이 연구는 1세대 스마트 온실의 재배환경 데이터와 장미 절 화의 품질 특성 데이터를 수집하고 그 요인들 간의 상관 관계 를 분석하여 절화수명 예측 및 최적 환경 조성의 기초 자료를 얻고자 수행되었다. 이를 위해, 토경재배(SC) 및 암면배지경 양액재배(RWH) 하우스 각 1개소를 선정하여 1년간 기온, 상 대습도(RH) 및 수증기압차(VPD), 일적산광량(DLI), 근권온도 등의 환경 데이터와 매월 말 수확된 장미 ‘Miss Holland’ 절 화의 품질 특성 데이터를 수집하였으며, 이 데이터와 절화수 명과의 상관관계를 분석하였다. 절화수명은 10월과 11월을 제외하고는 SC 하우스에서 RWH 하우스보다 더 길었다. 절 화수명과 환경 및 생육 특성 간의 상관관계 분석에서 SC 하우 스의 상관계수는 RWH 하우스보다 조금 더 높았으며, 절화수 명 예측을 위한 요소들도 두 하우스 간에 차이가 있었다. SC 하우스의 절화수명 Y=0.848X1+0.366X2-0.591X3+2.224X4- 0.171X5+0.47X6+0.321X7+9.836X8-110.219(X1-X8: 최고 RH, RH 일교차, DLI, pH, Hunter’s b value, EC, 절화 장, 잎 두께; R2=0.544)로 예측되었고, RWH 하우스의 절화수명 Y=-1.291X1+52.026X2-0.094X3+0.448X4-3.84X5+0.624X6 - 8.528X7+28.45(X1-X7: 경경, 야간 VPD, 최고 근권온도, 최 저 근권온도, 기온 일교차, RH 일교차, 최고 VPD; R2=0.5243) 로 예측되었다. 이 두 모델식으로부터 SC 하우스에서는 RH, EC 및 pH가, 그리고 RWH 하우스에서는 근권 온도가 절화수명에 더 큰 영향을 미친다는 것을 추론할 수 있다. 따라서 각 재배 방법에 따라 장미의 절화수명에 더 큰 영향을 미치는 환경적 요인을 효율적으로 관리할 필요가 있다.

algorithms for deriving and analyzing retroreflectivity influence factors through regression analysis. METHODS : An experimental road lane was created to examine the trends of retroreflectivity and LiDAR intensity values, and a controlled indoor experiment was conducted to identify influencing factors. The optimal algorithm was developed by regression analysis of the experimental data. RESULTS : The significance probability (P-value) through SPSS linear regression analysis was 0.000 for measured height, 0.001 for perpendicular angle, 0.157 for vertical angle, and 0.000 for LiDAR intensity, indicating that measured height, vertical angle, and LiDAR intensity are significant factors because the significance probability is less than 0.05, and vertical angle is not significant. The NNR regression model performed the best, so the measurement data with height (1.2m, 2m, 2.2m) and vertical angle (11.3°, 12.3°, 13.5°) were analyzed to derive the optimal LiDAR Intensity measurement height and vertical angle. CONCLUSIONS : For each LiDAR measurement height and vertical angle, the highest correlation between LiDAR Intensity and retroreflectivity was found at a measurement height of 1.2 meters and a vertical angle of 12.3°, where the model learning accuracy (R2) was the highest.

Complaints about foul odors are emerging as an issue, and the number of complaints is steadily increasing every year. Biofiltration is known to remove harmful or odorous substances from the atmosphere by using microorganisms, and full-scale biofilters are being installed and operated in various environmental and industrial facilities. In this study, the current status and actual odor removal efficiency of full-scale biofilters installed in publicly owned treatment facilities such as sewage, manure, and livestock manure treatment plants were investigated. In addition, the effects of design and operating factors on their efficiency were also examined. As a result, it was found that odor prevention facilities with less than 30% odor removal efficiency based on complex odors accounted for 40%-50% of the biofilters investigated. In investigating the appropriate level of operating factors on odor removal efficiency, it was found that compliance with the recommended values p lays a significant role in improving odor removal efficiency. In the canonical correlation analysis for the on-site biofilter operation and design data, residence time and humidity were found to be the most critical factors. The on-site biofilter operation and design data were analyzed through canonical correlation analysis, and the residence time and humidity maintenance were found to be the most important factors in the design and operations of the biofilter. Based on these results, it is necessary to improve the odor removal efficiency of on-site biofilters by reviewing the effectiveness of the operation factors, improving devices, and adjusting operating methods.

PURPOSES : Local governments in Korea, including Incheon city, have introduced the pavement management system (PMS). However, the verification of the repair time and repair section of roads remains difficult owing to the non-existence of a systematic data acquisition system. Therefore, data refinement is performed using various techniques when analyzing statistical data in diverse fields. In this study, clustering is used to analyze PMS data, and correlation analysis is conducted between pavement performance and influencing factors. METHODS : First, the clustering type was selected. The representative clustering types include K-means, mean shift, and density-based spatial clustering of applications with noise (DBSCAN). In this study, data purification was performed using DBSCAN for clustering. Because of the difficulty in determining a threshold for high-dimensional data, multiple clustering, which is a type of DBSCAN, was applied, and the number of clustering was set up to two. Clustering for the surface distress (SD), rut depth (RD), and international roughness index (IRI) was performed twice using the number of frost days, the highest temperature, and the average temperature, respectively. RESULTS : The clustering result shows that the correlation between the SD and number of frost days improved significantly. The correlation between the maximum temperature factor and precipitation factor, which does not indicate multicollinearity, improved. Meanwhile, the correlation between the RD and highest temperature improved significantly. The correlation between the minimum temperature factor and precipitation factor, which does not exhibit multicollinearity, improved considerably. The correlation between the IRI and average temperature improved as well. The correlation between the low- and high-temperature precipitation factors, which does not indicate multicollinearity, improved. CONCLUSIONS : The result confirms the possibility of applying clustering to refine PMS data and that the correlation among the pavement performance factors improved. However, when applying clustering to PMS data refinement, the limitations must be identified and addressed. Furthermore, clustering may be applicable to the purification of PMS data using AI.

본 연구는 병원간호사의 조직몰입 및 관련요인에 대한 선행연구를 체계적으로 고찰하고 메타분석을 시행하고자 한다. 이를 통해 병원간호사의 조직몰입에 대한 연구동향과 유효한 변수를 규명하고자 하 며, 간호사의 조직몰입 향상을 위한 전략 및 중재개발의 기초를 제공하고자 한다. 본 연구는 2008~2018년 발표된 연구에 대한 문헌고찰과 메타상관 분석을 실시하여 병원간호사의 조직몰입과 관 련된 요인들을 분석하였다. PRISMA표를 활용하여 연구에 대한 스크리닝과 질적 평가를 시행하였고, 최종 144개의 논문을 추출하였다. 조직몰입과 관련해서는 45개의 변수가 유의미하게 분류되었으며, Schaufeli’s Energy Compass Model에 따라 이 변수들을 6개 그룹(직무요구, 직무자원, 참여형 리더 십, 개인적 자원, 피고용인의 웰빙, 직무성과)으로 분류하였다. 이들 중 직무요구를 제외한 5개 범주가 조직몰입과 일정 정도의 강한 상관관계를 보였다. 또한, 조직몰입과 긍정적인 직무성과 간에는 강한 정(+)적 상관관계가 발견되었다. 본 연구 결과, 병원간호사의 조직몰입과 직무자원 간에는 상관관계가 존재한다는 것이 규명되었다. 본 연구 결과는 향후 병원간호사의 조직몰입을 높이기 위한 프로그램 개발 및 연구에 기초자료로 활용될 수 있을 것이다

This study measured the suspended fungal concentration in indoor multiple facilities nationwide. The regions were selected as representative cities by region: Seoul, Gyeonggi (Incheon), Gangwon, Gwangju, Daejeon, and Busan. A total of 2028 regional comparisons, including department stores, schools, public toilets, libraries, and banks, subway, sports facilities and comparative analysis were conducted for each multi-use facility industry. Among the nationwide, Among the regions, the average concentration of floating mold in indoor multi-use facilities was the lowest in Busan at 394.67 CFU/m3, followed by Gyeonggi and Incheon 487.90 CFU/m3, Seoul 542.84 CFU/m3, Daejeon 809.30 CFU/m3, Gangwon 1,145.22 CFU/m3, Gwangju was 1,371.10 CFU/m3 in the order. Busan was the lowest, and Gangwon was the highest. The reason that Busan, which has a high average temperature and population density, shows a lower mold concentration than Gangwon, is that floating mold in the indoor air is not affected by the external atmospheric environment, population density, and number of facility users. Although it cannot be said that there is no influence of the atmospheric environment, it was found that the indoor environment has different characteristics from the outdoor environment. The importance of air quality management has been confirmed, and further, it is necessary to subdivide the management standards by region and multi-use facilities, and the management standards need to be converted to maintenance rather than recommendations.

PURPOSE: 본 연구의 목적은 둥근어깨자세(round shoulder posture)와 전방머리자세 (forward head posture)에 따라 폐활량 측정과 산소포화도 및 횡격막 움직임 크기의 상관관계를 알아보는 것이다. METHODS: 연구의 대상은 만성 심장질환 및 호흡기 질환을 가지고 있거나, 정신적, 인지적 장애가 있는 자, 척추옆굽음증(scoliosis)이 있는 자, 목과 갈비뼈 손상이나 수술 병력이 없는 50명의 자원한 사람으로 선정되었습니다. 통계분석은 피어슨(Pearson)의 상관분석을 실시한다. RESULTS:둥근어깨자세는 FVC,FEV1,FEV1/FVC%,PEF 에 대해 양의 상관계수를 보이고 이중 PEF가 가장 상관성이 높았다(p<.05). 횡격막 움직임의 크기(DMD)에 대해서도 양의 상관계수를 보였다. 그러나 TAD(table acromion distance)와는 음의 상관관계를, SPO2는 PM/C7~acro, TAD(table acromion distance) 둘다 음의 상관관계가 나타났다(P>.05). 전방머리자세는 CVA와 CRA 모두 FVC,FEV1,FEV1/FVC, PEF 비율에 대해 유의한 상관관계가 없다(p>.05). CRA와 DMD에는 유의한 차이가 있는 음의 상관관계가 나타났지만(p<.05), CVA와 DMD에는 유의한 상관관계가 발견되지 않았다. 또한 CVA와 CRA 모두 SPO2에 대해 유의한 상관관계가 없다(p>.05). CONLUSION: 결론적으로 전방머리자세의 각도와 둥근어깨 자세에 따라 폐활량과 횡격막 움직임에 영향을 미친다는 것을 확인 할 수 있었다. 하지만 좀더 많은 인원과 대상자들의 경직된 자세에 대해 제한할 방법을 추가적으로 찾을 필요가 있다.

Phosphate coating is applied to the surface of the round bar material used in the multi-stage cold forging process for the purpose of lubrication. The film characteristics are determined according to the conditions of the phosphate film treatment process. In this study, the film properties according to the phosphate treatment conditions were defined as the coefficient of repeated friction and quantitative analysis was performed. Different friction behaviors were exhibited depending on the film properties, suggesting that optimization of the phosphate film treatment conditions is possible based on this. Finally, as a practical example, friction behavior according to the film characteristics was applied to the automotive engine bolt forming process. As a final conclusion, the need for linkage analysis with phosphating conditions for optimizing the forging process was raised. In addition, it can be seen that damage to the phosphate film should be considered in the process of predicting the limiting life of the die.

As modern society has emerged and developed, the subway has established itself as a representative means of transportation in the city due to its speed, accuracy, and accessibility. According to the Indoor Air Quality Management Act, underground stations have established and managed the maintenance and recommendation standards for PM10, PM2.5, CO2, CO, HCHO, NO2, Rn, VOCs However, th the standards for airborne mold has not been applied for subway stations even though management for the health effect of exposure to mold is necessay. In this study, the correlation with major contributing factors was analyzed by measuring the concentration of airborne molds in the indoor air of underground stations and through literature research. It was confirmed that there was a correlation between the concentration of airborne molds in subway stations and the major contributing factors. As a result of the analysis, it was found that the concentration of airborne molds became higher as the location of the platform became deeper underground, during periods of congestion, and especially in summer. There was no significant correlation with the year of construction. Our findings indicate that appropriate management measures should be devised in response to such contributing factors.

이 논문은 대중음악의 리듬에 큰 영향을 끼친 펑크 리듬과 아프로 큐반 리듬을 구조적 관점으로 분석하여 그 연관성과 응용과정을 연구하였다. 펑크 리듬은 1965년 제임스 브라운과 그의 밴드들 에 의해 발생 및 발전되었으며, 아프리카에서 온 흑인들에게 영향을 받은 라틴 음악의 리듬을 미 국 대중음악에 적용하고 융합하여 만들어 낸 리듬이다. 대중음악 리듬에 큰 영향을 끼치고 있는 펑크 리듬의 발생과 발전에 대해 체계적으로 분석하여, 리듬의 응용과 융합 방법의 원리를 제시하 는 것이 이 연구의 목적이다. 연구 방법은 대중음악 리듬의 혁명으로 불리는 1960년대 중반 이후 의 제임스 브라운의 앨범에 정착된 펑크 리듬과 아프로 큐반 음악의 리듬 구조를 비교하여 연관성 을 분석하였고, 대중음악 리듬으로 응용 및 적용하는 과정에 대해 추론하였다. 연구 결과 아프로 큐반의 대표적인 리듬들과 대중음악에서 사용되는 펑크의 중심 리듬에서 그 연관성을 찾을 수 있 었으며, 특히 드럼의 킥 패턴과 킥과 스네어 드럼 조합의 패턴을 응용하여 대중음악 리듬으로 만 들었다는 것을 도출해 내었다. 마지막으로 이 방법을 활용하여 좀 더 많은 전통 리듬들을 응용하 여 새로운 대중음악의 리듬을 응용하고 만들어내는 가능성을 제시하였다.

This paper analyzed the correlation between injection molding factors through correlation analysis. In addition, the decision-tree model, which is a white box model with excellent explanatory power, was used to obtain optimal molding conditions that satisfy multiple constraint conditions. First, 243 data to be used in the experiment were created through a full factorial design. Second, a correlation analysis was conducted to understand the correlation. Third, to verify the decision-tree model, the prediction performance was evaluated using RMSE. As a result, good prediction performance was confirmed. A decision-tree experiment analysis was conducted. As a result of the progress, the same results as the correlation analysis were derived. Based on the previous analysis results, optimal molding conditions were applied to CAE. As a result, the amount of deformation in the multi-cavity could be improved by about 1.1% and 2.72% while satisfying the constraint.

Background: Volleyball is a team sport that requires a lot of movement and explosive movement. Volleyball players have different roles depending on their position. The reason is that the spiker or center is tall and the libero or setter is relatively small compared to other positions. Objectives: To investigate a difference in basic physical fitness according to the positions of volleyball players and to examine the correlation between basic physical fitness items. Design: Correlational research designs. Methods: A total of 33 male professional volleyball players were recruited for each position by position: 15 spikers, 7 centers, 5 setters, and 6 liberos. Muscle endurance, power, agility, and balance ability were measured as basic physical fitness items. Results: There was a statistically significant difference in agility according to each position (P<.05), and a positive correlation was indicated in muscle endurance and power (P<.05). Conclusion: A training program can be developed based on the correlation between training and basic physical fitness according to the positions of volleyball players.

PURPOSES : In a previous study, an error was detected in data pertaining to the direction and velocity of a roller. Hence, in this study, the correlation between these two variables and acceleration data is analyzed. Relevant algorithms are developed by adding variables to existing algorithms. METHODS : A tachometer and GPS are used to acquire the velocity, compaction direction of rollers, and number of compactions. Subsequently, data input to an accelerometer are compared and analyzed. RESULTS : Based on FFT analysis, it is discovered that the data are inaccurate when a forward reverse is performed. Using the GPS, the velocity of the roller is differentiated based on the number of pledges, and then added as a variable to the algorithm. Subsequently, it is evaluated and analyzed only with data during forward movement based on changes in the latitude and longitude. CONCLUSIONS : It is discovered that the acceleration data values from both the left and right rollers differ owing to their weight difference, as indicated by the asphalt gradient. Data changes based on asphalt gradients are analyzed using gyro sensors. If the correlation between the two sets of data is high, then the algorithm is advanced by introducing a cross spectrum after calibrating the acceleration value based on the gradient.