Earticle

전국 경찰관서에서의 경찰관의 이륜차 안전운행을 위하여 중앙경찰학교에 입교 한 신임경찰 교육생 중 이륜차 운전 경험 교육생을 조사한 바에 의하면 약 35%정 도로 운전 유경험자라고 답변하였으나 이들 대부분은 친구나 혼자서 이륜차 운전 방법을 습득한 사례가 대부분을 차지하고 있어 이륜차와 관련하여 체계적· 전문적 인 교육을 받은 경험이 거의 없는 실정으로 나타났다. 대부분의 교육생들은 자전거를 탈 줄 알면 이륜차 주행이 가능하다고 생각하고 있으며 이륜차 운전을 쉽게 생각하고 안전운전에 필요한 능력과 실력을 갖추지 않 은 채 중앙경찰학교에서의 부족한 이륜차 수업에다가 이륜차 운전을 해보고 싶은 개인적 욕구 사로잡힌 채 졸업할 경우 일선 치안 현장에서의 업무수행 중 이륜차 에 의한 교통사고의 우려성이 높은 것이 사실이다. 2015년 6월 말 기준 경찰청 산하 관서별 112순찰차량 보유 대수는 3,852대이 며, 이륜차는 2,018대 [대형 614대(30%), 중형 1,397대(69%), 소형 7대(1%)]이 다. 지역경찰의 순찰차량의 절반이 넘는 수를 이륜차가 차지하고 있어 순찰차 운 전 교육 못지않은 이륜차 교육도 절실히 필요하다. 그렇지만 신임 교육생의 운전 교육 시간 중 이륜차 수업에 할당된 시간이 절대적으로 부족(26h/3h)하여 이륜차 안전교육 강화가 절실히 요청되고 있다. 경찰청 관서별 이륜차 보유 현황에서 전체 이륜차 중 125cc이하 중형 이륜차가 차지하는 비율은 약 69%로 125cc초과 대형 이륜차에 비해 압도적으로 많지만, 경찰에서의 중형 이륜차 주행을 위한 매뉴얼 및 초보 라이더를 위한 교재가 없는 실태로써, 먼저 중앙경찰학교 교육생을 대상으로 이륜차 주행능력 설문조사를 실 시하여 교육생의 이륜차 관련 지식을 확인하고, 초보라이더의 안전 운전에 필요한 사항을 정리하여 매뉴얼화 하여 한정된 수업시간에 이륜차 주행에 익숙해지는 방 법과 도로별, 교통상황별 주행 방법을 체계적으로 전달할 수 있는 교수방법을 정리했다.

The new police trainees joined the Central Police Academy in order for the policemen to take the safe operation of motorcycles, and the approximate-35% among them answered motorcycle-driving experiences by investigating the trainees on the motorcycle-driving, however, the situation showed that most of them have not ever experienced in systemic and technical-training regarding the motorcycles because they acquired how to drive motorcycles by themselves only or friends. Most of the trainees, once they know how to ride a bike, think that it is for them to drive motorcycles, and think the motorcycle-driving easier, due to, on the one hand, the lack of a motorcycle-class at Central Police Academy, on the other hand, personal needs for driving motorcycles without the abilities and skills which are necessary for safe motorcycle-driving , in this situation If they graduate themselves from this academy, it is true that the concerns of the traffic accidents of motorcycles are high during the job-performances in the front-line of reinforcement-fields. As of the end of June 2015, under the National Police Agency, each police station employs 3852 units of 112 patrol-vehicle fleet, and 2018 motorcycles of [largesized 614 units(30%), medium-sized 1,397 units (69%), small-sized 7 (1%)]. The motorcycles can be accounted for more than the half number of the localpolice patrol cars, hence the urgent driving-lessons are needed for the motorcycledriving as good as that of patrol-car. However, the allocated classes for new trainee's motorcycle-driving are absolutely lack(26h/3h) and thus, the intensification of safe education for the motorcycle is desperately requested. In the motorcycle-holding status of each police station, the proportion of 125cc (69%) or less, mid-sized motorcycles for all motorcycles are overwhelmingly larger than 125cc or more a large-sized motorcycle, but in the situation there is no textbook for manual and novice- riders for a medium-sized motorcycles, First, the survey was carried out on the motorcycle-driving skills targeting for the trainees of the Central Police Academy and checked on the trainees' motorcycleknowledges, the requirements necessary for safe driving of the novice-riders were cleared up and the manual was created, and also, the teaching methods were cleared up in order for the riders to familiarize themselves in the limited-hour of class how to be systematically informed and how to drive according to each situation by roads, and by traffics.

기상레이더를 이용한 강수추정에는 오차가 발생할 수 있는 가능성이 매우 많다. 본 연구에서는 전반 적인 기상레이더 강수추정 과정에서 발생할 수 있는 반사도 관측 오차(Z-bias)와 강수오차(R-bias)에 초점을 맞추었다. Z-bias 보정을 위해, 반사도, 차등반사도, 비차등위상차를 이용하는 자기상관관계 방법을 적용하였다. R-bias 보정을 위해서는 Mean Field Bias Cocrrection (MFBD)와 Local Gauge Correction (LGC) 방법의 두 가지 후처리방법을 이용하였다. Z-bias와 R-bais 오차보정방법들을 Radar- AWS Rainrate 모형에 적용하였다. 18개 강수사례에서 Z-bias 오차보정결과의 RMSE(7.37 → 7.21 mm/hr)와 상관계수(0.83 → 0.84)가 향상되었다. 강수형태에서는 장마와 지역강수발생에서 더 개선 되었다. Z-bias와 R-bias 오차보정 적용결과에서 LGC 방법이 MFBC 방법보다 RMSE: 63.7%, 상관계 수: 11.7% 더 정확성이 우수하였으며, 이는 LGC 방법이 각 격자마다 보정이 가능하기 때문으로 판단된다.

This study focused on the reflectivity measurement bias (Z-bias) and the rainfall bias (R-bias) in the radar-rainfall estimation process. To correct the Z-bias, the self-consistency constraint method using reflectivity, differential reflectivity, and specific differential phase was carried out. Then, the Mean Field Bias Correction (MFBC) method and the Local Gauge Correction (LGC) method, were conducted to correct the R-bias. All of correction methods were applied to the Radar-AWS Rainrate model to calculate radar-rainfall estimates. The accuracy of the Z-bias correction method in 18 rainfall cases was improved by considering the RMSE (from 7.37 to 7.21 mm/hr) and the Correlation Coefficient (CC) (from 0.83 to 0.84) on average. The accuracy of results in the Changma and local torrential cases was improved by applying the Z-bias correction. The accuracy obtained by the LGC method (by 63.7% in RMSE and 11.7% in CC compared to MFBC) was superior to the MFBC method results because, in the LGC method, different R-biases were applied to each rainfall estimates in each radar pixel.

The transforming growth factor-${\beta}1$ (TGF-${\beta}1$) gene 29 T/C polymorphism is thought to be associated with breast cancer risk. However, reports are largely conflicting and underpowered. We therefore conducted a meta-analysis of all available case-control studies relating the TGF-${\beta}1$ 29T/C polymorphism to the risk of developing breast cancer by including a total of 31 articles involving 24,021 cases and 31,820 controls. Pooled ORs were generated for the allele contrasts, with additive genetic, dominant genetic and recessive genetic models. Subgroup analysis was also performed by ethnicity for the TGF-${\beta}1$ 29T/C polymorphism. No association was found in the overall analysis (C vs T: OR=1.028, 95% CI=0.949-1.114, p-value 0.500; CC vs TC: OR= 1.022, 95% CI=0.963-1.085, p-value 0.478; CC vs TT: OR= 1.054, 95% CI=0.898-1.236, p-value 0.522; CC vs TT+ TC: OR= 1.031, 95% CI=0.946-1.124, p-value 0.482; TT vs CC+TC: OR= 0.945, 95% CI=0.827-1.080, p-value 0.403). Similarly, in the subgroup analysis by ethnicity, no association was found in Caucasian (C vs T: OR= 1.041, 95% CI=0.932-1.162, p-value 0.475; CC vs TC: OR= 1.031, 95% CI=0.951-1.118, p-value 0.464; CC vs TT: OR= 1.081, 95% CI=0.865-1.351, p-value 0.493; CC vs TT+TC: OR= 1.047, 95% CI=0.929-1.180, p-value 0.453; TT vs CC+TC: OR= 0.929, 95% CI=0.775-1.114, p-value 0.429;) and Asian populations (C vs T: OR= 1.004, 95% CI=0.908-1.111, p-value 0.931; CC vs TC: OR= 0.991, 95% CI=0.896-1.097, p-value 0.865; CC vs TT: OR= 1.015, 95% CI=0.848-1.214, p-value 0.871; CC vs TT+TC: OR= 1.000, 95% CI=0.909-1.101, p-value 0.994; TT vs CC+TC: OR= 0.967, 95% CI=0.808-1.159, p-value 0.720;). No evidence of publication bias was detected during the analysis. No significant association with breast cancer risk was demonstrated overall or on subgroup (Caucasian and Asian) analysis. It can be concluded that TGF-${\beta}1$ 29T/C polymorphism does not play a role in breast cancer susceptibility in overall or ethnicity-specific manner.