but even in the development process, applications are needed - for example on the motor test bench. The paper presents our ideas and solutions to software related tasks in vehicles for the whole development and validation process.

Open Access: Yes

DOI: 10.1109/INES.2015.7329737

Two Stages Outlier Removal as Pre-Processing Digitizer Data on Fine Motor Skills (FMS) Classification Using Covariance Estimator and Isolation Forest

Surya Sumpeno A. Tormási Nurul Zainal Fanani Festa Yumpi Rahmanawati K. Khamid Adri Gabriel Sooai Mauridhi Hery Purnomo Laszlo T. Koczy

Publication Name: International Journal of Intelligent Engineering and Systems

Publication Date: 2021-08-01

Volume: 14

Issue: 4

Page Range: 571-582

Description:

The increase of the classification accuracy level has become an important problem in machine learning especially in diverse data-set that contain the outlier data. In the data stream or the data from sensor readings that produce large data, it allows a lot of noise to occur. It makes the performance of the machine learning model is disrupted or even decreased. Therefore, clean data from noise is needed to obtain good accuracy and to improve the performance of the machine learning model. This research proposes a two-stages for detecting and removing outlier data by using the covariance estimator and isolation forest methods as pre-processing in the classification process to determine fine motor skill (FMS). The dataset was generated from the process of recording data directly during cursive writing by using a digitizer. The data included the relative position of the stylus on the digitizer board. x position, y position, z position, and pressure values are then used as features in the classification process. In the process of observation and recording, the generated data was very huge so some of them produce the outlier data. From the experimental results that have been implemented, the level of accuracy in the FMS classification process increases between 0.5-1% by using the Random Forest classifier after the detection and outlier removal by using covariance estimator and isolation forest. The highest accuracy rate achieves 98.05% compared to the accuracy without outlier removal, which is only about 97.3%.

Open Access: Yes

DOI: 10.22266/ijies2021.0831.50

Evaluation of response times on a touch screen using stereo panned speech command auditory feedback

Hunor Nagy György Wersényi

Publication Name: Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics

Publication Date: 2016-01-01

Volume: 9811 LNCS

Issue: Unknown

Page Range: 279-286

Description:

User interfaces to access mobile and handheld devices usually incorporate touch screens. Fast user responses are in general not critical, however, some applications require fast and accurate reactions from users. Errors and response times depend on many factors such as the user’s abilities, feedback types and latencies from the device, sizes of the buttons to press, etc. We conducted an experiment with 17 subjects to test response time and accuracy to different kinds of speech-based auditory stimuli over headphones. Speech signals were spatialized based on stereo amplitude panning. Results show significantly better response times for 3 directions than for 5, as well as for native language compared to English, and more accurate judgements based on the meaning of the speech sounds rather than their direction.

Open Access: Yes

DOI: 10.1007/978-3-319-43958-7_33

First names of female servants in a Józsefváros (Josefstadt) apartment building in the 19th-20th centuries

László Horváth

Publication Name: Nevtani Ertesito

Publication Date: 2016-01-01

Volume: Unknown

Issue: 38

Page Range: 79-84

Description:

The paper discusses the 19th-20th-century first names of female servants in an apartment building in Budapest compared to the female first names used by the families that employed them. Sources were register books listing the inhabitants of the building between 1899 and 1947. Female servants arrived to the capital from over 40% of the counties in the country at the time, while families employing them were mostly from Budapest. The most frequent first names in the register books coincide with the top 10 percent of first names in the country-wide statistics of the era. The assumption that mainly young unmarried female servants were listed in the register books by hypocoristic names has clearly not been justified. A comparison of the first names of the female servants and those of the female members of their employers' families displays the approximate similarity of the most frequent first names. Differences between the two name stocks can only be observed with respect to female servants' informal nicknames. The final conclusion of the paper is that first names borne exclusively by female servants did not exist.

Open Access: Yes

DOI: DOI not available

Evaluating the Return Volatility of Cryptocurrency Market: An Econometrics Modelling Method

Laszlo Vasa Ashutosh Kolte Avinash Pawar Jewel Kumar Roy Imre Vida

Publication Name: Acta Polytechnica Hungarica

Publication Date: 2022-01-01

Volume: 19

Issue: 5

Page Range: 107-126

Description:

Cryptocurrency is the blockchain financial technology used for transactions in financial institutions and exchanges. Bitcoin has attracted much coverage from investors and commentators as it represents the maximum market capitalization on a crypto-currency exchange. The study aims to determine the correlation between the daily log–returns and to understand the tendencies in the cryptocurrency market instability of Bitcoin, Litecoin, XRP, Nxt, Dogecoin, Vertcoin, DigiByte, DASH, Counterparty, and MonaCoin. The correlation among the selected cryptocurrencies exists in the study. The analysis is focused primarily upon reference information from the preserved servers of cryptocurrency websites and finance.yahoo.com. This research assesses regular details on the Logarithmic return of Bitcoin, Litecoin, XRP, Nxt, Dogecoin, Vertcoin, DigiByte, DASH, Counterparty, and MonaCoin for a timeframe spanning from October 01st, 2014, to April 30th, 2020. From 131 cryptocurrencies, we considered only 10 Cryptocurrencies due to the availability of data after October 2014. Where there was insufficient information, there were average results determined from preceding and succeeding data. Findings demonstrate that there is GARCH modelling of cryptocurrencies against Bitcoin. Litecoin, XRP, Nxt, Dogecoin, Vertcoin, DigiByte, DASH, Counterparty, and MonaCoin; variability values throughout the duration had a significant effect on the updates from Bitcoin returns. We believe that it helps create information and resources that are valuable to practitioners and scholars who research and form cryptocurrency markets in the future.

Open Access: Yes

DOI: 10.12700/APH.19.5.2022.5.6

Soil shear modulus from resonant column, torsional shear and bender element tests

Peter Hudacsek Zsolt Szilvágyi Richard P. Ray

Publication Name: International Journal of Geomate

Publication Date: 2016-01-01

Volume: 10

Issue: 2

Page Range: 1822-1827

Description:

This study compares results from three different testing methods: Resonant Column, Torsional Simple Shear, and Bender Element tests to determine shear modulus. The resonant column and torsional shear tests were performed on the same hollow cylinder specimen. The bender element test was performed on a triaxial specimen with the same void ratio and confining stress as well as others. Several effects were studied, among them confining stress, shear strain amplitude and for the bender element, anisotropic confinement. Testing methods and data analysis are discussed in the paper because data interpretation is very important in these tests. Results showed that the shear modulus values were almost identical between the resonant column and torsional shear but varied somewhat with the bender element results. Further research will focus on influence of stress anisotropy preparation methods.

Open Access: Yes

DOI: 10.21660/2016.20.39871

Foreign direct investment and shadow economy: One-way effect or multiple-way causality?

Laszlo Vasa Wojciech Cieśliński Inna Tiutiunyk Andrii Zolkover

Publication Name: Journal of International Studies

Publication Date: 2022-01-01

Volume: 15

Issue: 4

Page Range: 196-212

Description:

The article examines the relationship between the size of the shadow economy and indicators of the investment market development. Net inflow of foreign direct investments, volume of net investments in non-financial assets, volumes of portfolio investments, and net outflow of foreign direct investment were used as parameters characterizing the development of the investment market. The dependence between the indicators was analyzed using the regression equation, Shapiro-Wilk test. Research results demonstrate that the increase in the inflow and outflow of foreign direct investments leads to an increase in the size of the shadow economy without a time lag in Ukraine, Poland, Slovenia, Romania, Croatia, Lithuania, Latvia, Estonia, and with a time lag of 1 year in Slovakia and Hungary. The largest impact on the size of the shadow economy is made by the volume of inflow and outflow of direct foreign investments, while the volume of portfolio investments has a less significant effect. Consequently, it was concluded that the processes of inflow and outflow of direct foreign investments require enhanced control by specialized state executive bodies given the scale of their potential destabilizing impact on the macroeconomic stability of the country.

Open Access: Yes

DOI: 10.14254/2071-8330.2022/15-4/12

Evaluation and improvement of parallel discrete event simulation performance predictions: A rough-set-based approach

László Muka István Derka

Publication Name: Acta Polytechnica Hungarica

Publication Date: 2016-01-01

Volume: 13

Issue: 6

Page Range: 125-145

Description:

Simulation performance prediction methods make possible the realization of performance improvement potentials of Parallel Discrete Event Simulation (PDES) methods, important in the analysis of complex systems and large-scale networks. Currently, high performance execution environments (emerging clusters and computing clouds) advance the development of quality/cost analysis capabilities of performance prediction methods. In this paper, for the evaluation and management of prediction correctness/cost, the efficacy, efficiency and effectiveness coefficients and improvement operations are defined for predictions. The performance coefficients and improvement operations are embedded in the rough-set-modeling and learning process and presented as an enhancement approach of the conventional Coupling Factor Method (CFM). A case study based on the CFM analysis of PDES of a closed queuing network model is presented. In the example, after rough-modeling and train-and-test analysis, the correctness/cost evaluation and effectiveness improvement operations are shown for series of predictions and the feedback connection to modeling refinement phase is demonstrated too.

Open Access: Yes

DOI: DOI not available

Determining factors for tourist arrivals in Hungary

Ferenc Bakó Marcell Kupi

Publication Name: Journal of Infrastructure Policy and Development

Publication Date: 2024-01-01

Volume: 8

Issue: 8

Page Range: Unknown

Description:

This methodologically focused study examines the relationships between inflation and unemployment rates, political stability, and tourism, with particular emphasis on the impacts on tourist arrivals in Hungary. The research aims to uncover the direct and indirect influences of these macroeconomic indicators on the volume of tourism, specifically international tourist arrivals. The significance of the study lies in the clear correlation between economic stability and labor market conditions with tourism volume, where rising inflation and unemployment rates negatively correlate with the number of tourist arrivals. This relationship is further strengthened by the observation that improvements in political stability enhance tourist numbers over the long term, while political instability, such as conflicts and terrorist acts, negatively affects tourism demand. These correlations are crucial for aligning tourism policy with economic policy, as macroeconomic indicators and the political environment directly influence both domestic and foreign tourists’ willingness to travel. The research methodology focuses on forecasting using Random Forest and neural networks, which enables more accurate predictions of tourism volume and supports informed tourism policy-making. The findings indicate that the development of the tourism sector is closely linked to economic growth and underscore the necessity of boosting tourism to expand employment and maintain economic stability.

Open Access: Yes

DOI: 10.24294/jipd.v8i8.5862