An information technique for segmentation of military assets in conditions of uncertainty of initial data

To solve the applied task of detecting military assets in aerospace images the presented paper investigates the processes of constructing segmented maps of the images. The goal is to develop an information technique for detecting military assets in conditions of uncertainty of initial data. To achieve the goal, the following tasks were formulated: 1) to analyze usability of the existing segmentation methods for automatic detection of military assets in the images; 2) if the existing methods are inapplicable, to develop a new algorithm to solve the problem. In the paper the following methods are used: the methods of digital image processing, the methods of Boolean algebra and fuzzy sets, the methods of statistical analysis. The following results are received. Analysis of the known segmentation methods showed that due to camouflage coloring of the military assets, similarity of their color characteristics to those of underlying surfaces and due to the presence of large number of textured fragments in the images those methods provide segmented maps of poor quality. Among the common problems arising when conventional methods are used there are wrong segmentation, when the received contours do not coincide with the borders of the objects of interest; oversegmentation, when there are a lot of minor segments which produce "litter" objects; undersegmentation, when potentially possible segments are missed etc. As the conventional methods are inapplicable, in the paper it is suggested using the fuzzy logic systems. For each pixel the probability of the fact that the pixel belongs to the object or to the background is calculated. For making decision whether a pixel belongs to the object the production rules based on the chosen most significant factors (probabilistic values of spectral sub-bands, belonging of the neighboring pixels to the object, jumps of brightness in spectral sub-bands on the object's borders) are constructed. Conclusion. The suggested technique ensures high-quality definition of objects' borders, thus considerably increasing the reliability of military assets recognition.

OPTIMIZATION OF THE LENGTH OF THE TOWING CABLE IN THE OPERATIONAL MAGNETOMETRIC SEARCH OF UNDERWATER OBJECTS

One of the features of the creation of a new generation of marine magnetometry means is the requirement to increase the efficiency of the search for emergency underwater objects due to a reasonable reduction in the length of the magnetometer towing cable, which ensures a decrease in the length of the search tack. Traditionally, the length of the cablerope of a towed magnetometer is determined taking into account its sensitivity, as well as the magnetic characteristics of the vessel-tug and underwater object. At the same time, the stochastic nature of the search process is ignored, caused by random factors (the uncertain spatial position of the underwater object in the search strip, as well as the orientation noise of the measuring platform). A new approach to the algorithm for processing the statistical information of the magnetometric signals of the underwater object and the towing vehicle in the search bar makes it possible to determine the optimal length of the towing cable. In this case, the problem of minimizing the objective function of the dependence of two alternatives is solved: on the one hand, a decrease in the towing noise as the tow cable length increases, on the other, an increase in the orientation noise caused by the spatio-temporal oscillations of the magnetometer. In addition, the evaluation of the selection of the signal of the underwater object against the background of the towing vehicle interference in terms of the "statistical discrepancy of alternative hypotheses" – the Kullback divergence, makes it possible to optimize the length of the cable-rope with the given probabilistic values of the detection of the underwater object.

Probabilistic Prediction of Multi-Wells Production Based on Production Characteristics Analysis Using Key Factors in Shale Formations

In this study, we propose a novel workflow to predict the production of existing and new multi-wells. To perform reliable production forecasting on heterogeneous shale formations, the features of these formations must be analyzed by classifying the formations into various groups; the groups have different production characteristics depending on the key factors that affect the shale formation. In addition, the limited data obtained from nearby existing multi-wells should be used to estimate the production of new wells. The key factors that affect shale formation were derived from the correlation and principal component analysis of available production-related attributes. The production of existing wells was estimated by classifying them into groups based on their production characteristics. These classified groups also identified the relationship between hydraulic fracturing design factors and productivity. To estimate the production of new wells (blind wells), we generated groups with different production characteristics and leveraged their features to estimate the production. Probabilistic values of the group features were entered into the input layer of the artificial neural network model to consider the variation in the production of shale formations. All the estimated productions exhibited less error than the previous analytical results, suggesting the utilization potential of the proposed workflow.

Extended GRA Method Based on Cumulative Prospect Theory with Probabilistic Hesitant Fuzzy Information for MAGDM and its Application to Green Supplier Selection

An extended grey relational analysis (GRA) method is introduced in this article to reduce the limitations of the classical GRA method using the cumulative prospect theory (CPT) which takes into account psychological factors such as the risk appetite of decision makers. Moreover, the circumstance of probabilistic hesitant fuzzy (PHF) which assigns probabilistic values to DMs’ different levels of hesitation shows its superiority when making decisions in a complex environment. Meanwhile the weighting vector of each attribute is calculated according to the entropy which is calculated by the different prospect decision elements. Thus, in this paper, we proposed an extended GRA method based on cumulative prospect theory in the probabilistic hesitant fuzzy circumstance and applying the model in the selection of the green supplier. At last, the comparative analysis and the simulation analysis are made to show the practicability of this newly proposed method.

Haplotype network branch diversity, a new metric combining genetic and topological diversity to compare the complexity of haplotype networks

A common way of illustrating phylogeographic results is through the use of haplotype networks. While these networks help to visualize relationships between individuals, populations, and species, evolutionary studies often only quantitatively analyze genetic diversity among haplotypes and ignore other network properties. Here, we present a new metric, haplotype network branch diversity (HBd), as an easy way to quantifiably compare haplotype network complexity. Our metric builds off the logic of combining genetic and topological diversity to estimate complexity previously used by the published metric haplotype network diversity (HNd). However, unlike HNd which uses a combination of network features to produce complexity values that cannot be defined in probabilistic terms, thereby obscuring the values’ implication for a sampled population, HBd uses frequencies of haplotype classes to incorporate topological information of networks, keeping the focus on the population and providing easy-to-interpret probabilistic values for randomly sampled individuals. The goal of this study is to introduce this more intuitive metric and provide an R script that allows researchers to calculate diversity and complexity indices from haplotype networks. A group of datasets, generated manually (model dataset) and based on published data (empirical dataset), were used to illustrate the behavior of HBd and both of its terms, haplotype diversity, and a new index called branch diversity. Results followed a predicted trend in both model and empirical datasets, from low metric values in simple networks to high values in complex networks. In short, the new combined metric joins genetic and topological diversity of haplotype networks, into a single complexity value. Based on our analysis, we recommend the use of HBd, as it makes direct comparisons of network complexity straightforward and provides probabilistic values that can readily discriminate situations that are difficult to resolve with available metrics.

Fragility Curve Analysis of Medium Cable Stayed Bridge

The seismic performance of a bridge can be shown by analyzing the vulnerability of the structure in resisting an earthquake motion and then developing into fragility curves. This study presents a convenient method to establish the fragility curve for the cable-stayed bridge. For this purpose, three spans cable-stayed bridge is assessed using a series of seismic loads in different intensities to ensure that the structure was experiencing damage in several conditions. The fragility curve was obtained by analyzing the structure using Nonlinear Time History (NTHA) and Pushover Analysis. The ground motions of the earthquake were subjected to the bridge in different intensities, which were scaled from the initial ground motion. Hereafter, the structure’s ductilities were developed into the fragility curves as the responses of the bridge. HAZUS standard is used for classifying the damages of the bridge, which are grouped into; slight, moderate, extensive, and complete due to the seismic load. The values of the damage states were generated to the fragility curves using the probabilistic values of the damage states. To ensure the validity of the data statistically, Kolmogorov-Smirnov test was conducted to the fragility function. The result revealed that the fragility curve was qualified as the lognormal distribution.

Oil and gas potential of the deep-lying Jurassic and pre‑Jurassic deposits of the North of Western Siberia in unconventional traps

In-depth additional studies were carried out to assess oil and gas potential of deep-lying Jurassic and pre-Jurassic deposits of the northern territories of Western Siberia. As in previous work, the geological and mathematical program “Vybor” was used. Based on the first constructed series of model maps with probabilistic values of informative geochemical and geological parameters, the most promising both local and regional objects were selected. Increasing complexity of the traps structure with depth was noted. As a rule, from the Cretaceous deposits to the Jurassic and Paleozoic, the type of trap from the predominant anticline (in the Cretaceous) changes to a much more complex combined one, which requires special approaches (and new technologies) to identify and explore such objects. Studies based mainly on seismic data indicate rather high oil and gas content of both the Paleozoic and Triassic deposits, which have a platform occurence and large thicknesses, as well as crystalline basement formations. In this regard, unconventional combined traps of deep-lying deposits of the North of Western Siberia are of significant interest in terms of incremental oil and gas resources and reserves.

Possible changes of the isotopic composition of ice wedge as a result of self-diffusion

  The subject of this research is the assessment of changes of the isotopic composition of ice wedge as a result of self-diffusion. The author offers a relatively simple method of considering the impact of the process of self-diffusion upon redistribution of paleo-isotopic composition that allows accurately and quickly estimating the changes in the values δ18О and δ2H values in ice wedges at different periods of the quaternary (1000 years, 10,000 years, 100,000 years, and 1,000,000 years). The patterns of diffusion process in physico-chemical systems are described by two differential forms of Fick's diffusion laws, which are transformed into Gaussian integral, using six-digit Chambers charts for calculation of the threshold values δ18О. The article applies the experimentally determined real values of self-diffusion coefficient in the ice – D=(2–10)×10-15 m2/s. The values of the Gaussian integral are calculated for time intervals, at different distances between samples with different concentration; for the period of 1,000 years its values in all cases exceed 0.99. For longer time intervals, these values change significantly. The calculated probabilistic values of changes in the concentration of heavy oxygen isotopes in ice wedge under the impact of self-diffusion at different distances and concentration gradients are noticeable only for the time period of over 100,000 years.  

KEY ASPECTS OF USING NUMERICAL METHODS IN THE MECHANISM OF INVESTMENT OF SMALL AND MEDIUM-SIZED BUSINESS ENTERPRISES

In today's realities of investment activities, small and medium enterprises are faced with the dilemma of choosing areas of investment of monetary and non-monetary resources. Determining the feasibility of a particular investment is based on the use of appropriate mathematical apparatus and economic-mathematical models. The article considers some of the most important aspects of the use of numerical methods in the mechanism of investment of small and medium enterprises, developed on the basis of research on the development of such economic entities. The logical basis of the proposed methods is a proven division of the term of operation of enterprises into several stages of the life cycle, which differ significantly in the characteristics of incoming and outgoing cash flows. It is proposed to determine the absolute expediency of founding small and medium enterprises by calculating the probabilistic values of profitability of the enterprise based on the calculation of the area of geometric shapes limited by the functions of income and expenses during all stages of the life cycle. It is proved that such calculations are expedient by calculating the indefinite integral and applying the Newton-Leibniz formula.With regard to the functions that characterize the income and expenses of small and medium enterprises throughout their existence, the article proves that the most optimal in this case is the use of production functions. Among the whole set of existing production functions, we have identified the most optimal for the task Cobb-Douglas production function, CES production function, Linear production function, Leontief production function, adapted to the conditions of the microlevel. To calculate the elementary areas limited by the corresponding production functions, the article examines the relevant existing methods. Studies have been conducted on the possibility of using to calculate the areas limited by the production functions of income and expenses of small and medium enterprises during each stage of the life cycle, the methods of rectangles, trapezoids and parabolas. It is determined that they have limited conditions for use due to the need to divide the time period of operation of enterprises at intervals that do not coincide with the stages of the life cycle. Therefore, studies were continued, as a result of which it was proved that the most optimal method of calculating the elementary areas limited by the target functions of income and expenditure of small and medium enterprises is the Gaussian method with different variations.