The Perception of Market and Economic Risks by Owners and Managers of Enterprises in the V4 Countries

The aim of the paper is to assess the impact of the length of entrepreneurship on the perception of the most important business risks in Slovakia and the Visegrad Group of Countries (V4 countries). The empirical research was conducted in 2019-2020. It was focused on assessing the state of enterprise risk management (ERM) application. The research file contained 422 online questionnaires completed by owners and managers of enterprises (OMEs). The results of this case study were compared with the results of similar studies performed in the V4 countries in 2017-2018. In total, 1,781 OMEs participated in the surveys mentioned. The following statistical methods were used to assess the data: ANOVA, Bartlett’s test, Agostini test, good fit test, and Grubbs test. The overall results of the empirical research highlight the significance and importance of the assessment of business risks in the V4 countries. The results in Slovakia in 2019-2020 and the research results in the V4 countries in 2017-2018 show that OMEs still consider market and economic risks to be most important in their business. Market and economic risks are related to sources that exert the most negative influence on enterprise success. The results are valuable for entrepreneurs, enterprise managers and institutions that provide comprehensive entrepreneurship support in the V4 countries. The overall results are significant at the regional, national, and international levels of the V4 countries and have the ability to strengthen the competitiveness of entrepreneurs within the EU common market.

Detection of Outlier Observations in Piezometric Measurements: A Case Study in the Southern Region of Poland

One of the main modes of monitoring the geotechnical conditions of earth dams is piezometric measurement, which measures water levels in an open piezometer or water pressure in a closed piezometer. During piezometric measurements, various types of factors can cause disturbances in these measurements that take the form of systematic, accidental, or obvious mistakes. Before measurements from open or closed piezometers are analyzed, outliers due to coarse errors should be detected and rejected. Such observations may significantly influence the result of the analysis and cause erroneous assessment and interpretation of the phenomenon studied. To do this, statistical tests must be applied so that the doubtful measurement can be accepted or rejected at the assumed significance level. This paper uses five statistical tests for identifying and rejecting outliers: the Q-Dixon test, the Grubbs test, as well as the Hampel test, the Iglewicz and Hoaglin test, and the Rosner test. The aim of this article is to try to identify the most suitable test for periodic piezometric measurements. The scope of the study includes the analysis of piezometric measurements for the Czaniec Dam for the multi-year period 2017–2020.

Accurate Guidance Method and App Development for Assigning Parking Spaces Based on Indoor Wi-Fi

Existing parking guidance systems only provide road guidance outside the parking lot but do not provide accurate guidance to specific parking spaces inside the parking lot. By using a Kalman filter, the Grubbs test, and a neural network algorithm to improve the RSSI-based location fingerprint identification technology, an accurate location method based on indoor Wi-Fi is obtained, which implements precise route guidance and a reverse search function for parking spaces. We utilize Beidou positioning to develop a Gaode map for outdoor navigation and use an integrated system of ultrasonic detector/indicators and ground locks to manage parking spaces. Through the secondary development of an Android system and the application of a MySql database, an app for precise parking guidance was developed. The system makes full use of the Internet and parking information, eliminates information asymmetry, improves the utilization ratio of the urban static traffic resources, allocates parking spaces in real-time, breaks information islands, provides parking search and recommendation functions for users, achieves parking information-sharing, and effectively improves parking efficiency and the parking utilization ratio.

An Integrated Statistical-Graphical Approach for the Appraisal of the Natural Background Levels of Major Ions and Some Potentially Toxic Elements in the Groundwater of Urmia Aquifer, Iran

In this study, we attempted to calculate the Natural Background Level (NBL) for 19 selected chemical compounds in the Urmia aquifer, northwestern Iran. In this study, combined methods including pre-selection and statistical methods for determining NBL have been used. In the pre-selection method, the concentration of nitrate (NO3 ≥ 19.97 ppm) and chloride (Cl ≥ 200 ppm) were used as the main criteria to identify and eliminate samples affected by human activities. The selected concentration of nitrate is determined using the comparison of the results of various statistical and graphical evaluations including Quantile-Quantile plot (Q-Q plot), Box & Whisker plot (BW), Box & Whisker plot Iterative (BWI), Grubbs test, Mean and standard deviation (mean ± 2σ) (MSD), and median absolute deviation (MAD). After identifying the final data set, the NBL of the selected chemical compounds was calculated by two techniques including the Iterative 2σ technique (2σ) and calculated distribution function (CDF). Due to higher concentration relative to the reference values (REF), this study has focused on the calculation of NBL of SO4, F, As, Fe and Mn. Results showed that the upper limit of NBL calculated for these variables is about 125 ppm, 1 ppm, 8.5 ppb, 570 ppb, 80 ppb, respectively. Given that no study has been conducted to determine the NBL of chemical compounds in groundwater in Iran, the results of this study can be a roadmap for decision-makers and researchers to better manage this aquifer and other water resources in this country with limited freshwater resources.

Modeling of neutron flux density anomalies in the automated system of «Shelter» Object’s nu-clear safety control.

Analysis of the dynamics of neutron flux density (NFD) from fuel-containing masses (FCM) in the «Shelter» Object shows the presence of values that exceed the average values for different observation periods. Identification of such values by the criterion of «anomaly / non-anomaly» will allow excluding uninformative events from the array of observations. Or, in the case of the anomaly confirmation, it will allow forming effective actions for decision-making in order to eliminate the consequences of such events. To solve the problem of detecting anomalous measurements, now there is utilized the theory of statistical solutions which is based on the use of parametric methods. The utilization of these methods requires a priori information about the nature of the distribution of the measured process and its parameters. In order to find an effec-tive solution to the problem of detecting and eliminating anomalous measurements, it is necessary to know the statistical characteristics of normal and anomalous components. This paper proposes statistical criteria for estimating anomalies in time series of NFD which have different approaches to the formation of observation intervals, power and reliability of anomaly detection. Depending on the type of distribution of the array of observations, a set of criteria is proposed. These criteria are most expedient to use when checking the anomaly of series levels for the exponential distribution, the Poisson and Weibull distribution. The capacity of the criteria has been evaluated depending on the sample size. The article defines the accuracy of determination of anomalies by criteria with the known values of the mean and dispersion in the studied sample. As the result, it is recommended to use the Grubbs test to study the anomaly of the sample levels with n>700, and the Dixon and Smolyak-Titarenko criteria for the samples with n<50. The utilization of optimal criteria depending on the characteristics of the studied samples will increase the mathematical significance of the obtained results and, as a result, will improve the quality of management decisions and nuclear safety on the «Shelter» Object as a whole.

Transcriptome dataset of human corneal endothelium based on ribosomal RNA-depleted RNA-Seq data

The corneal endothelium maintains corneal transparency; consequently, damage to this endothelium by a number of pathological conditions results in severe vision loss. Publicly available expression databases of human tissues are useful for investigating the pathogenesis of diseases and for developing new therapeutic modalities; however, databases for ocular tissues, and especially the corneal endothelium, are poor. Here, we have generated a transcriptome dataset from the ribosomal RNA-depleted total RNA from the corneal endothelium of eyes from seven Caucasians without ocular diseases. The results of principal component analysis and correlation coefficients (ranged from 0.87 to 0.96) suggested high homogeneity of our RNA-Seq dataset among the samples, as well as sufficient amount and quality. The expression profile of tissue-specific marker genes indicated only limited, if any, contamination by other layers of the cornea, while the Smirnov-Grubbs test confirmed the absence of outlier samples. The dataset presented here should be useful for investigating the function/dysfunction of the cornea, as well as for extended transcriptome analyses integrated with expression data for non-coding RNAs.

Environment Monitoring for Anomaly Detection System Using Smartphones

Currently, the popularity of smartphones with networking capabilities equipped with various sensors and the low cost of the Internet have opened up great opportunities for the use of smartphones for sensing systems. One of the most popular applications is the monitoring and the detection of anomalies in the environment. In this article, we propose to enhance classic road anomaly detection methods using the Grubbs test on a sliding window to make it adaptive to the local characteristics of the road. This allows more precision in the detection of potholes and also building algorithms that consume less resources on smartphones and adapt better to real conditions by applying statistical outlier tests on current threshold-based anomaly detection methods. We also include a clustering algorithm and a mean shift-based algorithm to aggregate reported anomalies on data to the server. Experiments and simulations allow us to confirm the effectiveness of the proposed methods.

Improve of Footwear Comfort Sensation with Material Packages and Knitted Fabrics

The main goal of this paper was to analyse the hygienic properties of textile packages used for the construction of shoe uppers. Distance fabrics with varied hygienic properties were the basis of these packages. The discomfort indexes, which describe changes in footwear microclimate, were calculated according to the moisture absorbance capacity and temperature changes in the immediate surrounding of the foot skin surface. The experiment was done for a group of grain leather uppers, where the Grubbs test (a = 0.05) gave positive information about the outliers, describing such parameters as the water vapour permeability and water vapour coefficient. The phase changes of the shoe microclimate were detected via temperature and relative humidity sensors during simulation of the shoes used via an elliptical trainer for a group of 7 men. Statistically significant differences between the packages’ upper – lining confirmed the possibility of monitoring the circulation of biophysical mediums inside a footwear volume. The appropriate choice of package materials could raise the comfort conditions for users. For certain material configurations the microclimate conditions described by the discomfort index were improved.

An Assessment of GCM Performance at a Regional Scale Using a Score-Based Method

A multicriteria score-based method was developed to assess the performances of 18 general circulation models (GCMs) in the study region from 1970 to 2005. The results indicate the following. (1) GCMs simulate temperature better than rainfall. The temporal and spatial distributions of simulated temperature performed well compared with those from the observations. In comparison to temperature, the spatial distribution of simulated precipitation performed poorly. Most of the GCMs underestimated temperature and overestimated precipitation. (2) The Grubbs test was used to detect anomalous moving changes in the rank score (RS) results; the inm-cm4 and ipsl-cm5b-lr models were rejected when simulating temperature, while the bnu-esm and canesm2 models performed poorly when simulating precipitation. (3) Adding or removing any criterion does not significantly influence the RS result, which indicates that the multicriteria score-based method is robust. The advantages of using multicriteria score-based method to assess GCMs performance were demonstrated, and this method also provides a more comprehensive assessment when compared with the single-criterion method. The multicriteria method could replace other criteria as the research requirements and could be easily extended to different study regions; the results could be used for better informed regional climate change impact analyses.