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 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 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.

Vehicle parameters have a significant impact on handling, stability, and rollover propensity. This study demonstrates two methods that estimate the inertia values of a ground vehicle in real-time.

Through the use of the Generalized Polynomial Chaos (gPC) technique for propagating the uncertainties, the uncertain vehicle model outputs a probability density function for each of the variables. These probability density functions (PDFs) can be used to estimate the values of the parameters through several statistical methods. The method used here is the Maximum A-Posteriori (MAP) estimate. The MAP estimate maximizes the distribution of P(β|z) where β is the vector of the PDFs of the parameters and z is the measurable sensor comparison.

An alternative method is the application of an adaptive filtering method. The Kalman Filter is an example of an adaptive filter. This method, when blended with the gPC theory is capable at each time step of updating the PDFs of the parameter distributions. These PDF’s have their median values shifted by the filter to approximate the actual values.

The problem of poor quality of traffic accident data assembled in national databases has been addressed in European project InDeV. Vulnerable road users (pedestrians, cyclists, motorcyclists and moped riders) are especially affected by underreporting of accidents and misreporting of injury severity. Analyses of data from the European CARE database shows differences between countries in accident number trends as well as in fatality and injury rates which are difficult to explain. A survey of InDeV project partners from 7 EU countries helped to identify differences in their countries in accident and injury definitions as well as in reporting and data checking procedures. Measures to improve the quality of accident data are proposed such as including pedestrian falls in accident statistics, precisely defining minimum injury and combining police accident records with hospital data.

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.

Mathematics offers tools renowned for their objectivity, which is a cornerstone of scientific inquiry. Yet the question arises: how accurately do statistical methods really reflect the complexities of the real world?

The paper presents a classification of the healthy skin and the skin lesions (basal cell carcinoma) basing on a statistics of the envelope of ultrasonic echoes. The echoes envelopes distributions were modeled using Rayleigh and K-distribution. The distributions were compared with empirical data to find which of them better models the statistics of the echo-signal obtained from the human skin. The results indicated that the K-distribution provides a better fit.

Also, a characteristic parameter of the K-distribution, the effective number of scatterers (M), was investigated. The values of the M parameter, obtained for the skin cancer (basal cell carcinoma), were lower as compared to those obtained for the healthy skin. The results indicate that the statistical quantitative ultrasound parameters have a potential for extracting information useful for characterization of the skin condition.

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 purpose of the paper is to analyze the positioning of Ukraine in the global indices of innovative development and competitiveness, to evaluate the indicators of innovation activity and, based on the outcomes of the research, to determine the place of Ukraine in the global innovation space. The dynamics of innovation activity on an international scale based on the consolidated indicators of the Global Innovation Index are presented. Ukraine’s position in it and progress in achieving goals to better understand the processes that stimulate or constrain innovation are determined. Econometric methods to generalize the positioning of Ukraine in the global innovation space and the DEA method to study the relative individual effectiveness of the innovation environment and innovation activities in Europe are used.

The paper presents experimental results of the lifetime of light induced excess carriers in the n-type silicon. The lifetimes of carriers of silicon crystals were analysed as a function of the intensity of light illuminating the sample. As a measurement method of the lifetime of carriers, the photoacoustic method in a transmission configuration with different surfaces was used. The dependence character was next analysed in the frame of the Shockley Reed Hall statistics in approximation of the light low intensity.

The aquifer system of the Remila plain (Khenchela, Algeria), covering 250 km2, is one of the semiarid regions where groundwater is heavily exploited for urban supply and irrigation. An integrated hydrochemical and statistical analysis was performed on 70 water samples to identify the main processes and the origin of salinisation of our waters. Chemical analyses indicate salinity values (TDS) ranging from 568 to 1586 mg·dm–3 with an average of 869 mg·dm–3, with sulphate being the dominant ions, especially in the north and northeastern parts of the region. The identified chemical facies are SO4-Cl-Ca in the northeastern part, SO4-Cl-Ca-Mg present in most waters, and HCO3- Ca-Mg in the southeastern part.
We applied the statistical approach to group the waters into three categories using Principal Component Analysis (PCA) and Hierarchical Clustering Analysis (HCA); 1) saline waters (23%) (TDS > 1000 mg·dm–3 and SO42– dominance), 2) moderately saline waters (51%) with HCO3– dominance, 3) moderately saline waters (26%) with a mixed facies. The binary ion diagrams used suggest that the main hydrochemical processes are: evaporites dissolution and/or precipitation, accompanied by an exchange and/or reverse exchange of ions. Additionally, another process was detected in the northeastern part of the area; the saline intrusion of Sabkha waters, favoured by intensive aquifer exploitation.

Statistical moments have been used in different applications as in shape analysis of object, pattern recognition, edge detection texture analysis etc. The idea is to use the moments as features of high level for surface matching. The essential goal of surface matching is to determine transformation parameters between two surfaces generated in TIN or DEM without identical points. Statistical moments are considered as features that are applied to solve that goal, One of the main problems with using statistical moments for surface matching and for other applications is a very expensive computation time. To overcome this difficulty many algorithms have already been proposed. New approach of efficient computation of inertial moments for surface matching is proposed in the paper. The approach is based on Green's theorem that allows for transforming double integral into a line integral. In the consequence computation time of inertial moments of a single TIN-model (triangle) is reduced by a factor 4 as compared with time consumed by the use of direct method of double integral. The direct computation using line integral, that does not involve any approximation, ensures preservation of the accuracy of computed moments.

The paper presents estimation of positional accuracy of digital maps using statistical analysis. Investigations have been performed for four large-scale digital maps made using different methods of producing digital map data: new total station survey (object A), re-calculation of previous direct measurements (orthogonal and polar surveys) (object B), manual vectorisation of a raster orthophotomap image (object C) and graphical-and-digital processing of analogue maps (object D). Analysis has been performed for large statistical samples of sets of vectors of shift t: L of control points and their components, i.e. true errors t: x, t: r of increments of co-ordinates. In the case of a map produced by means of new survey with an electronic tacheometer, the true errors were represented by differences between co-ordinates of control points obtained from two separate set outs. In the case of other methods of data collection for digital map production true errors were represented by differences of co-ordinates acquired from an investigated map and co-ordinates calculated from new direct surveys.

This paper presents the results of a metrological analysis of the additively manufactured (AM) copies of a complex geometrical object, namely the fossil skull of Madygenerpeton pustulatum. This fossil represents the unique remains of an extinct “reptiliomorph amphibian” of high importance for palaeontological science. For this research, the surface was scanned and twelve different copies were 3D-printed using various devices, materials, and AM techniques. The same digitized model was used as a reference to compare with the surfaces obtained by Mitutoyo Coordinate Measuring Machine (CMM) CRYSTA-Apex S 9166 for each copy. The fidelity of the copies was assessed through statistical analysis of the distances between compared surfaces. The methodology provided a good background for the choice of the most accurate copies and the elimination of the less accurate ones. The proposed approach can be applied to any object of complex geometry when reproduction accuracy is to be assessed.

The paper evaluates the relationship between the selection of the probability density function and the construction price, and the price of the building's life cycle, in relation to the deterministic cost estimate in terms of the minimum, mean, and maximum. The deterministic cost estimates were made based on the minimum, mean, and maximum prices: labor rates, indirect costs, profit, and the cost of equipment and materials. The net construction prices received were given different probability density distributions based on the minimum, mean, and maximum values. Twelve kinds of probability distributions were used: triangular, normal, lognormal, beta pert, gamma, beta, exponential, Laplace, Cauchy, Gumbel, Rayleigh, and uniform. The results of calculations with the event probability from 5 to 95% were subjected to the statistical comparative analysis. The dependencies between the results of calculations were determined, for which different probability density distributions of price factors were assumed. A certain price level was assigned to specific distributions in 6 groups based on the t-test. It was shown that each of the distributions analyzed is suitable for use, however, it has consequences in the form of a final result. The lowest final price is obtained using the gamma distribution, the highest is obtained by the beta distribution, beta pert, normal, and uniform.

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.

We describe the spatial variability of snow accumulation on three selected glaciers in Spitsbergen (Hansbreen, Werenskioldbreen and Aavatsmarkbreen) in the winter seasons of 1988/89, 1998/99 and 2001/2002 respectively. The distribution of snow cover is determined by the interrelationships between the direction of the glacier axes and the dominant easterly winds. The snow distribution is regular on the glaciers located E-W, but is more complicated on the glaciers located meridionally. The western part of glaciers is more predisposed to the snow accumulation than the eastern. This is due to snowdrift intensity. Statistical relationships between snow accumulation, deviation of accumulation from the mean values and accumulation variability related to topographic parameters such as: altitude, slope inclination, aspect, slope curvature and distance from the edge of the glacier have been determined. The only significant relations occured between snow accumulation and altitude (r = 0.64-0.91).

The problem of estimation of the long-term environmental noise hazard indicators and their uncertainty is presented in the present paper. The type A standard uncertainty is defined by the standard deviation of the mean. The rules given in the ISO/IEC Guide 98 are used in the calculations. It is usually determined by means of the classic variance estimators, under the following assumptions: the normality of measurements results, adequate sample size, lack of correlation between elements of the sample and observation equivalence. However, such assumptions in relation to the acoustic measurements are rather questionable. This is the reason why the authors indicated the necessity of implementation of non-classical statistical solutions. An estimation idea of seeking density function of long-term noise indicators distribution by the kernel density estimation, bootstrap method and Bayesian inference have been formulated. These methods do not generate limitations for form and properties of analyzed statistics. The theoretical basis of the proposed methods is presented in this paper as well as an example of calculation process of expected value and variance of long-term noise indicators LDEN and LN. The illustration of indicated solutions and their usefulness analysis were constant due to monitoring results of traffic noise recorded in Cracow, Poland.

A non-classical model of interval estimation based on the kernel density estimator is presented in this paper. This model has been compared with interval estimation algorithms of the classical (parametric) statistics assuming that the standard deviation of the population is either known or unknown. The non-classical model does not have to assume belonging of random sample to a normal distribution. A theoretical basis of the proposed model is presented as well as an example of calculation process which makes possible determining confidence intervals of the expected value of long-term noise indicators Aden and LN. The statistical analysis was carried out for 95% interval widths obtained by using each of these models. The inference of their usefulness was performed on the basis of results of non-parametric statistical tests at significance level α = 0.05. The data used to illustrate the proposed solutions and carry out the analysis were results of continuous monitoring of traffic noise recorded in 2004 in one of the main arteries of Krakow in Poland.

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.

The article deals with issues related to the application of statistical methods used in the valuation process. The proposed algorithm for real estate valuation can be used in the statistical market analysis method in the process of mass appraisal. The algorithm uses a multiple linear regression model. Legal considerations indicate the need for such an algorithm for the determination of the value of representative properties. Due to the large size of the database of comparables, the proposed algorithm can be used only to appraise typical properties. A good statistical model is parsimonious, that is, it uses as few mathematical concepts as possible in a given situation. A model should extract what is systematic in the results observed, allowing for the presence of purely random deviations. The article discusses the basic principles of building a good statistical model. Attention is drawn to the number of market attributes that are entered into the model and the range of their values. As few explanatory variables as possible should be entered into the model to explain the phenomenon under study. Explanatory variables are only those characteristics of the property that differentiate prices in a given market defined and adopted by the appraiser as the basis for valuation. The article highlights the importance of taking into account market changes during the period under study.

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.