• 디자인학연구
• /
• 제16권2호
• /
• pp.355-364
• /
• 2003

본 연구는 디자인의 프로세스를 2단계모델과 3단계모델로 구분하고 이들 각 모델의 효율성에 대하여 검증하였다. 2단계모델은 디자이너의 창의적인 마인드를 바탕으로 주관적이고 감각적으로 수행하는 디자인활동을 의미하며 반대로 3단계모델인 경우 객관적이고 논리적인 소비자 중심적자인 활동을 의미한다. 기존 연구에서는 이러한 두 가지 모델에 대하여 상대적으로 어떤 모델이 더 효과적인가에 대하여 의견의 일치를 이루어내지 못하였다. 본 연구에서는 이들 두 모델에 대하여 시장선도전략(market leader strategy)과 시장탐색전략(market seeker strategy)의 개념을 통해 각각의 효율성을 제시하였다 즉, 실증분석을 통해 명성브랜드라면 2단계모델을 바탕으로 한 시장선도전략이 그리고 비명성브랜드인 경우에는 3단계 모델을 바탕으로 한 시장탐색전략이 더 효율적이라는 상황적 입장을 제시하였으며 다만 어떤 상황에서 어떤 모델이 더 효율적인지에 대한 다각적인 검토가 더 필요하다고 제안하고 있다.

• Asia pacific journal of information systems
• /
• 제11권3호
• /
• pp.23-42
• /
• 2001

Recently, knowledge management becomes a core management tool for efficient and effective organizations. However, there are little known researches on measuring knowledge management level. The objective of this paper is to develop a process capability model for knowledge management of an organization. We developed 5 stage process capability model for knowledge management. The 1st stage is the initial stage where no significant knowledge management activity is performed. The 2nd stage is the performed stage where planning and tracking activities are performed on organization level. The 3rd stage is the established, and the 4th stage is the predictable stage where processes and results of knowledge management can be predictable. Final stage is the optimizing stage where knowledge management process is continuously improved at an organizational level. We surveyed 37 korean companies to test the validity of the proposed stage model. Statistical tests show that the developed stage model of knowledge management is valid and sound in general conditions. The result of this study on process capability model can be a solid stepping stone for future works in this area.

• International Journal of Internet, Broadcasting and Communication
• /
• 제14권2호
• /
• pp.136-146
• /
• 2022

Some surface defects make the weak quality of steel materials. To limit these defects, we advocate a one-stage detector model RetinaNet among diverse detection algorithms in deep learning. There are several backbones in the RetinaNet model. We acknowledged two backbones, which are ResNet50 and VGG19. To validate our model, we compared and analyzed several traditional models, one-stage models like YOLO and SSD models and two-stage models like Faster-RCNN, EDDN, and Xception models, with simulations based on steel individual classes. We also performed the correlation of the time factor between one-stage and two-stage models. Comparative analysis shows that the proposed model achieves excellent results on the dataset of the Northeastern University surface defect detection dataset. We would like to work on different backbones to check the efficiency of the model for real world, increasing the datasets through augmentation and focus on improving our limitation.

• 기본간호학회지
• /
• 제9권1호
• /
• pp.123-132
• /
• 2002

Purpose: The purpose of this study was to develop an exercise intervention program based on stage of exercise using the Transtheoretical Model (TTM) for patients with type 2 diabetes mellitus (DM). Method : A methodological research design was used to develop the exercise intervention program based on stage of exercise using TTM. Result: The exercise intervention program consisted of theoretical background and goals of program, assessment tool for stage of change, and an exercise intervention program based on stage of exercise. Details for the exercise and a glossary are included, Conclusion : The exercise intervention based stage of exercise can apply for DM patients who are in any stages properly.

• 대한간호학회지
• /
• 제30권2호
• /
• pp.366-379
• /
• 2000

The purpose of this study was to identify causal relationships among variables of transtheoretical model for exercise in the elderly A predictivel model explaining the stage of change was constructed based on a transtheoretical model. Empirical data for testing the hypothetical model was collected from 198 old adults over 60 years old in a community setting in Seoul, Korea in April and May,1999. Data were analyzed by descriptive statistics and correlational analysis using pc-SAS program. The Linear Structural Modeling (LISREL) 8.0 program was used to find the best fit model which predicts causal relationship of variables. The fit of the hypothetical model to the data was X2=132.85. (df=22, p=.000). GFI=.88, NNFI=.35, NFI=.77, AGFI=.59 which was not favorable but the fit of modified model to the data was X2=46.90. (df=27, p=.01).GFI= .95, NNFI=.91, NFI=.92, AGFI=.87) which was more than moderate. The predictable variables of stage of change for exercise of the Korean elderly were helping relationship, self cognitive determination, conversion of negative condition in process of change and efficacy for exercise. These variables explained 68% of stage of change for exercise of the Korean elderly.

• 대한치과기공학회지
• /
• 제13권1호
• /
• pp.15-19
• /
• 1991

This study was made to effect on the porosity when model making for control of vibrator. Samples of total 600 were made by plaster and stone divided low, medium and high which is 100 each. The following results were obtained to observation porosity of surface by eyes. 1. Second stage was fewer than third stage, first stage was fewer than third stage in porosity number of plaster model. 2. Second stage was fewer than first stage in porosity number of stone model. 3. Stone model was fewer than plaster model in porosity number of third stage.

• Communications for Statistical Applications and Methods
• /
• 제18권4호
• /
• pp.423-431
• /
• 2011

본 논문에서는 사회적으로나 개인적으로 매우 민감한 조사에서 조사하고자 하는 모집단이 여러개의 층으로 구성되어 있는 경우에, 김종호등 (1992)이 제안한 2단계 무관질문모형에서 사용한 단순임의 추출법 대신에 층화추출법을 적용하여 각 층의 모비율에 대한 추정뿐만아니라 모집단 전체 모비율에 대한 추정을 할 수 있는 층화 2단계 무관질문모형을 제안하였다. 그리고 층화 2단계 무관질문모형을 층화 3단계 무관질문 모형으로 확장하였다. 또한, 제안한 2단계와 3단계 층화 무관질문모형들에 있어서 각 층의 표본배분에 대하여 비례배분과 최적 배분 문제를 고려하여 다루었다. 마지막으로 층화 2단계 무관질문모형과 층화 3단계 무관질문모형과의 상대효율을 비교하였으며, 그 결과 층화 3단계 무관질문모형이 층화 2단계 무관질문모형보다 효율성면에 있어서 더 우수함을 알 수 있었다.

• 응용통계연구
• /
• 제13권2호
• /
• pp.575-590
• /
• 2000

Greenberg et al.(1969)은 무관질문모형에서 무관한 속성이 미지인 경우 두 개의 독립표본을 이용하여 민감한 속성에 대한 모비율을 추정해 내는 이표본 무관질문모형을 제안하였다. 본 논문에서는 Mangat-Singh(1990)의 모형을 개선한 형태의 김종호 외 2인(1992)이 제안한 2단계 무관질문모형과 이기성과 홍기학(1998)이 제안한 개선된 무관질 문모형을 무관한 속성이 미지일 때 두 개의 독립표본을 이용하는 2단계 이표본 무관질 문모형과 개선된 이표본 무관질문모형으로 확장하였다. 그리고, Greenberg et al. 의 모형과 2단계 이표본 무관질문모형, 그리고 개선되 이표본 무관질문모형과의 효율성을 비교 하였다.

• 사상체질의학회지
• /
• 제22권3호
• /
• pp.87-97
• /
• 2010

1. Objectives: In SCM, a personal Sasang constitution must be determined accurately before any Sasang treatment. The purpose of this study is to develop an objective method for classification of Sasang constitution. 2. Methods: We collected samples from 5 centers where SCM is practiced, and applied two-stage decision tree analysis on these samples. We recruited samples from 5 centers. The collected data were from subjects whose response to herbal medicine was confirmed according to Sasang constitution. 3. Results: The two-stage decision tree model shows higher classification power than a simple decision tree model. This study also suggests that gender must be considered in the first stage to improve the accuracy of classification. 4. Conclusions: We identified important factors for classifying Sasang constitutions through two-stage decision tree analysis. The two-stage decision tree model shows higher classification power than a simple decision tree model.

• Smart Structures and Systems
• /
• 제29권1호
• /
• pp.29-39
• /
• 2022

Crack detection plays an important role in the maintenance and protection of steel box girder of bridges. However, since the cracks only occupy an extremely small region of the high-resolution images captured from actual conditions, the existing methods cannot deal with this kind of image effectively. To solve this problem, this paper proposed a novel three-stage method based on deep learning technology and morphology operations. The training set and test set used in this paper are composed of 360 images (4928 × 3264 pixels) in steel girder box. The first stage of the proposed model converted high-resolution images into sub-images by using patch-based method and located the region of cracks by CBAM ResNet-50 model. The Recall reaches 0.95 on the test set. The second stage of our method uses the Attention U-Net model to get the accurate geometric edges of cracks based on results in the first stage. The IoU of the segmentation model implemented in this stage attains 0.48. In the third stage of the model, we remove the wrong-predicted isolated points in the predicted results through dilate operation and outlier elimination algorithm. The IoU of test set ascends to 0.70 after this stage. Ablation experiments are conducted to optimize the parameters and further promote the accuracy of the proposed method. The result shows that: (1) the best patch size of sub-images is 1024 × 1024. (2) the CBAM ResNet-50 and the Attention U-Net achieved the best results in the first and the second stage, respectively. (3) Pre-training the model of the first two stages can improve the IoU by 2.9%. In general, our method is of great significance for crack detection.