• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.4
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• pp.586-594
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• 2018

In this paper, we propose a livestock theft detection system through moving object classification and tracking method. To do this, first, we extract moving objects using GMM(Gaussian Mixture Model) and RGB background modeling method. Second, it utilizes a morphology technique to remove shadows and noise, and recognizes moving objects through labeling. Third, the recognized moving objects are classified into human and livestock using skeletal features and color similarity judgment. Fourth, for the classified moving objects, CAM (Continuously Adaptive Meanshift) Shift and Kalman Filter are used to perform tracking and overlapping judgment, and risk is judged to generate a notification. Finally, several experiments demonstrate the feasibility and applicability of the proposed method.

• Journal of the Korea Society of Computer and Information
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• v.6 no.3
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• pp.35-43
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• 2001

Imposing electromagnetic field using transmitter of buried metal object in skill that detect underground object sensing person atonement in being widowed on the land being magnetized upside numerical value of buried metal object searching way used most widely current by skill be. This paper proposed about mode and detection system of underground object that sense the changed magnetic and judge real radish buried metal object sign of the cook because this treatise forms magnetic in land and design and composition of display device. Also, through simulation of detection system of underground object, showed that can measure radish judgment sign of the cock of underground object

• Fashion & Textile Research Journal
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• v.16 no.1
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• pp.66-78
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• 2014

The purpose of this study is to illuminate the location of fashion in contemporary society and to suggest a direction for fashion criticism in aesthetic$\hat{u}$cultural perspective. For this, literature researches about some of art criticism and fashion criticism theories and cultural studies related to fashion are performed. In this study, fashion criticism is defined as a linguistic analysis and interpretation about a variety of discursive networks around fashion as well as an aesthetic analysis of it. Considering this definition, an analytical framework for the contemporary fashion criticism combines Feldman's and Carney's models with Crane & Bovone's and Entwistle's sociological studies for aesthetic and cultural perspectives. At first, its aesthetic perspective shows 'Description'-'Descriptive formative features', 'Analysis'-'Locate the style' and 'Aesthetic value', 'Interpretation'- 'Interpretation of the fashion object' and 'Socio-cultural interpretation', 'Judgment'-'Critical judgment'. Then, its cultural perspective especially emphasizes 'Socio-cultural interpretation' of the 6 steps above. Socio-cultural interpretation gets tangled with the network of various cultural agents within the fashion system, producers/designers, retailers/suppliers, media/editors, consumers/spectators, and so on. In the course of the fashion system 5 analytical methods about the fashion object can be suggested and they are as follows: Analyses of texts, discourses and symbols of a fashion object, Analyses of fashion systems which produces symbolic values, Analyses of the communication of symbolic values and the disseminating processes through the media, Analyses of the attribution of symbolic values to a fashion object by consumers, and Cross-national studies of symbolic values expressed in a fashion object.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.4
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• pp.578-585
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• 2018

In this paper, we propose a classification and theft detection system for human and livestock for various moving objects in a barn. To do this, first, we extract the moving objects using the GMM method. Second, the noise generated when extracting the moving object is removed, and the moving object is recognized through the labeling method. And we propose a method to classify human and livestock using model formation and color for the unique form of the detected moving object. In addition, we propose a method of tracking and overlapping the classified moving objects using Kalman filter. Through this overlap determination method, an event notifying a dangerous situation is generated and a theft determination system is constructed. Finally, we demonstrate the feasibility and applicability of the proposed system through several experiments.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.5
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• pp.544-549
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• 2006

This research is to introduce about Judgment System for Intelligent Movement(JSIM) that can perform assistance work of human brain. JSIM can order autonomous command and also it can be directly controlled by user. This research assumes that control object is limited to Mobile Robot(MR) Mobile robot offers image and ultrasonic sensor information to user carrying JSIM and it performs guide to user. JSIM having PDA and Sensor-box controls velocity and direction of the mobile robot by soft-computing method that inputs user's command and information that is obtained to mobile robot. Also it controls mobile robot to achieve various movement. This paper introduces wearable JSIM that communicates with around devices and that can do intelligent judgment. To verify the possibility of the proposed system, in real environment, the simulation of control and application problem lot mobile robot will be introduced. Intelligent algorithm in the proposed system is generated by mixed hierarchical fuzzy and neural network.

• Korean Journal of Cognitive Science
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• v.29 no.2
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• pp.137-160
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• 2018

The present article reviews recent arguments on the moral-conventional distinction in moral judgment and discusses the implications for moral psychology research. Traditional research on moral judgment has considered both the evaluation of transgressive actions of others and the categorization of the norms on the moral-conventional dimension. Kohlberg, Piaget, and Turiel (1983) regard moral principles to be clearly distinguished from social-conventional norms and suggested criteria for the moral-conventional distinction. They assume that the moral domain should be specifically related to the value of care and justice, and the judgment for the moral transgression should be universal and objective. The cognitive developmental approach or social domain theory, which has been generally accepted by moral psychology researchers, is recently being challenged. In this article, we introduce three different approaches that criticize the assumptions for the moral-conventional distinction, namely, moral sentimentalism, moral parochialism, and moral pluralism. Moral sentimentalism emphasizes the role of emotion in moral judgment and suggests that moral and conventional norms can be continuously distributed on an affective-nonaffective dimension. Moral parochialism, based on the evidence from anthropology and cross-cultural psychology, asserts that norm transgression can be the object of moral judgment only when the action is relevant to the survival and reproduction of a group and the individuals within the group; judgment for moral transgression can be as relative as that for conventional transgression. Moral pluralism suggests multiple moral intuitions that vary with culture and individual, and questions the assumption of the social domain theory that morality is confined to care and justice. These new perspectives imply that the moral-conventional distinction may not properly tap into the nature of moral judgment and that further research is needed.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.3 s.96
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• pp.215-221
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• 1999

The object of the thermal error compensation system in machine tools is improving the accuracy of a machine tool through real time error compensation. The accuracy of the machine tool totally depends on the accuracy of thermal error model. A thermal error model can be obtained by appropriate combination of temperature variables. The proposed method for optimal variable selection in the thermal error model is based on correlation grouping and successive regression analysis. Collinearity matter is improved with the correlation grouping and the judgment function which minimizes residual mean square is used. The linear model is more robust against measurement noises than an engineering judgement model that includes the higher order terms of variables. The proposed method is more effective for the applications in real time error compensation because of the reduction in computational time, sufficient model accuracy, and the robustness.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.1
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• pp.125-129
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• 2012

In this paper, we propose an intelligent method to surveil moving objects and to judge an unusual-behavior by using network cameras. To surveil moving objects, the Scale Invariant Feature Transform (SIFT) algorithm is used to characterize the feature information of objects. To judge unusual-behaviors, the virtual human skeleton is used to extract the feature points of a human in input images. In this procedure, the Principal Component Analysis (PCA) improves the accuracy of the feature vector and the fuzzy classifier provides the judgement principle of unusual-behaviors. Finally, the experiment results show the effectiveness and the feasibility of the proposed method.

• Language and Information
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• v.11 no.1
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• pp.77-96
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• 2007

This paper investigates syntactic variations in English such as Dative Alternation, Particle Inversion, and Object Postposition (Heavy NP Shift) within the framework of Optimality Theory, and shows that the same set of morphological, informational, and processing constraints affect all these variations. In particular, it shows that the variants that used to be regarded as ungrammatical are in fact used fairly often in reality, especially when processing or informational conditions are met, and therefore, grammatical judgment may not be always categorical but sometimes gradient. It is argued that the notion of distance in constraint ranking in stochastic OT can effectively explain the gradience and variability of grammaticality in the variation phenomena.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.133-135
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• 2022

With the development of IoT and AI technologies and media, various digital devices are being used, and unmanned and automation is progressing rapidly. In particular, high-level image processing technology is required in fields such as smart factories, autonomous driving technology, and intelligent CCTV. However, noise present in the image affects processes such as edge detection and object recognition, and causes deterioration of system accuracy and reliability. In this paper, we propose a filtering algorithm using fuzzy weights to reconstruct images damaged by complex noise. The proposed algorithm obtains a reference value using noise judgment and calculates the final output by applying a fuzzy weight. Simulation was conducted to verify the performance of the proposed algorithm, and the result image was compared with the existing filter algorithm and evaluated.