• 한국근적외분광분석학회:학술대회논문집
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• 한국근적외분광분석학회 2001년도 NIR-2001
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• pp.1042-1042
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• 2001

In linear discriminant analysis there are two important properties concerning the effectiveness of discriminant function modeling. The first is the separability of the discriminant function for different classes. The separability reaches its optimum by maximizing the ratio of between-class to within-class variance. The second is the stability of the discriminant function against noises present in the measurement variables. One can optimize the stability by exploring the discriminant variates in a principal variation subspace, i. e., the directions that account for a majority of the total variation of the data. An unstable discriminant function will exhibit inflated variance in the prediction of future unclassified objects, exposed to a significantly increased risk of erroneous prediction. Therefore, an ideal discriminant function should not only separate different classes with a minimum misclassification rate for the training set, but also possess a good stability such that the prediction variance for unclassified objects can be as small as possible. In other words, an optimal classifier should find a balance between the separability and the stability. This is of special significance for multivariate spectroscopy-based classification where multicollinearity always leads to discriminant directions located in low-spread subspaces. A new regularized discriminant analysis technique, the principal discriminant variate (PDV) method, has been developed for handling effectively multicollinear data commonly encountered in multivariate spectroscopy-based classification. The motivation behind this method is to seek a sequence of discriminant directions that not only optimize the separability between different classes, but also account for a maximized variation present in the data. Three different formulations for the PDV methods are suggested, and an effective computing procedure is proposed for a PDV method. Near-infrared (NIR) spectra of blood plasma samples from daily monitoring of two Japanese cows have been used to evaluate the behavior of the PDV method in comparison with principal component analysis (PCA), discriminant partial least squares (DPLS), soft independent modeling of class analogies (SIMCA) and Fisher linear discriminant analysis (FLDA). Results obtained demonstrate that the PDV method exhibits improved stability in prediction without significant loss of separability. The NIR spectra of blood plasma samples from two cows are clearly discriminated between by the PDV method. Moreover, the proposed method provides superior performance to PCA, DPLS, SIMCA md FLDA, indicating that PDV is a promising tool in discriminant analysis of spectra-characterized samples with only small compositional difference.

• 한국대기환경학회지
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• 제3권1호
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• pp.27-33
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• 1987

삼중수소 ($^{3}H$) 에 관한 환경 및 생물학상의 연구는 1950년대 중반부터 선진국에서 수행되오고 있다. 삼중소소에 대한 잠재적 노출의 경우 통상적 처리절차는 삼중수소의 신체부하량이라고 일컬어지는 이른바 신체내에 축적된 삼중수소의 양을 결정하기 위하여 삼중수소수로서 오줌속에 포함되는 삼중수소 방사능의 생리분석이다. 전신에 있어서 삼중수소의 최대허용신체부하량은 신체조직에 대하여 약 $30{\mu}Ci/{\ell}$ 이다. 생리분석에서 오줌속에 삼중수소를 검출하는데 가장 보편적인 조사준위(照射准尉)는 최대허용신체부하량의 1/10 이다. 이러한 생리분석 연구계획을 위해서는 소광보정(消光補正) 곡선을 그리는 것이 가장 우선적이다. 이것은 검뇨용 오줌의 색깔이 일정하지 않기 때문에 필요한 것이다. 이 경우에서 소광효과는 주로 오줌시료에 의한 섬광빛의 흡수에 기인된다. 소광보정곡선으로 판단된 공식은 통계적 근거에서 최소자승법에 의하여 Y (%) = 0.771 + 1.836 ${\tmes}10^{-4}$X(count)로 얻어졌다. 여기서 Y는 섬광계수 효율로서 약 12%에서 31% 범위의 값으로 나타났다. 본 논문에서는 삼중수소의 생물학적 반감기와 신체계통적으로 분포된 삼중수소에 적용되고 있는 정체(停滯) 공식에 관한 간략한 이론에 관하여 서술된다.

• 전기학회논문지
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• 제67권1호
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• pp.114-123
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• 2018

This paper concerns a design and learning method of softmax function neural networks based on K-means clustering. The partial discharge data Information is preliminarily processed through simulation using an Epoxy Mica Coupling sensor and an internal Phase Resolved Partial Discharge Analysis algorithm. The obtained information is processed according to the characteristics of the pattern using a Motor Insulation Monitoring System program. At this time, the processed data are total 4 types that void discharge, corona discharge, surface discharge and slot discharge. The partial discharge data with high dimensional input variables are secondarily processed by principal component analysis method and reduced with keeping the characteristics of pattern as low dimensional input variables. And therefore, the pattern classifier processing speed exhibits improved effects. In addition, in the process of extracting the partial discharge data through the MIMS program, the magnitude of amplitude is divided into the maximum value and the average value, and two pattern characteristics are set and compared and analyzed. In the first half of the proposed partial discharge pattern classifier, the input and hidden layers are classified by using the K-means clustering method and the output of the hidden layer is obtained. In the latter part, the cross entropy error function is used for parameter learning between the hidden layer and the output layer. The final output layer is output as a normalized probability value between 0 and 1 using the softmax function. The advantage of using the softmax function is that it allows access and application of multiple class problems and stochastic interpretation. First of all, there is an advantage that one output value affects the remaining output value and its accompanying learning is accelerated. Also, to solve the overfitting problem, L2-normalization is applied. To prove the superiority of the proposed pattern classifier, we compare and analyze the classification rate with conventional radial basis function neural networks.

• 대한화학회지
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• 제21권5호
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• pp.307-319
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• 1977

Thiourea derivative인 $N-({\alpha}-dimethyl\;{\beta}-hydroxy)ethyl\;N'-cyclohexyl\;thiourea,\;C_{ll}H_{22}N_2OS)$의 결정 및 분자구조를 X-선 회절법으로 해명하였다. 이 화합물의 결정은 공간군 $P_{bca}$에 속하는 orthorhombic 형으로 a = 10.33(3), b = 11.82(3), c = 22.57(4)${\AA}$ 이고 Z = 8이다. Weissenberg 사진촬영으로 얻은 회절반점의 총수는 1414개이며 중원자법을 이용하여 구조해명을 한 후 최소자승법으로 정밀화하였으며 최종 R값은 0.13이다. Cyclohexane ring은 normal chair conformation을, thiourea 부분은 평면을 이루고 있다. 일차 알코올의 hydroxyl group은 N(2)원자와 분자내 수소결합을 이뤄서 전체분자를 안정화시키고 있다. 분자들은 결정내에서 수소결합과 van der Waals힘으로 서로 결합되어 있다. 분자내 수소결합 N(2)-H${\cdot}{\cdot}{\cdot}$O는 강한 수소결합으로 N${\cdot}{\cdot}{\cdot}$O 길이는 2.71${\AA}$이고, 분자간 수소결합 O${\cdot}{\cdot}{\cdot}$H${\cdot}{\cdot}{\cdot}$S의 O${\cdot}{\cdot}{\cdot}$S 길이는 3.02${\AA}$으로 b축에 나란하다.

• 대한화학회지
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• 제35권6호
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• pp.630-635
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• 1991

완전히 $Ca^{2+}$이온으로 치환한 제올라이트 A를 탈수한 후 브롬을 흡착한 결정구조(a = 12.211(2) ${\AA}$)를 입방공간군 Pm3m을 써서 단결정 X-선 회절법으로 해석하였다. 결정은 $360^{\circ}C$에서 2 ${\times}$ $10^{-6}$Torr하에서 2일간 진공 탈수한 후 $24^{\circ}C$에서 약 180 Torr의 브롬 기체로써 30분간 반응시켰다. 결과로 얻은 구조에서 6개의 $Ca^{2+}$이온은 6-링 산소와 결합하면서 두개의 다른 3회 회전축상에 위치하고 있었고 단이 세포당 총 6분자의 브롬이 흡착되었다. 각 브롬 분자는 골격구조의 산소이온과 전하이동착물을 형성하였다.(O-Br = 3.12(7) ${\AA}$, Br-Br = 2.64(9) ${\AA}$ 및 O-Br-Br = $178(2)^{\circ}$), Full-matrix 최소자승법 정밀화 계산에서 I > 3${\sigma}$ (I)인 103개의 독립반사를 써서 R = 0.104까지 얻었다.

• 한국수정란이식학회지
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• 제19권3호
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• pp.291-299
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• 2004

요크셔종과 버크셔종 교배 실험 집단을 활용하여 양적형질 유전자좌 (QTL)의 발현 특성 관련 유전 양식을 조사하였다. 총 512두의 F$_2$ 자손이 F$_1$간의 65교배 조합으로부터 생산되었으며 표현형 조사 기록은 일당증제량(ADG), 평균 등지방 두께(ABF), 10번째 등뼈 부위 등지방 두께(TRF) 및 등심단면적(LEA), 최후 척추부위 등지방 두께 (LRF)였다. 125종의 유전자 표지 (microsatellite)에 대한 3세대 개체별 유전자형이 분석되었으며 이들 정보를 통하여 최소자승 회귀 모형을 이용한 interval mapping 방법을 적용하였다. QTL의 유전양식 여부 검정에 대한 절차를 도식화하기 위해 귀무가설인 통상의 벤델리안 모형에 근거를 두고 수행하였다. 경험적 다중 검정 통계량에 대한 임계치는 단일 개개의 염색체 수준과 게놈 전반에 걸친 실험수준으로 유도하였으며, permutation에 의해 유도된 임계치의 유효성을 검증하기 위해 본 연구에 활용된 실험축 집단 구조와 유사한 simulation 집단 구조에 의해 산출된 결과들과 비교하여 유효성이 인정되었다. 본 연구에 활용된 실험축 집단구조와 Genome 전반에 걸친 QTL imprinting 여부를 조사한 결과 13종의 QTL 에 대한 imprinting이 확인되었으며 이들 중 9종의 QTL 유전 양식은 부계로부터 전달된 자손에게만 발현되는 것으로 추론되었다.

• Asian Pacific Journal of Cancer Prevention
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• 제16권12호
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• pp.5125-5135
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• 2015

Background: Total fat intake may be associated with increased risk of breast cancer, and fish oil has been suggested as a protection factor to breast cancer. But the effect of vegetable oils is inconclusive. We aimed to investigate the association with high vegetable oils consumption and breast cancer risk, and evaluated their dose-response relationship. Design: We systematically searched the MEDLINE, EMBASE, Cochrane databases, and CNKI updated to December 2014, and identified all observational studies providing quantitative estimates between breast cancer risk and different vegetable oils consumption. Fixed or random effect models were used to estimate summary odds ratios for the highest vs. lowest intake, and dose-response relationship was assessed by restricted cubic spline model and generalized least-squares trend (GLST) model. Results: Five prospective cohort studies and 11 retrospective case-control studies, involving 11,161 breast cancer events from more than 150,000 females, met the inclusion criteria. Compared with the lowest vegetable oils consumption, higher intake didn't increased the risk of breast cancer with pooled OR of 0.88 (95% CIs:0.77-1.01), and the result from dose-response analyses didn't show a significant positive or negative trend on the breast cancer risk for each 10g vegetable oil/day increment (OR=0.98, 95% CIs: 0.95-1.01). In the subgroup analyses, the oils might impact on females with different strata of BMI. Higher olive oil intake showed a protective effect against breast cancer with OR of 0.74 (95% CIs: 0.60-0.92), which was not significant among the three cohort studies. Conclusions: This meta-analyses suggested that higher intake of vegetable oils is not associated with the higher risk of breast cancer. Olive oil might be a protective factor for the cancer occurrence among case-control studies and from the whole. Recall bias and imbalance in study location and vegetable oils subtypes shouldn't be ignored. More prospective cohort studies are required to confirm the interaction of the impact of vegetable oils on different population and various cancer characteristic, and further investigate the relationship between different subtype oils and breast cancer.

• Asian-Australasian Journal of Animal Sciences
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• 제27권6호
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• pp.806-817
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• 2014

The objective of this experiment was to evaluate the effect of providing different levels of a supplement on the nutritional characteristics and productive performance of heifers on pasture during the rainy-dry transition and dry season in Brazil or tropical area. Thirty crossbred heifers with predominance of Zebu breed were used in a completely randomized experimental design. Treatments consisted of a mineral supplement and 0.5, 1.0, 1.5, or 2.0 kg/animal/d of a protein supplement containing 300 g crude protein (CP)/kg of dry matter (DM). In the rainy-dry transition season there was quadratic effect of the protein supplementation (p<0.10) on daily weight gain (DWG). A linear relationship (p<0.10) was found between increasing supplement intake and intakes of DM, organic matter (OM), crude protein (CP), ether extract (EE), non fibrous carbohydrates (NFC) and total digestible nutrients (TDN). Coefficients of apparent digestibility of CP, EE, and NFC increased linearly (p<0.10) with increasing supplement levels, but there was no effect on the DM apparent digestibility (p>0.10); the microbial efficiency (g CPmic/kg TDN) and the relationship of microbial nitrogen flow with nitrogen intake (g/g nitrogen intake) were negative linear profiles. In the dry season, the descriptive pattern least squares means showed a trend of stabilization of DWG from the supply of 0.98 kg of protein supplement; the intakes of DM, OM, CP, EE, NFC, and TDN showed increasing linear relationship (p<0.10) with protein supplement levels; the means of apparent digestibility coefficients of the different dietary fractions presented a linear-response-plateau (LRP); the microbial nitrogen flow (g/d) showed positive linear profile (p<0.10) for supplementation levels. It is concluded that supplementation improves the productive performance of grazing heifers and that 1.0 kg/d of supplement per animal gives the maximum increment of weight gain.

• 수산해양기술연구
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• 제37권2호
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• pp.133-139
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• 2001

계량어군탐지기에 의한 어류자원의 자원량 추정에 필요한 기초자료를 얻기 위하여, 우리나라 남해와 제주도 주변에서 많이 어획되는 돌돔과 독가시치의 두 어종에 대하여 어체의 유형자세별 등 방향 반사강도를 제한법으로 측정하였으며, 분석한 결과를 요약하면 아래와 같다. 돌돔의 전장과 체중에 따른 평균반사강도를 나타내는 식은, TS=-72.97+20 log L, TS=-61.29+20/3 log W 이었다. 그리고, 독가시치의 전장과 체중에 따른 평균반사강도를 나타내는 식은, TS=-63.16+20 log L TS=-50.50+20/3 log W 이었다. 주파수 200kHz용 송수파기에 의해 제한법으로 측정한 모든 실험어의 유영자세별 반사강도의 최대치는 돌돔인 경우$-12^\circ$-$-21^\circ$, 독가시치인 경우 $-1^\circ$-$-8^\circ$로 머리를 아래로 향하여 보다 깊은 수심으로 유영하여 가는 자세에서 최대치가 나타났다. 실험어에 대한 반사강도를 유영자세별로 평균한 결과, 실험어의 최대 반사강도는 돌돔의 경우 $-18^\circ$에서 -41.50dB이며 독가시치의 경우 $-6^\circ$에서 -30.69dB로 나타났다.

• 한국초지조사료학회지
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• 제37권4호
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• pp.350-357
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• 2017

Near infrared spectroscopy (NIRS) is a rapid and accurate method for analyzing the quality of cereals, and dried animal forage. However, one limitation of this method is its inability to measure fermentation parameters in dried and ground samples because they are volatile, and therefore, respectively lost during the drying process. In order to overcome this limitation, in this study, fresh coarse haylage was used to test the potential of NIRS to accurately determine chemical composition and fermentation parameters. Fresh coarse Italian ryegrass haylage samples were scanned at 1 nm intervals over a wavelength range of 680 to 2500 nm, and optical data were recorded as log 1/reflectance. Spectral data, together with first- and second-order derivatives, were analyzed using partial least squares (PLS) multivariate regressions; scatter correction procedures (standard normal variate and detrend) were used in order to reduce the effect of extraneous noise. Optimum calibrations were selected based on their low standard error of cross validation (SECV) values. Further, ratio of performance deviation, obtained by dividing the standard deviation of reference values by SECV values, was used to evaluate the reliability of predictive models. Our results showed that the NIRS method can predict chemical constituents accurately (correlation coefficient of cross validation, $R_{cv}^2$, ranged from 0.76 to 0.97); the exception to this result was crude ash ($R_{cv}^2=0.49$ and RPD = 2.09). Comparison of mathematical treatments for raw spectra showed that second-order derivatives yielded better predictions than first-order derivatives. The best mathematical treatment for DM, ADF, and NDF, respectively was 2, 16, 16, whereas the best mathematical treatment for CP and crude ash, respectively was 2, 8, 8. The calibration models for fermentation parameters had low predictive accuracy for acetic, propionic, and butyric acids (RPD < 2.5). However, pH, and lactic and total acids were predicted with considerable accuracy ($R_{cv}^2$ 0.73 to 0.78; RPD values exceeded 2.5), and the best mathematical treatment for them was 1, 8, 8. Our findings show that, when fresh haylage is used, NIRS-based calibrations are reliable for the prediction of haylage characteristics, and therefore useful for the assessment of the forage quality.