통합 검색 | Korea Science

In, Joon-Hwan;Lim, Joa-Sang
- 한국IT서비스학회:학술대회논문집
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- 한국IT서비스학회 2005년도 추계학술대회
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- pp.356-365
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- 2005
Since their first inception a few decades ago, software components have received much attention mainly due to their alleged benefits of quality and productivity improvement. Despite this, it is yet to be agreed upon what and how components should be designed. This paper aimed to bridge the gap by proposing a collaborative process where the voice of the customer is captured and documented by employing the event and entity models. These requirement elements (WHAT) are cross-tabulated in three relation matrices in accordance with the weights provided by the business users. The requirements are fed into the algorithm invented by the authors to optimize the component grouping (HOW). This collaborative process has been successfully validated at an enterprise wide software development project. The process was effective to help the users more actively involved in the design of the system and made the whole process faster and more adaptive to the changes.
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임좌상
- 한국IT서비스학회지
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- 제5권1호
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- pp.177-190
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- 2006
Since their first inception a few decades ago, software components have received much attention mainly due to their alleged benefits of quality and productivity improvement. Despite this, it is yet to be agreed upon what and how components should be designed. This paper aims to bridge the gap by proposing a collaborative process where the voice of the customer is captured and documented by employing the event and entity models. These requirement elements (WHAT) are cross-tabulated in three relation matrices in accordance with the weights provided by the business users. The requirements are fed into the algorithm invented by the authors to optimize the component grouping (HOW). This collaborative process has been successfully validated at an enterprise wide software development project. The process was effective to help the users more actively involved in the design of the system and made the whole process faster and more adaptive to the changes.
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Minjoo Joa;Rosy Oh;Man-Suk Oh
- Communications for Statistical Applications and Methods
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- 제30권5호
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- pp.517-530
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- 2023
Recent studies revealed that fine dust in ambient air may cause various health problems such as respiratory diseases and cancer. To prevent the toxic effects of fine dust, it is important to predict the concentration of fine dust in advance and to identify factors that are closely related to fine dust. In this study, we developed a Bayesian network model for predicting PM10 concentration in Seoul, Korea, and visualized the relationship between important factors. The network was trained by using air quality and meteorological data collected in Seoul between 2018 and 2021. The study results showed that current PM10 concentration, season, carbon monoxide (CO) were the top 3 effective factors in 24 hours ahead prediction of PM10 concentration in Seoul, and that there were interactive effects.
https://doi.org/10.29220/CSAM.2023.30.5.517 인용 PDF