The essay presents an original application of using the coolhunting method to discover new trends in architecture and design. The ability to identify trends is tied in with the possibility of attaining an advantage over the competition with the use of new designs that can become hits on the market, gaining the favor of customers. The term coolhunting can be broadly defined as the pursuit of inspiration and the forecasting of the directions of development. Initially, the term was applied to fashion, but quickly spread to other spheres of activity, like music, the arts, lifestyle and finally, to architecture and design. The essay is a slightly altered and improved rendition of the author's article published in Zastosowania ergonomii. Wybrane kierunki badań ergonomicznych w roku 2014 . (ed. Charytonowicz J.), Publ. Polskie Towarzystwo Ergonomiczne PTErg, o/Wrocław, 2014, p. 289-304. The method outlined therein is the result of research conducted under the author's supervision at the Institute of Architecture and Spatial Planning of the Poznań University of Technology between the years 2012 and 2014.
The paper aims at comparing forecast ability of VAR/VEC models with a non-changing covariance matrix and two classes of Bayesian Vector Error Correction – Stochastic Volatility (VEC-SV) models, which combine the VEC representation of a VAR structure with stochastic volatility, represented by the Multiplicative Stochastic Factor (MSF) process, the SBEKK form or the MSF-SBEKK specification. Based on macro-data coming from the Polish economy (time series of unemployment, inflation and interest rates) we evaluate predictive density functions employing of such measures as log predictive density score, continuous rank probability score, energy score, probability integral transform. Each of them takes account of different feature of the obtained predictive density functions.
While personality is strongly related to experienced emotions, few studies examined the role of personality traits on affective forecasting. In the present study, we investigated the relationships between extraversion and neuroticism personality traits and affective predictions about academic performance. Participants were asked to predict their emotional reactions two months before they will get their results for one important exam. At the same time, personality was assessed with the Big Five Inventory. All the participants were contacted by a text message eight hours after that the results were available, and they were requested to rate their experienced affective state. Results show moderate negative correlations between neuroticism and both predicted and experienced feelings, and that extraversion exhibits a weak positive correlation with predicted feelings, but not with experienced feelings. Taken together, these findings confirm that extraversion and neuroticism shape emotional forecasts, and suggest that affective forecasting interventions based on personality could probably enhance their efficiencies.
Households are the most significant group of consumers in the municipal and household sector in Poland. In 2010-2016, households consumed annually from 8.9 to 10.8 million Mg of coal (77-81% share in this sector). As of the beginning of 2018, seven voivodships in Poland have already introduced anti-smog resolutions, one has its draft, three are considering introduction of such resolutions. In the face of introducing anti-smog resolutions, the analysis of coal consumption by households was conducted for a situation where anti-smog resolutions will be introduced in all voivodships in Poland. A forecast of hard coal consumption by Polish households in 2017-2030 was presented in the article. Two scenarios differentiated in terms of calorific value of coal were taken into account: (i) concerned coal with a calorific value of 24 MJ/kg (min. Q for eco-pea coal: grain size 5.0-31.5 mm), (ii) – coals with a calorific value of 26 MJ/kg (Q recommended for use by producers of class 5 boilers). In the perspective of 2030, the largest decrease in hard coal consumption can be expected (jointly) in the voivodships of Śląskie, Dolnośląskie, Opolskie and Lubuskie. Under the assumptions made, in relation to 2016, it may be reduced by half and fall from 2.8 to the level of 1.4-1.5 million Mg. The smallest decreases in consumption may occur (jointly) in the Małopolskie, Lubelskie, Podkarpackie and Świętokrzyskie voivodships – decrease by 16-22% and fall from 2.6 to approximately 1.9-2.0 million Mg. On a national scale, coal consumption may decrease from the current 10.4 (2016) to around 6.3-6.8 million Mg (a decrease of 30-35%). Despite the decrease in hard coal consumption in the 2030 perspective, one should expect an increase in demand for high quality coal dedicated to modern boilers (usually pea assortments) as well as qualified coal fuels (mainly eco-pea coal).
The aim of the paper is to point out that the Monte Carlo simulation is an easy and flexible approach when it comes to forecasting risk of an asset portfolio. The case study presented in the paper illustrates the problem of forecasting risk arising from a portfolio of receivables denominated in different foreign currencies. Such a problem seems to be close to the real issue for enterprises offering products or services on several foreign markets. The changes in exchange rates are usually not normally distributed and, moreover, they are always interdependent. As shown in the paper, the Monte Carlo simulation allows for forecasting market risk under such circumstances.
A forecast of the negative impact exerted on the environment by selected trace elements in “Bełchatów” Power Plant has been prepared on the basis of the results of investigations into these elements’ distribution carried out as part of earlier research on coal from “Bełchatów” Field and the data on updated analyses of the content of these elements in 55 brown coal samples from test boreholes. Work in “Bełchatów” Power Plant, which is supplied with coal from “Szczerców” Field, will be accompanied by trace elements transfer. On the basis of the conducted investigations it has been found that the biosphere is most threatened by mercury emissions. As shown by the presented results of analyses and calculations, the emissions of mercury in “Bełchatów” Power Plant are low. Mercury is accumulated chiefl y in gypsum produced in the FGD plant. The content of mercury in slag and ash is low.
The article is an attempt to evaluate accuracy of Marx’s predictions and to present some reasons for Marx’s ineffectiveness as a forecaster. The article discusses contemporary research on forecasting, uses the results to Marx, and analyses the dialectic aspect of laws in order to explain forecasting weaknesses of Marx. The author of Capital turns out to be – in P.E. Tetlock’s typology – a ‘hedgehog’, i.e.: a bad forecaster, who uses questionable methods to defend his predictions at all costs.
Coal production in 2018 increased by 3.3% and amounted to 7.81 million tons. Compared to 2010, it increased by 620 million tons. The structure of coal production in the world is very stable in the analyzed period of 2010–2018. Steam coal dominates in production with a share of 77%. Since 1990, the share of coal in the consumption of primary energy carriers has fallen by 3% in the global economy. In the EU, the share of coal in the consumption of primary energy carriers is more than twice lower than in the world, and in 2018 amounted to 13%. BP estimates the sufficiency of coal proven reserves based on 2018 data for the next 132 years. For oil and gas, they are estimated at 51 years. The decline in hard coal production in the European U nion can be dated almost continuously since 1990, which has decreased by 74%. In 2018, 74 million tons of coal were produced in the EU. In 2018, hard coal consumption in EU countries dropped to 226 million tons, i.e. by 20.6%. In 2018, global trade in steam coal amounted to 1.14 billion tons. The situation in China is crucial for the international coal market. The slight change in the import policy of this country significantly affects the situation in international trade in steam coal. In 2019, coal prices (at Newcastle, Richards Bay, ARA ports) dropped by an average of 23 U SD/ton. The average decreases for these three indices were 33%. The prices of steam coal in the forecasts presented in the paper are under pressure of the falling demand.
The never before published paper is one of the last writings of Juliusz Żórawski (1898–1967), professor architect and theoretician of architecture. The notion of limited complexity introduced here relates to individual characteristics of the conceptual abilities of man. Tasks of architecture are based on prognoses, and this brings with it the risk of making errors. The author criticises J. Fourastié’s prognoses related to the Earth’s overpopulation in 3000 AD, which would force building new cities above the ground, contrary to human psychosomatic nature and habitude.
Traffic related noise is currently considered as an environmental pollution. Paper presents results of multidirectional study attempting to serve urban traffic without the need to erect noise barriers interfering urban space. Initial concept of the road expansion included construction of 1000 m of noise barriers dividing city space. Improvement in the acoustic conditions after construction completion is possible due to the applied noise protection measures: vehicle speed limit, smooth of traffic flow, use of road pavement of reduced noise emission and the technical improvement of the tramway.
The paper presents selected issues related to the development of international coal markets. World consumption of coal dropped for the second year in a row in 2016, primarily due to the lower demand from China and the US. The share of coal in global primary energy consumption decreased to 28%. World coal production accounted to 3.66 billion toe and it was lower by 6.2% when compared to the previous year. More than 60% of this decline took place in China. The decline in global production was more than four times higher than the decrease in consumption. The sufficiency of the world resources of coal are estimated at 153 years – that is three times more than the sufficiency of oil and gas resources. After several years of decline, coal prices increased by 77% in 2016. The current spot prices are at the level of $80/ton and are close to the 2014 prices. In the European market, after the first half of the year, coal prices reached the level of around 66% higher than in the same period of the last year. The average price in the first half amounted to PLN 12.6/GJ, which is close to the 2012 prices. The share of spot trade in the total purchase amount accounted to approx. 20%. Prices in futures contracts can be estimated on the basis of the Japan-Australia contracts prices and prices in supplies to power plants located in Germany. On average, the prices in supplies to these power plants were higher by approximately 9% in the years 2010 – 2016 and prices in Australia – Japan contracts were 12% higher than CIF ARA prices in 2017. Global energy coal trade reached about 1.012 billion tons in 2016. A decline by 4.8% is expected in 2019 primarily due to the expected reduction in demand in major importing countries in Asia.
The methane hazard is one of the most dangerous phenomena in hard coal mining. In a certain range of concentrations, methane is flammable and explosive. Therefore, in order to maintain the continuity of the production process and the safety of work for the crew, various measures are taken to prevent these concentration levels from being exceeded. A significant role in this process is played by the forecasting of methane concentrations in mine headings. This very problem has been the focus of the present article. Based on discrete measurements of methane concentration in mine headings and ventilation parameters, the distribution of methane concentration levels in these headings was forecasted. This process was performed on the basis of model-based tests using the Computational Fluid Dynamics (CFD). The methodology adopted was used to develop a structural model of the region under analysis, for which boundary conditions were adopted on the basis of the measurements results in real-world conditions. The analyses conducted helped to specify the distributions of methane concentrations in the region at hand and determine the anticipated future values of these concentrations. The results obtained from model-based tests were compared with the results of the measurements in realworld conditions. The methodology using the CFD and the results of the tests offer extensive possibilities of their application for effective diagnosis and forecasting of the methane hazard in mine headings.
This paper researches the application of grey system theory in cost forecasting of the coal mine. The grey model (GM(1.1)) is widely used in forecasting in business and industrial systems with advantages of minimal data, a short time and little fluctuation. Also, the model fits exponentially with increasing data more precisely than other prediction techniques. However, the traditional GM(1.1) model suffers from the poor anti-interference ability. Aimed at the flaws of the conventional GM(1.1) model, this paper proposes a novel dynamic forecasting model with the theory of background value optimization and Fourier-series residual error correction based on the traditional GM(1.1) model. The new model applies the golden segmentation optimization method to optimize the background value and Fourier-series theory to extract periodic information in the grey forecasting model for correcting the residual error. In the proposed dynamic model, the newest data is gradually added while the oldest is removed from the original data sequence. To test the new model’s forecasting performance, it was applied to the prediction of unit costs in coal mining, and the results show that the prediction accuracy is improved compared with other grey forecasting models. The new model gives a MAPE & C value of 0.14% and 0.02, respectively, compared to 1.75% and 0.37 respectively for the traditional GM(1.1) model. Thus, the new GM(1.1) model proposed in this paper, with advantages of practical application and high accuracy, provides a new method for cost forecasting in coal mining, and then help decision makers to make more scientific decisions for the mining operation.
In recent years, the rate of urban growth has increased rapidly especially in Egypt, due to the increase in population growth. The Egyptian government has set up new cities and established large factories, roads and bridges in new places to solve this trouble. This paper investigates the change monitoring of land surface temperature, urban and agricultural area in Egypt especially Kafr EL-Sheikh city as case study using high resolution satellite images. Nowadays, satellite images are playing an important role in detecting the change of urban growth. In this paper, cadastral map for Kafr El-Sheikh city with scale 1:5000, images from Landsat 7 with accuracy 30 meters; images from Google Earth with accuracy 0.5 meter; and images from SAS Planet with accuracy 0.5 m are used where all images are available during the study period (for year’s 2003, 2006, 2009, 2012, 2015 and 2017). The analysis has been performed in a platform of Geographical Information System (GIS) configured with Remote Sensing system using ArcGIS 10.3 and ERDAS Imagine image processing software. From the processing and analysis of the specified images during the studied time period, it is found that the building area was increased by 28.8% from year 2003 up to 2017 from Google Earth images and increased by percentage 34.4% from year 2003 up to year 2017 from supervised Landsat 7 images but for unsupervised Landsat 7 images, the building area was increased by percentage 35.9%. In this study, land surface temperature (LST) was measured also from satellite images for different years through 2003 until 2017. It is deduced that the increase in the building area (urban growth) in the specified city led to increase the land surface temperature (LST) which will affect some agricultural crops. Depending on the results of images analysis, Forecasting models using different algorithms for the urban and agricultural area was built. Finally, it is deduced that integration of spacebased remote sensing technology with GIS tools provide better platform to perform such activities.