• Journal of Korean Elementary Science Education
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• v.32 no.1
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• pp.1-9
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• 2013

This study aimed to analyze the characteristics of good science teachings regarded by preservice elementary school teachers. It also aimed to suggest a direction of peer teaching practice to help preservice teachers' professional development. Adjacency pairs were adopted to analyze the characteristics of good science teachings. The results showed that pre-service elementary teachers were accustomed to adjacency pairs. Almost of their discourse were organized by adjacency pairs. 'Question-Answer' and 'Request-Accept' were mainly used in science classes by pre-service elementary teachers. Based on the findings, the study suggested science teacher educators to provide chances to analyze exemplary science teachers' science class or chances to analyze their science teachings in terms of competence of science classroom discourse.

• Cross-Cultural Studies
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• v.27
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• pp.435-470
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• 2012

This paper aims to examine directives and its adjacency pair directives-responses in the Chinese textbook Hanyu Kouyu from the speech act theory, and give some suggestions for Chinese speaking instruction. For analysis of directives, it is important to consider context surrounding it at first. Context includes space for speaking, person who speak with, adjacent speech act, etc., so this paper considers context firstly before explaining directives and discusses how each element of context effects interpretation of its meaning. From the politeness perspective, directives and rejection as one of the responses are easy to be FTAs(face-threatening acts) fundamentally, so they are required to have some strategies for minimizing the threat, and it is found that there are strategies for positive face and negative face in the textbook. In the textbook, it is also examined that directives-responses contribute for interlocutor to accomplish social acts, for example, negotiating, insisting, maintaining, making alternative ideas, etc.

• Kyungpook Mathematical Journal
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• v.59 no.2
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• pp.335-340
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• 2019

The energy of a graph G is the sum of the absolute values of the eigenvalues of the adjacency matrix of G. Some variants of energy can also be found in the literature, in which the energy is defined for the Laplacian matrix, Distance matrix, Commonneighbourhood matrix or Seidel matrix. The Seidel matrix of the graph G is the square matrix in which $ij^{th}$ entry is -1 or 1, if the vertices $v_i$ and $v_j$ are adjacent or non-adjacent respectively, and is 0, if $v_i=v_j$. The Seidel energy of G is the sum of the absolute values of the eigenvalues of its Seidel matrix. We present here some families of pairs of graphs whose Seidel matrices have different eigenvalues, but who have the same Seidel energies.

• Korean Journal of Remote Sensing
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• v.22 no.6
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• pp.613-619
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• 2006

This study proposed an unsupervised image classification through the dendrogram of agglomerative clustering as a higher stage of image segmentation in image processing. The proposed algorithm is a hierarchical clustering which includes searching a set of MCSNP (Mutual Closest Spectral Neighbor Pairs) based on the data structures of RAG(Regional Adjacency Graph) defined on spectral space and Min-Heap. It also employes a multi-window system in spectral space to define the spectral adjacency. RAG is updated for the change due to merging using RNV (Regional Neighbor Vector). The proposed algorithm provides a dendrogram which is a graphical representation of data. The hierarchical relationship in clustering can be easily interpreted in the dendrogram. In this study, the proposed algorithm has been extensively evaluated using simulated images and applied to very large QuickBird imagery acquired over an area of Korean Peninsula. The results have shown it potentiality for the application of remotely-sensed imagery.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.1
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• pp.89-98
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• 2016

In this paper, we proposed an automated areal feature matching method based on geometric similarity without user intervention and is applied into areal features of many-to-many relation, for confusion of spatial data-sets of different scale and updating cycle. Firstly, areal feature(node) that a value of inclusion function is more than 0.4 was connected as an edge in adjacency matrix and candidate corresponding areal features included many-to-many relation was identified by multiplication of adjacency matrix. For geometrical matching, these multiple candidates corresponding areal features were transformed into an aggregated polygon as a convex hull generated by a curve-fitting algorithm. Secondly, we defined matching criteria to measure geometrical quality, and these criteria were changed into normalized values, similarity, by similarity function. Next, shape similarity is defined as a weighted linear combination of these similarities and weights which are calculated by Criteria Importance Through Intercriteria Correlation(CRITIC) method. Finally, in training data, we identified Equal Error Rate(EER) which is trade-off value in a plot of precision versus recall for all threshold values(PR curve) as a threshold and decided if these candidate pairs are corresponding pairs or not. To the result of applying the proposed method in a digital topographic map and a base map of address system(KAIS), we confirmed that some many-to-many areal features were mis-detected in visual evaluation and precision, recall and F-Measure was highly 0.951, 0.906, 0.928, respectively in statistical evaluation. These means that accuracy of the automated matching between different spatial data-sets by the proposed method is highly. However, we should do a research on an inclusion function and a detail matching criterion to exactly quantify many-to-many areal features in future.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10b
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• pp.1591-1596
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• 1991

The present paper describes a method of recognizing a polyhedron employing the notion of network constraint analysis. Typical difficulties in three-dimensional object recognition, other than shading, reflection, and hidden line problems, include the case where appearances of an object vary according to observation points and the case where an object to be recognized is occluded by other objects placed in its front, resulting in incomplete information on the object shape. These difficulties can, however, be solved to a large extent, by taking account of certain local constraints defined on a polyhedral shape. The present paper assumes a model-based vision employing an appearance-oriented model of a polyhedron which is provided by placing it at the origin of a large sphere and observing it from various positions on the surface of the sphere. The model is actually represented by the sets of adjacent faces pairs of the polyhedron observed from those positions. Since the shape of a projected face gives constraint to that of its adjacent face, this results in a local constraint relation between these faces. Each projected face of an unknown polyhedron on an acquired image is examined its match with those faces in the model, producing network constraint relations between faces in the image and faces in the model. Taking adjacency of faces into consideration, these network constraint relations are analyzed. And if the analysis finally provides a solution telling existence of one to one match of the faces between the unknown polyhedron and the model, the unknown polyhedron is understood to be one of those memorized models placed in a certain posture. In the performed experiment, a polyhedron was observed from 320 regularly arranged points on a sphere to provide its appearance model and a polyhedron with arbitrarily postured, occluded, or imposed another difficulty was successfully recognized.

• Journal of Korea Multimedia Society
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• v.12 no.9
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• pp.1217-1232
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• 2009

In this paper, we propose a semi-automatic 3D building reconstruction method using uncalibrated images which includes the facade of target building. First, we extract feature points in all images and find corresponding points between each pair of images. Second, we extract lines on each image and estimate the vanishing points. Extracted lines are grouped with respect to their corresponding vanishing points. The adjacency graph is used to organize the image sequence based on the number of corresponding points between image pairs and camera calibration is performed. The initial solid model can be generated by some user interactions using grouped lines and camera pose information. From initial solid model, a detailed building model is reconstructed by a combination of predefined basic Euler operators on half-edge data structure. Automatically computed geometric information is visualized to help user's interaction during the detail modeling process. The proposed system allow the user to get a 3D building model with less user interaction by augmenting various automatically generated geometric information.

• KIISE Transactions on Computing Practices
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• v.21 no.2
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• pp.109-114
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• 2015

This paper presents a computational model on the transfer of airborne fine particles to analyze the similarities and influences among the 25 districts in Seoul by quantifying a time series data collected from each district. The properties of each district are driven with the model of a time series of the fine particle concentrations, and the calculation of edge-based weights are carried out with the transfer entropies between all pairs of the districts. We applied a modularity-based graph clustering technique to detect the communities among the 25 districts. The result indicates the discovered clusters correspond to a high transfer-entropy group among the communities with geographical adjacency or high in-between traffic volumes. We believe that this approach can be further extended to the discovery of significant flows of other indicators causing environmental pollution.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.2
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• pp.93-98
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• 2013

Multi-temporal high resolution satellite images are essential data for efficient city analysis and monitoring. Yet even when acquired from the same location, identical sensors as well as different sensors, these multi-temporal images have a geometric inconsistency. Matching points between images, therefore, must be extracted to match the images. With images of an urban area, however, it is difficult to extract matching points accurately because buildings, trees, bridges, and other artificial objects cause shadows over a wide area, which have different intensities and directions in multi-temporal images. In this study, we analyze a shadow effect on image matching of high resolution satellite images in urban area using Scale-Invariant Feature Transform(SIFT), the representative matching points extraction method, and automatic shadow extraction method. The shadow segments are extracted using spatial and spectral attributes derived from the image segmentation. Also, we consider information of shadow adjacency with the building edge buffer. SIFT matching points extracted from shadow segments are eliminated from matching point pairs and then image matching is performed. Finally, we evaluate the quality of matching points and image matching results, visually and quantitatively, for the analysis of shadow effect on image matching of high resolution satellite image.