993 resultados para Spatial Reasoning
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Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies.
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Basic relationships between certain regions of space are formulated in natural language in everyday situations. For example, a customer specifies the outline of his future home to the architect by indicating which rooms should be close to each other. Qualitative spatial reasoning as an area of artificial intelligence tries to develop a theory of space based on similar notions. In formal ontology and in ontological computer science, mereotopology is a first-order theory, embodying mereological and topological concepts, of the relations among wholes, parts, parts of parts, and the boundaries between parts. We shall introduce abstract relation algebras and present their structural properties as well as their connection to algebras of binary relations. This will be followed by details of the expressiveness of algebras of relations for region based models. Mereotopology has been the main basis for most region based theories of space. Since its earliest inception many theories have been proposed for mereotopology in artificial intelligence among which Region Connection Calculus is most prominent. The expressiveness of the region connection calculus in relational logic is far greater than its original eight base relations might suggest. In the thesis we formulate ways to automatically generate representable relation algebras using spatial data based on region connection calculus. The generation of new algebras is a two pronged approach involving splitting of existing relations to form new algebras and refinement of such newly generated algebras. We present an implementation of a system for automating aforementioned steps and provide an effective and convenient interface to define new spatial relations and generate representable relational algebras.
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El libro presenta un conjunto de tests de aptitud (para medir el potencial de éxito de una persona) y tests de inteligencia normalizados, cada vez más utilizados en procesos de contratación, selección y evaluación de personal. Organizados en cuatro apartados, tests de aptitud verbal, espacial, numérica y tests de inteligencia, permiten trabajar distintas áreas (significado de palabras, gramática y comprensión, aptitud verbal avanzada, análisis lógico, cálculo mental, secuencias numéricas y problemas numéricos) para mejorar las habilidades verbales, numéricas y de razonamiento del lector.
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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.
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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.
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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.
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The analysis of spatial relations among objects in an image is an important vision problem that involves both shape analysis and structural pattern recognition. In this paper, we propose a new approach to characterize the spatial relation along, an important feature of spatial configurations in space that has been overlooked in the literature up to now. We propose a mathematical definition of the degree to which an object A is along an object B, based on the region between A and B and a degree of elongatedness of this region. In order to better fit the perceptual meaning of the relation, distance information is included as well. In order to cover a more wide range of potential applications, both the crisp and fuzzy cases are considered. In the crisp case, the objects are represented in terms of 2D regions or ID contours, and the definition of the alongness between them is derived from a visibility notion and from the region between the objects. However, the computational complexity of this approach leads us to the proposition of a new model to calculate the between region using the convex hull of the contours. On the fuzzy side, the region-based approach is extended. Experimental results obtained using synthetic shapes and brain structures in medical imaging corroborate the proposed model and the derived measures of alongness, thus showing that they agree with the common sense. (C) 2011 Elsevier Ltd. All rights reserved.
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This paper describes a logic-based formalism for qualitative spatial reasoning with cast shadows (Perceptual Qualitative Relations on Shadows, or PQRS) and presents results of a mobile robot qualitative self-localisation experiment using this formalism. Shadow detection was accomplished by mapping the images from the robot’s monocular colour camera into a HSV colour space and then thresholding on the V dimension. We present results of selflocalisation using two methods for obtaining the threshold automatically: in one method the images are segmented according to their grey-scale histograms, in the other, the threshold is set according to a prediction about the robot’s location, based upon a qualitative spatial reasoning theory about shadows. This theory-driven threshold search and the qualitative self-localisation procedure are the main contributions of the present research. To the best of our knowledge this is the first work that uses qualitative spatial representations both to perform robot self-localisation and to calibrate a robot’s interpretation of its perceptual input.
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This study aims to understand individual differences in preschooler’s early comprehension of spatial language. Spatial language is defined as terms describing location, direction, shape, dimension, features, orientation, and quantity (e.g location, shape). Spatial language is considered to be one of the important factors in the development of spatial reasoning in the preschool years (Pruden, Levine, & Huttenlocher, 2011). In recent years, research has shown spatial reasoning is an important predictor of successes in STEM (Science, Technology, Engineering, and Mathematics) fields (e.g. Shea, Lubinski & Benbow, 2001; Wai, Lubinksi &Benbow, 2009). The current study focuses on when children begin to comprehend spatial terms, while previous work has mainly focused on production of spatial language. Identifying when children begin to comprehend spatial terms could lead to a better understanding of how spatial reasoning develops. We use the Intermodal Preferential Looking paradigm (IPLP) to examine three-year-old children’s ability to map spatial terms to visual representations. Fourteen spatial terms were used to test these abilities (e.g. bottom, diamond, longer). For each test trial children were presented with two different stimuli simultaneously on the left and right sides of a television screen. A female voice prompted the child to find the target spatial relation (e.g. “can you find the boy pointing to the bottom of the window”; Figure 1). A Tobii X60 eye-tracker was used to record the child’s eye gaze for each trial. For each child the proportion of looking to the target image divided by their total looking during the trial was calculated; this served as the dependent variable. Proportions above .50 indicated that the child had correctly mapped the spatial term to the target image. Preliminary data shows that the number of words comprehended in the IPLP task is correlated to parental report of the child’s comprehension of spatial terms (r[14]=.500, p<.05).
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This study aims to understand individual differences in preschooler’s early comprehension of spatial language. Spatial language is defined as terms describing location, direction, shape, dimension, features, orientation, and quantity (e.g location, shape). Spatial language is considered to be one of the important factors in the development of spatial reasoning in the preschool years (Pruden, Levine, & Huttenlocher, 2011). In recent years, research has shown spatial reasoning is an important predictor of successes in STEM (Science, Technology, Engineering, and Mathematics) fields (e.g. Shea, Lubinski & Benbow, 2001; Wai, Lubinksi &Benbow, 2009). The current study focuses on when children begin to comprehend spatial terms, while previous work has mainly focused on production of spatial language. Identifying when children begin to comprehend spatial terms could lead to a better understanding of how spatial reasoning develops. We use the Intermodal Preferential Looking paradigm (IPLP) to examine three-year-old children’s ability to map spatial terms to visual representations. Fourteen spatial terms were used to test these abilities (e.g. bottom, diamond, longer). For each test trial children were presented with two different stimuli simultaneously on the left and right sides of a television screen. A female voice prompted the child to find the target spatial relation (e.g. “can you find the boy pointing to the bottom of the window”; Figure 1). A Tobii X60 eye-tracker was used to record the child’s eye gaze for each trial. For each child the proportion of looking to the target image divided by their total looking during the trial was calculated; this served as the dependent variable. Proportions above .50 indicated that the child had correctly mapped the spatial term to the target image. Preliminary data shows that the number of words comprehended in the IPLP task is correlated to parental report of the child’s comprehension of spatial terms (r[14]=.500, p<.05).
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Este estudo analisa o modo como se desenvolve a aprendizagem do conceito de volume nos alunos do 6º ano de escolaridade, no quadro de uma proposta pedagógica que dá ênfase a actividades que apelam à visualização e ao raciocínio espacial. O seu objectivo principal foi o de compreender as ideias que os alunos do 6.º ano têm sobre volume e perceber como se desenvolvem quando são envolvidos numa experiência de ensino, tendo por base uma cadeia de tarefas que apelam à visualização e ao raciocínio espacial. O estudo seguiu uma metodologia de investigação qualitativa baseada em estudos de caso. A proposta pedagógica foi desenvolvida em quatro aulas; três de noventa minutos e uma de quarenta e cinco minutos, durante os 2º e 3º períodos do ano lectivo de 2009/2010. A recolha de dados envolveu a realização de gravações áudio, em ambiente de sala de aula, dos alunos que constituíram os estudos de caso, registo de observações do desempenho dos alunos e os documentos produzidos por estes. Os resultados mostram que, ao longo da proposta pedagógica, os alunos adquiriram estratégias de contagem que lhes permitiram criar estruturas, para compreender a organização dos paralelepípedos e desenvolver o conceito de volume. iii ABSTRACT This study examines how 6th graders’ students develop the concept of volume in a learning experience context which emphasizes the visualization and spatial reasoning. The main objective of this study is to understand the ideas of 6th grade students about volume and see how they develop them when they are involved in a learning experience, based on a sequence of tasks that call for visualization and spatial reasoning. The study followed a qualitative research methodology based on case studies. The learning experience was developed in four classes, three ninety minutes period and one forty-five minutes, during the 2nd and 3rd terms of the school year 2009/2010. Data collection involved the use of audio recordings in the classroom environment, recording observations of student performance and the documents produced by them. The results showed that, over the learning experience, students acquired counting strategies that allowed them to create structures for understanding the organization of cubes arrays and develop the concept of volume.
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Qualitative spatial reasoning (QSR) is an important field of AI that deals with qualitative aspects of spatial entities. Regions and their relationships are described in qualitative terms instead of numerical values. This approach models human based reasoning about such entities closer than other approaches. Any relationships between regions that we encounter in our daily life situations are normally formulated in natural language. For example, one can outline one's room plan to an expert by indicating which rooms should be connected to each other. Mereotopology as an area of QSR combines mereology, topology and algebraic methods. As mereotopology plays an important role in region based theories of space, our focus is on one of the most widely referenced formalisms for QSR, the region connection calculus (RCC). RCC is a first order theory based on a primitive connectedness relation, which is a binary symmetric relation satisfying some additional properties. By using this relation we can define a set of basic binary relations which have the property of being jointly exhaustive and pairwise disjoint (JEPD), which means that between any two spatial entities exactly one of the basic relations hold. Basic reasoning can now be done by using the composition operation on relations whose results are stored in a composition table. Relation algebras (RAs) have become a main entity for spatial reasoning in the area of QSR. These algebras are based on equational reasoning which can be used to derive further relations between regions in a certain situation. Any of those algebras describe the relation between regions up to a certain degree of detail. In this thesis we will use the method of splitting atoms in a RA in order to reproduce known algebras such as RCC15 and RCC25 systematically and to generate new algebras, and hence a more detailed description of regions, beyond RCC25.
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The use of technologies called computedassisted, such as CAD - (Computed Aided Design), CAM - (Computed Aided Manufacturing) and CNC - (Computed Numerical Control), increasingly demanded by the market, are needed in the teaching of subjects technical drawing and design courses for engineering and design. However its use findl barriers in the more conservative wing of the academy, who advocate the use of traditional drawing, for the settling of the concepts and the development of spatial reasoning. This study aimed to show the results obtained with the design and production of an apparatus for measuring a three-dimensional computer-aided milling machine, interaction, integration and consolidation of concepts, fully demonstrating that the learning of computer-assisted technology is possible, and its use is most appropriate, meaningful and productive, than the use of instruments in the classic design.
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Image content interpretation is much dependent on segmentations efficiency. Requirements for the image recognition applications lead to a nessesity to create models of new type, which will provide some adaptation between law-level image processing, when images are segmented into disjoint regions and features are extracted from each region, and high-level analysis, using obtained set of all features for making decisions. Such analysis requires some a priori information, measurable region properties, heuristics, and plausibility of computational inference. Sometimes to produce reliable true conclusion simultaneous processing of several partitions is desired. In this paper a set of operations with obtained image segmentation and a nested partitions metric are introduced.