Circulation and Climate Variability in the Czech Republic between 1961 and 2020: A Comparison of Changes for Two “Normal” Periods

Thirty-year periods are treated in climatology as spans with relatively representative and stable climatic patterns, which can be used for calculating climate normals. Annual and seasonal series of circulation types were used to compare two 30-year sub-periods, 1961–1990 and 1991–2020, the second one being strongly influenced by recent global warming. This analysis was conducted according to the objective classification of circulation types and the climatic characteristics of sunshine duration, temperature, humidity, precipitation, and wind speed as calculated for the territory of the Czech Republic during the 1961–2020 period. For both sub-periods, their statistical characteristics were calculated, and the statistical significance of differences between them was evaluated. There was a statistically significant increase in the annual frequencies of anticyclonic circulation types and a significant decrease in cyclonic circulation types during 1991–2020 compared with 1961–1990. Generally, in both 30-year periods, significant differences in means, variability, characteristics of distribution, density functions, and linear trends appear for all climatic variables analysed except precipitation. This indicates that the recent 30-year “normal” period of 1991–2020, known to be influenced more by recent climate change, is by its climatic characteristics unrepresentative of the stable climatic patterns of previous 30-year periods.

Radar Imaging Statistics of Non-Gaussian Rough Surface: A Physics-Based Simulation Study

This paper investigates the radar image statistics of rough surfaces by simulating the scattered signal’s dependence on the surface roughness. Statistically, the roughness characteristics include the height probability density (HPD) and, to the second-order, the power spectral density (PSD). We simulated the radar backscattered signal by computing the far-field scattered field from the rough surface within the antenna beam volume in the context of synthetic aperture radar (SAR) imaging. To account for the non-Gaussian height distribution, we consider microscopic details of the roughness on comparable radar wavelength scales to include specularly, singly, and multiply scatterers. We introduce surface roughness index (RSI) to distinguish the statistical characteristics of rough surfaces with different height distributions. Results suggest that increasing the RMS height does not impact the Gaussian HPD surface but significantly affects the Weibull surface. The results confirm that as the radar frequency increases, or reaches a relatively larger roughness, the surface’s HPD causes significant changes in incoherent scattering due to more frequent multiple scattering contributions. As a result, the speckle move further away from the Rayleigh model. By examining individual RSI, we see that the Gaussian HPD surface is much less sensitive to RMS height than the Weibull HPD surface. We demonstrate that to retrieve the surface parameters (both dielectric and roughness) from the estimated RCS, less accuracy is expected for the non-Gaussian surface than the Gaussian surface under the same conditions. Therefore, results drawn from this study are helpful for system performance evaluations, parameters estimation, and target detection for SAR imaging of a rough surface.

Properties of the compressibility and transport motion in wall-bounded turbulent flows at Mach 8

The compressibility effect and transport motion in highspeed turbulent boundary layer (TBL) is a fundamental problem because they dominate the average and statistical characteristics. Using the statistical methods and flow visualization technology, flat-plate TBLs at [Formula: see text] with high- and low-wall temperatures, [Formula: see text] and 1.9, are investigated based on the direct numerical simulation (DNS) datasets. Compared with previous studies, this study considers relative higher Mach number and strong cold wall temperature condition at the same time. First, the turbulent Mach number and turbulent intensity show that the compressibility effects are enhanced by the cooling process. Second, the high-order statistical moments and structure parameters confirm cold wall that causes stronger compressibility and the corresponding increased intensities of local streamwise and wall-normal transport motions. Finally, for uncovering the relationship between the compressibility effect and turbulent transport, more in-depth visualization analyses of velocity streaks are performed. It is found that ‘knot-like’ structures are generated when cooling the wall, and they lead to stronger intermittent, which results in the rapid increase of local compressibility effect and the wall-normal transport motion. Our research sheds light on providing a theoretical basis for further understanding the compressibility effects of TBL at high Mach number.

Monte-Carlo simulation for moderate seismic zones using artificial accelerograms

The present technical note deals with a new method to generate seismic accelerograms based on statistical characteristics and the classification of seismic waves. A short heterogeneous sitebased analyse of these accelerograms is given with a seismic wave propagation code in 1D. After, a numerical simulation is done in order to obtain PGA using Newmark’s explicit scheme, and finally, Monte-Carlo simulation is used to determinate failure’s probability of structures localised in moderate seismic zones in hexagonal France.

Research on the Relationship Between Service Guarantee Perception and Customer Value in the Chinese Context

As an excellent management tool, service guarantee can improve the competitive advantage of enterprises and allow consumers to obtain high-quality products and services. However, in the current Chinese context, this tool has not played its proper function. One important reason is the perception deviation of Chinese consumers. This research analyzes the main reasons for this deviation, puts forward related hypotheses and research models, and discusses the influence of disposition to trust of contract, perceived structural assurance (PSA), and subjective norm on service guarantee perception (SGP). Also, this study discusses SGP of customers through perceived risk and quality. Through the verification of 574 sample data, the main conclusions are as follows: (1) Disposition to trust of contract, subjective norms, and PSA significantly affect SGP positively; (2) SGP positively affects customer value (CUV); and (3) SGP s are obviously different between people of different ages, education levels, and income levels. Hopefully, these conclusions can have the following enlightenment to enterprises serving Chinese consumers: (1) in the designing stage of service guarantee, perception of customers of this guarantee should be a consideration; (2) CUV can be a proper direction if an enterprise wish to lead the guarantee perception of the customer; (3) Not all products need the same level of service guarantee; and (4)The proper service guarantee level depends on various statistical characteristics of target customers of the service.

Efficient Approach towards Detection and Identification of Copy Move and Image Splicing Forgeries Using Mask R-CNN with MobileNet V1

With the technological advancements of the modern era, the easy availability of image editing tools has dramatically minimized the costs, expense, and expertise needed to exploit and perpetuate persuasive visual tampering. With the aid of reputable online platforms such as Facebook, Twitter, and Instagram, manipulated images are distributed worldwide. Users of online platforms may be unaware of the existence and spread of forged images. Such images have a significant impact on society and have the potential to mislead decision-making processes in areas like health care, sports, crime investigation, and so on. In addition, altered images can be used to propagate misleading information which interferes with democratic processes (e.g., elections and government legislation) and crisis situations (e.g., pandemics and natural disasters). Therefore, there is a pressing need for effective methods for the detection and identification of forgeries. Various techniques are currently employed for the identification and detection of these forgeries. Traditional techniques depend on handcrafted or shallow-learning features. In traditional techniques, selecting features from images can be a challenging task, as the researcher has to decide which features are important and which are not. Also, if the number of features to be extracted is quite large, feature extraction using these techniques can become time-consuming and tedious. Deep learning networks have recently shown remarkable performance in extracting complicated statistical characteristics from large input size data, and these techniques efficiently learn underlying hierarchical representations. However, the deep learning networks for handling these forgeries are expensive in terms of the high number of parameters, storage, and computational cost. This research work presents Mask R-CNN with MobileNet, a lightweight model, to detect and identify copy move and image splicing forgeries. We have performed a comparative analysis of the proposed work with ResNet-101 on seven different standard datasets. Our lightweight model outperforms on COVERAGE and MICCF2000 datasets for copy move and on COLUMBIA dataset for image splicing. This research work also provides a forged percentage score for a region in an image.

ВПЛИВ МЕХАНІЧНОЇ АКТИВАЦІЇ НА РОЗМІРНІ ХАРАКТЕРИСТИКИ ТА ФОРМУ ЧАСТИНОК ГЛИНОПОРОШКІВ РІЗНОГО ТИПУ

Purpose. Determination of the influence of the process of preliminary mechanical activation on the dimensional characteristics and shape of particles of different types of clay powders.Methodology. Clay powders of montmorillonite and palygorskite type were chosen as the objects of research in this work. The process of mechanical activation of clay powders was carried out using a laboratory ball mill. For microanalysis of sample particles, the method of optical polarizing microscopy was used. Morphometric analysis of clay powder particles was performed by image analysis using the ImageJ software. At the same time, the area and perimeter were determined, and the equivalent diameter and also the shape index of the particles of the samples were calculated. The experimental data were statistically processed using the Statistica and Excel software packages.Results. The paper investigates the effect of the process of mechanical activation on the dimensional characteristics and shape of particles of montmorillonite and palygorskite type clay powders. It was found that the decrease in the average values of the equivalent particle diameter in the process of mechanical action (~14–15%) is realized mainly due to the destruction of their largest aggregates. Moreover, the intensity of this process is noticeably higher for clay of the montmorillonite type. It is shown that for both studied samples, the process of mechanical activation leads to an increase in the average values of the particle shape index (~ by 9–10%) and an increase in the uniformity of their distribution by this index.Scientific novelty. Using a detailed morphometric analysis of particles of various types of clay powders, the regularities of the influence of the mechanical activation process on the quantitative statistical characteristics of their distribution over the equivalent diameter and shape index have been established.Practical value. The results obtained will make it possible to reasonably approach the choice of pretreatment methods for clay powders intended for the production of polymer filled nanocomposite materials.

Frequency Analysis of the Nonstationary Annual Runoff Series Using the Mechanism-Based Reconstruction Method

Due to climate change and human activities, the statistical characteristics of annual runoff series of many rivers around the world exhibit complex nonstationary changes, which seriously impact the frequency analysis of annual runoff and are thus becoming a hotspot of research. A variety of nonstationary frequency analysis methods has been proposed by many scholars, but their reliability and accuracy in practical application are still controversial. The recently proposed Mechanism-based Reconstruction (Me-RS) method is a method to deal with nonstationary changes in hydrological series, which solves the frequency analysis problem of the nonstationary hydrological series by transforming nonstationary series into stationary Me-RS series. Based on the Me-RS method, a calculation method of design annual runoff under the nonstationary conditions is proposed in this paper and applied to the Jialu River Basin (JRB) in northern Shaanxi, China. From the aspects of rationality and uncertainty, the calculated design value of annual runoff is analyzed and evaluated. Then, compared with the design values calculated by traditional frequency analysis method regardless of whether the sample series is stationary, the correctness of the Me-RS theory and its application reliability is demonstrated. The results show that calculation of design annual runoff based on the Me-RS method is not only scientific in theory, but also the obtained design values are relatively consistent with the characteristics of the river basin, and the uncertainty is obviously smaller. Therefore, the Me-RS provides an effective tool for annual runoff frequency analysis under nonstationary conditions.

Detection of Multi-pixel Low Contrast Object on a Real Sea Surface

The video images captured at long range usually have low contrast floating objects of interest on a sea surface. A comparative experimental study of the statistical characteristics of reflections from floating objects and from the agitated sea surface showed the difference in the correlation and spectral characteristics of these reflections. The functioning of the recently proposed modified matched subspace detector (MMSD) is based on the separation of the observed data spectrum on two subspaces: relatively low and relatively high frequencies. In the literature the MMSD performance has been evaluated in generally and moreover using only a sea model (additive Gaussian background clutter). This paper extends the performance evaluating methodology for low contrast object detection and moreover using only the real sea dataset. This methodology assumes an object of low contrast if the mean and variance of the object and the surrounding background are the same. The paper assumes that the energy spectrum of the object and the sea are different. The paper investigates a scenario in which an artificially created model of a floating object with specified statistical parameters is placed on the surface of a real sea image. The paper compares the efficiency of the classical Matched Subspace Detector (MSD) and MMSD for detecting low-contrast objects on the sea surface. The article analyzes the dependence of the detection probability at a fixed false alarm probability on the difference between the statistical means and variances of a floating object and the surrounding sea.