• 지역연구
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• 제12권2호
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• pp.37-57
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• 1996

Intra-metropolitan spatial segmentation of the labor marker requires barriers of mobility on both supply and demand side of the local labor marker. The phenomena of spatial segmentation of the labor market are particularly applied to the secondary workers rather than to the primary workers. Supply side barriers include the costs of obtaining job information regarding jobs outside of the immediate area, commuting costs, and barriers to residential mobility. Demand side barriers include site-specific technology and product demand, and discrimination. In this paper, I discuss these barriers and examine their implications for differences in segmentation by demographic and skill groups at the intra-metropolitan scale. In particular, I apply a job search model to examine supply side barriers such as information and commuting costs, and an implicit contract model to explain demand side barriers such as dual/internal labor market and firms' (re) location strategies.

• 한국감성과학회:학술대회논문집
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• 한국감성과학회 2002년도 추계학술대회 논문집
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• pp.250-254
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• 2002

컴퓨터의 발달과 더불어 인간과 컴퓨터 인터페이스에 있어서도 많은 발전을 하고 있다. 본 연구는 두뇌-컴퓨터 인터페이스(brain-computer interface : BCI)를 위해서 인간에 있어서 가장 간단한 의사문제라고 여겨지는 긍정이나 부정을 선택할 때 나타나는 뇌파를 AR 모델을 이용하여 시간-주파수 분석을 한 후 topographical map을 그렸다. 그 결과 문제에 대답하는 시점 전후에서 파워스펙트럼이 유사하였고, 피험자가 문제를 읽고 판단하고, 동작하는 시점(reaction time : RT) 전으로 1초 ~ 0.5초 사이에 전두엽과 두정엽 부위에서 16Hz ~ 24Hz, 80 ∼ 88Hz의 주파수 대역에서 유의미한 차이를 보였다.

• Communications for Statistical Applications and Methods
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• 제24권2호
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• pp.129-142
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• 2017

In this paper we consider the problem of the model selection/discrimination among three different positively skewed lifetime distributions. Lindley, Weibull, and gamma distributions have been used to effectively analyze positively skewed lifetime data. This paper assesses how much closer the Lindley distribution gets to Weibull and gamma distributions. We consider three techniques that involve the likelihood ratio test, asymptotic likelihood ratio test, and minimum Kolmogorov distance as optimality criteria to diagnose the appropriate fitting model among the three distributions for a given data set. Monte Carlo simulation study is performed for computing the probability of correct selection based on the considered optimality criteria among these families of distributions for various choices of sample sizes and shape parameters. It is observed that overall, the Lindley distribution is closer to Weibull distribution in the sense of likelihood ratio and Kolmogorov criteria. A real data set is presented and analyzed for illustrative purposes.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1998년도 제13차 학술회의논문집
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• pp.167-172
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• 1998

The physical parameters of controlled systems are uncertain and are accompanied with nonlinearity. The transfer function of the controlled system should, therefore, be expressed by interval polynomials. This paper describes the realization of robust performance for that type of control system (interval system) via model reference feedback. First, we will analyze an invariance problem of dynamic characteristics such that the dominant roots do not break away from a specified circular area, and will present a discrimination algorithm (i.e., a division algorithm) for the extreme points of the uncertain coefficients. Then, we will present a design method of control systems which have a robust performance such that the location of the dominant roots dose not vary excessively.

• 대한전기학회논문지:시스템및제어부문D
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• 제52권5호
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• pp.277-282
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• 2003

In this paper we propose Using Higher Order Neuron on the Supervised Learning Machine of the Kohonen Feature Map. The architecture of proposed model adopts the higher order neuron in the input layer of Kohonen Feature Map as a Supervised Learning Machine. It is able to estimate boundary on input pattern space because or the higher order neuron. However, it suffers from a problem that the number of neuron weight increases because of the higher order neuron in the input layer. In this time, we solved this problem by placing the second order neuron among the higher order neuron. The feature of the higher order neuron can be mapped similar inputs on the Kohonen Feature Map. It also is the network with topological mapping. We have simulated the proposed model in respect of the recognition rate by XOR problem, discrimination of 20 alphabet patterns, Mirror Symmetry problem, and numerical letters Pattern Problem.

• 대한원격탐사학회지
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• 제19권5호
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• pp.381-392
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• 2003

Multi-temporal approaches using sequential data acquired over multiple years are essential for satisfactory discrimination between many land-cover classes whose signatures exhibit seasonal trends. At any particular time, the response of several classes may be indistinguishable. A harmonic model that can represent seasonal variability is characterized by four components: mean level, frequency, phase and amplitude. The trigonometric components of the harmonic function inherently contain temporal information about changes in land-cover characteristics. Using the estimates which are obtained from sequential images through spectral analysis, seasonal periodicity can be incorporates into multi-temporal classification. The Normalized Difference Vegetation Index (NDVI) was computed for one week composites of the Advanced Very High Resolution Radiometer (AVHRR) imagery over the Korean peninsula for 1996 ～ 2000 using a dynamic technique. Land-cover types were then classified both with the estimated harmonic components using an unsupervised classification approach based on a hierarchical clustering algorithm. The results of the classification using the harmonic components show that the new approach is potentially very effective for identifying land-cover types by the analysis of its multi-temporal behavior.

• ETRI Journal
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• 제41권4호
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• pp.483-493
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• 2019

Considering the high dimensions of video sequences, it is often challenging to acquire a sufficient dataset to train the tracking models. From this perspective, we propose to revisit the idea of hand-crafted feature learning to avoid such a requirement from a dataset. The proposed tracking approach is composed of two phases, detection and tracking, according to how severely the appearance of a target changes. The detection phase addresses severe and rapid variations by learning a new appearance model that classifies the pixels into foreground (or target) and background. We further combine the raw pixel features of the color intensity and spatial location with convolutional feature activations for robust target representation. The tracking phase tracks a target by searching for frame regions where the best pixel-level agreement to the model learned from the detection phase is achieved. Our two-phase approach results in efficient and accurate tracking, outperforming recent methods in various challenging cases of target appearance changes.

• International Journal of Computer Science & Network Security
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• 제21권7호
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• pp.93-102
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• 2021

This study aimed to test method on the accuracy of estimating the items parameters and ability, using the Three Parameter Logistic. To achieve the objectives of the study, an achievement test in chemistry was constructed for third-year secondary school students in the course of "natural sciences". A descriptive approach was employed to conduct the study. The test was applied to a sample of (507) students of the third year of secondary school in the "Natural Sciences Course". The study's results revealed that the (EAP) method showed a higher degree of accuracy in the estimation of the difficulty parameter and the abilities of persons higher than the MML method. There were no statistically significant differences in the accuracy of the parameter estimation of discrimination and guessing regarding the difference of the two methods: (MML) and (EAP).

• 한국안전학회지
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• 제38권1호
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• pp.1-8
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• 2023

It is extremely important to design safety-guaranteed industrial processes because such process determine the ultimate outcomes of industrial activities, including worker safety. Application of artificial intelligence (AI) in industrial safety involves modeling industrial safety systems by using vast amounts of safety-related data, accident prediction, and accident prevention based on predictions. As a preliminary step toward realizing AI-based industrial safety in Korea, this study discusses neural network-based modeling of industrial safety systems. The input variables that are the most discriminatory relative to the output variables of industrial safety processes are selected using two information-theoretic measures, namely entropy and cross entropy. Normalized frequency and severity of industrial accidents are selected as the output variables. Our simulation results confirm the effectiveness of the proposed neural network model and, therefore, the feasibility of extending the model to include more input and output variables.

• 국제학술발표논문집
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• The 2th International Conference on Construction Engineering and Project Management
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• pp.366-375
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• 2007

Our nation has a problem with discrimination of income distribution and inefficient of resources distribution caused by real estate price rising from a sudden economy growth and industrialization. Specially, in recent years, there is a great disparity of condominium price between the north and south of the Han river. Because the housing price is deciede by the immanent value of a house and neighborhood effects of the regional where the house is situated, the housing price is occurred difference. In this study, I analyzed the differences of housing price determinants about condominium developments in the old and new residential areas, and found the important factors that affect the condominium price using Structural Equation Modeling(SEM) The purpose of study is to analyze the influence of various factors of housing price. Also, this study tried to predict real estate market and to establish previous effective real estate policy.