• 한국해양공학회지
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• 제8권1호
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• pp.62-70
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• 1994

In order to estimate the detection range of a active SONAR system, the SONAR equation is commonly used. In this paper, an algorithm to calculate detection range in active SONAR system as function of SONAR depth and target depth is presented. For given SONAR parameters and environment, the transmission loss and background level are found, signal excess is computed. Using log-normal distribution, signal excess is converted to detection probability at each range. Then, the detection range is obtained by integrating the detection probability as function of range for each depth. The proposed algorithm have been applied to the case of omni-directional source with center frequency 30Hz for summer and winter sound profiles. It is found that the optimal search depth is the source depth since the detection range increase at source depth where the signal excess is maximized.

• 한국산업보건학회지
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• 제8권1호
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• pp.76-87
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• 1998

The concentration of welding fume was measured by 221 welders themselves in chassis frame workplace of the manufactory from February, 1, 1996 to May, 31, 1997. Welding parameters were the welding current and the distance between helmet and arc. Those two optimum conditions were proposed by excess probability analysis using logistic regression, so the best position in the workplace was proposed considering two factors to control the welding fume. The results are as followings; 1) The excess proability of welding fume TLV was over 99% in above 260 Amperes of welding current and also in below 30cm of distanced between helmet and arc. 2) The equation from logistic regression analysis using SPSS/PC+5.02 had the welding current as a independent variable and the excess of welding fume TLV as a dependent variable (p<0.05). Logit(welding fume TLV) = 0.1296 ${\times}$ wlding currnet - 28.8750 3) The equation from logistic regression analysis using SPSS/PC+5.02 had the distance between helmet and arc as a independent variable and the excess of welding fume threshold limit value a, a dependent variable (p<0.05). Logit (welding fume TLV) = -0.6809 ${\times}$ distance between helmet and arc +25.1665 4) Considering both cases or 2) and 3). the result equation is following. (p<0.05). Logit (welding fume TLV) = 0.1346 ${\times}$ welding current -0.3859 ${\times}$ distance between helmet and arc -15.7382 5) The excess probability of welding fume threshold limit value was 100% in above 240 Ampere of welding current. Thus, below 220 Ampere can be suggested to reduce the 40% number of welders who have a excess welding fume threshold limit value. 6) The excess probability of welding fume TLV was 100% in below 34cm of distance between helmet and arc. Thus, over 38cm can be suggested to reduce the 33% number of welders who have a excess welding fume TLV. 7) Considering both 5) and 6) cases, first of all, the best welding current can be 200 Ampere to have a below 15% of welding fume excess probability for the welders who works in distance of 34-37cm. Secondly, to have a below 30% excess probability of welding fume TLV, the working distance must be over 38cm in 220 Ampere and 32cm in 200 Ampere. 8) To reduce the average exposure concentration of welding fume ($8.21{\pm}5.83mg/m^3$), the movable local exhaust system equipped with flexible hoods can be used.

• 전기의세계
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• 제14권5호
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• pp.8-14
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• 1965

Because of the flat slope of the magnetic characteristic curves at high saturation, the transformer inrush current peakes may assume an extreme magnitude. Even though such is rarely any danger to the transformer itself, the currents can cause serious problems in associated apparatus. This paper has analyzed various limiting factors of excess inrush currents, and then has suggested how to determine the frequency of encountering the inrush current peaks higher than an arbitrarily chosen value by deriving the probability equations of inrush current occurrence.

• Journal of the Korean Statistical Society
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• 제22권2호
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• pp.307-324
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• 1993

The limiting distribution of the excess over the boundary is determined for the autoregressive process.

• 한국군사과학기술학회지
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• 제15권5호
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• pp.630-634
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• 2012

It is very important to place receiver in multistatic sonar. Inefficient placement of the receiver reduce detection probability and to increase the probability of detection should be used more receivers. Therefore, detection of targets in searching area, detection performance of limited receiver depends on how to place. Through the optimized receiver placement, detection area between each sonar as much as possible avoid duplication, as optimization, the minimum receiver can be maintained detection performance. In this paper we prove mathematical verification of maximum signal excess value based on sonar placement and we calculate a signal excess value by using computer simulations and suggest optimal sonar placement.

• 한국자동차공학회논문집
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• 제10권5호
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• pp.107-113
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• 2002

LPG has been well known as a clean alternative fuel for vehicles. Recently, several LPG engines for heavy duty vehicles have been developed, which can replace some diesel engines that are one of the main sources for air pollution in the urban area. Because cylinder bore of heavy duty LPG engine is larger than that of gasoline, the study of knock characteristics of LPG engine are needed. In this study, the knock characteristics were investigated with various engine speed, air excess ratios and LPG fuel compositions. Experimental results indicated that the Knock occurrence probability decreases with increasing engine speed and propane fraction of fuel. The Knock occurrence probability is highest at excess air ratio of 1 and decreases as the mixture strength became leaner.

• Journal of the Korean Statistical Society
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• 제19권2호
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• pp.160-170
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• 1990

A new approximation method is proposed for the ARL of CUSUM chart which is based on the log probability ratio statistic. This method uses the condition of before-stopping time to derive the expectation of excess over boundaries. The proposed method is compared to some other approximation methods in normal and exponential cases.

• 대한토목학회논문집
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• 제29권6B호
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• pp.513-526
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• 2009

홍수피해를 줄이기 위해 적정한 설계빈도에 맞는 치수대책을 수립한다. 일반적으로 설계빈도는 지역의 현황, 중요도뿐만 아니라 확률강우량 등을 반영한다. 따라서 본 연구에서는 최근 10년간 주요 호우사상에 의해 홍수피해가 발생한 지역을 대상으로 지속시간별로 최대강우량의 빈도를 산정하였다. 그리고 빈도별 확률강우량을 초과하는 강우사상의 시간적 특성을 분석하기 위해 초과강우량과 초과횟수 및 단위초과강우량을 산정하여 변동성과 경향성 분석을 수행하였다. 또한 강우관측소의 위치와 시간강우량 특성을 이용해 군집분석을 실시하고 강우관측소를 군집화 하였다. 군집된 지역을 대상으로 평균초과강우량과 평균초과횟수 및 평균단위초과강우량을 산정하였고, 군집지역별 초과강우량과 초과횟수에 대해 변동성 및 경향성을 분석을 실시하여 시간적 변화를 비교하였다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2007년도 학술발표회 논문집
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• pp.1798-1802
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• 2007

The practice of business estimate flood discharge by rainfall-flow relation that is easy collection of observation data. The important factor is rainfall, coefficient of runoff, and drainage area for analysis of runoff-flow relation.The practice of business usually use probability rainfall that use a weighted average value after each observation post estimate probability of non-same time. It has more error than same time probability rainfall, and it can excess of estimation because it can't consider space distribution of rainfall.The study of result showed similar aspect with existing ARF but width of coefficient become smaller. And the comparison of peak flow did not different what used by ARF and same time probability rainfall(A group). But non-same time probability rainfall is bigger 25% more than another(B group). Between A group and B group of the difference increased with the lapse of time.

• 산업기술연구
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• 제27권A호
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• pp.95-102
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• 2007

The practice of business estimate flood discharge by rainfall-flow relation that is easy collection of observation data. The important factor is rainfall, coefficient of runoff, and drainage area for analysis of runoff-flow relation. The practice of business usually use probability rainfall that use a weighted average value after each observation post estimate probability of non-same time. It has more error than same time probability rainfall, and it can excess of estimation because it can't consider space distribution of rainfall. The study of result showed similar aspect with existing ARF but width of coefficient become smaller. And the comparison of peak flow did not different what used by ARF and same time probability rainfall(A group). But non-same time probability rainfall is bigger 25% more than another(B group). Between A group and B group of the difference increased with the lapse of time.