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Found 6319 publications

Exchange rate impacts on international trade

Laszlo Vasa Robert Magda Jalil Mehtiyev

Publication Name: Economic Annals Xxi

Publication Date: 2021-07-10

Volume: 190

Issue: 5

Page Range: 12-22

Description:

As international trade activities are increased, there are more regulative practices which might be barriers to trade. One of such hindrances is exchange rate volatility that afects trade activities both directly and indirectly. Exchange rate volatility of currencies can afect the trade engagements and as well as the trade balance of a country. One of the implications of the study is that the impacts of monetary policy changes on trade activities can be noticed signifcantly in the long-term. While impacts on export levels are usually immediate, import levels are changed in long-run. The research analyzes the correlation between infation and devaluation and clearly states their impacts on trade balance. The case study about devaluation of the currency of Azerbaian elaborates the impacts of currency volatility on exports which is illustrated and analyzed in this research. Moreover, infation and devaluation correlations and their impacts on import level of a country are studied through correlation and multiple regression analyses based on the data exported from OECD and World Bank. The results conclude that exchange rate volatility signifcantly impacts the trade balance in terms of imports and exports. Given the results, exchange rate is a non-trade barrier and afects foreign trade.

Open Access: Yes

DOI: 10.21003/EA.V190-02

The impact of global socio-economic changes on the regional role of universities

Bálint Filep Zsuzsanna Pupp

Publication Name: Economic Annals Xxi

Publication Date: 2021-07-10

Volume: 190

Issue: 5-6

Page Range: 33-47

Description:

Economic and regional development and rapid, often unpredictable changes across the globe in technical fields have an effect on everything, including universities, training, research and services as well. Universities must find their place in this continuously changing environment, they need to continuously reinterpret themselves and their own roles, whilst ensuring that education and knowledge transfer take priority. The pace of change is increasingly accelerating with technological novelties and innovations by high-tech industries surpassing themselves at an astounding rate. Therefore, knowledge, as the facilitator and creator of these results, plays an increasingly important role for those who wish to rank among the winners of the competition both locally and globally. Today, the primary creators of knowledge are still educational institutions, and universities are the fundamental platforms of research. However, it is not enough to be «only» a university, they must educate and research and become part of the developed world alongside participants who would like to provide scientific answers to practical problems. In our paper we address the question of breaking points along which the role of universities can be transformed in order to remain open to the needs of both their narrower and wider environment while maintaining theirfundamental mission, thus becoming successful players on the global stage. The development of high-tech industries has resulted in a science-driven period when economic development is unimaginable without the scientific results and the interconnection of individual disciplines. This development will presumably lead to the deterioration of certain individual knowledge and the deepening of others. Higher education must also adapt to this with the development of an education system that strengthens digital skills and serves regional expectations. Nowadays entrepreneurial universities have emerged, which are able to operate with an entrepreneurial approach, thereby responding independently to challenges from outside. The ability to co-operate must be a key aspect of university existence, and the deepening of educational, research and business partnerships is a prerequisite for success. In order to spread management approach and create an entrepreneurial ecosystem, successful R&D work and innovation, it is also necessary to involve external, tender resources and grants, besides own resources. However, these resources need to be used well, but the lack of a pre-planned, conscious strategy results in less efficient use. Regional cooperation, common thinking, training and innovation, science workshops and science parks all contribute to the development of institutions and related regions.

Open Access: Yes

DOI: 10.21003/EA.V190-04

Proposal of an Autonomous Vehicle Control Architecture

Claudiu Radu Pozna Csaba Antonya

Publication Name: Ines 2021 IEEE 25th International Conference on Intelligent Engineering Systems Proceedings

Publication Date: 2021-07-07

Volume: Unknown

Issue: Unknown

Page Range: 37-42

Description:

In this paper, a control program architecture is proposed for autonomous vehicles. This set of programs is structured in a hierarchy and it is inspired by the human driver behavior. It contains three levels connected by specific links: the strategic, the tactical, and the operational level. Autonomous vehicles and human-driven vehicles will share the roads in future transportation systems. The human-like driving behavior will allow other participants to predict the autonomous vehicle's behavior.

Open Access: Yes

DOI: 10.1109/INES52918.2021.9512914

Highly toughened blends of poly(lactic acid) (PLA) and natural rubber (NR) for FDM-based 3D printing applications: The effect of composition and infill pattern

Ferenc Ronkay Imre Fekete László Lendvai

Publication Name: Polymer Testing

Publication Date: 2021-07-01

Volume: 99

Issue: Unknown

Page Range: Unknown

Description:

In this study, the suitability of natural rubber (NR) toughened poly(lactic acid) (PLA)-based blends were investigated for additive manufacturing applications. Filaments for fused deposition modeling (FDM) were prepared with an NR concentration of 0 … 20 wt% using a twin-screw extruder. Subsequently, specimens were fabricated with a desktop 3D printer machine working on FDM principles. Besides the composition of PLA/NR blends, the effect of infill orientation was also analyzed by preparing two sets of specimens: i) one set prepared with an alternating raster angle of ±45° (3DGRID) and ii) another one with a linear infill parallel to the length of the specimens (3DPAR). Quasi-static and dynamic mechanical properties, morphology and thermal characteristics of the fabricated specimens were investigated. The tensile tests revealed that the presence of NR effectively enhances the ductility of PLA filaments, however, the achieved improvement was highly dependent on the applied infill pattern. Samples prepared using the 3DPAR infill exhibited an excellent deformability when paired with NR. On the other hand, the ones fabricated with the 3DGRID technique only showed a marginal improvement in elongation. Similarly, the Charpy impact tests indicated an outstanding impact resistance of NR-toughened 3DPAR specimens, while the 3DGRID types showed little to no improvement. Scanning electron microscopic analysis revealed a weaker interlayer adhesion in the specimens containing NR, which greatly contributed to the discrepancies observed between the mechanical properties of the samples prepared with different infill. The differential scanning calorimetry revealed an almost completely amorphous structure of 3D printed PLA due to the quite rapid cooling characteristic of the FDM technique, which was not affected by the embedded NR component.

Open Access: Yes

DOI: 10.1016/j.polymertesting.2021.107205

Identification of the nonlinear steering dynamics of an autonomous vehicle

Gabor Rodonyi R. Toth M. Schoukens Péter Korös Dániel Pup Ádám Kisari G. I. Beintema Zsombor Vigh Alexandros Soumelidis József Bokor

Publication Name: IFAC Papersonline

Publication Date: 2021-07-01

Volume: 54

Issue: 7

Page Range: 708-713

Description:

Automated driving applications require accurate vehicle specific models to precisely predict and control the motion dynamics. However, modern vehicles have a wide array of digital and mechatronic components that are difficult to model, manufactures do not disclose all details required for modelling and even existing models of subcomponents require coefficient estimation to match the specific characteristics of each vehicle and their change over time. Hence, it is attractive to use data-driven modelling to capture the relevant vehicle dynamics and synthesise model-based control solutions. In this paper, we address identification of the steering system of an autonomous car based on measured data. We show that the underlying dynamics are highly nonlinear and challenging to be captured, necessitating the use of data-driven methods that fuse the approximation capabilities of learning and the efficiency of dynamic system identification. We demonstrate that such a neural network based subspace-encoder method can successfully capture the underlying dynamics while other methods fall short to provide reliable results.

Open Access: Yes

DOI: 10.1016/j.ifacol.2021.08.444

A New Strategic Marketing Management Model for the Specificities of E-Commerce in the Supply Chain

Laszlo Vasa Yuriy Bilan Balázs Gyenge Imre Vida Zoltán Máté

Publication Name: Journal of Theoretical and Applied Electronic Commerce Research

Publication Date: 2021-07-01

Volume: 16

Issue: 4

Page Range: 1136-1149

Description:

The study seeks to answer the question of what strategic directions and opportunities we have for business in the midst of the info-communication changes of our time. In this research, we compare the results of non-representative primary research (cluster analysis and discriminant analysis) with the factors and latest methods of e-commerce or even mobile commerce and traditional commerce and their main differences. Based on the four clusters examined, we develop a new strategic model for practice with suggestions which can be used by small and medium-sized enterprises (SMEs) and which they can incorporate directly into their business models. Starting point of our hypothesis was that in order to develop an effective and delivered communication, a market needs to be targeted and at least four different clusters should be formulated.

Open Access: Yes

DOI: 10.3390/jtaer16040064

Examining cross‐border cultural tourism as an indicator of territorial integration across the slovak–hungarian border

Tamás Hardi Eszter Szemerédi Gyula Ocskay Marcell Kupi

Publication Name: Sustainability Switzerland

Publication Date: 2021-07-01

Volume: 13

Issue: 13

Page Range: Unknown

Description:

There are numerous examples of cross‐border regions in Europe, which are regions not properly demarcated by national borders. One of the main driving forces of the European Union is to turn the dividing borders into connecting borders by strengthening the cohesion between states and regions, thus, encouraging regions to remedy the existing ethnic and cultural fragmentation by increasing the intensity and number of cross‐border contacts. Our research focuses on proving that, in symbolic places, such as the cross‐border area of Komárom and Komárno, the cultural values, monuments, and heritage sites are the strongest attraction factors for nationality‐based cultural tourism. To support our hypothesis, we conducted an empirical survey within the framework of the H2020 SPOT (Social and Innovative Platform on Cultural Tourism and its potential towards deepening Europeanisation) in the cross‐border region of Komárom and Komárno. The evaluation con-centrated on four aspects of cultural tourism: the nature of cultural tourism in the area, the resident and visitor perceptions of the cultural tourism offerings, opportunities to increase cross‐border col-laboration, and options to improve the cultural tourism offerings of the area. Our results show that, although there is a great potential in the cross‐border tourist destination of Komárom–Komárno, the integration of the (once united) two towns is advancing very slowly, which can be witnessed in the weaknesses of tourism integration as well.

Open Access: Yes

DOI: 10.3390/su13137225

Data-driven linear parameter-varying modelling of the steering dynamics of an autonomous car

Gabor Rodonyi R. Toth Péter Korös Dániel Pup Ádám Kisari Zsombor Vigh József Bokor

Publication Name: IFAC Papersonline

Publication Date: 2021-07-01

Volume: 54

Issue: 8

Page Range: 20-26

Description:

Developing automatic driving solutions and driver support systems requires accurate vehicle specific models to describe and predict the associated motion dynamics of the vehicle. Despite of the mature understanding of ideal vehicle dynamics, which are inherently nonlinear, modern cars are equipped with a wide array of digital and mechatronic components that are difficult to model. Furthermore, due to manufacturing, each car has its personal motion characteristics which change over time. Hence, it is important to develop data-driven modelling methods that are capable to capture from data all relevant aspects of vehicle dynamics in a model that is directly utilisable for control. In this paper, we show how Linear Parameter-Varying (LPV) modelling and system identification can be applied to reliably capture personalised model of the steering system of an autonomous car based on measured data. Compared to other nonlinear identification techniques, the obtained LPV model is directly utilisable for powerful controller synthesis methods of the LPV framework.

Open Access: Yes

DOI: 10.1016/j.ifacol.2021.08.575

Review and conceptual design of FPGA-based application for data-driven power electronic systems

Adrienn Dineva Adam Zsuga

Publication Name: 2021 17th Conference on Electrical Machines Drives and Power Systems Elma 2021 Proceedings

Publication Date: 2021-07-01

Volume: Unknown

Issue: Unknown

Page Range: Unknown

Description:

AI-based data-driven methods are an emerging research direction in the field of power electronics. However, because of the absence of large datasets, the development of these solutions have some barriers to overcome. To properly train machine learning algorithms and neural networks a large amount of training data is necessary. This dataset can be a union of simulation and measured data. Generating simulation data with computer simulations can be slow process and gathering real data is not cost-effective. Real-Time simulators based on FPGAs can be powerful tools to accelerate simulation, and create datasets for AI applications in a cost-effective and accurate way. In this paper the possible FPGA-based solutions, which can be applicable for the problems, have been reviewed. Their applicability have been discussed, moreover a simplified FPGA-based concept have been designed and embedded into two possible AI-based application area.

Open Access: Yes

DOI: 10.1109/ELMA52514.2021.9503033