• 성인간호학회지
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• 제20권3호
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• pp.489-499
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• 2008

Purpose: The purpose of this study was to assess the importance and contribution of 9 nursing outcomes and their indicators that could be applied to cerebrovascular patients. Methods: Data were collected from 175 neurosurgical nurses working at two university affiliated hospitals and five secondary hospitals located in Gwang-ju. The Fehring method was used to estimate outcome content validity(OCV) and outcome sensitivity validity(OSV) of nursing outcomes and their indicators. Stepwise regression was used to evaluate relationship between outcome and its indicators. Results: The core outcomes identified by the OCV were Tissue Perfusion: Cerebral, Nutritional Status, Neurological Status, and Wound Healing: Primary Intention, whereas highly supportive outcomes identified by the OSV were Oral Health, Self-Care: ADL, and Nutritional Status. All the critical indicators selected for Fehring method were not included in stepwise regression model. By stepwise regression analysis, the indicators explained outcomes from 19% to 52% in importance and from 21% to 45% in contribution. Conclusion: This study identified core and supportive outcomes and their indicators which could be useful to assess the physical status of cerebrovascular patients. Further research is needed for the revision and development of nursing outcomes and their indicators at neurological nursing area.

• 대한산업공학회지
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• 제40권6호
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• pp.628-641
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• 2014

Stepwise efficiency improvement in data envelopment analysis (DEA)-based benchmarking is a realistic and effective method by which inefficient decision making units (DMUs) can choose benchmarks in a stepwise manner and, thereby, effect gradual performance improvement. Most of the previous research relevant to stepwise efficiency improvement has focused primarily on how to stratify DMUs into multiple layers and how to select immediate benchmark targets in leading levels for lagging-level DMUs. It can be said that the sequence of benchmark targets was constructed in a myopic way, which can limit its effectiveness. To address this issue, this paper proposes an optimization approach to the construction of a sequence of benchmarks in DEA-based benchmarking, wherein two optimization criteria are employed : similarity of input-output use patterns, and proximity of input-output use levels between DMUs. To illustrate the proposed method, we applied it to the benchmarking of 23 national universities in South Korea.

• Journal of Microbiology and Biotechnology
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• 제10권4호
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• pp.476-481
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• 2000

A linear correlation, by the stepwise multiple regression analysis, was found between the sensory test of Sigumjang aroma and the gas chromatographic data which were transformed with logarithm. GC data is the most objective method to evaluate Sigumjang aroma. A multiple correlation coefficient and a determination coefficient of more than 0.9 were obtained at the 9th and 13th steps, respectively. At step 31, the coefficient of determination level of 0.95 was attained. The accuracy of its estimation became higher as the number of the variables entered into the regression model increased. Over 90% of the Sigumjang aroma was explained by 13 compounds indentified on GC. The contributing proportion of the peak 26 was the highest followed by peaks 57 (9.27%), 29 (7.51%), 54 (6.01%), 8 (5.99%), 49 (4.97%), and 13 (4.11%).

• 한국산학기술학회논문지
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• 제12권6호
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• pp.2840-2850
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• 2011

임베디드 시스템을 설계하기 위해서는 하드웨어 설계와 소프트웨어 설계를 동시에 진행하여 마지막으로 그들을 통합하여 시스템을 구축하는 하드웨어/소프트웨어 공동 설계라는 설계 방법을 사용한다. 본 연구에서는 기존의 임베디드 시스템 설계의 문제점을 분석하고 그 해결 방안으로 SpecC 기술을 이용한 시스템 레벨 설계 방법을 제안한다. 또한 시스템 레벨 설계의 단계적 상세화를 실현하기 위해 소프트웨어 공학의 리팩토링 기술을 적용하여 체계적이고, 구체적인 단계적 상세화 방법을 제시한다.

• Journal of the Korean Data and Information Science Society
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• 제26권1호
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• pp.31-39
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• 2015

본 논문은 확률효과모형에서 사영에 근거한 분산성분을 구하는 방법을 다루고 있다. 분산성분을 추정하기 위한 ANOVA방법에서 제곱합의 계산에 사영을 이용하는 방법을 제시하고 있다. 분산성분을 구하기 위한 사영의 이용은 모형행렬에 의한 사영공간을 분산성분별 제곱합을 얻기 위한 상호직교하는 부분공간들로 분할하게 된다. 부분공간들로 분할하기 위해 모형행렬 X로의 사영에 단계별 방법(stepwise procedure)을 적용하여 해당하는 공간으로의 사영행렬을 구하는 방법을 다루고 있다. 단계별 방법에 의해 주어지는 부분공간들의 직교성으로 인해 사영행렬의 곱은 영행렬로 주어지는 성질을 갖는다. 단계별 방법에 의한 순차적 사영은 해당하는 공간으로의 사영행렬에 대한 확인과 사영행렬의 구조를 파악할 수 있는 이점이 있다. 또한 분산성분의 추정을 위한 제1종 제곱합을 구하기 위한 방법으로 유용하다.

• 산업공학
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• 제22권3호
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• pp.252-262
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• 2009

It is crucial to prevent low yields in the semiconductor industry. Since many factors affect variation in yield and they are deeply related, preventing low yield is difficult. There have been substantial researches in the field of yield prediction. Many researchers had used the statistical methods. Many studies have shown that artificial neural network (ANN) achieved better performance than traditional statistical methods. However, despite ANN's superior performance some problems such as over-fitting and poor explanatory power arise. In order to overcome these limitations, a relatively new machine learning technique, support vector machine (SVM), is introduced to classify the yield. SVM is simple enough to be analyzed mathematically, and it leads to high performances in practical applications. This study presents a new efficient classification methodology, Stepwise-SVM (SSVM), for detecting high and low yields. SSVM is step-by-step adjustment of parameters to be precisely the classification for actual high and low yield lot. The objective of this paper is to examine the feasibility of SVM and SSVM in the yield classification. The experimental results show that SVM and SSVM provides a promising alternative to yield classification for the field data.

• 한국약용작물학회지
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• 제21권3호
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• pp.204-212
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• 2013

In general, stepwise hot steaming process is known to be effective in improving its biological activities; however, not much employed in processing Codonopsis lanceolata due to its hardness. The complex processed C. lanceolata showed highest free radical scavenging acitivity as 45.21%. Total phenol and flavonoid content were of complex processed C. lanceolata higher than conventional extract and alone steaming process. It was showed the lower melanogenesis rate on melanin production test by B16F10 cells as 27.46%. High inhibitory of tyrosinase was also measured as 28.61% by adding steamed Codonopsis lanceolata extracts by high pressure extraction of 1.0 $mg/m{\ell}$. And anti-wrinkle activity were 39.08%. In comparing phenolic acids profiles in the extract, in general higher amounts of polyphenol were obtained possibly by easy release of active components during thermal processing, which results in better antioxidant activities than that of general extract. This findings can also be supported by result that the extract by steaming process showed better activities than the general extraction extract.

• Journal of the Korean Data and Information Science Society
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• 제26권2호
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• pp.347-354
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• 2015

본 논문은 균형불완비블럭설계 (balanced incomplete block design)의 자료분석에 사영을 이용한 블럭내 분석 (intrablock analysis)방법을 다루고 있다. 블럭내 분석을 위해 단계별 방법 (stepwise procedure)에서 유도되는 분석모형을 이용하고 있다. 단계별 방법의 적용으로 인해 모형행렬로 주어지는 사영공간이 변동요인에 따른 부분공간들로 직교분할됨을 보여주고 있다. 단계별 과정에서 변동요인에 따른 변동량을 구하기 위해 해당하는 효과벡터의 계수행렬에 근거한 사영의 구조적 형태를 기술하고 있으며 상호직교하는 부분공간으로의 사영을 이용하여 블럭효과에 적합된 처리효과의 변동량를 구하는 과정을 구체적으로 다루고 있다. 또한, 사영에 의해 처리효과를 구하는 과정을 제시하고 있으며 단계별로 잔차벡터를 이용하여 모형설정하는 방법과 고유벡터에 의한 추정가능함수의 구성과 추정가능성을 논의하고 있다.

• Journal of Information Technology Applications and Management
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• 제20권4호
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• pp.221-234
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• 2013

In this paper, we report bankruptcy risk level forecasting result for automobile parts manufacturing industry. With the premise that upstream supply risk and downstream demand risk could impact on automobile parts industry bankruptcy level in advance, we draw upon industry input-output table to use the economic indicators which could reflect the extent of supply and demand risk of the automobile parts industry. To verify the validity of each economic indicator, we applied simple linear regression for each indicators by varying the time lag from one month (t-1) to 12 months (t-12). Finally, with the valid indicators obtained through the simple regressions, the composition of valid economic indicators are derived using stepwise linear regression. Using the monthly automobile parts industry bankruptcy frequency data accumulated during the 5 years, R-square values of the stepwise linear regression results are 68.7%, 91.5%, 85.3% for the 3, 6, 9 months time lag cases each respectively. The computational testing results verifies the effectiveness of our approach in forecasting bankruptcy risk forecasting of the automobile parts industry.

• 센서학회지
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• 제25권1호
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• pp.13-19
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• 2016

Nowadays, most major automobile manufacturers are very interested, and actively involved, in developing driver alcohol detection system for safety (DADSS) that serves to prevent driving under the influence. DADSS measures the blood alcohol concentration (BAC) from the driver's breath and limits the ignition of the engine of the vehicle if the BAC exceeds the reference value. In this study, to optimize the sensor array of the DADSS, we selected sensors by using three different methods, configured the sensor arrays, and then compared their performance. The Wilks' lambda, stepwise elimination and filter method (using a principal component) were used as the sensor selection methods [2,3]. We compared the performance of the arrays, by using the selectivity and sensitivity as criteria, and Sammon mapping for the analysis of the cluster type of each gas. The sensor array configured by using the stepwise elimination method exhibited the highest sensitivity and selectivity and yielded the best visual result after Sammon mapping.