• International Journal of Contents
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• v.14 no.3
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• pp.32-38
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• 2018

This study examined the factors influencing the intention to use smartwatches using the integrated model of technology acceptance model (TAM) and innovation diffusion theory (IDT). An online survey was conducted and the data were analyzed using the structural equation modeling (SEM). The results showed that the research model had an acceptable fit, and all paths, except for the one from the perceived ease of use to the intention to use, were supported. Regarding paths from IDT to TAM, it was observed that higher the compatibility, the users perceived greater usefulness. Additionally, both observability and trialability influenced the perceived ease of use. However, perceived ease of use affected the intention only through the mediated effect of perceived usefulness. The implication of the study lies on the major focus on the effects of users' perceptions regarding innovative characteristics of smartwatches on the intention to adopt and attempted to increase the explanatory power of the TAM and IDT by combining both.

• Proceedings of the Korean Reliability Society Conference
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• 2006.05a
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• pp.181-191
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• 2006

As an alternative to traditional life testing, degradation tests can be effective in assessing product reliability when measurements of degradation leading to failure can be observed. This article proposes a new model to describe the nonlinear degradation paths caused by nano-contamination for plasma display panels (PDPs) : a bi-exponential model with random coefficients. A sequential likelihood ratio test was executed to select random effects in the nonlinear model. Analysis results indicate that the reliability estimation can be improved substantially by using the nonlinear random-coefficients model to incorporate both inherent degradation characteristics and contamination effects of impurities for PDP degradation paths.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.1A
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• pp.99-106
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• 2004

In this Paper, the matched filter for searching initial synchronization in DSSS (direct sequence spread spectrum) receiver is studied. The matched filter with a single data flow path is described which can be presented by HDL (Hardware Description Language). In order to improve the processing time of operations for the filter, equations are arranged to represent two data flow paths and the associated hardware model is proposed. The model has an architecture based on parallelism and pipeline for fast processing, in which two data flow paths with a series of memory, multiplier and accumulator are placed in parallel. The performance of the model is analyzed and compared with the matched filter with a single data flow path.

• Korean Journal of Construction Engineering and Management
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• v.24 no.5
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• pp.73-82
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• 2023

Optimization of Construction Site Layout Planning (CSLP) heavily relies on workers' travel paths. However, traditional path generation approaches predominantly focus on the shortest path, often neglecting critical variables such as individual wayfinding tendencies, the spatial arrangement of site objects, and potential hazards. These oversights can lead to compromised path simulations, resulting in less reliable site layout plans. While Deep Reinforcement Learning (DRL) has been proposed as a potential alternative to address these issues, it has shown limitations. Despite presenting more realistic travel paths by considering these variables, DRL often struggles with efficiency in complex environments, leading to extended learning times and potential failures. To overcome these challenges, this study introduces a refined model that enhances spatial navigation capabilities and learning performance by integrating workers' visibility into the reward functions. The proposed model demonstrated a 12.47% increase in the pathfinding success rate and notable improvements in the other two performance measures compared to the existing DRL framework. The adoption of this model could greatly enhance the reliability of the results, ultimately improving site operational efficiency and safety management such as by reducing site congestion and accidents. Future research could expand this study by simulating travel paths in dynamic, multi-agent environments that represent different stages of construction.

• Journal of muscle and joint health
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• v.5 no.1
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• pp.7-25
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• 1998

Rheumatoid arthritis, unlike other chronic diseases, causes the patients to experience uncertainty in their daily lives and thus to feel threat on their emotional comfort because of inconsistent and unpredictable symptoms such as pain. Therefore, a theoretical framework is needed for explanation of uncertainty in patients having rheumatoid arthritis. A hypothetical model was constructed on the basis of Mishel's Uncertainty Theory and other literature review. The model included 9 theoretical concepts and 19 paths. Subjects of the study constituted 330 partients who visited outpatient clinics of two university hospitals and one general hospital in Seoul. Self report questionnaires were used to measure the variables affecting uncertainty. Reliability coefficients of these instruments were found Cronbach's Alpha=$.70{\sim}.94$. In data analysis, SAS program and PC-LISREL 8.03 computer program were utilized for descriptive statistics and covariance structure analysis. The results of covariance structure analysis for model fitness were as follows : 1) Hypothetical model showed a good fit to the empirical data : Chi-square($X^2$)=41.81 (df=11, P=.000), Goodness of Fit Index=.974, Root Mean Square Residual=.049, Normed Fit Index=.928, Non Normed Fit Index=.814. 2) For the validity and the parcimony of model, a modified model was constructed by appending 2 paths and deleting 5 paths according to the criteria of statistical significance and meaningfulness. 3) The results of hypothesis testing were as follows : (1) Educational level, event familiarity and severity of illness had a direct effect on uncertainty : Event congruency had both direct and indirect effect on uncertainty : Credible authority and symptom consistency had a nonsignificant direct effect on uncertainty, (2) Illness duration, symptom consistency, and event congruency had a direct effect on severity of illness ; Credible authority had a both direct and indirect effect on severity of illness ; Event congruency had the greatest effect on severity of illness, and event familiarity had a nonsignificant direct effect on severity of illness.

• Journal of the Korean Geotechnical Society
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• v.32 no.7
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• pp.15-24
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• 2016

To investigate the unsaturated characteristics of the Boeun granite weathered soil, matric suction and volumetric water content were measured in both drying and wetting paths using Automated Soil-Water Characteristics Curve Apparatus. Based on the measured results, Soil-Water Characteristics Curve was estimated by van Genuchten (1980) model. The relationship between effective degree of saturation and matric suction showed the non-linear curve with S-shape and the hysteresis phenomenon occurred during drying and wetting paths. Suction Stress Characteristics Curve was estimated by the Lu and Likos (2006) model. The suction stress in drying path was constantly maintained and that in wetting path tended to increase when the effective degree of saturation was low. But the suction stress in drying path was larger than that in wetting path at the same degree of saturation when the effective degree of saturation became larger. Meanwhile, Hydraulic Conductivity Function was evaluated by the van Genuchten (1980) model which is one of the parameter estimation methods. The unsaturated hydraulic conductivity decreased with increasing the matric suction, and the decreasing velocity regarding to the matric suction in drying path was larger than that in wetting path.

• The Journal of Korean Academic Society of Nursing Education
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• v.8 no.1
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• pp.61-71
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• 2002

purpose : The purpose of this study was to find out the influencing factors of smoking-cessation behavior of patients with coronary heart disease and to suggest the model of smoking-cessation behavior which was based on the relationship between influencing factors and then to test its fitness empirically. method : This study was based on the Theory of Reasoned Action and a hypothetical model was constructed with fifteen paths in consideration of main predictive factors of smoking-cessation behavior such as biological factor, disease-related characteristics, self-efficacy, supportive factor, environmental factor, disease-related perception factor, intention-to-quit, and psychological factor. The validity of a smoking- cessation model was tested to 264 patients with coronary heart disease by using SPSS 8.0 and Window LISREL 8.12a. results : 1. Seven of the 15 paths of smoking-cessation behavior proved to be significant. 2. The final model excluded three paths in the hypothetical model was demonstrated to be improved by $x^2$=44.31 (df=38, p=.22), Goodness of Fit Index (GFI)=.98, Adjusted Goodness of Fit Index (AGFI)=.96, Non-Normed Fit Index(NNFI)=1.00, Normed Fit Index(NFI)=1.00, and Root Mean Square Residual(RMR)=.24. 3.The smoking-cessation behavior was influenced directly by biological factor, self-efficacy, supportive factor, environmental factor, intention-to-quit, and psychological factor. The smoking-cessation behavior was accounted for 82% of variance by these factors. conclusion : although the adolescents' smoking behavior can be predicted by only smoking intention, it is hard to predict the adults' smoking-cessation behavior by only this factor. Therefore, intention-to-quit, self-efficacy, supportive factor should be improved because these are promotive factors for smoking-cessation behavior. Biological factor, environmental factor, and psychological factor are inhibitive factors, so nicotine replacement therapy is helpful to the high nicotine-dependents, and ex-smokers avoid other smokers in their environment and also patients should learn and practice the stress coping-skills.

• Journal of Korean Academy of Nursing
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• v.35 no.2
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• pp.239-251
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• 2005

Purpose: This study was designed to construct a structural model for explaining mental health status in middle - aged women. Methods: The data was collected by self - reported questionnaires from 206 middle - aged women in Seoul. Data analysis was done with the SAS pc program for descriptive statistics and a PC - LISREL Program for finding the best fit model which assumes causal relationships among variables. Results: The overall fit of the hypothetical model to the data was good, but paths and variables of the model were modified by considering theoretical implications and statistical significances of parameter estimates. Thus it was modified by excluding 3 paths, The modified model showed was good fit to the data($x^2=177.55$, p=.00), GFI=0.908, AGFI=0.860, RMR=0.013, NFI=0.972, NNFI=0.982). Perceived stress, anger expression method, and self -esteem were found to have direct effects on mental health status in middle - aged women. These predictive variables of mental health status explained $66.6\%$ of the model. Conclusion: Programs to enhance mental health status in middle - aged women should include stress management skill, anger expression skill, and self -esteem enhancement skills to be effective.

• Korean Journal of Child Studies
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• v.26 no.1
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• pp.261-278
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• 2005

The purpose of this study was to demonstrate the paths among the risk-protective factors that related to the resilience based on the Challenge Model. The subjects for this study were 209 children from divorced families in the 4th, 5th, and 6th grades of elementary schools in Seoul and Gyunggi-do. As the results, there were 28 paths which affected the resilience of children from divorced families based on the Challenge Model. The protective factors were easy temperament, problem-focused coping style, parental support, peer's support, higher socio-economic status, experiences in therapy, presence of siblings, contact with adult caretakers. The risk factors were higher grade, emotion-focused coping style, and children's gender, especially girls. This result demonstrated that each risk and protective factor not only affected resilience separately but interacted with one another.

• Journal of the Korea Society of Computer and Information
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• v.21 no.1
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• pp.115-123
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• 2016

In this study, we collect various side effect pairs which are appeared frequently at many drugs, and select side effect pairs that have higher severity. For every selected side effect pair, we extract common genetic networks which are shared by side effects' genes and drugs' target genes based on PPI(Protein-Protein Interaction) network. For this work, firstly, we gather drug related data, side effect data and PPI data. Secondly, for extracting common genetic network, we find shortest paths between drug target genes and side effect genes based on PPI network, and integrate these shortest paths. Thirdly, we develop a classification model which uses this common genetic network as a classifier. We calculate similarity score between the common genetic network and genetic network of a drug for classifying the drug. Lastly, we validate our classification model by means of AUC(Area Under the Curve) value.