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조동혁,박종우 한국IT서비스학회 2015 한국IT서비스학회지 Vol.14 No.3
The spread of mobile commerce due to popularization of smartphones not only broke down the boundary between online and offline, but also changed the consumer life, and hence brought change of commerce paradigm that creates new demand. The success of innovative information technology such as mobile shopping can be defined as an individual accepting the technology and continuously using it, but the studies on the usage behavior after the acceptance have been done in very restrictively, despite its importance. In this study, in order to empirically investigate the factors that influence the continuance in mobile shopping usage experience and its causal relationship, Social Cognitive Theory and Habit Theory were applied to IS Continuance Model,and the extended IS Continuance Model was suggested and proved. As a result, the usefulness, enjoyment, and self-efficacy perceived in usage experience significantly influence satisfaction, and usefulness, self-efficacy, and satisfaction influence habit. Also, usefulness, self-efficacy, satisfaction, and habit significantly influence continuance intention. This study provides a valuable asset in providing an opportunity to understand the usage behavior of mobile shopping service users after the acceptance, and furthermore proving directionality in improving customer loyalty.
조동혁,Young-seog Lee 한국자동차공학회 2019 International journal of automotive technology Vol.20 No.Supp
This study proposes a fast running model that interconnects input and output data for a single-pass cold bar drawing process through the use of Artificial Neural Network (ANN) and automatically generated a large volume of elasticplastic finite element (FE) analysis results. The prediction accuracy of the FE analysis was verified by comparing the FE analysis with measurements from a drawing experiment. A Python-based script that automatically controls ABAQUS was coded to sequentially produce output data that varies according to the input data, which is a combination of 18 grades of steel and 1,000 process conditions. The ANN was trained using input and output data, and then a nine-dimensional fast running model was developed. The fast running model predicted the values of output variables (drawing force, strain at the center, strain on the surface, accumulated damage at the center, contact pressure, and the fracture (or non-fracture) of the material) in 0.1 second no matter how the mechanical properties of the steels and process conditions change. With this fast running model, engineers in the drawing industry can easily determine or modify the process conditions to improve productivity and product quality even when a grade of steel that has never been employed before is drawn.
조동혁,장윤찬,이영석 대한기계학회 2019 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.33 No.9
In this study, we selected six ductile fracture (DF) criteria to assess their capability to predict material fracture when high-alloy steel was cold drawn at a wide range of reduction ratios and die semi-angles in a single-pass drawing process. A user-defined subroutine VUSDFLD for each DF criterion was coded in Fortran and integrated into ABAQUS. Twenty-eight drawing tests were performed using a combination of reduction ratio (r) range (10-49 %) and die semi-angle (a) range (4°-25°). Test results were compared with the results of finite element simulations. The results showed that, if three macroscopic variables (namely, stress triaxiality, maximum principal stress, and equivalent stress) and a cut-off value are combined in a DF criterion, the fracture of the material being drawn can be predicted at a sufficient level. This DF criterion showed a much higher prediction accuracy than the other five DF criteria, especially in the operating region (a < 10° and r > 40 %) where the producer of cold-drawn steel bar (or rod) products prefers to increase productivity and improve quality.
제2형 당뇨병 환자에서 경동맥 죽상경화증이 사구체여과율의 감소에 미치는 영향
조동혁,정진욱,정동진,정민영 대한내분비학회 2011 Endocrinology and metabolism Vol.26 No.4
Background: Cardiovascular risk is higher among people with diabetic nephropathy than among those with normal renal function. Carotid intima-media thickness (IMT) is an independent predictor of cardiovascular mortality in type 2 diabetic patients. However, the relationship between carotid IMT and diabetic nephropathy is not well known. The aim of our study was to elucidate whether carotid IMT is associated with progression of diabetic nephropathy in type 2 diabetic patients. Methods: We recruited a total of 354 type 2 diabetic patients with diabetic nephropathy. Renal function was evaluated by serum creatinine levels, estimated glomerular filtration rate (eGFR), and urinary albumin/creatinine ratio (ACR). Carotid IMT was assessed using B-mode ultrasound by measuring generally used parameters. Baseline-to-study end changes in eGFR were calculated,and the yearly change of eGFR (mL/min/yr) was computed. Results: Age, diabetes duration, ACR, and eGFR were significantly correlated with mean or maximal carotid IMT; however, lipid profiles, HbA1c, and blood pressure were not correlated. The mean yearly eGFR change was -4.9 ± 5.3 mL/min/yr. The yearly eGFR change was negatively correlated with mean and maximal carotid IMT. After adjusting for age and diabetes duration, the mean IMT is an independent predictor of yearly eGFR change. Conclusion: Carotid IMT may be a predictor of diabetic nephropathy progression in patients with type 2 diabetes.