• Korean Journal of Childcare and Education
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• v.7 no.1
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• pp.93-120
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• 2011

This study was aimed at inquiring into the role characteristics of a early childhood teacher, who can put an act of tending & examining into practice, and organizing a role by analyzing the concrete reality based on the relationship with a early childhood teacher's role in Korea and Japan. As a result, this study could take a look at the characteristics, such as relation with conversation, relation through sensation and body, relation with familiarity, and relation by living through the cases in Korea. As for the cases in Japan, there appear the characteristics, such as relation through natural things, relation as an equal participant, relation with bodily movement, and relation with daily life. Based on the result of the analysis, this study organized a early childhood teacher's role as relationship through object-oriented language, relationship based on sensation, relationship based on fellowship, and ecological relationship.

• International Journal of Control, Automation, and Systems
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• v.4 no.2
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• pp.204-216
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• 2006

Latest advances in hardware technology and state of the art of mobile robot and artificial intelligence research can be employed to develop autonomous and distributed monitoring systems. And mobile service robot requires the perception of its present position to coexist with humans and support humans effectively in populated environments. To realize these abilities, robot needs to keep track of relevant changes in the environment. This paper proposes a localization of mobile robot using the images by distributed intelligent networked devices (DINDs) in intelligent space (ISpace) is used in order to achieve these goals. This scheme combines data from the observed position using dead-reckoning sensors and the estimated position using images of moving object, such as those of a walking human, used to determine the moving location of a mobile robot. The moving object is assumed to be a point-object and projected onto an image plane to form a geometrical constraint equation that provides position data of the object based on the kinematics of the intelligent space. Using the a priori known path of a moving object and a perspective camera model, the geometric constraint equations that represent the relation between image frame coordinates of a moving object and the estimated position of the robot are derived. The proposed method utilizes the error between the observed and estimated image coordinates to localize the mobile robot, and the Kalman filtering scheme is used to estimate the location of moving robot. The proposed approach is applied for a mobile robot in ISpace to show the reduction of uncertainty in the determining of the location of the mobile robot. Its performance is verified by computer simulation and experiment.

• Smart Media Journal
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• v.4 no.1
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• pp.16-24
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• 2015

In this paper, we propose a method for multi-touch tracking using MRF-based particle filters and gesture likelihood estimation Each touch (of one finger) is considered to be one object. One of frequently occurring issues is the hijacking problem which means that an object tracker can be hijacked by neighboring object. If a predicted particle is close to an adjacent object then the particle's weight should be lowered by analysing the influence of neighboring objects for avoiding hijacking problem. We define a penalty function to lower the weights of those particles. MRF is a graph representation where a node is the location of a target object and an edge describes the adjacent relation of target object. It is easy to utilize MRF as data structure of adjacent objects. Moreover, since MRF graph representation is helpful to analyze multi-touch gestures, we describe how to define gesture likelihoods based on MRF. The experimental results show that the proposed method can avoid the occurrence of hijacking problems and is able to estimate gesture likelihoods with high accuracy.

• The Journal of the Korea institute of electronic communication sciences
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• v.8 no.3
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• pp.409-414
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• 2013

With the increase of multimedia information such as images, researches have been realized on how to extract the high-level semantic information from low-level visual information, and a variety of techniques have been proposed to generate this information automatically. However, most of these technologies extract the semantic information between single images, it's difficult to extract semantic information when a combination of multiple objects within the image. In this paper, we extract the visual features of objects within the image and training images stored in the DB and the features of each object are defined by measuring the similarity. Using ontology reasoner, each object feature within images infers the semantic information by positional relation and associative relation. With this, it's possible to infer semantic information between objects within images, we proposed a method for inferring more complicated and a variety of high-level semantic information.

• Journal of English Language & Literature
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• v.53 no.2
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• pp.219-241
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• 2007

This study takes its point of departure from Lacanian psychoanalysis and explores the point that an irremediable gap in the human subject can be illuminated in terms of the Lacanian categories, fantasy, symptom, gaze or voice as cause of desire of the Other. With respect to the category of the symptom, Lacan claims that the Other is always already there in the constitution of the subject, that is, the relation of the subject to the Other that is overwhelming as well as attracting the subject. Chapter II deals with the unthought, excessive ground of the conscious that borders on the subject, as is the case of self-excentric aspect of the man. Indeed, in Lacan's early work, the subject is essentially a relationship to the Other as desire(objet petit a), and there is no such thing as a symptom or fantasy without some subjective involvement. Lacanian unknown real, perpetual excess as the cause of desire animates the subject even as it threatens to blast it apart. The structures that establish the lines of desire in every individual are derived from an ineluctably intersubjective field. The Other is always already there in the constitution of the subject. In the final years of Lacan's teaching we find a kind of universalization of the symptom and almost everything that is becomes in a way symptom. Symptom, embodied in Laura in "Goblin Market," is her only substance, the only positive support of her being. By looking at the Laura's symptom in chapter III we gain an insight into the forbidden domain, into a real space that should be left unseen and unthought. The voice of goblin men therefore functions as a sublime object that is animating as well as dominating element even as it threatens to disintegrate the subject. Objet petit a as a sublime object that must be excluded in reality returns in the real, taking on a certain materiality which has an effect on Laura, that is, animates Laura's desire. Objet petit a is a real object, signifying nothing. In conclusion, the theoretical importance of Lacanian psychoanalysis is the relation between a subject and an Other as Objet petit a.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.1
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• pp.54-68
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• 2001

This paper proposes a new algorithm that detects and separates the occluding and occluded objects in a 2D image. An input image is represented by the attributed graph where a node corresponds to a surface and an arc connecting two nodes describes the adjacency of the nodes in the image. Each end of arc is weighted by relation value which tells the number of edges connected to the surface represented by the node in the opposite side of the arc. In attributed graph, homogeneous nodes pertained to a same object always construct one of three special patterns which can be simply classified by comparison of relation values of the arcs. The experimental results have shown that the proposed algorithm efficiently separates the objects overlapped arbitrarily, and that this approach of separating objects before matching operation reduces the matching time significantly by simplifying the matching problem of overlapped objects as the one of individual single object.

• Journal of Korea Multimedia Society
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• v.3 no.5
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• pp.550-556
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• 2000

This paper comes to derive optimal decision rule from incomplete information using the concept of indiscernibility relation and approximation space in Rough set. As there may be some errors in case that processing information contains multiple or missing data, the method of removing or minimizing these data is required. Entropy which is used to measure uncertainty or quantity in information processing field is utilized to remove the incomplete information of rough relation database. But this paper does not always deal with the information system which may be contained incomplete information. This paper is proposed object relation entropy and attribute relation entropy using Rough set as information theoretical measures in order to remove the incomplete information which may contain condition attribute and decision attribute of information system.

• Journal of Advanced Navigation Technology
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• v.16 no.3
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• pp.455-462
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• 2012

The loss due to caching replacement in the wireless mobile proxy caching structure has a significant effect on streaming QoS. This paper proposes a similarity-based caching loss minimization (SCLM) for minimizing the loss caused by the caching replacement. The proposed scheme divides object segments, and then it performs the similarity relation about them. Segments that perform the similarity relation generates similarity relation tree (SRT). The similarity is an important metric for deciding a relevance feedback, and segments that satisfy these requirements in the cache block for caching replacement. Simulation results show that the proposed scheme has better performance than the existing prefix caching scheme, segment-based caching scheme, and bi-directional proxy scheme in terms of QoS, average delayed startup ratio, cache throughput, and cache response ratio.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.6
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• pp.101-108
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• 1998

An efficient approach to recognize occluded objects is to detect a number of essential features on the boundary of the unknown shape. The salient points including corner points, tangential points and inflection points are detected by the relation of neighboring pixels of each pixel on the boundaries. Corner points are usually detected in the curvature function and tangential points and inflection points are detected by median filtering the curvature function to avoid the effect of quantization noise as corner points is not sufficient to represent an object with lines and arcs. Then, these salient points are used as features for object matching. Discrete Hopfield Neural Network is used for object matching. Experimental results show that the matching result using salient points is better than those of using corner points only when an object consists of lines and arcs.

• Proceedings of the Korea Information Processing Society Conference
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• 2018.05a
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• pp.377-380
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• 2018

인간의 추론 능력이란 문제에 주어진 조건을 보고 문제 해결에 필요한 것이 무엇인지를 논리적으로 생각해 보는 것으로 문제 상황 속에서 일정한 규칙이나 성질을 발견하고 이를 수학적인 방법으로 법칙을 찾아내거나 해결하는 능력을 말한다. 이러한 인간인지 능력과 유사한 인공지능 시스템을 개발하는데 있어서 핵심적 도전은 비구조적 데이터(unstructured data)로부터 그 개체들(object)과 그들간의 관계(relation)에 대해 추론하는 능력을 부여하는 것이라고 할 수 있다. 지금까지 딥러닝(deep learning) 방법은 구조화 되지 않은 데이터로부터 문제를 해결하는 엄청난 진보를 가져왔지만, 명시적으로 개체간의 관계를 고려하지 않고 이를 수행해왔다. 최근 발표된 구조화되지 않은 데이터로부터 복잡한 관계 추론을 수행하는 심층신경망(deep neural networks)은 관계추론(relational reasoning)의 시도를 이해하는데 기대할 만한 접근법을 보여주고 있다. 그 첫 번째는 관계추론을 위한 간단한 신경망 모듈(A simple neural network module for relational reasoning) 인 RN(Relation Networks)이고, 두 번째는 시각적 관찰을 기반으로 실제대상의 미래 상태를 예측하는 범용 목적의 VIN(Visual Interaction Networks)이다. 관계 추론을 수행하는 이들 심층신경망(deep neural networks)은 세상을 객체(objects)와 그들의 관계(their relations)라는 체계로 분해하고, 신경망(neural networks)이 피상적으로는 매우 달라 보이지만 근본적으로는 공통관계를 갖는 장면들에 대하여 객체와 관계라는 새로운 결합(combinations)을 일반화할 수 있는 강력한 추론 능력(powerful ability to reason)을 보유할 수 있다는 것을 보여주고 있다. 본 논문에서는 관계 추론을 수행하는 심층신경망(deep neural networks) 중에서 Sort-of-CLEVR 데이터 셋(dataset)을 사용하여 RN(Relation Networks)의 성능을 재현 및 관찰해 보았으며, 더 나아가 파라미터(parameters) 튜닝을 통하여 RN(Relation Networks) 모델의 성능 개선방법을 제시하여 보았다.