• 한국소음진동공학회논문집
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• 제19권3호
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• pp.313-319
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• 2009

The blasting has a lot of economic efficiency and speediness but it can damage to a neighbor structure, a domestic animal and a cultured fish due to the blasting vibration, then the public grievance is increased. Therefore, we need to manage the blasting vibration efficiently. The prediction of the correct vibration velocity is not easy because there are lots of different kinds of the scale of blasting vibration and it has a number of a variable effect. So we figure the optimum line through the least-squares regression by using the vibration data measured in hard rock blasting and compared with the design vibration prediction equation. As a result, we confirm that the vibration estimated in this paper is bigger than the design vibration prediction equation in the same charge and distance. If there is a Gaussian normal distribution data on the left-right side of the least squares regression, then we can estimate the vibration prediction equation on reliability 50%(${\beta}=0$), 90%(${\beta}=1.28$), 95%(${\beta}=1.64$). 99.9%(${\beta}=3.09$). As a result, it appears to be suitable that the reliability is 99% at the transverse component, the reliability 95% is at the vertical component, the reliability 90% is at the longitudinal component and the reliability is 95% at the peak vector sum component.

• 환경영향평가
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• 제33권2호
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• pp.84-98
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• 2024

본 연구는 인천, 수원, 원주, 양산 지역에서 발파작업 동안 취득한 320개의 발파 진동 및 발파 소음 데이터를 사용하여, 발파 진동 및 발파 소음 추정에 적용가능한 예측식을 개발하였다. 발파진동 예측식은 회귀분석결과, SRSD 및 CRSD에 의한 상관계수가 각각 0.879, 0.890이며 두 경우 모두 R² ≥ 0.7로 나타났다. 발파소음 예측식은 단계적 회귀분석을 수행한 결과, 상관계수는 0.911, R² ≥ 0.7로 유의미하게 높은 상관관계를 보였다. 상수값 결정을 위한 추가 회귀분석 결과 상관계수는 0.881, R² ≥ 0.7로 나타났다. 상기의 결과, 개발된 예측식이 다른 도시지역의 재건축사업이나 공동주택 건설에 따른 환경영향평가나 교육환경평가의 소음·진동분야 보고서 작성 시 정합성이 높은 발파소음·진동 예측값을 도출할 수 있을것으로 기대한다.

• 한국연초학회지
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• 제21권1호
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• pp.95-101
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• 1999

This study was carried out to analyze chemical components in burley tobacco using near infrared spectroscopy(NIRS). Samples were collected in '96 and '97 crop year. Calibration equations were developed by modified partial least square. The standard error performance(SEP) of '96 crop year samples between NIRS and standard laboratory analysis were 0.25% for nicotine, 0.18% for total nitrogen, 0.59% for crude ash, 0.32% for ether extracts, and 0.14% for chlorine, respectively. The analytical results of '97 crop year samples were similar to those of '96 crop year samples. The analytical result of '97 crop year samples analyzed by '96 calibration equation was more inaccurate than that of '96 crop year samples. The SEP of '96 or '97 crop year samples applying calibration equation derived from '96 plus '97 crop year samples was similar to that of '96 or '97 crop year samples analyzed by '96 or '97 calibration equation, respectively. The SEP of '97 crop year samples analyzed by calibration equation derived from '96 plus '97 crop year samples was more accurate than that of '97 crop year samples analyzed by '96 calibration equation. To improve the analytical inaccuracy caused by the difference of crop year between calibration and prediction samples, we need to include the prediction sample spectra which were different from calibration sample spectra in recalibration sample spectra, and then develop recalibration equation. The NIRS can apply to analyze burley leaf tobacco, leaf process or tobacco manufacturing process which were required the rapid analytical result.

• 한국화재소방학회논문지
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• 제21권2호
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• pp.48-53
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• 2007

혼합물의 인화점에 대한 지식은 산업 현장에서 화재화재 예방 및 방호를 위해서 매우 중요하다. 본 연구에서는 water+2-propanol 계의 인화점을 Tag 개방식 장치(ASTM D1310-86)를 이용하여 측정하였다. 실험값은 Raoult의 법칙, Van Laar 모델식과 NRTL 모델식에 의해 계산된 값들과 비교되었다. 그 결과, Van Laar 모델식과 NRTL(non random two liquids) 모델식에 의한 예측값이 Rauolt의 법칙에 의한 예측값 보다 실험값에 더욱 근접하였다. 이는 water+2-propanol 계와 같은 비이상용액의 활동도 계수값을, Van Laar 및 NRTL 모델식이 Raoult의 법칙보다 정확하게 계산하기 때문이다. 또한, Van Laar 모델식의 실험값에 대한 모사성이 NRTL 모델식의 그것 보다 우수하였다.

• Animal Bioscience
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• 제34권10호
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• pp.1623-1631
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• 2021

Objective: This study aimed to validate and evaluate the dry matter (DM) intake prediction model of the Korean feeding standards for dairy cattle (KFSD). Methods: The KFSD DM intake (DMI) model was developed using a database containing the data from the Journal of Dairy Science from 2006 to 2011 (1,065 observations 287 studies). The development (458 observations from 103 studies) and evaluation databases (168 observations from 74 studies) were constructed from the database. The body weight (kg; BW), metabolic BW (BW^0.75, MBW), 4% fat-corrected milk (FCM), forage as a percentage of dietary DM, and the dietary content of nutrients (% DM) were chosen as possible explanatory variables. A random coefficient model with the study as a random variable and a linear model without the random effect was used to select model variables and estimate parameters, respectively, during the model development. The best-fit equation was compared to published equations, and sensitivity analysis of the prediction equation was conducted. The KFSD model was also evaluated using in vivo feeding trial data. Results: The KFSD DMI equation is 4.103 (±2.994)+0.112 (±0.022)×MBW+0.284 (±0.020)×FCM-0.119 (±0.028)×neutral detergent fiber (NDF), explaining 47% of the variation in the evaluation dataset with no mean nor slope bias (p>0.05). The root mean square prediction error was 2.70 kg/d, best among the tested equations. The sensitivity analysis showed that the model is the most sensitive to FCM, followed by MBW and NDF. With the in vivo data, the KFSD equation showed slightly higher precision (R² = 0.39) than the NRC equation (R² = 0.37), with a mean bias of 1.19 kg and no slope bias (p>0.05). Conclusion: The KFSD DMI model is suitable for predicting the DMI of lactating dairy cows in practical situations in Korea.

• 한국정보과학회논문지:컴퓨팅의 실제 및 레터
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• 제10권4호
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• pp.299-308
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• 2004

최근 단백질 및 도메인과 관련된 방대한 양의 데이타들이 인터넷상에 공표되고 축적됨에 따라, 단백질간의 상호작용에 대한 예측 시스템의 필요성이 제기되고 있다. 본 논문에서는 이러한 데이타를 이용하여 계산적으로 도메인 조합 쌍에 기반하여 단백질의 상호작용 확률을 예측하는 새로운 단백질 상호작용 예측 시스템을 제안한다. 제안된 예측 시스템에서는 기존의 도메인 쌍(domain pair)의 제약성을 극복하기 위하여 도메인 조합(domain combination)과 도메인 조합 쌍(domain combination pair)의 개념이 새롭게 도입하였다. 그리고 도메인 조합 쌍(domain combination pair 또는 dc-pair)을 단백질 상호작용의 기본 단위로 간주하고 예측을 시도한다. 예측 시스템은 크게 예측 준비 과정과 서비스 과정으로 구성되어 있다. 예측 준비 과정에서는 상호작용이 있는 것으로 알려진 단백질 쌍 집합과 상호작용이 없는 것으로 추정되는 단백질 도메인 쌍 집합으로부터 각각 도메인 조합 정보와 그 출현 빈도를 추출한다. 추출된 정보들은 출현 확률 배열(Appearance Probability Matrix 또는 AP matrix)로 불리는 배열 구조에 저장된다. 논문에서는 출현 확률 배열에 기반을 두어, 단백질-단백질 상호작용을 예측하는 확률식 PIP(Primary Interaction Probability)를 고안하고, 고안된 확률식을 이용하여, 상호작용이 있는 것으로 알려진 단백질 쌍 집합과 상호작용이 없는 것으로 추정되는 단백질 도메인 쌍 집합의 확률 값 분포를 생성시킨다. 예측서비스 과정에서는 예측 준비 과정에서 얻어진 분포와 확률식을 이용하여 임의의 단백질 쌍의 상호작용 확률을 계산한다. 예측 모델의 유효성은 효모(yeast)에서 상호작용이 있는 것으로 보고된 단백질 쌍 집합과 상호작용이 없는 것으로 추정되는 단백질 쌍 집합을 이용하여 검증하였다. DIP(Database of Inter-acting Proteins)의 상호작용이 있는 것으로 알려진 효모 단백질 쌍 집합의 80%를 학습 집단으로 사용했을 때, 86%의 sensitivity와 56%의 specificity를 나타내어, 도메인을 기반으로 한 기존의 예측 시스템에 비해서 우월한 예측 정확도를 보여주었다. 이와 같은 예측 정확도의 개선은 본 예측 시스템이 상호작용의 기본 단위로 dc-pair를 채택한 점과 분류를 위하여 새롭게 고안하여 사용한 PIP식이 유효했던 것으로 판단된다.

• Asian-Australasian Journal of Animal Sciences
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• 제28권9호
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• pp.1335-1344
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• 2015

A set of prediction equations to estimate the nitrogen-corrected apparent metabolizable energy (AMEn) of individual ingredients and diets used in the poultry feed industry was evaluated. The AMEn values of three energy ingredients (maize, sorghum and defatted maize germ meal), four protein ingredients (soybean meal, maize gluten meal 60% crude protein, integral micronized soy and roasted whole soybean) and four diets (three containing four feedstuffs, complex diets, and one containing only corn-soybean meal, basal diet) were determined using a metabolism assay with male broilers from 1 to 7, 8 to 21, 22 to 35, and 36 to 42 days old. These values were compared to the AMEn values presented in the tables of energy composition or estimated by equation predictions based on chemical composition data of feedstuffs. In general, the equation predictions more precisely estimated the AMEn of feedstuffs when compared to the tables of energy composition. The equation AMEn (dry matter [DM] basis) = 4,164.187+51.006 ether extract (% in DM basis)-197.663 ash-35.689 crude fiber (% in DM basis)-20.593 neutral detergent fiber (% in DM basis) ($R^2=0.75$) was the most applicable for the prediction of the energy values of feedstuffs and diets used in the poultry feed industry.

• 한국지반공학회논문집
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• 제19권1호
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• pp.221-228
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• 2003

해성점토를 이용한 준설매립공사에 있어서 준설매립 지반의 자중압밀현상을 예측하기 위해 준설점토의 간극비-유효응력-투수계수의 관계인 구성관계 산정은 가장 중요한 사항이다. 그러나 준설매립 지반은 고함수비의 재료특성으로 인해 실험을 통한 구성관계의 산정에 많은 어려움이 발생하게 된다. 이를 위해 저응력 압밀시험기 등을 이용한 실험을 통해 산정하고자 하는 연구들이 진행되고 있다. 본 연구에서는 저응력 압밀시험기를 이용하여 구성관계를 산정하였고, 저응력 압밀시험기를 이용한 실험시 많은 시간이 소요되는 단점을 극복하고자 준설점토를 이용한 컬럼실험에서 얻어진 변수들을 바탕으로 초연약 준설매립점토의 구성관계를 산정할 수 있는 산정식에 대한 연구를 실시하였다 저응력 압밀 및 투수실험을 통해 준설점토의 구성관계를 파악할 수 있었고, 또한 침강 및 자중압밀 실험결과를 이용하는 구성관계 산정식을 통해 저응력 단계에 대한 구성관계를 얻을 수 있었으며, 저응력 압밀시험에서 얻어진 결과와의 연속성을 확인할 수 있었다. 따라서 본 연구의 산정식을 이용하여 간편하게 구성관계를 파악할 수 있었다. 본 연구의 구성관계 산정식을 이용하여 준설매립지반의 자중압밀현상을 예측에 이용할 수 있으리라고 판단된다.

• Asian-Australasian Journal of Animal Sciences
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• 제33권4호
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• pp.615-622
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• 2020

Objective: The objectives were to investigate correlations between energy digestibility (digestible energy [DE]:gross energy [GE]) and various fiber types including crude fiber (CF), total dietary fiber (TDF), soluble dietary fiber (SDF), insoluble dietary fiber (IDF), neutral detergent fiber (NDF), and acid detergent fiber (ADF), and to develop prediction equations for estimating DE in feed ingredients and diets for growing pigs. Methods: A total of 289 data with DE values and chemical composition of feeds from 39 studies were used to develop prediction equations for DE. The equations were validated using values provided by the National Research Council. Results: The DE values in feed ingredients ranged from 2,011 to 4,590 kcal/kg dry matter (DM) and those in diets ranged from 2,801 to 4,203 kcal/kg DM. In feed ingredients, DE:GE was negatively correlated (p<0.001) with NDF (r = -0.84), IDF (r = -0.83), TDF (r = -0.82), ADF (r = -0.78), and CF (r = -0.72). A best-fitting model for DE (kcal/kg) in feed ingredients was: 1,356 + (0.704 × GE, kcal/kg) - (60.3 × ash, %) - (27.7 × NDF, %) with R² = 0.80 and p<0.001. In diets, DE:GE was negatively correlated (p<0.01) with NDF (r = -0.72), IDF (r = -0.61), TDF (r = -0.52), CF (r = -0.45), and ADF (r = -0.34). A best-fitting model for DE (kcal/kg) in diets was: 1,551 + (0.606 × GE, kcal/kg) - (22.1 × ash, %) - (25.6 × NDF, %) with R² = 0.62 and p<0.001. All variables are expressed as DM basis. The equation developed for DE in feed ingredients had greater accuracy than a published equation for DE. Conclusion: All fiber types are reasonably good independent variables for predicting DE of swine feeds. The best-fitting model for predicting DE of feeds employed neutral detergent fiber as an independent variable.

• 대한지역사회영양학회지
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• 제19권6호
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• pp.568-580
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• 2014

Objectives: The purpose of this study was to measure the resting metabolic rate (RMR) and to assess the accuracy of RMR predictive equations for Korean farmers. Methods: Subjects were 161 healthy Korean farmers (50 males, 111 females) in Gangwon-area. The RMR was measured by indirect calorimetry for 20 minutes following a 12-hour overnight fasting. Selected predictive equations were Harris-Benedict, Mifflin, Liu, KDRI, Cunningham (1980, 1991), Owen-W, F, FAO/WHO/UNU-W, WH, Schofield-W, WH, Henry-W, WH. The accuracy of the equations was evaluated on the basis of bias, RMSPE, accurate prediction and Bland-Altman plot. Further, new RMR predictive equations for the subjects were developed by multiple regression analysis using the variables highly related to RMR. Results: The mean of the measured RMR was 1703 kcal/day in males and 1343 kcal/day in females. The Cunningham (1980) equation was the closest to measured RMR than others in males and in females (males Bias -0.47%, RMSPE 110 kcal/day, accurate prediction 80%, females Bias 1.4%, RMSPE 63 kcal/day, accurate prediction 81%). Body weight, BMI, circumferences of waist and hip, fat mass and FFM were significantly correlated with measured RMR. Thus, derived prediction equation as follow : males RMR = 447.5 + 17.4 Wt, females RMR = 684.5 - 3.5 Ht + 11.8 Wt + 12.4 FFM. Conclusions: This study showed that Cunningham (1980) equation was the most accurate to predict RMR of the subjects. Thus, Cunningham (1980) equation could be used to predict RMR of Korean farmers studied in this study. Future studies including larger subjects should be carried out to develop RMR predictive equations for Korean farmers.