• Tunnel and Underground Space
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• v.32 no.6
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• pp.386-396
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• 2022

To analyze the influence of variables of roadheaders, the linear cutting testing data of pick cutter were collected from the former literatures. The input factors were set up as uniaxial compressive strength, cutting depth, cutting spacing, attack angle, skew angle, and output factors were determined as specific energy, average cutting force, maximum cutting force, average vertical force, and maximum vertical force. After composing a table of the design of experiment (DOE). The contribution level of each factor was calculated by analysis of variance (ANOVA). As a result, the factors having greatest influence on cutting force and specific energy were uniaxial compressive strength and cutting spacing.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.2
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• pp.185-191
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• 2004

Partial least squares(PLS) is one of multiplicate statistical process methods and has been developed in various algorithms with the characteristics of principal component analysis, dimensionality reduction, and analysis of the relationship between input variables and output variables. But it has been limited somewhat by their dependency on linear mathematics. The algorithm is proposed to classify for the non-linear data using PLS and the residual compensator(RC) based on radial basis function network (RBFN). It compensates for the error of the non-linear data using the RC based on RBFN. The experimental result is given to verify its efficiency compared with those of previous works.

• 한국HCI학회:학술대회논문집
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• 2007.02a
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• pp.649-652
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• 2007

이 논문에서는 영화, CF 같은 영상물 제작 시 CG/실사 합성을 위해 배경기하정보를 추출하는 알고리즘을 제안한다. Metric Reconstruction 은 카메라 자동 보정을 통해 이루어지며 이는 오랫동안 연구되어 온 분야이다. 접근방법은 영상의 특징점 추적 정보와 카메라 내부변수 가정으로부터 유도되는 자기 보정 방식과 공간상에서 미리 기하 정보를 알고 있는 보정틀을 사용하는 방식으로 크게 분류될 수 있다. CG/실사 합성의 작업 효율성을 위해서는 배경 영상에 보정틀이 보이지 않는 것이 좋은데 자연 특징점(Natural Feature)에만 의존하는 자기 보정 방식의 경우 2K 급 영상에서 CG 객체를 합성했을 때 떨림이 느껴지지 않을 만큼 정확한 결과를 얻기 힘들다. 이 논문에서는 Polleyfeys[2]가 제안하였던 영상 시퀀스를 입력으로 하는 자기 보정 시스템을 바탕으로 마야 작업 환경에서의 핀홀 카메라 모델에 맞도록 카메라 내부변수의 비선형 최적화를 수행하는 방법과 사용자 개입을 통한 카메라 변수 정확도 향상방법을 제안한다.

• Proceedings of the Korean Information Science Society Conference
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• 2000.10b
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• pp.431-433
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• 2000

본 논문에서는 얼굴인식에 주로 사용되는 PCA를 얼굴포즈판별로 적용해 보았다. 얼굴포즈판별은 개개인의 얼굴특징을 강조해야 하는 얼굴인식과는 달리 일반적인 얼굴특징을 이용하기 때문에 PCA에 적합한 응용분야이다. 그러나, 다양한 얼굴포즈에 대한 영상을 하나의 표본집합으로 사용하면, 표본집합의 분산이 크기 때문에 포즈별로 표본집합을 달리하여 PCA모듈을 구성하는 것이 타당하다. 표본수집의 어려움은 3차원 한국인 표준모형을 이용해 극복하고, 이를 통하여 다양한 조명방향 및 얼굴포즈에 대한 표본을 수집하였다. 5방향의 얼굴포즈에 대한 판별 실험을 통하여 모율화된 PCA의 분류기로서의 가능성을 살펴보고, 조명에 따른 오류를 완하하고자 비 선형적 패턴을 나타내는 각 PCA모듈의 결과를 신경망에 적용하여 보았다.

• The KIPS Transactions:PartB
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• v.10B no.6
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• pp.657-664
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• 2003

Reliable tracking of moving humans is essential to motion estimation, video surveillance and human-computer interface. This paper presents a new approach to human motion tracking that combines appearance-based and model-based techniques. Monocular color video is processed at both pixel level and object level. At the pixel level, a Gaussian mixture model is used to train and classily individual pixel colors. At the object level, a 3D human body model projected on a 2D image plane is used to fit the image data. Our method does not use inverse kinematics due to the singularity problem. While many others use stochastic sampling for model-based motion tracking, our method is purely dependent on nonlinear programming. We convert the human motion tracking problem into a nonlinear programming problem. A cost function for parameter optimization is used to estimate the degree of the overlapping between the foreground input image silhouette and a projected 3D model body silhouette. The overlapping is computed using computational geometry by converting a set of pixels from the image domain to a polygon in the real projection plane domain. Our method is used to recognize various human motions. Motion tracking results from video sequences are very encouraging.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.6
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• pp.1135-1141
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• 2004

In this study, this system makes use of the analog infrared rays sensor and converts the feature of fish outline when sensor is operating with CPU(80C196KC). Then, after signal processing, this feature is classified a special feature and a outline of fish by using the neural network, one of the artificial intelligence scheme. This neural network classifies fish pattern of very simple and short calculation. This has linear activation function and the error back propagation is used as a teaming algorithm. And the neural network is learned in off-line process. Because an adaptation period of neural network is too long when random initial weights are used, off-line teaming is induced to decrease the progress time.

• The Transactions of the Korean Institute of Power Electronics
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• v.11 no.6
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• pp.535-542
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• 2006

A large signal stability analysis of the solar array regulator system is performed to facilitate the design and analysis of a Low-Earth-Orbit satellite power system. The effective load characteristics of every controllable method in the solar array system are classified to analyze the large signal stability. Then, using the state plane analysis technique, the stability of various equilibrium points is analyzed. A nonlinear transformation algorithm, which changes the effective load characteristic of the solar array regulator as constant resistive load, is also proposed for the large signal stability. The proposed resistive current mode control system can control the solar array output for purposes such as peak power tracking control and battery charging control. For the verification of the proposed large signal analysis and resistive current mode control, a solar array regulator system consisting of two 100W parallel module buck converters has been built and tested using a real 200W solar array.

• Korean Journal of Environmental Biology
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• v.34 no.2
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• pp.79-90
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• 2016

This study investigates seasonal variation and spatial distribution of meiobenthic community of Gamak Bay (one of the major bays of southern coastal area of Korea). Total of 6 surveys of 10 stations took place, once in February, June and October of 2009 and through 2010. Community structure, taxon diversity (H') and nematodes/copepods ratio of meiobenthos were studied in Gamak Bay. During the study period, nematodes and harpacticoids were the most dominant taxa among the meiofaunal groups in Gamak Bay. Taxon diversity (H') was the highest at the outer stations and the lowest at the inner stations in the Gamak Bay. The nematodes/copepods ratio was seasonally studied as an index of pollution monitoring for the benthic ecosystem at each station. As a result, nematodes/copepods ratio was the highest at the inner stations and the lowest at the outer stations in Gamak Bay.

• Management & Information Systems Review
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• v.39 no.1
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• pp.35-57
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• 2020

Recently, research F&E(Facilities and Equipment) have become very important as tools and means to lead the development of science and technology. The government has been continuously expanding investment budgets for R&D and research F&E, and the need for efficient operation and systematic management of research F&E built up nationwide has increased. In December 2010, The government developed and completed a standardized classification system for national research F&E. However, accuracy and trust of information classification are suspected because information is collected by a method in which a user(researcher) directly selects and registers a classification code in NTIS. Therefore, in the study, we analyzed linearly using linear discriminant analysis(LDA) and analysis of variance(ANOVA), to measure the classification accuracy for the standardized classification system(8 major-classes, 54 sub-classes, 410 small-classes) of the national research facilities and equipment established in 2010, and revised in 2015. For the analysis, we collected and used the information data(50,271 cases) cumulatively registered in NTIS(National Science and Technology Service) for the past 10 years. This is the first case of scientifically verifying the standardized classification system of the national research facilities and equipment, which is based on information of similar classification systems and a few expert reviews in the in-outside of the country. As a result of this study, the discriminant accuracy of major-classes organized hierarchically by sub-classes and small-classes was 92.2 %, which was very high. However, in post hoc verification through analysis of variance, the discrimination power of two classes out of eight major-classes was rather low. It is expected that the standardized classification system of the national research facilities and equipment will be improved through this study.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.19 no.4
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• pp.91-97
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• 2005

As the developing of industry, the nonlinear equipments as inverter, converter, SMPS(Switching Mode Power Supply) and motor have been increased. But the sensitive electronic loads to the power quality, such as computers and other electronic equipments, have been spreaded out very fast. Thus, the power quality(PQ) problems and the real time power quality monitering(PQM) are one of the important issues in industry and building area for the intelligent control of the systems. One of them, PQM using PLC(Power Line Communication) have good merits that can send and receive the PQ information without any new network line. This paper presents the PQM hardware and software to monitor the PQ information by using PLC that meets the categories of IEEE Std. 1159.