Learner-generated drawings by students with mathematical learning difficulties in finishing open number sentences

Although MLD students do not have good mathematical performance in completing addition and subtraction operations of integers, MLD students have suggestive ideas in the form of drawings produced in solving open number sentences questions. This study aims to classify the types and identify changes in the drawing produced by MLD students in solving open number sentences questions. This research method is qualitative with a micro generic study approach to understand students' thinking individually and explore drawing changes in solving open number sentences questions between sessions. The research subjects were 2 out of 20 MLD grade 5 elementary school students who produced the most varied drawings in solving open number sentences questions. Data collection techniques used are giving questions and interviews. The results showed that MLD students produced: discrete object drawings by focusing on the cardinality of the quantity of a number; transitions from objects to the number line by focusing on the magnitude of numbers; partitioning the number line using magnitude reasoning; number sentences; and others using verbal reasoning. Changes in the drawings produced by MLD students between sessions indicate the development of students' understanding towards a better direction in interpreting symbolic representations to visual representations. The results of this study contribute to the theory that although MLD students have low mathematical performance. However, MLD students can produce variations and changes in drawings with rich mathematical idea information representing integer operations.

Concept Lattice-Based Classification in NLP

Classification in discrete object space is a widely used machine learning technique. In this case, we can construct a rule set using attribute level implication rules. In this paper, we apply the technique of formal concept analysis to generate the rule base of the classification. This approach is suitable for cases where the number of possible attribute subsets is limited. For testing of this approach, we investigated the problem of the part of speech prediction in natural language texts. The proposed model provides a better accuracy and execution cost than the baseline back-propagation neural network method.

Women, Peace and Security: A Critical Cartography

This introductory chapter offers a mapping of the field of research to which we – the authors of the chapter and the editors of the volume – hope that the volume itself will contribute. Using the motif of ‘new directions’, we chart historical and contemporary scholarship on Women, Peace, and Security (WPS), tracing avenues of enquiry, streams of argument, and architectures of practice across geographical, temporal, and institutional scales. In the course of our mapping, we identify overlapping waves of WPS scholarship, beginning with those who came to study WPS primarily through peace activism and women’s movements (including those who engaged directly with the politics and processes that produced UNSCR 1325), through the emergence of ‘WPS’ as a discrete object of analysis, and to the current state of art represented by the contributions to this volume. In doing so we show how WPS has gone from peace activism at the margins to a more significant landmark in the peace and security environment than perhaps anyone had envisaged. This cataloguing constitutes the first substantive section of the chapter. In the second section of the chapter, we map the contours of the contemporary field of study, proposing three new horizons of WPS scholarship: new themes; new actors; and new methods of encounter. In the final section, we conclude our cartography with a discussion of the ways in which the more recent contributions to WPS scholarship and practice are producing interesting new contestations, tensions, and constellations of power, and re-situate the new politics of WPS in relation to the geographical, temporal and institutional scales which will shape its future trajectories.

Generation of classification schemes in the form of logical trees in discrete object recognition problems

This work is devoted to the problems of recognition of discrete objects. It continues a series of articles devoted to the study of recognition systems in the form of logical trees, optimization of synthesized systems of classification of discrete objects, studies of their maximum complexity and the possibility of building effective methods to minimize them. Here the scheme of construction of system of recognition of discrete objects on the basis of a logical tree is step by step considered, and in the center of research there is a graph-circuit model of system of recognition in the form of a logical tree. Note that the results of this robot are relevant for all pattern recognition problems, in which the resulting recognition scheme can be represented as a logical tree.

The effects of cue placement on the relative dominance of boundaries and landmark arrays in goal localization

Two types of visual features are identified as reference points used by individuals to encode locations: surface-based boundaries and discrete-object-based landmarks. Previous research show that learning locations relative to a boundary can overshadow learning relative to a landmark, but not vice versa, suggesting that environmental boundaries play a privileged role in representing individual locations. However, other research has revealed that a less accurate cognitive map is derived from boundary-related learning than from landmark-related learning, suggesting that a boundary is less privileged in representing inter-location spatial relations. The current study aims to reconcile these inconsistent findings. Experiment 1, using both a cue-competition paradigm and a cognitive mapping task, replicated the finding that participants preferred a circular boundary to a four-landmark array for encoding four locations (1A), but that the cognitive maps of the locations derived from the landmark array were more accurate (1B). Using the cue-competition paradigm, Experiments 2-4 manipulated the placement and distinctiveness of the two cues. The results showed that manipulating the placement of the landmark array effectively modulated the relative reliance upon the boundary/landmark-array in encoding individual location. Whereas increasing the distinctiveness of the landmark-array alone is not sufficient to eliminate the boundary advantage in localization. We propose that the boundary privilege occurs in selecting reference points for encoding locations due to its relative peripheral placement in the environment, whereas the landmark advantage occurs in inferring inter-location spatial relations due to the common reference point provided by the single landmark.

METHOD FOR ASSESSING THE SYMMETRY OF OBJECTS ON DIGITAL BINARY IMAGES BASED ON FOURIER DESCRIPTOR

<p><strong>Abstract.</strong> In this paper we solve the problem of finding the symmetry axis of the object in a digital binary image. A new axial symmetry criterion is formulated for a connected discrete object. The problem of determining the symmetry measure and finding the symmetry axes arises in a variety of applications. In discrete images, exact symmetry is possible only in special cases. The disadvantage of the existing methods solving this problem is the high computational complexity. To improve computational efficiency, it is proposed to use the so-called Fourier descriptor. A new method for estimating the asymmetry of a discrete silhouette is proposed. The described algorithm for calculating the measure of asymmetry and determining the axis of symmetry is quadratic by the number of contour points. Methods for reducing the volume of calculations using a convex hull and taking into account the values of the modules of Fourier coefficients are proposed. Computational experiments are conducted with silhouettes of aircraft extracted from earth remote sensing images. The reliability of the described solution is established.</p>