This study aimed to assess the pollution level in 13 crowded subway stations in an effort to understand the spatial and seasonal factors of Indoor Air Quality. The main measured items were particulate pollutants such as PM10 and PM2.5 and gaseous pollutants such as CO2, HCHO, Rn, TVOC, BTEX, and Styrene at concourses and platforms in the summer and winter periods. The influence of the draught created by the movement of the train was classified into lateral and island platforms, and the concentrations of PM by location (entrance, middle, and end) were statistically compared and analyzed. As a result, the concentrations of PM were confirmed high in the order of Platform > Concourse > Ambient air. In particular, in the case of platform PM10, the frequency exceeding the standard value (100 μg/m3) was 38.5% and the maximum concentration was 196.2 μg/m3. All gaseous pollutants were at lower levels than the standard, and the factors affecting CO2 and Rn were identified as the number of users and geological characteristics, respectively. The principal component analysis (PCA) demonstrated that PM was found to be a major indicator of the air quality management of subway stations. In particular, the concentrations at entrance and end areas in the lateral platform were about 1.4 times higher with regard to PM10 than in the middle area, and about 1.9 times higher with regard to PM2.5 due to the effect created by the draught produced by the movement of the train. Therefore, in order to manage PM in the platform area, a specialized management plan for places with particularly high PM concentration within the platform area is required. In addition, it is necessary to evaluate the effect created by the draught produced by train movement when selecting locations for measuring indoor air quality.

본 연구에서는 선택배지와 건조필름을 이용하여 신선편이 엽채류 3종(양상추, 양배추, 어린잎채소)에서 병원성 E. coli를 분리하였고, 의심집락 동정을 위해 생화학적 분석법을 사용하여 동정한 후 결과를 비교 분석하였다. 양상추 20 g, 양배추 20 g, 어린잎채소 10 g에 병원성 E. coli 혼합 균액(Enterohemorrhagic E. coli NCCP11142, Enterotoxigenic E. coli NCCP14037, Enteropathogenic E. coli NCCP14038, Enteroaggregative E. coli NCCP14039, Enteropathogenic E. coli NCCP15661)을 최종농도가 1, 2, 3 log CFU/g이 되도록 접종하였고, BPW (80~90 ml)을 넣은 후60초 동안 균질화하여 분석하였다. 연구결과, 모든 시료에서 건조필름 시험 양성, 양상추 시료 일부(최종농도 3 log CFU/g 접종시료)를 제외한 모든 시료에서 증균배양법을 이용한 정성시험결과가 음성으로 나타났다. 증균배양과 건조필름 시험을 통해 분리한 병원성 E. coli를 이용하여 생화학적 분석을 실시한 결과, 양상추에서 분리한 병원성 E. coli의 경우, API 20E 100% (44/44), Microgen GNA 100% (44/44), Food System 66.7% (10/15)의 동정률이 나타났다. 양배추의 경우, API 20E 64.7% (22/34), Microgen GNA 50% (16/32), Food System 60% (9/15), 어린잎채소의 경우, API 20E 65.1% (28/43), Microgen GNA 62.3% (27/43), Food System 53.3% (8/15)가 병원성 E. coli로 동정되었다. 본 연구의 결과는 신선편이 엽채류에 대한 병원성 E. coli 검출법 선택에 유용하게 이용될 것으로 판단된다.

This paper presents a new shape-based algorithm using affine category shape model for object category recognition and model learning. Affine category shape model is a graph of interconnected nodes whose geometric interactions are modeled using pairwise potentials. In its learning phase, it can efficiently handle large pose variations of objects in training images by estimating 2-D homography transformation between the model and the training images. Since the pairwise potentials are defined on only relative geometric relationship between features, the proposed matching algorithm is translation and in-plane rotation invariant and robust to affine transformation. We apply spectral matching algorithm to find feature correspondences, which are then used as initial correspondences for RANSAC algorithm. The 2-D homography transformation and the inlier correspondences which are consistent with this estimate can be efficiently estimated through RANSAC, and new correspondences also can be detected by using the estimated 2-D homography transformation. Experimental results on object category database show that the proposed algorithm is robust to pose variation of objects and provides good recognition performance.

This paper deals with a tangible interface system that introduces robot as remote avatar. It is focused on a new method which makes a robot imitate human arm motions captured from a remote space. Our method is functionally divided into two parts: capturing human motion and adapting it to robot. In the capturing part, we especially propose a modified potential function of metaballs for the real-time performance and high accuracy. In the adapting part, we suggest a geometric scaling method for solving the structural difference between a human and a robot. With our method, we have implemented a tangible interface and showed its speed and accuracy test.

양배추의 고부가가치 이용방안 연구의 일환으로 선택적 가열 및 추출특성이 알려진 마이크로파 에너지(50 W, 2,450 MHz)를 이용하여 양배추 추출물의 총 수율과 총 페놀 함량 및 전자공여능의 효율적 추출조건을 설정하였다. 에탄올 용매에서 건조 양배추의 입자 크기는 20 mesh 정도가 적당하였고, 시료와 용매비는 생체시료(수분 )와 건조시료(수분 ) 모두에서 1:10(5 g/50 mL) 정도가 가장 타당한 것으로 나타났다. 추출용매의 영향에서