• East Asian mathematical journal
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• v.24 no.4
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• pp.359-368
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• 2008

The object of this paper is to establish a unique common fixed point theorem through weak compatibility for a sequence of self-maps satisfying a generalized contractive condition in a generalized Menger space. It improves and generalizes the result of Milovanovic-Arandelovic [2], Vasuki [10] and Sehgal and Bharucha-Reid [8]. All the results presented in this paper are new.

• Journal of Platform Technology
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• v.9 no.2
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• pp.46-54
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• 2021

Recently, interest in the safety of Self-driving has been increasing. Self-driving have been studied and developed by many universities, research centers, car companies, and companies of other industries around the world since the middle 1980s. In this study, we propose the automatic extraction method of the threatening obstacle on the Road for the Self-driving. A threatening obstacle is defined in this study as a comparatively large object at center of the image. First of all, an input image and its decreased resolution images are segmented. Segmented areas are classified as the outer or the inner area. The outer area is adjacent to boundaries of the image and the other is not. Each area is merged with its neighbors when adjacent areas are included by a same area in the decreased resolution image. The Obstacle area and Non Obstacle area are selected from the inner area and outer area respectively. Obstacle areas are the representative areas for the obstacle and are selected by using the information about the area size and location. The Obstacle area and Non Obstacle area consist of the threatening obstacle on the road. Through experiments, we expect that the proposed method will be able to reduce accidents and casualties in Self-driving.

• Journal of the Korean Society of Combustion
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• v.4 no.1
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• pp.105-115
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• 1999

The structure of a non-axisymmetric propane diffusion flame was investigated. Tomographic reconstruction method to convert the line-integrated self-emission data of a fuel-rich diffusion flame with square cross-section was applied to get the spatially reconstructed emission data. Modified Shepp-Logan filter and concentric squares raster were chosen for reconstructing arbitrarily shaped object in this process. Spatially reconstructed emission data were then interpreted to several physical quantities, such as flame edge, FWHM, perimeter and 3-D flame temperature distribution. Necessary assumptions were discussed and the results were interpreted. In comparison with axisymmetric flame, flame edge was developed higher, and sooting region of upstream was broader than in this non-axisymmetric one. At some height, the flame was shrunk very rapidly and finally formed circular cross-section.

• Journal of Family Resource Management and Policy Review
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• v.5 no.2
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• pp.45-57
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• 2001

The object of this study is to understand the determinants of housewives’internet usage, examining empirically their internet usage motivation and activity, and to find the way to promote housewives’internet usage. The major findings of this study can be summarized as follows; 1) the housewives’internet usage motivation was composed of the motivation to make a good use of leisure by internet, self-developmental, practical, and children educational motivations. The mean score of self-developmental motivation was the highest in the internet users and that of child educational motivation was the highest in the non-internet users. 2) the significant variables which affected on the internee usage of housewives were age, internet related housing environment the perception of internet usefulness, internet usage of husband, the motivation to make a good use of leisure by internet, and children educational motivation.

• Journal of the Korean Society of Costume
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• v.51 no.1
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• pp.163-174
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• 2001

The purpose of this study is to review the features of eroticism expressed in men's fashion, to explain psychological and social contexts which engender eroticism and to analyze in what way eroticism is portrayed in men s fashion in this context. Eroticism as the metonymy of forbidden sexual desire, has been embodied mostly in visual forms such as picture and photo. From a psychoanalytic view, the context in which eroticism is formed can be explained by primary narcissism and fetishism. Primary narcissism is the feeling of satisfaction with the self in which the subject who is admiring and the object of admiration are one and the same. Accordingly, in order to give rise to eroticism, both subject and object have to exist. Fetishism, the metonymy of castrated penis, is also one of the factors to produce eroticism. Metaphorically seen as a woman who has a penis, a man who dresses in the same manner as a woman dresses can be a source of eroticism to gays. From a sociological view, the context in which eroticism is fostered depends on the dynamic relations among social powers. In these relations, who is a subject or who is an object has been continuously changing. In the Post-modern culture appearing in the late 20th century, power begins to take various forms, and gays and women who had never been subjects begin to make man an object of eroticism. The other point is that social morality, ignoring desire itself, objectifies sexual desire and seeks to remove It by exchanging it for objectified symbols. The design elements provoking eroticism in men s fashion are exposure and decoration. In particular, models in exposure and decorative fashion have been objectified through the methods of fragmentation rather than showing the whole figure or removing a person s individuality or will,.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.3
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• pp.389-395
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• 2022

Because of improvement of deep learning techniques, deep learning using computer vision such as classification, detection and segmentation has also been used widely at many fields. Expecially, automatic driving is one of the major fields that applies computer vision systems. Also there are a lot of works and researches to combine multiple tasks in a single network. In this study, we propose the network that predicts the individual depth of pedestrians and vehicles. Proposed model is constructed based on YOLOv3 for object detection and Monodepth for depth estimation, and it process object detection and depth estimation consequently using encoder and decoder based on hard parameter sharing. We also used attention module to improve the accuracy of both object detection and depth estimation. Depth is predicted with monocular image, and is trained using self-supervised training method.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.168.1-168
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• 2001

This article describes a novel model-based compensating neural network (NN) model developed to be used in our active binocular head controller, which addresses both the kinematics and dynamics aspects in trying to precisely track a moving object of interest to keep it in view. The compensating NN model is constructed using two classes of self-tuning neural models: namely Neural Gas (NG) algorithm and SoftMax function networks. The resultant servo controller is shown to be able to handle the tracking problem with a minimum knowledge of the dynamic aspects of the system.

• Publications of The Korean Astronomical Society
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• v.17 no.1
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• pp.11-14
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• 2002

Our examination of the relations of spherically symmetric accretion on a massive point object to viscous drag, neglecting gas pressure and using self-similar transformation, shows the behaviors of the asymptotic solutions? in the regions near to and far from the center. The viscosity reduces the free-fall velocity by the factor $(1\;+\;\zeta) ^{-1}$, and causes flattening in the density distribution. Therefore, the viscosity leads to the reduction of the mass accretion rate.

• Journal of the Optical Society of Korea
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• v.10 no.4
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• pp.178-183
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• 2006

An in-line phase-shifting digital holographic microscopy system was constructed by inserting a conventional microscope in the object arm of a Mach-Zehnder interferometer. It was used to measure the three dimensional shape of a micro Fresnel lens. It was also shown that both the lateral and the axial resolutions of the in-line phase-shifting system using a self-calibration algorithm were superior to those of the best off-axis system.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.12
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• pp.561-568
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• 2021

In recent years, autonomous driving technologies have become a high-value-added technology that attracts attention in the fields of science and industry. For smooth Self-driving, it is necessary to accurately detect an object and estimate its movement speed in real time. CNN-based deep learning algorithms and conventional dense optical flows have a large consumption time, making it difficult to detect objects and estimate its movement speed in real time. In this paper, using a single camera image, fast object detection was performed using the YOLOv5 algorithm, a deep learning algorithm, and fast estimation of the speed of the object was performed by using a local dense optical flow modified from the existing dense optical flow based on the detected object. Based on this algorithm, we present a system that can predict the collision time and probability, and through this system, we intend to contribute to prevent tram accidents.