• Magazine of the Korean Society of Agricultural Engineers
• /
• v.44 no.6
• /
• pp.49-60
• /
• 2002

This study was conducted to estimate the design flood by the determination of best fitting order of LH-moments of the annual maximum series at six and nine watersheds in Korea and Australia, respectively. Adequacy for flood flow data was confirmed by the tests of independence, homogeneity, and outliers. Gumbel (GUM), Generalized Extreme Value (GEV), Generalized Pareto (GPA), and Generalized Logistic (GLO) distributions were applied to get the best fitting frequency distribution for flood flow data. Theoretical bases of L, L1, L2, L3 and L4-moments were derived to estimate the parameters of 4 distributions. L, L1, L2, L3 and L4-moment ratio diagrams (LH-moments ratio diagram) were developed in this study. GEV distribution for the flood flow data of the applied watersheds was confirmed as the best one among others by the LH-moments ratio diagram and Kolmogorov-Smirnov test. Best fitting order of LH-moments will be derived by the confidence analysis of estimated design flood in the second report of this study.

• Korean Journal of Computational Design and Engineering
• /
• v.14 no.1
• /
• pp.10-17
• /
• 2009

Surface detection and parameter estimation in point cloud is a relevant subject in CAD/CAM, reverse engineering, computer vision, coordinate metrology and digital factory. In this paper we present a software for a fully automatic surface detection and parameter estimation in unordered, incomplete and error-contaminated point cloud with a large number of data points. The software consists of three algorithmic modules each for object identification, point segmentation, and model fitting, which work interactively. Our newly developed algorithms for orthogonal distance fitting(ODF) play a fundamental role in each of the three modules. The ODF algorithms estimate the model parameters by minimizing the square sum of the shortest distances between the model feature and the measurement points. We demonstrate the performance of the software on a variety of point clouds generated by laser radar, computer tomography, and stripe-projection method.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.67 no.9
• /
• pp.1232-1238
• /
• 2018

This paper proposes methods for improving mass spectral resolution for a gas chromatograph mass spectrometer. The slope signs of the 1st and 2nd fitting functions for the ion signal block of each mass index are obtained, and the unnecessary element signals in the ion signal block are removed. The spectrum can be obtained by obtaining the second-order fitting function of the reconstructed ion signal block using only the effective ion signals. In addition, the resolution of the mass spectrum can be improved by correcting the error caused by the shift of the spectral peak position. To verify the performance of the proposed methods, computer simulations were performed using the actual ion signals obtained from the GC-MS system under development. Simulation results show that the proposed method is valid.

• Communications of the Korean Mathematical Society
• /
• v.37 no.3
• /
• pp.915-938
• /
• 2022

We are interested in the problem of fitting a parabola to a set of data points in ℝ³. It can be usually solved by minimizing the geometric distances from the fitted parabola to the given data points. In this paper, a parabola fitting algorithm will be proposed in such a way that the sum of the squares of the geometric distances is minimized in ℝ³. Our algorithm is mainly based on the steepest descent technique which determines an adequate number λ such that h(λ) = Q(u - λ𝛁Q(u)) < Q(u). Some numerical examples are given to test our algorithm.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2020.01a
• /
• pp.69-70
• /
• 2020

본 논문에서는 자전거 피팅을 좀 더 정교하고 신속하게 진행하기 위해 자전거 피팅 소프트웨어와 하드웨어를 통합한 시스템을 개발하기 위한 DB구축을 목표로 포괄적인 자전거 피팅 방법의 표준화가 요구됨에 따라 다수의 임상결과와 실험을 통해 이에 맞는 자전거 피팅 방법을 제안한다. 이 자전거 피팅 방법은 심층상담, 자전거체크, 정교한 신체사이징 및 분석을 통해 라이더를 위한 자전거 세팅 값을 결정할 수 있으며 이 세팅 값으로 조정된 자전거에서 고정 라이딩을 통해 자세와 페달링 토크를 분석하고 이을 통해 가장 효율이 높은 세팅 값을 찾아 자전거를 라이더의 요구에 맞게 최적화 할 수 있는 피팅 방법에 대한 결과를 도출 했다. 이와 같은 피팅 방법은 자전거 라이더의 만족도를 높일 수 있으며 정확한 자전거 세팅 값을 통해 부상예방도 기대할 수 있다. 본 논문은 자전거피팅 방법에 대해 국내·외를 통틀어 가장 구체적으로 제시된 결과로 본 논문이 최종 추구하는 자전거피팅 시스템이 구현된다면 글로벌 시장에서도 인정받을 수 있는 자전거 피팅 기술로 자리 잡을 수 있다.

• Proceedings of the Korean Institute of Building Construction Conference
• /
• 2020.06a
• /
• pp.107-108
• /
• 2020

The severity of the global climate crisis is increasing due to greenhouse gases caused by human activities. As a result, countries and industries are making efforts to reduce carbon dioxide emissions, the biggest cause of global warming. Many studies have been conducted to predict carbon emissions in the construction sector to reduce this, but they have not actually produced a highly usable formula in the field. Therefore, the two variables 'Curve Fitting' were performed based on the data of excavators and trucks measured at the field. As a result, we have obtained a carbon dioxide emission prediction model for construction equipment, and we would like to use it to help establish an eco-friendly process plan.

• Journal of Advanced Information Technology and Convergence
• /
• v.9 no.1
• /
• pp.127-134
• /
• 2019

In terms of deep Reinforcement Learning (RL), exploration can be worked stochastically in the action of a state space. On the other hands, exploitation can be done the proportion of well generalization behaviors. The balance of exploration and exploitation is extremely important for better results. The randomly selected action with ε-greedy for exploration has been regarded as a de facto method. There is an alternative method to add noise parameters into a neural network for richer exploration. However, it is not easy to predict or detect over-fitting with the stochastically exploration in the perturbed neural network. Moreover, the well-trained agents in RL do not necessarily prevent or detect over-fitting in the neural network. Therefore, we suggest a novel design of a deep RL by the balance of the exploration with drop-out to reduce over-fitting in the perturbed neural networks.

• Proceedings of the Korean Operations and Management Science Society Conference
• /
• 1994.04a
• /
• pp.147-147
• /
• 1994

• Proceedings of the KIEE Conference
• /
• 1987.07a
• /
• pp.326-328
• /
• 1987

• Journal of the Korea Fashion and Costume Design Association
• /
• v.15 no.3
• /
• pp.137-156
• /
• 2013

The purpose of this study is to analyze the general status of wearing clothes and clothing purchase of middle-aged women in the 40's to 50's, the patterns and colors of clothes they prefer, clothing preference related with fitting or such, and also complaints. And this paper also divides the middle-aged women into those in the 40's and 50's to analyze how they differ in terms of the apparel brands and fitting they prefer and also the status of wearing clothes. For the research, a survey was performed to 350 women, and the survey data went through x2 and t-test analysis by using SPSS 20.0 to examine significant difference. The results of this study are as follows: the women in the 40's included as the subjects showed a high frequency of clothing purchase from casual brands or SPA brands and regarded design to be important at the clothing purchase. Meanwhile, the women in the 50's indicated a higher frequency of clothing purchase of middle-aged women's apparel brands, outdoor brands, madam clothes, or designer brands and thought activity to be crucial at the clothing purchase. As the women in the 40's and 50's showed difference in the brands they preferred, particularly the fitting indicated difference in terms of dissatisfaction. While those in the 40's preferring and buying young casual showed particularly more fitting problems in the arm-hole girth, upper arm circumference, bust size, and thigh or hip area, those in the 50's indicated fitting problems in the hip circumference or waist measurement. It is expected that this study will be used as foundational data to set up the target age by related apparel companies or develop clothes with great size fitting and design satisfaction.