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Chapter 6 Frames of reference in hemineglect: a computational approach

The features of modeling a graphic-verbal polycode text, including a static image and an accompanying inscription, are considered. The study was conducted on the example of a demotivator dedicated to the problems of mass self-isolation at the very beginning of the pandemic and the introduction of restrictive measures. Significant semantic components, represented as part of only the iconic component, only the verbal component, and also as part of the verbal and iconic components at the same time are established. The semantic relations between the selected semantic components are revealed, the types of these links, revealing the different nature of their correlation are determined. On the basis of the data obtained, a network model of the considered static polycode text in the form of a semantic network was built. Cases of semantic components correlation are considered, reflecting the generally objective aspects of the situation and unrealistic ideas based on irony and hyperbole to create a comic effect. Based on quantitative analysis, representative semantic relations were established: “partitive”, “localization (in)”, “attributive”, “subject-object”. Non-representative semantic relations between the semantic components in the analyzed polycode text are revealed: “coincidence”, “localization (on)”, “temporal”, “subject-instrument”, “subject-result”.

Nowadays, there is an increasing interest in non-verbal means of written forms of interpersonal communication. It is explained by the fact that the informational component and the pragmatic potential of non-verbal means of communication are often much higher than those of verbal means. As a result, the researchers focus their studies on texts which structural organization contains, in addition to verbal code units, the means of other semiotic codes. Such texts are called creolized or polycode. Polycode texts are a distinctive feature of academic texts, and their interpretation poses certain difficulties for students. The purpose of this study is to analyze the structural components of academic polycode texts; to study the ways of organizing verbal and iconic components; to describe the functional characteristics of iconic elements; to establish the mechanisms of interaction between linguistic and paralinguistic means when creating a single semantic unity of a polycode text. The main research methods are analysis, synthesis, comparison and observation. The textbook for the training of professional engineersCambridge English for Engineering written by M. Ibbotsonis used as the empirical material. The authors come to the following conclusions: there are four types of academic polycode texts; each type has a different pragmatic potential of verbal and iconic parts; in some types, the information function is more prominent in the iconic component; the use of photographs as iconic means facilitates the process of text interpretation and scientific and technical data exchange.

With “Spatial Reference Frames” we refer to systems of coordinates by which the central nervous system encodes the relative positions of objects in space, including that of the body itself. A reference system is a way of representing the positions of the subjects / objects in space. The spatial position of an object can be represented in the brain with respect to different classes of reference points, which may be related or not to the position of the subject. In a nutshell, we can say that there are two types of transformations of space imagery: the allocentric spatial transformations, that involve a system of representation from object to object and encode information about the location of an object or its parts in relation to other objects, and egocentric spatial transformations that involve a system of subject-object representation. The human being switches from one code to another, depending on the contingent requirements, giving preference to one or another system according to a set of heterogeneous factors. The gender difference (male / female), for example, plays a key role. Even the individual cognitive strategies make use of different representations in a significantly different way. Manipulation of spatial reference systems constitute a “transnosographic trait” in various neurological and psychiatric disorders. Each of these diseases (autism, schizophrenia, epilepsy, spatial anxiety, Parkinson) reaches some of the structures involved in the manipulation of referential of different spaces. The chapter illustrates Piaget's study on the representation of space in the child and the use of different spatial coding systems, and provides a brief overview of the scientific debate following the Piagetian position.

Is it possible to quickly and reliably understand the position of objects in space without vision? This is one of the biggest challenge blind people face daily. We developed a novel algorithm called the Topo-Speech which conveys the spatial position of objects via speech manipulations. We ran a pilot study on blindfolded sighted adults (n=5) to test the extent to which users can locate objects’ spatial positions after short training with the Topo-Speech, as well as their ability to locate untrained spatial positions. Participants were trained for ~30 minutes on the detection of objects’ positions on a 3×3 grid. Then they were tested on the same spatial locations (though using different stimuli). Finally, participants were tested on identifying the positions of objects on a 5×5 grid (i.e. additional spatial locations) without any specific training. Our results showed that participants performed significantly above chance for both trained and untrained spatial positions. This in turn suggests the feasibility of the Topo-Speech to convey spatial related information via a non-visual channel and prompt to quickly test such approach with people who are visually impaired.

Introduction/Main Objectives: This study aims to develop and test the feasibility and effectiveness of DEKASI (Location Plan) learning media to improve understanding of location and direction in grade 1 elementary school students. The background of this study comes from the need for concrete and fun learning media so that students can understand the concept of space visually. The phenomenon raised in this study is the low understanding of students regarding the direction and position of objects in space. This study has an element of novelty in the development of interactive media based on location plans, presented in an interesting and easy-to-understand manner by students in early grades. Research Methods: This study uses a descriptive method with a qualitative and quantitative approach, involving a validation process by experts and limited trials on grade 1 elementary school students. The instruments used in the study were validation sheets and student response questionnaires. Finding/Results: The validation results showed that this media was very feasible to use (90% feasibility), while student responses showed high enthusiasm and ease of understanding of the concept of direction and location. Conclusion: The conclusion of this study is that DEKASI media is effective and interesting to use in learning the topic of location and direction in grade 1 elementary school. The implication of this study is the need for integration of visual and interactive media in basic learning to improve students' spatial understanding.

Probably one of the most important of the visual clues by which a person can estimate the relative distances and positions of objects in space is stereoscopic localization. These clues arise from the disparities between the two retinal images caused by the slightly different points of view of the two eyes. That stereopsis is the means for the most accurate discrimination of the relative distances of objects is, of course, universally appreciated. It has not been sufficiently recognized, however, that stereoscopic vision also plays an important role in the subjective orientation of all objects in the entire binocular visual field, in the sense of a rotation about the point of fixation. In the absence of strong perspective clues, this particular capacity may provide one of the important visual criteria by which a person can orient himself in the outside world of objects. Certain experiments which demonstrate a relation

The study of the formation of conditioned reactions to the position of objects in space is an important question not only for physiology and psychology, but to education. It is on the basis of these conditioned reactions that the infant establishes concepts of space (near — far; closer — further, etc.).

Modern industrial systems and robotic complexes use machine vision systems to increase productivity and automate processes. Deep learning systems are used to assist the operator and make decisions. The creation of industrial systems within the framework of "Industry 4.0" and "Industry 5.0" is impossible without precise control of the position of objects in space. Implementing ma-chine vision systems allows you to control the position of robot elements, objects, and humans. Information about objects and their constituent parts allows predicting their movement based on the accumulated knowledge and the embedded algorithm of the program. The analysis of the position of a material point in space and the forecast of its movement under the conditions of without apriori information about the process can be carried out both using neural networks (a large amount of knowledge is needed for training) and using computational methods (exact conditions are required). On the other hand, the fixed data is affected by noise. The appearance of noise is due to: not the ideality of the sensor (the CCD matrix does not consist of pure groups, but contains impurities in the composition); to the influence of external factors (electrical interference, inter-pixel inter-action, etc.); uneven accumulation, and drainage of the charge of the CCD of the matrix; destruction of the pixel; inaccuracy during subsequent digitization of data (quantization noise), etc. Methods of data accumulation and averaging, neural networks, or computational methods can be used to eliminate the noise component. The article discusses a data filtering method based on the analysis of vector spaces and the formation of an optimal solution according to the combined criterion that minimizes the distance between the maximum approximation, monotony, and minimum deviation of the difference in the norms of data vectors. The article contains 4 theorems and their proofs. In work, practical examples of processing data were obtained for various practical applications, including forecasting, searching for object boundaries in images, and data filtering. On a set of test sequences, the results obtained were compared with an example of data processing by approximation functions, which showed the coincidence of the results with an accuracy of 100%. For the case of the presence of a noise component, the accuracy is more than 94%, with a noise standard deviation of 25% of the signal power. It should be noted, that the proposed filtering method can reduce the effect of the noise component in the absence of a priori information about the belonging of a pure signal to any parametric class of functions. In the presence of the specified information, the approximation of the implementation by a function from the corresponding class may be more accurate.

The ability to use a mirror as an instrument for spatial reasoning enables an agent to make meaningful inferences about the positions of objects in space based on the appearance of their reflections in mirrors. The model presented in this paper enables a robot to infer the perspective from which objects reflected in a mirror appear to be observed, allowing the robot to use this perspective as a virtual camera. Prior work by our group presented an architecture through which a robot learns the spatial relationship between its body and visual sense, mimicking an early form of self-knowledge in which infants learn about their bodies and senses through their interactions with each other. In this work, this self-knowledge is utilized in order to determine the mirror's perspective. Witnessing the position of its end-effector in a mirror in several distinct poses, the robot determines a perspective that is consistent with these observations. The system is evaluated by measuring how well the robot's predictions of its end-effector's position in 3D, relative to the robot's egocentric coordinate system, and in 2D, as projected onto it's cameras, match measurements of a marker tracked by its stereo vision system. Reconstructions of the 3D position end-effector, as computed from the perspective of the mirror, are found to agree with the forward kinematic model within a mean of 31.55mm. When observed directly by the robot's cameras, reconstructions agree within 5.12mm. Predictions of the 2D position of the end-effector in the visual field agree with visual measurements within a mean of 18.47 pixels, when observed in the mirror, or 5.66 pixels, when observed directly by the robot's cameras.

The article theoretically examines the choice of the most optimal of the possible trajectories of cargo in the process of moving goods from one place to another, placing them in the most optimal shape and size, taking into account the characteristics of the cargo. At the same time, using the method of mathematical modeling, the position of objects in space was determined using the functions of the Cartesian and polar coordinate systems. For optimal planning and management of the placement of goods, as well as transport operations along any spatial trajectory, the matrix method of mathematical modeling of these processes was used. Practically all possible cases of cargo movement were investigated and a mathematical expression was formed taking into account the geometry and kinematics of their placement in the given volumes. Based on the results of theoretical studies, three conclusions were drawn

3D point clouds represent a structured collection of elementary geometrical primitives. They can characterize size, shape, orientation and position of objects in space. In the field of building modelling and Cultural Heritage documentation and preservation, the classification and segmentation of point clouds result challenging because of the complexity and variety of point clouds due to irregular sampling, varying density, different types of objects. After moving into the era of multimedia big data, machine-learning approaches evolved into deep learning approaches, which are a more powerful and efficient way of dealing with the complexity of semantic object classification. Despite the great benefits that such approaches brought in automation, a great obstacle is to generate enough training data, which are nowadays manually labeled. This task results time-consuming for two reasons: the variety of point density and geometry, which are typical for the Cultural Heritage domain. In order to accelerate the development of powerful algorithms for CH point cloud classification, in this paper, it is presented a novel framework for automatic generation of synthetic dataset of point clouds. This task is performed using Blender, an open source software which permits to access to each point in an object creating one in a new mesh. The algorithms described allow to create a great number of point cloud synthetically, simulating a virtual laser scanner at a variable distance. Furthermore, these two algorithms not only work with a single object, but it is possible to create simultaneously many point clouds from a scene in Blender also with the use of an existing model of ancient architectures.

Microsoft SQL Server 2008 introduces new geography and geometry spatial datatypes that enable the storage of structured data describing the shape and position of objects in space. This is an interesting and exciting new feature, with many potentially useful applications. Beginning Spatial with SQL Server 2008 covers everything you need to know to begin using these new spatial datatypes, and explains how to apply them in practical situations involving the spatial relationships of people, places, and things on the earth. All of the spatial concepts introduced are explained from the ground up, so you need not have any previous knowledge of working with spatial data. Every section is illustrated with code examples that you can use directly in SQL Server. All of the topics covered in this book apply to all versions of SQL Server 2008, including the freely available SQL Server 2008 Express. What youll learn Understand the fundamental concepts involved in working with spatial data, including spatial references and coordinate systems. Apply these concepts in the collection and storage of spatial data in SQL Server 2008, using the new geometry and geography field types. Create different types of spatial data objectspoints, lines, and polygonsand use these to describe realworld objects. Learn how to analyze spatial data using a range of supported methods, and be aware of a number of different practical applications for these methods. Be shown how to integrate SQL Server with other tools, such as Microsoft Virtual Earth, to display a visual representation of spatial data. Know how to ensure the performance of spatially enabled databases by creating appropriate spatial indexes. Who is this book for? SQL Server developers who wish to use spatial data in Microsoft SQL Server 2008. About the Apress Beginning Series The Beginning series from Apress is the right choice to get the information you need to land that crucial entrylevel job. These books will teach you a standard and important technology from the ground up because they are explicitly designed to take you from novice to professional. Youll start your journey by seeing what you need to knowbut without needless theory and filler. Youll build your skill set by learning how to put together realworld projects step by step. So whether your goal is your next career challenge or a new learning opportunity, the Beginning series from Apress will take you thereit is your trusted guide through unfamiliar territory!

The article focuses on describing the realization of the logic-semantic category of contrast in the polycode news text. Scientific originality of the study is in the finding that actualization of contrast in the polycode text, considered as a complicated combination of different semiotic codes, occurs not only by multi-level linguistic means - morphological, lexical, syntactical - but also by the opposition of verbal and iconic components. The authors identify and describe structural, semantic, compositional and stylistic types of contrast and examine its fundamental role in the realization of comical effect within the media discourse. The findings indicate that contrast is most frequently realized by the following stylistic means based on the contradiction of two semantic planes: antithesis, oxymoron, metaphor, figurative comparison, litotes, and hyperbola. In most cases there is a convergence of different means of expressing contrast, which serves to emphasize comical effect.

The algorithm of estimation and compensation of ionosphere influence on the measurement of parameters of the motion of space objects in two-position radar system with account of radio physical effects depending on elevation angles and the operating frequency is developed. It is assumed that the observed space object is traсked object, the orbital parameters which are well known, including the dependence of the velocity of the point on the orbit, and the uncertainty of the current coordinates of the object is caused mainly by forecast error of its position of in orbit (longitudinal error). To estimate the true position of space object in the orbit and the parameter, determining the influence of the ionosphere, a joint optimal processing of measurement of ranges to the object, obtained by two separated radars, taking into account the relevant ionospheric propagation delays and available a priori data on observable object trajectory. Estimation of unknown parameters are obtained on the basis of the criterion of maximum a posteriori probability density for these parameters, taking into account the measured and a priori data. The task of searching for maximum a posteriori probability density is reduced to task of searching of minimum weighted sum of squares, for the solution of which the cascade algorithm of iteration through is implemented in the work. Estimation accuracy of the position of space objects in orbit after compensation of ionosphere influence have been studied by Monte-Carlo method. Dependencies of mean square error of the position estimation of space objects upon elevation angles, operation frequency and solar activity have been obtained. It is shown that the effectiveness of the algorithm increases with the spatial base of measurements (for a fixed orbit of the object).