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The aim of this paper is to investigate the possibility of using two different methods together to detect more accurately and to evaluate thermal defects in the envelope of agricultural buildings. The structure of heated agricultural buildings is significantly influenced by the characteristics of the indoor environment (aggressive gaseous and liquid substances, high humidity, higher heating temperatures, etc.). In this study, research has been conducted that synergistically combines two methods for the evaluation of thermal defects, where the structure is evaluated using infrared thermography and at the same time described as a numerical model for a more detailed identification of envelope defects and thermal bridges. The study confirmed that in agricultural building structures, thermal defects are most commonly found in the areas of window lintels, ceiling and bracing structures, window and door joints, and foundation and floor joints, while the proposed combination of the two methods for assessing thermal defects in structures demonstrated superior performance in terms of accuracy and detail of results obtained compared to the standard partial use of only one of these methods.

In this study, we evaluate the thermal and mechanical properties of materials based on polypropylene (PP), high-density polyethylene (HDPE), and polyethylene terephthalate (PET) using the thermogravimetric analysis and impulse excitation technique. The results show that even if the melted input material together with the pressure of ~4 MPa was used to produce the samples, we can find small cavities around the sand grains in the samples. In case of thermal stability, the results show that in case of HDPE + PET combination, higher temperature should be used. Besides that, the results show that sand should increase the Young’s modulus of the samples from recycled materials.

This study presents the thermogravimetric analysis results of various samples of vineyard pruning residues from Rakvice Stand in the Moravian viticultural region. The samples of Welschreisling, Grüner Veltliner, Gewürztraminer, and Palava were investigated in several heating-isotherm steps. Based on the results, three of these samples were found to not meet the conditions for the B category (≤3%) according to the EN ISO 17225 in terms of ash content. Only the Palava sample showed 2.76% of ash content in dry matter, which makes it suitable for technological applications, such as combustion in small residential biomass boilers. Considering the other samples, the results indicate that it is more appropriate to combust them as a part of mixture with added content of different wood biomasses.

This paper deals with the relationship between grain yield and grain losses during harvest. Measurements were carried out on a combine harvester with axial harvesting device allowing various adjustments to combine harvester parameter settings, such as rotor speed, gap between separator and rotor, fan speed, holes of the upper and lower sieves. Values of harvest losses in combine harvester with custom settings for the given crops were compared with values of losses obtained by a harvester with manufacturer’s recommended settings. This paper observes the losses in grains of spring barley and winter wheat crops. All the measurements made showed lower grain losses when the combine harvester settings were customized. In general, custom settings provided quantitative losses lower by 0.198% than settings recommended by manufacturer.

Mutual trade restrictions between the USA and the PRC caused by the USA feeling of imbalance of trade between these two countries have significantly influenced not only the trade between these two states but also the overall atmosphere of the international trade in the last few years. The objective of the contribution is to find out whether machine learning forecasting is capable of equalizing time series so that the model effectively forecasts the future development of the time series even in the context of an extraordinary situation caused by such factors as the mutual sanctions of the USA and PRC. The dataset shows the course of the time series at monthly intervals starting from January 2000 to June 2019. There is regression carried out using neural structures. Three sets of artificial neural networks are generated. They are differ in the considered time series lag. 10,000 neural networks are generated, out of which 5 with the best characteristics are retained. The mutual USA and PRC sanctions did not affect the success rate of the machine learning forecasting of the CR import from the PRC. It is evident that the mutual sanctions shall affect the trade between the CR and the PRC.

The aim of this paper is to mechanically predict the import of the United States of America (USA) from the People's Republic of China (PRC). The trade restrictions of the USA and the PRC caused by the USA feeling of imbalance of trade between the two states have significantly influenced not only the trade between the two players, but also the overall climate of international trade. The result of this paper is the finding that multilayer perceptron networks (MLP) appear to be an excellent tool for predicting USA imports from the PRC. MLP networks can capture both the trend of the entire time series and its seasonal fluctuations. It also emerged that time series delays need to be applied. Acceptable results are shown to delay series of the order of 5 and 10 months. The mutual sanctions of both countries did not have a significant impact on the outcome of the machine learning prediction.

This research deals with the processing of wood using a circular saw, which is associated with several risks and factors that affect the wood-splitting process. One of them is the wear of the teeth of the saw blade that change the magnitude of the cutting forces. The aim of this study is to compare real measured values and theoretical values when processing Norway spruce wood using two types of saw blades, i.e., sintered carbide (SC) and high-speed steel (HSS), with a diameter of 600 mm and 54 and 56 teeth, respectively. Experimental measurements were carried out on a special test device with the possibility of moving the tested wood into the cutting devices and a simple saw blade replacement system. The results of the contributions show significant differences, based on defined factors which represent the cutting and feed speed, which are supported by FEM analysis of cutting forces in the process of cutting wood—when changing the design of the saw blade. The results of the experiment show that the cutting conditions (cutting speed and feed speed) do not have a significant effect on the size of the cutting forces. The theoretical and real stress values for HSS discs ranged from 14 to 22 MPa. Significantly larger differences were recorded for discs with SC, where the real values of the maximum stresses were around 14 MPa and the theoretical ones around 25 MPa. When cutting spruce with a disc with SC slices, the maximum values of the theoretical cutting forces were in the range of 76 to 94 N and the maximum values of the measured cutting forces were in the range of 40 to 44 N. [ABSTRACT FROM AUTHOR]

Through time series analysis, it is possible to obtain significant statistics and other necessary data characteristics. Prediction of time series allows predicting future values based on previously observed values. The exact prognosis of the time series is very important for a number of different areas, such as transport, energy, finance, economics, etc. It is within the topic of economy that the analysis and prediction of time series can also be used for exchange rates. The exchange rate itself can greatly affect the whole foreign trade. The aim of this article is therefore to analyze the exchange rate development of two currencies by analyzing time series through artificial neural networks. Experimental results show that neural networks are potentially usable and effective for exchange rate prediction.

Thanks to public debt, nations maintain a stable tax rate and at the same time raise expenses for suppressing budget crises. Public debt is considered risk-free and is issued by the national government. However, extensive public debt raises interest rates, extrudes private investments, worsens fixed balance, widens short-term fluctuation and has a negative impact on economic growth. The performance of the economy can be measured mostly by GDP, which is expressed as the monetary value of all finished products and services produced in a certain time period in one country. The aim of this paper is to explore the relationship, or rather identify the mutual correlation of public debt of one country and its performance (GDP). The research includes countries of the European Union, which have an identifiable timeline of public debt and GDP. The source of this data is the database of the World Bank. The information is from the period of years from 1995 through 2015. The correlation of the whole file of countries and then individual countries is ascertained. On the basis of the results, we can state that in the explored sample of countries, high dependence between public debt and GDP has been proven.

A remarkable success depends on a variety of factors, one of which is the ability to motivate the employees, increasing motivation of managers, measuring business processes and measuring and observing values of the company. The tangible results are also shown by the indicator of return on equity (ROE). The article aims at reflecting the importance of ROE for the EVA Equity (economic value added for shareholders) calculation of Motor Jikov Strojírenská, a.s. The data come from Albertina database. These are details of financial statements from 2000-2015. As a matter of fact, weighted average costs of capital, alternative cost value of equity capital and EVA Equity are calculated. Software Statistica and its sophisticated tool data mining - automated neural networks was used for finding a correlation between EVA Equity indicator and ROE. In addition, 10,000 neural networks were generated, five of which with the best results have been stored. The results show that EVA Equity is not dependent on the ROE rate.

The aim of the paper is to determine the actual cost of equity capital in the accommodation and food service activites sector in the Czech Republic between 2015 and 2019. The data was collected from the Albertina database and processed based on changes in retained earnings from previous years and the current financial year's profit. The results show the resulting cost of equity capital, which in the years under consideration averaged between 32.40 - 67.25% and the median values ranged between 11.78 - 22.72%. The contribution of this paper can be seen in bringing the resulting value of the actual cost of equity capital in the selected industry on which subsequent predictions for the future can be based. The limitation of the research can be seen in the use of older data. [ABSTRACT FROM AUTHOR]

Copyright of Urbanismus a Uzemni Rozvoj is the property of Institute for Spatial Development and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Thanks to its relative novelty, the sharing economy is still an insufficiently studied concept; it has however been raising increasing awareness among population, and therefore its study is very important. During the years 2010-2020, it began to account for an increasing share of the total GDP of almost all world countries. In the sector of the sharing economy, there are companies that offer an ever-growing range of goods and services. At present, these are accommodation, transport, and multimedia services. In the Czech Republic, with the increased share of the sharing economy, an increase in the ICT sector was also recorded. There are more than 700 vehicle sharing companies operating worldwide. Relevant published data are openly available through the Czech Statistical Office (CSO) public database and companies engaged in analytical activities, and also included in annual reports for investors of particular companies (the model company). An analysis of academic and scientific publications published so far on this topic shows that this area of economics has significant potential for future research. [ABSTRACT FROM AUTHOR]

The objective of the contribution is to propose a methodology of taking into consideration the seasonal fluctuations in time series equalization using artificial neural networks on the example of the United States of America export to the People´s Republic of China. For the research, the data from the period between January 1985 and August 2018 are used. For the prediction, two types of neural networks and two variants of input data sets are used. In the second variant, the seasonal fluctuation is represented by a categorical variable. It resulted that all retained structures are applicable, but the retained MLP networks of the B alternative achieve better results. It has been proven that with the use of artificial neural networks, it is possible to predict the export development efficiency and with a high degree of accuracy, especially in the short term and considering specific seasonal fluctuations. [ABSTRACT FROM AUTHOR]

The aim of our paper was to create a methodology for determining the value of small tangible fixed assets. For this, a flat-rate valuation method is used. The compilation of the instrument for determining the value of small tangible fixed assets is based on observation of the Czech market in this type of goods. The method is applied to the model association XYZ, which was in the research before its transformation into a limited liability company. The results presented in the form of an amortization scale can be applied to other types of valued assets, provided all requirements are met. [ABSTRACT FROM AUTHOR]

The aim of this paper is to determine the value of market rent and to assess the differences in valuation of the healthcare business just mentioned. For the purposes of this paper, a gynecological clinic is used as a medical facility, using the complete documentation of the facility. The property method is used for valuation purposes. However, given that the method chosen does not take sufficient account of the benefits of the reputatation of the gynecological clinic, goodwill, the intangible asset component, is valued at the interest rate level of the average profit corrected for past periods. Corrected earnings are expressed for all available periods. Thus, the monthly rent is fixed, the value of the goodwill is determined separately. A generally applicable methodology for the valuation of intangible assets for any medical facility is presented [ABSTRACT FROM AUTHOR]

In the case of the deposit of assets into a successor in the form of a limited company, it is possible to use the assets of the Association which has preceded the new formation. The need for the valuation of the Association´s assets is necessary under such circumstances. The contribution focuses on the method of valuating intangible assets of the Association of two natural persons. The method of the difference of Association’s assets value and yield value was used. The specific items forming the company’s asset are valued by various procedures based on their characteristics. It has been proved that it is possible to set quickly and accurately the book value of intangible assets in case it has not been previously included in the Association’s accounts. The value of intangible assets is set on the basis of the difference of asset and yield values. [ABSTRACT FROM AUTHOR]

Copyright of Waste Forum is the property of Czech Environment Management Center (CEMC) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)