To evaluate the performance of a new automated coliform enumeration system (TEMPO® CC) for the quantitative test of coliform bacteria contaminated in domestic livestock processed foods, a total of 507 samples of livestock foods were tested by the TEMPO® CC method, the most probable number (MPN) method, and Petrifilm method, respectively. The results of those three methods were compared to each other. Of 507 samples of livestock processed foods used in this study, 217 samples were contaminated artificially with coliform bacteria and the rest (n=290) were contaminated naturally. The results of the TEMPO® CC method for all samples were equivalent to those obtained from the MPN method, except 8 samples. In addition, 496 (97.8%) out of 507 samples made agreement between the TEMPO® CC method and the Petrifilm method. The correlation coefficients between TEMPO® CC and MPN methods as well as between TEMPO® CC method and Petrifilm method were above 0.9, and the slope and intercept of the linear regression model was different in less than 1 value. In conclusion, there were statistically equivalent levels of performance between the TEMPO® CC and the reference and alternative methods for the enumeration of coliform bacteria in livestock processed foods in this study.

This study was carried out to estimate the usefulness of metal oxide semiconductor(MOS) sensor as an odor measuring instrument. In this study, sensor output for 12 legal malodorous compounds was measured by two kinds of the marketed MOS sensor and was investigated the correlation coefficient between sensor output and odor indicators as like odor concentration, air dilution ratio. As a results, it was estimated that MOS sensor has a high use possibility as odor measuring device for the single compound analysis, as the correlation coefficient between sensor outputs and odor concentration, R2 appeared to 0.9 or more high.

This study was conducted to propose a way to increase the accuracy and precision of β-ray measurement equipment. Statistical processing results of equivalent evaluation data from 2016 to 2021 confirmed that the concentration of micro dust measured by β-ray measurement equipment was higher than that of micro dust sampler. According to quarterly data, it was confirmed that the data from the third quarter (July to September) showed a different trend from other periods, which is assumed to be due to weather conditions. This study indicates that automatic micro-dust measurement equipment evaluation at air pollution measuring stations during the third quarter should be excluded. The evaluation cycle should be changed from once every two years to quarterly. In addition, when the criterion for determining equivalence evaluation falls within the range of the slope and intercept values of the existing trend line, it is necessary to evaluate the R2 value together and reduce the slope from 0.9-1.1 to 0.9-1.0.

암반사면을 안전하고 효과적으로 해석하기 위해서 암반의 역학적 특성을 면밀하게 조사해야 한다. 하지만 클리노미터를 사용한 절리조사의 한계점으로 인해 이를 보완한 새로운 측정법의 연구가 필요하다. 본 연구에서는 절리방향의 특성을 분석하기 위해 절리의 방향성을 현장에 적용할 수 있는 절리조사 측정장비를 개발하였다. 개발된 측정장비는 해석 소프트웨어와 하드웨어로 구분된다. 하드웨어는 암반 절리 방향성을 측정하는 측정모듈, 측정자료를 전송하는 전송모듈로 구성되었다. 소프트웨어는 측정모듈을 통해 얻은 데이터로부터 절리의 방향성을 분석하기 위해 개발하였으며 Drone Joint Orientation Survey Measurement로 명명하였다. 개발된 측정장비는 접근이 어려운 지역 등 조사자가 측정할 수 없는 경우에 현장적용성이 양호하며 절리의 방향성에 대한 실내시험결과를 효과적으로 분석할 수 있었다.

Purpose: Introduction of the LEGO Mindstorms EV3 as a low cost research tool for various studies and to show how study tools could be built using the LEGO with ease. Methods: To show what the LEGO Mindstorms EV3 could do for studies, programming method was described and some example devices used previous papers were reconstructed; EX1 - Selection of left right device for Stoet(2010), EX2 - Time expectation device for Kim and Ryu(2015), and EX3 - Four digits random number generator for Huh and Lee(2015). Time delay of each example device was tested to evaluate effectiveness of the LEGO Mindstorms EV3 as research device. Results: Combination of single execution structure and button switch on the EV3 brick showed 1 ms error of time measurement, and combination of single execution structure and touch sensor showed 10 ms error of time measurement. 1 ms error of time measurement is same accuracy achieved by Windows based computer system.