This paper proposes a software development evaluation index for the productivity related to Spring 2.5 and EJB 3.0 with same lightweight container architecture. Spring is a known successful open source standard model for lightweight container architecture. EJB in an enterprise environment as a standard framework is most commonly used in production. However, there is no comparison research about the performance of Spring 2.5 and EJB 3.0 with same identical platform. Quantitative analysis is supported as a part of LoC(Line of Code) analysis. There is a limit to develop the updated software with no the specific evaluating index for the productivity of the software. In this study, the development platform environment based on the same database schema system Spring 2.5 and EJB 3.0 is in the design and implementation. In addition, comparison and standardization of software development productivity assessment is to provide guidance.

This paper proposes a standard open source software development guidance and an evaluation index for the productivity related to Seam 2.0 and Spring 2.5 framework. However, there is no comparison research about the performance of Seam 2.0 and Spring 2.5 framework with same identical platform. Quantitative analysis is supported as a part of LoC analysis. There is a limit to develop the updated software with no the specific evaluating index for the productivity of the software. This work proposes an specific index for evaluating the productivity of Seam 2.0 and Spring 2.5 framework on a platform. Base on the result, the specific guidance of the developing software is obtained.

This paper proposes an object-oriented software development guidance and an evaluation index for the productivity related to Spring Framework 2.0 and 2.5. Spring Framework is a known successful open source standard model for lightweight container architecture. However, there is no comparison research about the performance of Spring Framework 2.0 and 2.5 with same identical platform. Quantitative analysis is supported as a part of LOC(Line Of Code) analysis. There is a limit to develop the updated software with no the specific evaluating index for the productivity of the software. This work proposes an specific index for evaluating the productivity of new version Spring Framework on a platform. Base on the result, the specific guidance of the developing software is obtained.

본 연구는 서울시 북동지역의 군자동에 위치한 세종대학교를 중심으로 2001년 봄철 3월에서 4월까지 PM2.5와 PM10을 채취하여, 이들과 결합된 중금속 성분들에 대한 농도분포의 특성을 살펴보았다. 전체 관측기간 동안 산출된 PM2.5, PM10, 조대입자 영역(PM10-PM2.5)의 평균농도는 49.3±29.2, 95.5±46.1, 50.5±35.0 μg/m3으로 나타났다. 연구대상지역의 중금속 오염도를 살펴보기 위해 부화계수(enrichment factor: EF)를 비교한 결과, 미세 및 조대입자 모두에서 Zn, V, Cr, Pb, Cu, Ni, Co, Mo 등의 중금속 성분들의 EF값이 수십, 수백의 범위에 달할 정도로 오염의 수준이 심각하다는 것을 확인할 수 있었다. 미세/조대입자 영역간에 형성되는 농도비를 비교한 결과, Zn, Cr, Pb, Ni 등이 미세입자 영역에서 뚜렷하게 더 높은 농도를 보이는 것으로 확인되었다. 중금속 농도에 대해 보다 세부적인 분석을 실시한 결과, 중금속 성분들의 농도는 상당 수준 증가하는데, 이와 같은 증가는 황사의 영향을 상당 수준 받는 것으로 나타났다.

In this study, the contributions of emissions (foreign and domestic) and atmospheric physical and chemical processes to PM2.5 concentrations were evaluated during a high PM2.5 episode (March 24-26, 2018) observed on the Jeju Island in the spring of 2018. These analyses were performed using the community multi-scale air quality (CMAQ) modeling system using the brute-force method and integrated process rate (IPR) analysis, respectively. The contributions of domestic emissions from South Korea (41-45%) to PM2.5 on the Jeju Island were lower than those (81-89%) of long-range transport (LRT) from China. The substantial contribution of LRT was also confirmed in conjunction with the air mass trajectory analysis, indicating that the frequency of airflow from China (58-62% of all trajectories) was higher than from other regions (28-32%) (e.g., South Korea). These results imply that compared to domestic emissions, emissions from China have a stronger impact than domestic emissions on the high PM2.5 concentrations in the study area. From the IPR analysis, horizontal transport contributed substantially to PM2.5 concentrations were dominant in most of the areas of the Jeju Island during the high PM2.5 episode, while the aerosol process and vertical transport in the southern areas largely contributed to higher PM2.5 concentrations.

In order to investigate the variations and corelation among PM10, PM2.5 and PM1 concentrations, the hourly concentrations of each particle sizes of 300 ηm to 20 μm at a city, Gangneung in the eastern mountainous coast of Korean peninsula have been measured by GRIMM aerosol sampler-1107 from March 7 to 17, 2004. Before the influence of the Yellow Dust event from China toward the city, PM10, PM2.5 and PM1 concentrations near the ground of the city were very low less than 35.97 μg/m3, 22.33 μg/m3 and 16.77 μg/m3, with little variations. Under the partial influence of the dust transport from the China on March 9, they increased to 87.08 μg/m3, 56.55 μg/m3 and 51.62 μg/m3. PM10 concentration was 1.5 times higher than PM2.5 and 1.85 times higher than PM1. Ratio of (PM10-PM2.5)/PM2.5 had a maximum value of 1.49 with an averaged 0.5 and one of (PM2.5-PM1)/PM1 had a maximum value of 0.4 with an averaged 0.25. PM10 and PM2.5 concentrations were largely influenced by particles smaller than 2.5 μm and 1 μm particle sizes, respectively. During the dust event from the afternoon of March 10 until 1200 LST, March 14, PM10, PM2.5 and PM1 concentrations reached 343.53 μg/m3, 105 μg/m3 and 60 μg/m3, indicating the PM10 concentration being 3.3 times higher than PM2.5 and 5.97 times higher than PM1. Ratio of (PM10-PM2.5)/PM2.5 had a maximum value of 7.82 with an averaged 3.5 and one of (PM2.5-PM1)/PM1 had a maximum value of 2.8 with an averaged 1.5, showing PM10 and PM2.5 concentrations largely influenced by particles greater than 2.5 μm and 1 μm particle sizes, respectively. After the dust event, the most of PM concentrations became below 100 μg/m3, except of 0900LST, March 15, showing the gradual decrease of their concentrations. Ratio of (PM10-PM2.5)/PM2.5 had a maximum value of 3.75 with an averaged 1.6 and one of (PM2.5-PM1)/PM1 had a maximum value of 1.5 with an averaged 0.8, showing the PM10 concentration largely influenced by corse particles than 2.5 μm and the PM2.5 by fine particles smaller than 1 μm, respectively. Before the dust event, correlation coefficients between PM10, PM2.5 and PM1 were 0.89, 0.99 and 0.82, respectively, and during the dust event, the coefficients were 0.71, 0.94 and 0.44. After the dust event, the coefficients were 0.90, 0.99 and 0.85. For whole period, the coefficients were 0.54, 0.95 and 0.28, respectively.