Experimental Methodology to Find the Center of Gravity of a Solid

The center of gravity of a three-dimensional object found through an experimental method can be made easier and faster than when calculating the movement manually in order to make the movement in computer graphic images look more natural. In addition, in various sports such as skating, the score can be increased by appropriately moving the position of the center of gravity. Lastly, it is expected that it can be used even when the performance is high in the manufacturing process to increase the stability and speed of various means of transportation (eg, automobiles, airplanes, etc.).

Deep Learning Based Classification of Time Series of Chaotic Systems over Graphic Images

In this study, for the first time in the literature, identification of different chaotic systems by classifying graphic images of their time series with deep learning methods is aimed. For this purpose, a data set is generated that consists of the graphic images of time series of the most known three chaotic systems: Lorenz, Chen, and Rossler systems. The time series are obtained for different parameter values, initial conditions, step size and time lengths. After generating the data set, a high-accuracy classification is performed by using transfer learning method. In the study, the most accepted deep learning models of the transfer learning methods are employed. These models are SqueezeNet, VGG-19, AlexNet, ResNet50, ResNet101, DenseNet201, ShuffleNet and GoogLeNet. As a result of the study, classification accuracy is found between 96% and 97% depending on the problem. Thus, this study makes association of real time random signals with a mathematical system possible.

Transdisciplinary convergent approach - human factor

The article is devoted to the systemic problems of the study of the human factor, which are associated with the cognitive aspects of human-computer interaction. The rapid development of mathematical modeling has created systemic problems of safety, control and forecasting of the functioning of dynamic transport systems in difficult conditions. The accumulation of latent contradictions and interdisciplinary conflict are the main reasons for the systemic complexity of the problems of education and science, which have increased the importance of the human factor. The main goal of the work is to further develop a convergent approach to studying the problems of the safety of the human factor on a transdisciplinary basis. The key reason for systemic security problems and the manifestation of the human factor is self-organized criticality, the manifestation of which in information transmission lines causes nonlinearity and instability of fractal signals of various natures. The work establishes a connection between the transitional functional states of a person with the individuality of his cognitive activity. A toolkit for identifying induced spatial and temporal inhomogeneities of information transmission media, which generate hidden spatio-temporal relationships at different scale levels, is proposed. These interconnections are determined by the individuality of the cognitive graphic images of fractal and multifractal signals of various natures. The creation of a knowledge base of cognitive graphic images of the dynamic structure of fractal and multifractal signals of various nature will allow finding solutions not yet available to the brain and computer separately. The application of the transdisciplinary convergent approach and tools based on it to electrophysiological signals of a human operator demonstrates advantages and new possibilities. In particular, revealing hidden spatio-temporal relationships that determine the manifestation of human factor in difficult conditions. The innovative potential of the convergent approach to training and forecasting activities of operators (pilot, dispatcher, etc.) is being discussed.

Finding Errors in Programs for Processing Graphic Images using the Fuzzing Method

Increasing number of software for automated graphics processing requires effective testing methods. One of these methods is fuzzing, for which it is necessary to determine the most effective algorithms for creating test data in order to increase the number of errors found and minimize hardware resources. The comparison of algorithms for creating test data for finding errors in the executable code of programs designed for processing graphic images is the result of the performed research. Using Bayesian networks to describe fuzzing allows determining the relationships between structural components during testing. Based on the results of the comparison of fuzzing algorithms for creating test data, the most effective algorithms for finding errors in the executable code of programs for processing graphic images have been identified. The performance of the proposed algorithms was tested on a number of existing vulnerabilities classified as CVE (Common Vulnerabilities and Exposures). The processing of the results of experiments on the creation of test data was carried out using the simulation environment, allowing analyzing the testing process step by step. The obtained research results, algorithms for creating test data for finding errors can be used at various stages of software testing

Women as Heroes in Shakespearean Drama

Shakespeare studies Nature in the context of human behaviour. His drama deals with transformations and he displays these changes on both social and personal levels through alternating the graphic images from characters to situation. In an authoritarian society where lives of women were governed by a belief system which resulted out of Nature’s disposition of preordained roles in society, the portrayal of dominating female voices would have bothered many. Shakespearean drama is a protest against the society which is always dominated by the destructive forces of male paranoia, egocentrism, patriarchal instinct of exploitation of the weak, male sexual anxiety and corrupt abuse of rules of justice by the powerful. A study of the female mind presented in Shakespearean drama is seen at its best in The Winter’s Tale. The following article is an attempt to explore some of the aspects of Womanhood in Shakespearean art.

THE DEITY AS A MOSAIC: IMAGES OF THE GOD XIPE TOTEC IN DIVINATORY CODICES FROM CENTRAL MESOAMERICA

In this article I argue that the graphic images of the gods in the divinatory codices are composed of signs of different semantic values which encode particular properties. All of them contribute to creating the identity of the god. However, these graphic elements are not only shared by different deities, but even differ between representations of the same god. Analyzing the graphic images of Xipe Totec, one of the best-studied deities and one of the oldest in Mesoamerica, I elaborate a hypothesis that the images of the gods in the divinatory codices were perceived by their authors as a mosaic of different properties, which at the same time were dynamic. Consequently, there was not even one “prototypical” representation of a single god, since possibly the identity of a god was defined precisely when composing his/her image with particular graphic signs, thus crystallizing some of his/her multiple properties, important at this precise moment.

STRUCTURAL-PHOTOMETRIC IMAGES AS REFLECTION OF THE TIEN SHAN INTEGRAL TECTONIC SEGMENTATION

The article discusses (first) the possibility of the structural-photometric images application for the Tian Shan intracontinental orogen segmentation. With the help of the Photoshop Pro program, the geological map into a system of graphic images was transformed. This technique allowed to identify the integral structural and morphological heterogeneity of the Kyrgyz Tian Shan upper crust and to create a scheme of the region's morphostructural segmentation.

DEVELOPEMENT AN ALGORITM FOR RECOGNIZING TEXT DATA IN DIGITAL GRAPHIC IMAGES

Предложен алгоритм распознавания, реализующий процедуры: обучения выбранных классификаторов и распознавания текстовых данных, учитывающие статистические характеристики распределения коэффициентов частотной области цифровых графических изображениях формата JPEG. The article presents an approach to development an algorithm for recognizing text data within JPEG format digital graphic images. Considered a hypothesis about influence text data content in JPEG digital graphic images on the distribution of values of the discrete cosine transformation coefficients in the frequency domain JPEG images of the format. Statistical classifiers models that provide a solution to the problem of recognition of text data in JPEG images based on analysis of its frequency domain have been determined. A recognition algorithm is proposed that implements the following procedures: training of selected classifiers and recognition of text data, taking into account the statistical characteristics of the distribution of frequency domain coefficients in JPEG format images.