Economic Impact of Credit Guarantee System - Hungarian Case Study

This paper is a in-depth analysis and impact assessment of the credit guarantee system of Hungary. This study focuses mainly on the practice of Garantiqa Creditguarantee Closed Co. Ltd and evaluates and analyzes the impact of the credit guarantee on Hungarian economy in providing benefits tosmall and medium sized enterprises (SMEs), which contributes to the economic development of Hungarythrough providing benefits to the banks. Based on a comparative analysis this study shows a positive impact on the Hungarian economy

Determinants of deforestation in Vietnam, 2008 – 2015

2022 Summer.Includes bibliographical references.New methods including satellite data, geographic information systems (GIS), and remote sensing processing have discovered human expansion over forest areas referred as forest degradation. This study acknowledges these findings but insists on using official data to address some drawbacks of previous studies. These drawbacks include (1) the focusing on limited areas, Central Highlands areas, instead of a national scale, (2) exclusion of resources trade from the analysis, (3) lacking consideration of the spatial and longitudinal autocorrelation, which is overlooked in panel analysis; and (4) the inconsistency of the relation between poverty and deforestation. This research investigated the effects of land-use change from agricultural expansion and timber extraction, resources trade, and community poverty on province-level forest coverage in Vietnam from 2008 to 2015 using panel and spatial autoregressive modelling. After accounting for resources trade, effect of agricultural expansion as well as forest extraction disappear. In addition, panel analysis suggests no covariate along poverty rate affects forest coverage while the spatial analysis suggests literacy rate and agricultural land are also have significant effects

Convoifilter: A case study of doing cocktail party speech recognition

This paper presents an end-to-end model designed to improve automatic speech recognition (ASR) for a particular speaker in a crowded, noisy environment. The model utilizes a single-channel speech enhancement module that isolates the speaker's voice from background noise, along with an ASR module. Through this approach, the model is able to decrease the word error rate (WER) of ASR from 80% to 26.4%. Typically, these two components are adjusted independently due to variations in data requirements. However, speech enhancement can create anomalies that decrease ASR efficiency. By implementing a joint fine-tuning strategy, the model can reduce the WER from 26.4% in separate tuning to 14.5% in joint tuning.Comment: 6 page

Development of a New Framework for Distributed Processing of Geospatial Big Data

Geospatial technology is still facing a lack of “out of the box” distributed processing solutions which are suitable for the amount and heterogeneity of geodata, and particularly for use cases requiring a rapid response. Moreover, most of the current distributed computing frameworks have important limitations hindering the transparent and flexible control of processing (and/or storage) nodes and control of distribution of data chunks. We investigated the design of distributed processing systems and existing solutions related to Geospatial Big Data. This research area is highly dynamic in terms of new developments and the re-use of existing solutions (that is, the re-use of certain modules to implement further specific developments), with new implementations continuously emerging in areas such as disaster management, environmental monitoring and earth observation. The distributed processing of raster data sets is the focus of this paper, as we believe that the problem of raster data partitioning is far from trivial: a number of tiling and stitching requirements need to be addressed to be able to fulfil the needs of efficient image processing beyond pixel level. We attempt to compare the terms Big Data, Geospatial Big Data and the traditional Geospatial Data in order to clarify the typical differences, to compare them in terms of storage and processing backgrounds for different data representations and to categorize the common processing systems from the aspect of distributed raster processing. This clarification is necessary due to the fact that they behave differently on the processing side, and particular processing solutions need to be developed according to their characteristics. Furthermore, we compare parallel and distributed computing, taking into account the fact that these are used improperly in several cases. We also briefly assess the widely-known MapReduce paradigm in the context of geospatial applications. The second half of the article reports on a new processing framework initiative, currently at the concept and early development stages, which aims to be capable of processing raster, vector and point cloud data in a distributed IT ecosystem. The developed system is modular, has no limitations on programming language environment, and can execute scripts written in any development language (e.g. Python, R or C#)

Assessing the impact of the credit guarantee fund for SMEs in the field of agriculture : the case of Hungary

Credit guarantee has an important role in promoting the development of small and medium sized enterprises (SMEs). Especially many countries including Hungary applied the credit guarantee fund to promote SMEs in the field of agriculture and rural. This study aims to assess the impact of credit guarantee foundation through the case of Rural Credit Guarantee Foundation of Hungary for SMEs in the agricultural sector. In this study, the author used quantitative method to evaluate the impact of Rural Credit Guarantee Foundation for SMEs in reducing financial cost, increasing sales, increasing investment etc