• Journal of Electrical Engineering and Technology
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• 제13권3호
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• pp.1304-1316
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• 2018

An adaptive sliding-mode observer for speed estimation in sensorless vector controlled induction machine drives is proposed in this paper to balance the dilemma between the requirement of fast reaching transient and the chattering phenomenon reduction on the sliding-mode surface. It is well known that the sliding-mode observer (SMO) suffers from the chattering phenomenon. However, the reduction of the chattering phenomenon will lead to a slow transient process. In order to balance this dilemma, an adaptive exponential reaching law is introduced into SMO by optimizing the reaching way to the sliding-mode surface. The adaptive exponential reaching law is based on the options of an exponential term that adapts to the variations of the sliding-mode surface and system states. Moreover, the proposed sliding-mode observer considering adaptive exponential reaching law, which is called adaptive sliding-mode observer (ASMO), is capable for reducing the chattering phenomenon and decreasing the reaching time simultaneously. The stability analysis for ASMO is achieved based on Lyapunov stability theory. Simulation and experimental results both demonstrate the correctness and the effectiveness of the proposed method.

• 한국양식학회지
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• 제10권3호
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• pp.301-310
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• 1997

황해서식 두족류 (class Cephalopoda)의 가용성 단백질에 대한 연구를 위해, 인천 및 목포 연근해에서 채집된 두족류 3목 5종의 (오징어목 : 참갑오징어 (Sepia esculenta) 및 쇠갑오징어 (Sepiella japonica), 살오징어목 : 한치꼴뚜기 (Loligo chinensis) 및 참꼴뚜기 (Loligo beka), 문어목 : 낙지 (Octopus minor)의 안구단백질, 근육단백질 및 간조직을 추출하여, 각종 전기영동 (Davis-PAGE 및 SDS-PAGE, Exponential gradient SDS-PAGE, 등전점 전기영동, 2차원 전기영동) 방법에 의한 단백질 분리 양상을 통해 두족류 종사이의 유전적 근연관계를 분석하였다. 시료의 안구 및 근육 단백질에 대한 exponential gradient SDS-PAGE 전기영동 결과 대략 분자량 35-50 KDa 사이에서 단백질 분리 양상의 차이를 볼 수 있었으며, 등전점 전기영동 방법(IEF)에 의해서는 pI값 7.5-8.5 사이에서 종간 특이성을 갖는 단백질 분리 양상을 볼 수 있었다. 특히 유의성이 있다고 판단된 시료의 안구 단백질을 2차원 전기영동 방법에 의해 분리 해 본 결과 대부분 분자량 30-50 KDa 사이에 분포하고 있어 exponential gradient SDS-PAGE 전기 영동에 의한 결과와 일치함을 알 수 있었다.

• 한국컴퓨터정보학회논문지
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• 제11권5호
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• pp.9-18
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• 2006

유한고장수를 가진 비동질적인 포아송 과정에 기초한 모형들에서 잔존 결함 1개당 고장 발생률은 일반적으로 상수, 혹은 단조증가 및 단조 감소 추세를 가지고 있다. 본 논문에서는 기존의 소프트웨어 신뢰성 모형인 Goel-Okumoto 모형과 Yamada-Ohba-Osaki 모형을 재조명하고 최근에 Gupta 와 Kundu(2001)에 의해서 2 모수 감마분포나 와이블 분포의 대체모형으로서 여러 가지 수명자료를 분석함에 있어서 효율적 분포가 됨이 밝혀진 지수화된 지수 분포를 이용한 모형을 제안하였다. 고장 간격시간으로 구성된 자료를 이용한 모수추정 방법은 최우추정법과 일반적인 수치해석 방법인 이분법을 사용하여 모수 추정을 실시하고 효율적인 모형 선택은 편차자승합(SSE), AIC 통계량 및 콜모고로프 거리를 적용하여 모형들에 대한 효율성 입증방법을 설명하였다. 소프트웨어 고장 자료 분석에서는 NTDS 자료를 통하여 분석하였다. 이 자료들에서 기존의 모형과 지수화된 지수 분포 모형의 비교를 위하여 산술적 및 라플라스 검정, 편의 검정 등을 이용하였다.

• 한국수학교육학회지시리즈D:수학교육연구
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• 제26권3호
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• pp.253-270
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• 2023

This study aims to investigate the extent to which Korean high school textbooks incorporate opportunities for students to engage in the mathematical modeling process through tasks related to exponential and logarithmic functions. The tasks in three textbooks were analyzed based on the actions required for each stage in the mathematical modeling process, which includes identifying essential variables, formulating models, performing operations, interpreting results, and validating the outcomes. The study identified 324 units across the three textbooks, and the reliability coefficient was 0.869, indicating a high level of agreement in the coding process. The analysis revealed that the distribution of tasks requiring engagement in each of the five stages was similar in all three textbooks, reflecting the 2015 revised curriculum and national curriculum system. Among the 324 analyzed tasks, the highest proportion of the units required performing operations found in the mathematical modeling process. The findings suggest a need to include high-quality tasks that allow students to experience the entire process of mathematical modeling and to acknowledge the limitations of textbooks in providing appropriate opportunities for mathematical modeling with a heavy emphasis on performing operations. These results provide implications for the development of mathematical modeling activities and the reconstruction of textbook tasks in school mathematics, emphasizing the need to enhance opportunities for students to engage in mathematical modeling tasks and for teachers to provide support for students in the tasks.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제16권9호
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• pp.2991-3007
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• 2022

Two dimensional locality preserving projections (2D-LPP) is an improved algorithm of 2D image to solve the small sample size (SSS) problems which locality preserving projections (LPP) meets. It's able to find the low dimension manifold mapping that not only preserves local information but also detects manifold embedded in original data spaces. However, 2D-LPP is simple and elegant. So, inspired by the comparison experiments between two dimensional linear discriminant analysis (2D-LDA) and linear discriminant analysis (LDA) which indicated that matrix based methods don't always perform better even when training samples are limited, we surmise 2D-LPP may meet the same limitation as 2D-LDA and propose a novel matrix exponential method to enhance the performance of 2D-LPP. 2D-MELPP is equivalent to employing distance diffusion mapping to transform original images into a new space, and margins between labels are broadened, which is beneficial for solving classification problems. Nonetheless, the computational time complexity of 2D-MELPP is extremely high. In this paper, we replace some of matrix multiplications with multiple multiplications to save the memory cost and provide an efficient way for solving 2D-MELPP. We test it on public databases: random 3D data set, ORL, AR face database and Polyu Palmprint database and compare it with other 2D methods like 2D-LDA, 2D-LPP and 1D methods like LPP and exponential locality preserving projections (ELPP), finding it outperforms than others in recognition accuracy. We also compare different dimensions of projection vector and record the cost time on the ORL, AR face database and Polyu Palmprint database. The experiment results above proves that our advanced algorithm has a better performance on 3 independent public databases.

• Bulletin of the Korean Chemical Society
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• 제32권2호
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• pp.524-530
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• 2011

In the present study, we demonstrate that SRM LC-MS/MS method developed by Luo et al. (ref. 10) can be successfully applied to the quantitative analysis of intracellular metabolites in E. coli that are collected at the exponential and stationary growth phases. A focus is given on measuring the changes in the concentrations of intracellular metabolites in batch cultures, which were induced during both the dynamically changing exponential and stationary growth phases. The following intracellular metabolites are quantified in the exponential and stationary phases of E. coli growth, using the SRM mode of a triple quadrupole mass spectrometer: glucose-1-phosphate, fructose-1,6-bisphosphate, phosphoenolpyruvate, pyruvate, acetyl-coenzyme A, 6-phosphogluconate, ribulose-5-phosphate, xylulose-5-phosphate, erythrose-4-phosphate. The determined intracellular metabolite concentration profiles are shown to be in a good agreement with the growth profiles of E. coli, which clearly indicates that SRM LC-MS/MS can be successfully used for following the metabolite changes induced at different growth stages.

• Journal of the Korean Data and Information Science Society
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• 제25권2호
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• pp.393-402
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• 2014

수명시간 분석에서 자주 이용되는 분포 중 하나는 지수분포이다. 본 논문에서는 임의중도절단 자료의 분석에서 중도절단모형이 지수분포의 모수추정에 어떤 영향을 주는지에 대해서 알아보았다. 고려한 중도절단모형은 Koziol-Green 모형과 일반화 지수분포 모형으로 이들은 의미상 매우 다른 모형이다. 모의실험을 통해서 살펴본 결과 중도절단모형이 모수의 평균적인 추정값에는 크게 영향을 주지 않는다고 보이나 가정한 모형이 실제의 모형과 차이가 심하게 나는 경우 추정량의 MSE가 커지는 경향을 보였다.

• 전기학회논문지
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• 제62권2호
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• pp.149-154
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• 2013

Short term load forecasting for electric power demand is essential for stable power system operation and efficient power market operation. High accuracy of the short term load forecasting can keep the power system more stable and save the power market operation cost. We propose an optimal coefficient selection method for exponential smoothing model in short term load forecasting on weekdays. In order to find the optimal coefficient of exponential smoothing model, load forecasting errors are minimized for actual electric load demand data of last three years. The proposed method are verified by case studies for last three years from 2009 to 2011. The results of case studies show that the average percentage errors of the proposed load forecasting method are improved comparing with errors of the previous methods.

• 한국품질경영학회:학술대회논문집
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• 한국품질경영학회 1998년도 The 12th Asia Quality Management Symposium* Total Quality Management for Restoring Competitiveness
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• pp.225-232
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• 1998

A Markov Chain Monte Carlo method with data augmentation is developed to compute the features of the posterior distribution. This data augmentation approach facilitates the specification of the transitional measure in the Markov Chain. Bayesian analysis of the mixture exponential model discusses using the Gibbs sampler. Parameter and reliability estimators are obtained. A numerical study is provided.

• Journal of the Korean Data and Information Science Society
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• 제23권5호
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• pp.1017-1025
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• 2012

We consider estimations for the reliability in two independent variables with Pareto and uniform or exponential distributions. And then we compare the mean squared errors of two reliability estimators for each case. We also observe the skewness of densities of the ratio for each case.