• Journal of Biosystems Engineering
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• 제29권6호
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• pp.515-520
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• 2004

A device far estimating the optimal artificial insemination time consisted of a computer, RS module, and six direct-reflex photo-sensors. Program was written in LabWindows CVI. In order to establish references for estimating optimal artificial insemination time, lying rate of the thirty three $Berkshire{\times}Hampshire crossbred sows (parity 5 to 6) was recorded from 2 days after moving into stalls to artificial insemination using a time lapse VCR and was measured every hour with one minute interval using the scan point sampling method. Twenty low hours in a day were divided into three comparing periods : 21:00 to 06:59, 07:00 to 13:59, and 14:00 to 20:59. If sum of the percentages of tying during a comparing period was less than the reference value, the starting hour of the comparing period was considered as onset of estrus and the optimal artificial insemination time was estimated at 20 to 24 hours after onset of estrus. The experimental device was evaluated with twenty five $Berkshire{\times}Hampshire$ crossbred sows (parity 2 to 7) and 23 of 25 sows $(92\%)$ were pregnant. This result suggests that the experimental device is excellent in performance for estimating optimal artificial insemination time.

• Smart Structures and Systems
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• 제22권2호
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• pp.231-237
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• 2018

A significant data problem is encountered with condition monitoring because the sensors need to measure vibration data at a continuous and sometimes high sampling rate. In this study, compressive sensing approaches for condition monitoring are proposed to demonstrate their efficiency in handling a large amount of data and to improve the damage detection capability of the current condition monitoring process. Compressive sensing is a novel sensing/sampling paradigm that takes much fewer data than traditional data sampling methods. This sensing paradigm is applied to condition monitoring with an improved machine learning algorithm in this study. For the experiments, a built-in rotating system was used, and all data were compressively sampled to obtain compressed data. The optimal signal features were then selected without the signal reconstruction process. For damage classification, we used the Variance Considered Machine, utilizing only the compressed data. The experimental results show that the proposed compressive sensing method could effectively improve the data processing speed and the accuracy of condition monitoring of rotating systems.

• 한국소음진동공학회논문집
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• 제26권6_spc호
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• pp.651-659
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• 2016

Condition monitoring (CM) encounters a large data problem due to sensors that measure vibration data with a continuous, and sometimes, high sampling rate. In this study, compressive sensing approaches for condition monitoring are proposed to demonstrate the efficiency in handling a large amount of data and to improve the damage detection capability of the current condition monitoring process. Compressive sensing is a novel sensing/sampling paradigm that takes much fewer samples compared to traditional sampling methods. For the experiments a built-in rotating system was used and all data were compressively sampled to obtain compressed data. Optimal signal features were then selected without the reconstruction process and were used to detect and classify damage. The experimental results show that the proposed method could improve the data processing speed and the accuracy of condition monitoring of rotating systems.

• 응용통계연구
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• 제27권3호
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• pp.501-512
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• 2014

상당수의 사업체 조사는 절사표본설계법을 사용하고 있다. 이는 절사표본설계법에서 얻은 전수층이 많은 정보를 포함하고 있어 전체 표본크기를 최소화 할 수 있는 장점이 있기 때문이다. 그러나 최근 전수층에 포함된 사업체들의 무응답률이 높아감에 따라 전수층이 가지고 있는 장점에 한계가 나타나고 있다. 이에 Lee (2011), Shin과 Lee (2013)는 표본설계 단계에서부터 주어진 허용오차를 만족하면서 전수층 규모를 최소화하는 연구를 실시하였다. 본 연구에서는 주어진 허용오차를 만족하고 Hidiroglou (1986)가 제안한 방법으로 산출 된 표본크기를 고정한 상태에서 표본층 분산에 알려진 함수를 적합하여 전수층 크기를 최소화하는 새로운 최적 절사점을 제안하였다. 또한 Hidiroglou (1986)와 Shin과 Lee (2013)가 제안한 절단분포를 이용한 방법과 본 연구에서 제안한 방법을 모의실험과 사례연구를 통해 비교하였다.

• 디지털산업정보학회논문지
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• 제13권4호
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• pp.91-98
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• 2017

Previous works for detecting arrhythmia have mostly used nonlinear method such as artificial neural network, fuzzy theory, support vector machine to increase classification accuracy. Most methods require higher computational cost and larger processing time. Therefore it is necessary to design efficient algorithm that classifies PVC(premature ventricular contraction) and decreases computational cost by accurately detecting minimal feature point based on only R peak through optimal R wave. We propose an optimal R wave detection and PVC classification method through extracting minimal feature point in IoT environment. For this purpose, we detected R wave through optimal threshold value and extracted RR interval and R peak pattern from noise-free ECG signal through the preprocessing method. Also, we classified PVC in realtime through RR interval and R peak pattern. The performance of R wave detection and PVC classification is evaluated by using record of MIT-BIH arrhythmia database. The achieved scores indicate the average of 99.758% in R wave detection and the rate of 93.94% in PVC classification.

• Applied Microscopy
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• 제46권4호
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• pp.188-192
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• 2016

Proper sample preparation prior to microscopy is necessary for maintaining the components of tissues in a state as close to a living state as possible. For optimal preservation of biological samples, the sampling conditions are as important as the fixation itself. Various factors influence the selection and fixation efficiencies of a fixative, including sample size, osmolarity, pH, penetration rate and depth, fixative temperature, fixation time, fixative concentration, fixative amount, and retention time. Therefore, several factors for selecting and administering fixation procedures are evaluated pertaining to optimal sample preparation for transmission electron microscopy.

• 응용통계연구
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• 제31권5호
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• pp.621-636
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• 2018

정보적 표본설계 기법을 적용하여 무응답의 영향을 줄이기 위한 연구가 진행되고 있다. 특히 초모집단모형(super population model)에 포함된 오차의 분포가 정규분포를 따르고 응답률이 지수함수를 따를 때 지수형 응답률 정보를 모수추정에 사용함으로써 추정의 정확성이 향상되는 것으로 알려져 있다. 최근 Chung과 Shin (2017)은 정보적 표본설계의 가중치를 구하기 위해 세부 층을 등간격으로 나누는 방법을 고려하였으며 세부 층의 개수가 추정의 정확성에 영향을 주는 것을 확인하였다. 이에 본 연구에서는 주어진 표본 규모에 따른 최적의 세부 층 개수와 최적의 층 경계를 구하기 위해 등간격, 분위수, LH 알고리즘을 이용하여 층을 나누는 방법을 살펴보았으며 모의실험을 통하여 각 방법의 결과를 비교하였다. 또한 다양한 형태의 보조변수 분포를 이용하여 실무에서 사용할 수 있는 세부 층 경계와 세부 층 개수를 정하는 기준을 제안하였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.327-330
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• 1996

It is well known that the controller output limits have a signifiant effect on the closed loop system performance. Considering the input constraints in GPCF, an effective selection method of the control weighting(.gamma.) is proposed to reduce the amplitude and the rate of control signals so that control signals lie within the limits. It is based on the relation between control weighting(.gamma.) and optimal solution of the unconstrained GPCF. The GPCFIC algorithm chooses an .gamma. at each sampling time so that all unconstrained GPCF output over the control horizon satisfy the rate and the amplitude constraints. In order to evaluate the performance of the GPCFIC, the computer simulations have been done for level control of PWR steam generator in low power operation and shown satisfactory results.

• 수면정신생리
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• 제6권1호
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• pp.52-60
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• 1999

목 적 : 임상 뇌파의 비선형 분석시, 분석시간을 단축시킬 수 있는 방법과 보다 정확한 상관차원을 얻기 위한 새로운 알고리즘 고안을 시도하였다. 또 뇌파신호 분석을 위한 적절한 신호획득 조건을 결정하는 방법을 제시하기 위하여 여러 상이한 실험조건에서 상관차원을 계산하였으며, 여기서 얻은 결과를 이용하여 각 실험실마다 공통적으로 적용할 수 있는 표준화된 실험 조건을 결정하고자 하였다. 방 법 : 임의의 한 개인을 대상으로 13개의 두피전극에서 얻은 뇌파신호를 대상으로 하였다. 12비트 해상도에서 1000 헤르츠로 32초간 얻은 뇌파신호를 디지털화 하여 각 전극당 32000개의 시계열자료를 얻었다. 이 자료를 10, 20, 30초 간격의 시간단위로 나누고, 각각에 대해 1000, 500, 250, 125, 62.5 Hz 등 5가지 신호추출조건을 달리 하여 각 전극마다 총 15개의 시계열 자료를 만들었다. 여기에 상관차원 계산시간 단축을 위해 고안된 계산 알고리듬 및 상관차원 추정 정확도를 개선하기 위해 적용한 최소절단자승기법을 적용하여 상관 차원을 계산하였다. 이렇게 얻은 상관차원 결과를 신호획득시간과 신호추출빈도에 따라 비교하였다. 또 로그연산을 비트 연산으로 바꾸어 계산시간 단축의 효과를 평가하였으며, 최소 절단자승기법과 최소자승추정기법을 비교하였다. 결 과 : 신호추출시간이 증가함에 따라 상관차원의 값도 통계적으로 유의하게 증가하는 양상을 보였다. 신호추출빈도가 62.5Hz일때는 신호추출시간에 무관하게 높은 상관차원값을 나타냈으나 그밖의 빈도에서는 유사한 상관차원값을 보였다. 본 연구에서 고안된 계산 알고리듬은 종래 사용하던 알고리듬에 비해 통계적으로 유의한 계산시간 단축효과를 보였다. 또 종래의 방법인 최소자승추정에 의한 상관차원에 비하여 본 연구에 적용된 최소절단자승추정법은 보다 안정된상관차원 값을 추정하였다. 결 론 : 본 연구는 다량의 뇌파 시계열 자료를 분석하는데 신속하고 보다 정확한 상관차원 추정에 알맞는 분석방법을 제공하였다. 또한 뇌파 시계열 자료의 상관차원 계산시 12비트의 해상도에서 125Hz의 신호추출빈도로 20초간 뇌파신호를 획득하면 적정한 수준의 상관차원을 계산할 수 있음을 보였다.

• 한국환경보건학회지
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• 제36권5호
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• pp.383-390
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• 2010

Exposure to fugitive dust can contribute to several respiratory health problems, and proper sampling of fugitive dust is necessary to assess exposure. However, field sampling of soil dust encounters problems from spatial and temporal differences in soil properties, field operations, and meteorological conditions. To minimize these problems, we designed a dust generator that simulates dust generation from soil. The dust generator consisted of a rotating chamber where soil samples were loaded and tumbled, and a settling chamber, where airborne soil dust samples were collected. As standard operating conditions, we decided on 2 g soil mass, 10 min sampling time, and 20 rpm rotating speed, with a flow rate of 30 l/min, based on three common soil textures of loam, sandy loam and silt loam. To evaluate optimal operating conditions, we used mixtures of Joomoonjin silica sand and clay. Although the average $PM_{10}$ concentration of Joomoonjin silica sand was low, dust concentrations were increased by an increased content of clay. The dust concentrations were consistent across repeated experiments, and showed similar concentration profiles during the sampling time with mixtures of clay and sand (coefficient of variation was $13.6{\pm}w;7.1%$). The results demonstrated that these standard operating conditions were suitable for the dust generator, which can be used to investigate variations in soil properties that affect dust production and potential potency of fugitive dust exposure.