• Archives of design research
• /
• v.16 no.2
• /
• pp.355-364
• /
• 2003

This research verified efficiency of 2 design process models; 2-stage model and 3-stage model. 2-stage model means subjective and sensitive design process based on designer's creative mind. Contrarily, 3-stage model means objective, logical and consumer-oriented design process. Past researches have suggested inconsistent conclusions on efficiency of 2 design process models. This study suggested efficiency of 2 design process model based on the concept of market leader strategy and market seeker strategy. The study results imply that, in condition of high prestige brand, 2-stage model based on market leader strategy is more effective and contrarily in case of low prestige brand, 3-stage model based on market seeker strategy is more efficient. However, it is requested to perform various investigation about situations in which each design process model is more effective for the generalization of the study results.

• Asia pacific journal of information systems
• /
• v.11 no.3
• /
• 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
• /
• v.14 no.2
• /
• 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.

• Journal of Korean Academy of Fundamentals of Nursing
• /
• v.9 no.1
• /
• 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.

• Journal of Korean Academy of Nursing
• /
• v.30 no.2
• /
• 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.

• Journal of Technologic Dentistry
• /
• v.13 no.1
• /
• 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
• /
• v.18 no.4
• /
• pp.423-431
• /
• 2011

For procuring more sensitive information and estimating stratum target population proportion as well as an overall one form a sensitive population composed of several strata we suggest a two-stage stratified unrelated question model that uses stratified random sampling instead of simple random sampling in the two-stage unrelated question model by Kim et al. (1992) and extend it to the three-stage stratified unrelated question model. We also deal with the proportional and optimal allocation problems in each suggested model, compare the relative efficiency of the suggested two models, and show that the three-stage stratified unrelated question model is more efficient than the two-stage one in view of the variance.

• The Korean Journal of Applied Statistics
• /
• v.13 no.2
• /
• pp.575-590
• /
• 2000

In this paper, we extended the Kim et al.'s two-stage unrelated question model(1992) and the Lee et al.'s improved unrelated question model(1998) to two sample unrelated question model of using two independent samples in the case of unknown $\pi_y$.

• Journal of Sasang Constitutional Medicine
• /
• v.22 no.3
• /
• 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
• /
• v.29 no.1
• /
• 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.