Calculation of Weibull Distribution parameters at low wind speed and performance analysis

In this study, the compatibility of the real wind energy potential to the estimated wind energy potential by Weibull Distribution Function (WDF) of a region with low average wind speed potential was examined. The main purpose of this study is to examine the performance of six different methods used to find the coefficients of the WDF and to determine the best performing method for selected region. In this study seven-year hourly wind speed data obtained from the general directorate of meteorology of this region was used. The root mean square error (RMSE) statistical indicator was used to compare the efficiency of all used methods. Another main purpose of this study is to observe the how the performance of the used methods changes over the years. The obtained results showed that the performances of the used methods showed slight changes over the years, but when evaluated in general, it was observed that all method showed acceptable performance. Based on the obtained results, when the seven-year data is evaluated in this selected region, it can be said that the MM method shows the best performance.

From ex situ simulation to in situ simulation in the "Comprehensive educational program to reduce infant mortality in the Khabarovsk Territory"

Infant mortality is an important statistical indicator, and at the same time an indirect criterion of the economic, social and political component of the state. The experience of conducting simulation training "in situ" within the framework of the "Comprehensive educational program to reduce infant mortality in the Khabarovsk Territory" is presented.

Housing-Price Prediction in Colombia using Machine Learning

It is a common practice to price a house without proper evaluation studies being performed for assurance. That is why the purpose of this study provide an explanatory model by establishing parameters for accuracy in interpretation and projection of housing prices. In addition, it is intentioned to establish proper data preprocessing practices in order to increase the accuracy of machine learning algorithms. Indeed, according to our literature review, there are few articles and reports on the use of Machine Learning tools for the prediction of property prices in Colombia. The dataset in which the research is built upon was provided by an existing real estate company. It contains near 940,000 items (housing advertisements) posted on the platform from the year 2018 to 2020. The database was enriched using statistical imputation techniques. Housing prices prediction was performed using Decision Tree Regressors and LightGBM methods, thus deriving in better alternatives for house price prediction in Colombia. Moreover, to measure the accuracy of the proposed models, the Root Mean Squared Logarithmic Error (RMSLE) statistical indicator was used. The best cross validation results obtained were 0.25354±0.00699 for the LightGBM, 0.25296 ±0.00511 for the Bagging Regressor, and 0.25312±0.00559 for the ExtraTree Regressor with Bagging Regressor, and it was not found a statistical difference between their performances.

Local Correlation among the Chiral Condensate, Monopoles, and Color Magnetic Fields in Abelian Projected QCD

Using the lattice gauge field theory, we study the relation among the local chiral condensate, monopoles, and color magnetic fields in quantum chromodynamics (QCD). First, we investigate idealized Abelian gauge systems of (1) a static monopole–antimonopole pair and (2) a magnetic flux without monopoles, on a four-dimensional Euclidean lattice. In these systems, we calculate the local chiral condensate on quasi-massless fermions coupled to the Abelian gauge field, and find that the chiral condensate is localized in the vicinity of the magnetic field. Second, using SU(3) lattice QCD Monte Carlo calculations, we investigate Abelian projected QCD in the maximally Abelian gauge, and find clear correlation of distribution similarity among the local chiral condensate, monopoles, and color magnetic fields in the Abelianized gauge configuration. As a statistical indicator, we measure the correlation coefficient r, and find a strong positive correlation of r≃0.8 between the local chiral condensate and an Euclidean color-magnetic quantity F in Abelian projected QCD. The correlation is also investigated for the deconfined phase in thermal QCD. As an interesting conjecture, like magnetic catalysis, the chiral condensate is locally enhanced by the strong color-magnetic field around the monopoles in QCD.

Inquiring electromagnetic quantum fluctuations about the orientability of space

Orientability is an important global topological property of spacetime manifolds. It is often assumed that a test for spatial orientability requires a global journey across the whole 3-space to check for orientation-reversing paths. Since such a global expedition is not feasible, theoretical arguments that combine universality of physical experiments with local arrow of time, CP violation and CPT invariance are usually offered to support the choosing of time- and space-orientable spacetime manifolds. Another theoretical argument also offered to support this choice comes from the impossibility of having globally defined spinor fields on non-orientable spacetime manifolds. In this paper, we argue that it is possible to locally access spatial orientability of Minkowski empty spacetime through physical effects involving quantum vacuum electromagnetic fluctuations. We study the motions of a charged particle and a point electric dipole subject to these electromagnetic fluctuations in Minkowski spacetime with orientable and non-orientable spatial topologies. We derive analytic expressions for a statistical orientability indicator for both of these point-like particles in two inequivalent spatially flat topologies. For the charged particle, we show that it is possible to distinguish the orientable from the non-orientable topology by contrasting the time evolution of the orientability indicators. This result reveals that it is possible to access orientability through electromagnetic quantum vacuum fluctuations. However, the answer to the central question of the paper, namely how to locally probe the orientability of Minkowski 3-space intrinsically, comes about only in the study of the motions of an electric dipole. For this point-like particle, we find that a characteristic inversion pattern exhibited by the curves of the orientability statistical indicator is a signature of non-orientability. This result makes it clear that it is possible to locally unveil spatial non-orientability through the inversion pattern of curves of our orientability indicator for a point electric dipole under quantum vacuum electromagnetic fluctuations. Our findings might open the way to a conceivable experiment involving quantum vacuum electromagnetic fluctuations to locally probe the spatial orientability of Minkowski empty spacetime.

Development of a method for improving stability method of applying digital watermarks to digital images

A technique for increasing the stability of methods for applying digital watermark into digital images is presented. A technique for increasing the stability of methods for applying digital watermarks into digital images, based on pseudo-holographic coding and additional filtering of a digital watermark, has been developed. The technique described in this work using pseudo-holographic coding of digital watermarks is effective for all types of attacks that were considered, except for image rotation. The paper presents a statistical indicator for assessing the stability of methods for applying digital watermarks. The indicator makes it possible to comprehensively assess the resistance of the method to a certain number of attacks. An experimental study was carried out according to the proposed method. This technique is most effective when part of the image is lost. When pre-filtering a digital watermark, the most effective is the third filtering method, which is averaging over a cell with subsequent binarization. The least efficient is the first method, which is binarization and finding the statistical mode over the cell. For an affine type attack, which is an image rotation, this technique is effective only when the rotation is compensated. To estimate the rotation angle, an affine transformation matrix is found, which is obtained from a consistent set of corresponding ORB-descriptors. Using this method allows to accurately extract a digital watermark for the entire range of angles. A comprehensive assessment of the methodology for increasing the stability of the method of applying a digital watermark based on Wavelet transforms has shown that this method is 20 % better at counteracting various types of attacks

INFORMATION AND ANALYTICAL SUPPORT OF LOGISTICS MARKET RESEARCH

Introduction. Logistics as a type of economic activity plays one of the main roles in the formation and development of market relations, so its study is especially relevant in a market economy. Information resources are one of the most important subsystems of the resource potential of the firm, and information is a key element of logistics operations. The information specifies the needs of the objects of logistics systems and supply chain links. The article investigates that logistics is one of the important components of the state economy and now this component is at the stage of its formation and requires a scientific approach to study; the place of the information and analytical center as an infrastructural component of logistics systems is determined; the information and analytical support of the market research of logistics services is substantiated and the system of statistical indicators of the research of this market is formed. It is determined that the prospects for the development of the logistics services market in Ukraine directly depend on the state of the country's economy. Methods. The following scientific methods were used in the research process: inductions and deductions - in the process of studying the general tendencies of logistics development in Ukraine; analysis and synthesis - during the theoretical generalizations, the formation of appropriate conclusions; bibliographic - research of literary sources to obtain the necessary information on the research topic; method of associations and analogies - for the proposed new ideas and suggestions that arise from comparison with other more or less similar objects. Results. Logistics in Ukraine is developing in accordance with world trends, has a significant impact on the economic potential of the country, stimulates the development of related, interconnected and complementary industries, is a reflection of the competitiveness of our country in the world. Logistics efficiency is now at the forefront of the agenda for professionals, private firms, and international organizations. Thus, the logistics of information flow is relevant in the field of logistics. Information resources are one of the most important subsystems of the resource potential of the firm, and information is a key element of logistics operations. The current level of logistics development requires constant improvement and introduction of new information systems. Discussion. The main task set during the writing of the article is to substantiate the feasibility of using logistics services in Ukraine, taking into account the peculiarities of business globalization. Keywords: logistics, segment, logistics market, data sources, information and analytical support, logistics services market, statistical indicator.

Wind Shear Prediction from Light Detection and Ranging Data Using Machine Learning Methods

The main aim of this paper is to propose a statistical indicator for wind shear prediction from Light Detection and Ranging (LIDAR) observational data. Accurate warning signal of wind shear is particularly important for aviation safety. The main challenges are that wind shear may result from a sustained change of the headwind and the possible velocity of wind shear may have a wide range. Traditionally, aviation models based on terrain-induced setting are used to detect wind shear phenomena. Different from traditional methods, we study a statistical indicator which is used to measure the variation of headwinds from multiple headwind profiles. Because the indicator value is nonnegative, a decision rule based on one-side normal distribution is employed to distinguish wind shear cases and non-wind shear cases. Experimental results based on real data sets obtained at Hong Kong International Airport runway are presented to demonstrate that the proposed indicator is quite effective. The prediction performance of the proposed method is better than that by the supervised learning methods (LDA, KNN, SVM, and logistic regression). This model would also provide more accurate warnings of wind shear for pilots and improve the performance of Wind shear and Turbulence Warning System.

The 3D Neural Network for Improving Radar-Rainfall Estimation in Monsoon Climate

The reflectivity (Z)—rain rate (R) model has not been tested on single polarization radar for estimating monsoon rainfall in Southeast Asia, despite its widespread use for estimating heterogeneous rainfall. The artificial neural network (ANN) regression has been applied to the radar reflectivity data to estimate monsoon rainfall using parametric Z-R models. The 10-min reflectivity data recorded in Kota Bahru radar station (in Malaysia) and hourly rain record in nearby 58 gauge stations during 2013–2015 were used. The three-dimensional nearest neighbor interpolation with altitude correction was applied for pixel matching. The non-linear Levenberg Marquardt (LM) regression, integrated with ANN regression minimized the spatiotemporal variability of the proposed Z-R model. Results showed an improvement in the statistical indicator, when LM and ANN overestimated (6.6%) and underestimated (4.4%), respectively, the mean total rainfall. For all rainfall categories, the ANN model has a positive efficiency ratio of >0.2.

Structural-semantic analysis of the English metaphors in road, aviation, and maritime terminology

The goal of this article consists in the analysis of metaphors pertaining to transport in the English language on the example of road, aviation, and maritime terminology. According to the authors, metaphor is the use of words and phrases in a figurative sense based on similarity or analogy. It is established that transport terminology contains a wide variety of terms that are formed with the use of metaphors. The subject of this research is metaphors in the scientific-technical text. The object is metaphors in transport terminology. The relevance of this article is substantiated by the fact that despite sufficient coverage of private terminological systems of specific types of transport, there are very few comprehensive and comparative works. In the course of research, the author determines a new statistical indicator – the index of metaphoricity of terminological system, as well as describes the key semantic and structural peculiarities of the terms-metaphors of different branches of transport. The analysis of language material allows determining that most of the terms formed with the use of metaphors are attributed to metaphors based on associations with the elements of human body and animal kingdom. From structural perspective, it is established that terminological combinations are widely represented among the terms-metaphors of all terminological systems that were subjected to analysis, while simple terms – in the terminological systems of road and aviation transport.