In 2015 an important part of the official evaluation of Polish scientific journals was left to experts’ judgement. In this paper we try to establish which observable factors (with available data) are closely related to the outcome of experts’ evaluation of Polish journals in economic sciences. Using the multiple regression statistical model we show that only 5 variables (out of 17) significantly explain almost 50% of the empirical variance of the experts’ evaluation. The determinants of particular interest, not entering the formal criteria and not related to the impact on global science, are: the number of citations mainly in Polish journals and the affiliation with the Polish Academy of Sciences.
Spatial Disorder vs. Data Collection on Spatial Planning in Poland. The article deals with the issue of spatial disorder as a consequence of lack of information about spatial planning in local government administration units. An efficient monitoring system of spatial planning on the local level is indispensable for the effective implementation of public policies, development strategies and operational programmes. Lack of full knowledge of land use leads to irrational and unsustainable use of resources in municipalities. The activities of public statistics in the field of the quality of information on spatial management concern the quality and methods of obtaining data, while adjusting the information available to the needs of authorities responsible for spatial planning at all levels.
The paper presents the least admissible dimensions of black lines of spatial object images, according to Saliszczew, adjusted to the needs of database generalization. It is pointed out, that the adjusted dimensions are in agreement with the cartographic norm included in the National Map Accuracy Standards , and their application to the generalization 1 will allow, for any map scale, the determination of the: • value of the scale-dependent parameter of the generalization process, without user action; • measure of recognizability of the shortest black line section on the map, what helps to obtain unique results of line generalization; • measure of recognizability of black lines in the image – using a standard (elementary triangle) – helpful in obtaining unique result of line simplification, and an assessment of the process; • recognizability distance between lines of close buildings, securing unique aggregation of them; • verification of spatial object image lines visualization. The new solutions were tested with the Douglas-Peucker (1973) generalization algorithm, modified by the author, which treats the minimal dimensions as geometric attributes, while object classes and their data hierarchy as descriptive attributes. This approach secures uniqueness of results on any level of generalization process, in which data of spatial objects in the DLM model are transformed to conform with the requirements for the DCM model data.
The TerraSAR-X add-on for Digital Elevation Measurement ( TanDEM-X) mission launched in 2010 is another programme – after the Shuttle Radar Topography Mission (SRTM) in 2000 – that uses space-borne radar interferometry to build a global digital surface model. This article presents the accuracy assessment of the TanDEM-X intermediate Digital Elevation Model (IDEM) provided by the German Aerospace Center (DLR) under the project “Accuracy assessment of a Digital Elevation Model based on TanDEM-X data” for the southwestern territory of Poland. The study area included: open terrain, urban terrain and forested terrain. Based on a set of 17,498 reference points acquired by airborne laser scanning, the mean errors of average heights and standard deviations were calculated for areas with a terrain slope below 2 degrees, between 2 and 6 degrees and above 6 degrees. The absolute accuracy of the IDEM data for the analysed area, expressed as a root mean square error (Total RMSE), was 0.77 m.
The locally resonant sonic material (LRSM) is an artificial metamaterial that can block underwater sound. The low-frequency insulation performance of LRSM can be enhanced by coupling local resonance and Bragg scattering effects. However, such method is hard to be experimentally proven as the best optimizing method. Hence, this paper proposes a statistical optimization method, which first finds a group of optimal solutions of an object function by utilizing genetic algorithm multiple times, and then analyzes the distribution of the fitness and the Euclidean distance of the obtained solutions, in order to verify whether the result is the global optimum. By using this method, we obtain the global optimal solution of the low-frequency insulation of LRSM. By varying parameters of the optimum, it can be found that the optimized insulation performance of the LRSM is contributed by the coupling of local resonance with Bragg scattering effect, as well as a distinct impedance mismatch between the matrix of LRSM and the surrounding water. This indicates coupling different effects with impedance mismatches is the best method to enhance the low-frequency insulation performance of LRSM.
Nutrient pollution such as nitrate (NO3−) can cause water quality degradation in rivers used as a source of drinking water. This situation raises the question of how the nutrients have moved depending on many factors such as land use and anthropogenic sources. Researchers developed several nutrient export coefficient models depending on the aforementioned factors. To this purpose, statistical data including a number of factors such as historical water quality and land use data for the Melen Watershed were used. Nitrate export coefficients are estimates of the total load or mass of nitrate (NO3−) exported from a watershed standardized to unit area and unit time (e.g. kg/km2/day). In this study, nitrate export coefficients for the Melen Watershed were determined using the model that covers the Frequentist and Bayesian approaches. River retention coefficient was determined and introduced into the model as an important variable.
Defining species boundaries, due to morphological variation, often represents a significant challenge in paleozoology. In this paper we report results from multi− and univariate data analyses, such as enhanced clustering techniques, principal coordinates ordination method, kernel density estimations and finite mixture model analyses, revealing some morphometric patterns within the Eocene Antarctic representatives of Palaeeudyptes penguins. These large−sized birds were represented by two species, P. gunnari and P. klekowskii , known mainly from numerous isolated bones. Investigations focused on tarsometatarsi, crucial bones in paleontology of early penguins, resulted in a probability−based framework allowing for the “fuzzy” partitioning the studied specimens into two taxa with partly overlapping size distributions. Such a number of species was supported by outcomes from both multi− and univariate studies. In our opinion, more reliance should be placed on the quantitative analysis of form when distinguishing between species within the Antarctic Palaeeudyptes .
The aim of the article to assess the functioning of the NewConnect market over 10 years from the organizer’s and participants’ perspective. This helps to diagnose the most important organizational advantages and problems of the Polish MTF, determine further development prospects and propose potential changes to neutralize the negative factors. To illustrate the problem, a comprehensive analysis will be made of aggregated statistical data from 2007–2017, which show the changes and trends on this market, and additionally include the data comparing the current state of the NewConnect market with other alternative markets organized by European stock exchanges. The conducted research does not allow to view the NewConnect market as an organizational success. The analysis identified a number of problems in the functioning of the Polish MTF, ranging from the inappropriate organization of the primary market, resulting in the admittance of too high a number of issuers of dubious credibility, to the consequences appearing on the secondary shares market. It does not give unambiguous grounds to expect positive prospects for the market development in the future. In order to stop unfavorable trends and to improve the issuers’ quality, a discussion on the regulations regarding issuers’ admission, i.e. the size of the minimum equity, IPO, capitalization and the issue price of the debuting company, should be initiated.
In 2018, the 90th anniversary of Professor Vasiliy Danilovich Bondaletov`s birth will be celebrated. The aim of the article is to remind readers of the quantitative and qualitative method of statistical analysis in anthroponomastic research developed by Professor Bondaletov, as well as to show its advantages over simplified descriptions of the frequency of personal names. In this article, the detailed analysis of male Christian names found in customs books from Northern Russia (1633–1636 and 1678–1680) was conducted. The comparison of statistical data, according to the suggestion of Professor V. D. Bondaletov, enabled us to observe subtle differences between the abovementioned resources, namely to estimate the level of their (dis)similarity and describe the dynamics of the evolution of the resources of male Christian names throughout the 17th century, as well as changes in the popularity of various names.
The aim of the study was to choose and validate the tool(s) to predict the number of hospitalized patients by testing three predictive algorithms: a linear regression model, Auto-Regressive Moving Average (ARMA) model, and Generalized Auto-Regressive Conditional Heteroskedasticity (GARCH) model. The study used data from the collection of data on infl ammatory bowel diseases (IBD) from the public database of the National Health Fund for the years 2009–2017, data recalculation taking into account the population of provinces and the country in particular years, and prediction making for the number of patients who would require hospitalization in 2017. Th e anticipated numbers were compared with real data and percentage prediction errors were calculated. Results of prediction for 2017 indicated the number of hospitalizations for Crohn’s disease (CD) and ulcerative colitis (UC) at 17 and 16 respectively per 100,000 persons and 72 per 100,000 persons for all IBD cases. Th e actual outcomes were 21 for both CD and UC (81% and 75% accuracy of prediction, respectively), and 99 for all IBD cases (73% accuracy). The prediction results do not diff er signifi cantly from the actual outcome, this means that the prediction tool (in the form of a linear regression) actually gives good results. Our study showed that the newly developed tool may be used to predict with good enough accuracy the number of patients hospitalized due to IBD in order to organize appropriate therapeutic resources.