• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1986년도 한국자동제어학술회의논문집; 한국과학기술대학, 충남; 17-18 Oct. 1986
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• pp.119-122
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• 1986

An algorithm is proposed to find a stable rational function, which is frequently used in the linear system theory, by curve-fitting a given data. This problem is essentially a nonolinear optimization problem. In order to converge faster to the solution, the following method is used. First, the coefficients of the denominator polynomial are fixed and only the coefficients of the numerator polynomial are adjusted by its linear relationships. Then the coefficients of the numerator are fixed and the coefficients of the denominator polynomial are adjusted by nonlinear programming. This whole process is repeated until a convergent solution is found. The solution obtained by this method converges better than by other algorithms and its versatility is demonstrated by applying it to the design of a feedback control system and a low pass filter.

• Journal of Information Processing Systems
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• 제16권3호
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• pp.557-571
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• 2020

The existing methods for detection of fire smoke in a video easily lead to misjudgment of cloud, fog and moving distractors, such as a moving person, a moving vehicle and other non-smoke moving objects. Therefore, an algorithm for detection of fire smoke in a video based on wavelet energy slope fitting is proposed in this paper. The change in wavelet energy of the moving target foreground is used as the basis, and a time window of 40 continuous frames is set to fit the wavelet energy slope of the suspected area in every 20 frames, thus establishing a wavelet-energy-based smoke judgment criterion. The experimental data show that the algorithm described in this paper not only can detect smoke more quickly and more accurately, but also can effectively avoid the distraction of cloud, fog and moving object and prevent false alarm.

• 대한가정학회지
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• 제50권7호
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• pp.37-48
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• 2012

The purpose of this study was conducted to improve middle and high school students' satisfaction on their uniforms and to provide basic information for their better size systems. This study analyzed the purchasing and modification behavior, fitting evaluation, and size decision aspect of students. This study was surveyed middle and high schools students in Daegu City. The collected data were analyzed by frequency analysis, percentage, t-test, chisquare test. The results of this study are as follows; 61.3% of the students interviewed have experienced to modify their uniforms. Since the unfittable size and non-fashionable design caused the students to modify their uniforms, it seems necessary to set up the various uniform sizes, as well as figuring out its aesthetic characteristic. Between middle school and high school students, and students with a uniform modification and students without a uniform modification, there were partially differences in fitting evaluation, and size decision.

• 한국의류학회지
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• 제40권5호
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• pp.894-909
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• 2016

This study analyzed a somatotype that was more suitable to a virtual fitting model and to improve the reality of a virtual model size. We analyzed 1,868 women 18-59 years old from the 6th Size Korea data. First, factor analysis was done for abstracting new criteria for dividing the somatotype; subsequently, we selected the waist height proportion to stature (body proportion) and drop (torso shape). Next, the cluster analysis was done with these criteria and 7 body proportion types and 11 torso shapes were distinguished. A virtual model size for the most common somatotype was also developed by a regression analysis of constituting sizes of each factor that was compared with body sizes well as with Clo's virtual model size. The model of this research showed a high similarity in sizes with body as well as improved better realisty than the Clo model which presented size problems such as longer limbs, bigger bust, smaller waist and a smaller arm circumference than the real body.

• Transactions on Control, Automation and Systems Engineering
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• 제3권2호
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• pp.133-138
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• 2001

This paper describes a system that can used to recognize an unknown material regardless of the change of ambient tem-perature using temperature response curve fitting and fuzzy neural network(FNN). There are some problems to realize the recogni-tion system using temperature response. It requires too many memories to store the vast temperature response data and it has to be filtered to remove noise which occurs in experiment. And the temperature response is influenced by the change of ambient tempera-ture. So, this paper proposes a practical method using curve fitting the remove above problems of memories and nose. And FNN is propose to overcome the problem caused by the change of ambient temperature. Using the FNN which is learned by temperature responses on fixed ambient temperature and known thermal conductivity, the thermal conductivity of the material can be inferred on various ambient temperature. So the material can be recognized by the thermal conductivity.

• 대한가정학회지
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• 제44권10호
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• pp.145-154
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• 2006

The purpose of this study was to examine how the garment sizes by junior brand manufactures reflect Tween Generation's (ages from 5th grade to 9th grade) actual body sizes. They have diverse clothing preferences in styles and fitting levels as well as diverse body sizes and shapes. The subjects of this study were 520 students (the 5th and 6th grades in elementary schools, the 1st, 2nd and 3rd grades in middle schools) who lived in Jeonju. A questionnaire was used in this study. The data were analyzed by frequency, means, t-test and $\chi^2$. The results were as follows. In the selection of garment size, both the girl and boy students most preferred selecting garments after trying them on by themselves. Boy students tended to select garment size according to their mothers' advice. On the other hand, elementary school students showed a tendency to select garment size with their mothers. In fitting sizes, middle school girls wanted the size to fit tightly rather than loosely on their bodies much more than elementary school girls. Junior brand manufacturers produced sizes that well reflected actual body sizes of elementary and middle school girls. Specifically, the pants best covered their body sizes.

• 한국컴퓨터정보학회:학술대회논문집
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• 한국컴퓨터정보학회 2018년도 제58차 하계학술대회논문집 26권2호
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• pp.389-390
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• 2018

본 논문에서는 3차원 복원을 위한 특징점 추출 및 매칭에 대한 보다 정확한 방법을 제안한다. 이 방법은 컴퓨터 비전의 기본이 되는 분야로 복원뿐 만 아니라 SLAM과 같은 지도 작성 및 자율 운행에도 필요한 방법이다. 본 연구는 3차원 물체 복원을 위해서 사용하는 방법 중 하나인 Column space fitting(CSF)을 이용하여 turntable-image data에 적용하여 성능을 평가하여 정확성을 검증을 한다. 오늘날 3D scanner를 이용하여 물체를 3차원 모델을 획득하고 3D프린터를 이용하여 다양한 분야에 적용한다. 그러나 고가의 장비이기 때문에 접근성이 떨어진다. 본 연구는 영상들만을 가지고 기하학적 계산을 통해 3차원 모델을 획득한다. 본 연구결과는 기존의 방법인 KLT 알고리즘과 비교하여 RMSE의 값을 약 5배를 줄이는 성능 향상을 보인다.

• 한국자기공명학회논문지
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• 제9권2호
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• pp.93-102
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• 2005

Purpose: To develop an advanced non-linear curve fitting (NLCF) algorithm for dynamic susceptibility contrast study of brain. Materials and Methods: The first pass effects give rise to spuriously high estimates of $K^{trans}$ in voxels with large vascular components. An explicit threshold value has been used to reject voxels. Results: By using this non-linear curve fitting algorithm, the blood perfusion and the volume estimation were accurately evaluated in T2*-weighted dynamic contrast enhanced (DCE)-MR images. From the recalculated each parameters, perfusion weighted image were outlined by using modified non-linear curve fitting algorithm. This results were improved estimation of T2*-weighted dynamic series. Conclusion: The present study demonstrated an improvement of an estimation of kinetic parameters from dynamic contrast-enhanced (DCE) T2*-weighted magnetic resonance imaging data, using contrast agents. The advanced kinetic models include the relation of volume transfer constant $K^{trans}\;(min^{-1})$ and the volume of extravascular extracellular space (EES) per unit volume of tissue $\nu_e$.

• The Journal of Asian Finance, Economics and Business
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• 제8권1호
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• pp.1-6
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• 2021

This research examines the stock market index determinants and the prediction using the FFT curve fitting of the Jakarta Stock Exchange (JKSE) Composite Index during the COVID-19 pandemic. This paper has used daily data of Jakarta Stock Exchange (JKSE) Composite Index, interest rate, and exchange rate from 15 October 2019 to 15 September 2020, and a total of 224 observations, retrieved from Indonesia Stock Exchange (IDX), Indonesia Statistics Central Bureau and Observation & Research of Taxation. The study covers descriptive statistics, multicollinearity test, hypothesis tests, determination test, and prediction using FFT curve fitting. The results unveil four fresh and robust evidence. Partially, the interest rate has affected positively and significantly the stock market index. Partially, the exchange rate has affected negatively and significantly the stock market index. The F-test result, interest rate, and exchange rate have significantly affected the stock market index (JKSE) simultaneously. Furthermore, the FFT curve fitting has predicted that the stock market fluctuates and increases over time. The results have shown a strong influence of the independent variables and the dependent variable. The value of Adjusted R-Square is 0.719, which means that the independent variables have simultaneously impacted the dependent variable for 71.9%; other factors have influenced the remaining 28.1%.

• 대한의용생체공학회:의공학회지
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• 제42권4호
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• pp.159-166
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• 2021

In order to analyze cell images, accurate segmentation of each cell is indispensable. However, the reality is that accurate cell image segmentation is not easy due to various noises, dense cells, and inconsistent shape of cells. Therefore, in this paper, we propose an algorithm that combines marker-based watershed segmentation and ellipse fitting method for glioblastoma cell segmentation. In the proposed algorithm, in order to solve the over-segmentation problem of the existing watershed method, the marker-based watershed technique is primarily performed through "seeding using local minima". In addition, as a second process, the concave point search using ellipse fitting for final segmentation based on the connection line between the concave points has been performed. To evaluate the performance of the proposed algorithm, we compared three algorithms with other algorithms along with the calculation of segmentation accuracy, and we applied the algorithm to other cell image data to check the generalization and propose a solution.