• Korean Journal of Occupational Health Nursing
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• v.26 no.3
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• pp.151-159
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• 2017

Purpose: The purpose of this study was to identify the effects of service orientation on the organizational commitment and management performance of public health center workers. Methods: A cross-sectional survey design was used. A convenience sample of 280 workers was recruited from six public health centers in J province, South Korea. Data were collected by self-report questionnaires, including general characteristics, service orientation, organizational commitment, and management performance. Data were analyzed with descriptive statistics, Pearson correlation coefficients, independent t-test, one-way ANOVA, and hierarchical regression using the SPSS 22.0 program. Results: The service orientations explained 34.1%of the variance in organizational commitment and explained 31.4% of the variance in management performance. The service orientation was a significant predictor of organizational commitment and management performance. Conclusion: The results of this study suggest that better strategies for service orientations will be helpful to enhance organizational commitment and management performance in the public health center.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.2
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• pp.583-593
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• 2021

The purpose of this study was to examine the relationship between transformational leadership and organizational performance with readiness to change and empower knowledge sharing quality as mediating variables. The survey was conducted by collecting the respondents' data by filling up forms which were designed using the google form application and collecting it using WhatsApp. This was performed on 400 respondents, encompassing employees from the National Agency of Drug and Food Control in Indonesia. The research model adopted was validated using Structural Equation Modeling technique with AMOS tool. The findings showed transformational leadership as a significant predictor of readiness to change and it proved relevant in empowering knowledge sharing quality, which in turn affects organizational performance. Furthermore, the effects of both two mediating variables was also examined, and only readiness to change significantly influenced the relationship between predictors of transformational leadership and organizational performance. The findings of this study showed the need for transformational leaders as the research focused on understanding the differences in employee character. This is required to encourage better performance by empowering quality knowledge dissemination mechanisms, with continuous in-house training activities. Therefore, the model adopted in this research and the hypotheses prove the direct effect of transformational leadership on organizational performance, achievable through the mediating role of readiness to change.

• Geomechanics and Engineering
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• v.12 no.3
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• pp.441-464
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• 2017

The determination of the mixture parameters of stabilization has become a great concern in geotechnical applications. This paper presents an effort about the application of artificial intelligence (AI) techniques including radial basis neural network (RBNN), multi-layer perceptrons (MLP), generalized regression neural network (GRNN) and adaptive neuro-fuzzy inference system (ANFIS) in order to predict the unconfined compressive strength (UCS) of silty soil stabilized with bottom ash (BA), jute fiber (JF) and steel fiber (SF) under different freeze-thaw cycles (FTC). The dosages of the stabilizers and number of freeze-thaw cycles were employed as input (predictor) variables and the UCS values as output variable. For understanding the dominant parameter of the predictor variables on the UCS of stabilized soil, a sensitivity analysis has also been performed. The performance measures of root mean square error (RMSE), mean absolute error (MAE) and determination coefficient ($R^2$) were used for the evaluations of the prediction accuracy and applicability of the employed models. The results indicate that the predictions due to all AI techniques employed are significantly correlated with the measured UCS ($p{\leq}0.05$). They also perform better predictions than nonlinear regression (NLR) in terms of the performance measures. It is found from the model performances that RBNN approach within AI techniques yields the highest satisfactory results (RMSE = 55.4 kPa, MAE = 45.1 kPa, and $R^2=0.988$). The sensitivity analysis demonstrates that the JF inclusion within the input predictors is the most effective parameter on the UCS responses, followed by FTC.

• Journal of Fisheries and Marine Sciences Education
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• v.25 no.2
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• pp.349-363
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• 2013

Using data from 286 employees who were working in medium and small company in Busan, the study analyzed the influence of educational training program traits perceived by employee on organizational effectiveness and job performance. The main results were as the followings. First, for organizational effectiveness, job relation and objective setting among educational training program traits had statistically significant influence on job satisfaction and involvement in organization after controlling the employee's characteristics. Second, for job performance, after controling the employee's characteristics, job relation, educational method, educational training environment, and objective setting had statistically significant influence on active participation, the improvement of task performance ability and confidence, or professional knowledge improvement. Additionally, among the employee's characteristics, the number of educational training participation was statistically significant predictor for job performance. Based on the main results, some suggestions and the limitations of the study were discussed.

• Journal of the Korean Society of Safety
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• v.29 no.2
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• pp.68-75
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• 2014

The study examined the relationship between six broad personality traits(i.e., HEXACO; Honesty-humility, Emotionality, eXtraversion, Agreeableness, Conscientiousness, Openness to experience), safety job performance, and traffic accidents of Korean occupational bus drivers. Based on the job performance model, we included safety participation as well as safety compliance as safety job performance. Analyses on the data from a total of 492 bus drivers showed that all HEXACO personality traits except Honesty-humility, were valid predictors for both safety compliance and safety participation. Honesty-humility was only related to safety compliance. Among the six personality traits, high conscientiousness and low emotionality were best predictors of safety job performance. As for traffic accidents, conscientiousness was a sole significant predictor. Furthermore, the mediation analysis showed that the effect of conscientiousness on traffic accidents was completely explained by safety compliance and safety participation. The implications of the current findings for practice and future research as well as the limitations of the current study were discussed.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.15 no.2
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• pp.144-152
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• 2005

To evaluate the effect of lead biomarkers including bone lead on neurobehavioral test in lead workers, 652 lead workers without any occupational exposure to organic solvent, mercury and arsenic were agreed to participate this study. For the control subjects 102 non-occupationally lead exposed blue collar workers in general manufacturing industries were also joined this study. All study subjects joined this study with written informed consent. The study variables of lead exposure were blood and patella lead. For the general characteristics of study subjects, standardized questionnaire regarding age, sex, past disease history, job duration, body mass index (BMI), drinking and smoking habit were provided. For the past history of neurotoxicity related diseases, all study subjects were interviewed by qualified occupational health physician. The results obtained were as follows: 1. Compared with controls without occupational lead exposure, lead exposed subjects had worse performance on all tests(p<0.05). 2. After adjustment for covariates (age, sex, job duration, education level, BMI, smoking and drinking status), the signs of the regression coefficients for blood lead were negative for 13 of the 14 tests. Blood lead was a significant predictor of poorer scores on 8 tests (simple reaction time(ms & root MSD), Trail-Making Test B, Digit Symbol Substitution, Purdue Pegboard assembly, Digit Span Test, Benton Visual Retention, and Purdue pegboard both hand). 3. After adjustment for covariates (age, sex, job duration, education level, BMI, smoking and drinking status), the signs of the regression coefficients for patella lead were negative for 12 of the 14 tests. Patella lead was a significant predictor of poorer scores on 8 tests (simple reaction time(ms). Purdue Pegboard assembly, Digit Span Test, Benton Visual Retention. Pursuit Aiming rest (no. of correct & no. of incorrect), Purdue pegboard non-dominant hand and both hand). With above results, blood lead and patella lead were associated with poorer performance of neurobehavioral tests. In addition, patella lead was confirmed to be better predictor of manual dexterity test in neurobehavioral test battery in lead workers

• Journal of KIISE:Computer Systems and Theory
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• v.32 no.6
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• pp.306-313
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• 2005

Conditional branch prediction is an important technique for improving processor performance. Branch mispredictions, however, waste a large number of cycles, inhibit out-of-order execution, and waste electric power on mis-speculated instructions. Hence, the branch predictor with higher accuracy is necessary for good processor performance. In global-history-based predictors like gshare and GAg, many mispredictions come from commit update of the history. Some works on this subject have discussed the need for speculative update of the history and recovery mechanisms for branch mispredictions. In this paper, we present a simple mechanism for recovering the branch history after a misprediction. The proposed mechanism adds an age_counter to the original predictor and doubles the size of the branch history register. The age_counter counts the number of outstanding branches and uses it to recover the branch history register. Simulation results on the Simplescalar 3.0/PISA tool set and the SPECINTgS benchmarks show that gshare and GAg with the proposed recovery mechanism improved the average prediction accuracy by 2.14$\%$ and 9.21$\%$, respectively and the average IPC by 8.75$\%$ and 18.08$\%$, respectively over the original predictor.

• The Journal of Korean Academic Society of Nursing Education
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• v.21 no.2
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• pp.168-181
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• 2015

Purpose: This study was conducted to determine the factors affecting the prevention of needle stick injury. Methods: Data collection was conducted during the period July 15-31, 2013 by a self-administered questionnaire involving 220 nurses working in 7 hospitals. The data was analyzed by SPSS v18 and AMOS v18. Results: Actions by nurses to prevent needle stick injury were directly and indirectly influenced by perceived benefits, attitude toward the behavior, perceived behavioral control, and intention underlying the behavior. Specially, perceived behavioral control is verified to have not only direct influence but also indirect influence on the performance of preventive action through the intention underlying the behavior. Also, perceived benefits indirectly influence the intention toward the behavior and performance of preventive action through attitude toward the behavior and perceived behavioral control. The predictor variables in this model are 52% explicable in terms of intention of prevention action against needle stick injury, and 66% explicable in terms of performance of preventive action. Conclusion: To ensure high performance of preventive action against needle stick injury, constructing not only the solution that inspires the intention toward behavior but also a system that can positively solve and improve obstructive factors in behavioral performance is of primary importance.

• Asian Oncology Nursing
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• v.12 no.2
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• pp.156-165
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• 2012

Purpose: This study was to identify predictors of sexual function in gynecologic cancer patients. Methods: The participants were 154 patients treated at a university medical center in A city, Korea. The data collection was performed through a structured questionnaire from July to December, 2010. The instruments used in this study were Female Sexual Function Index (FSFI) perceived health status scale, Eastern Cooperative Oncology Group (ECOG) performance status, body image, and depression. Data were analyzed using descriptive statistics, Mann-Whitney test, Kruskal-Wallis test and stepwise multiple regression with the SPSS 18.0. Results: The mean score of perceived health status was 8.42 and sexual function was 8.42. The lowest score among sexual function was lubrication. The scores of sexual function was significantly different by age, job, marital status, period after diagnosis of cancer and diagnosis. There were significant correlations between sexual function, perceived health status, ECOG performance, body image and depression. In multiple regression analysis, predictors were identified as ECOG performance, age, diagnosis and period after diagnosis of cancer (Adj.$R^2$=.28). The most powerful predictor of female sexual function was ECOG performance (19.0%). Conclusion: The above findings indicate that it is necessary to develop a more effective and personalized sexual function improvement program for gynecologic cancer patient.

• Korean Journal of Applied Biomechanics
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• v.30 no.1
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• pp.83-91
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• 2020

Objective: The study aimed to develop a functional performance index that evaluates the functional performance of Parkinson's patients, i.e., to integrate biomechanical measurements of walking, balance, muscle strength and tremor, and to use multiple linear regression with stepwise methods to identify the most suitable predictors for the progression of disease. Method: A total of 60 subjects were tested for sub-variables of four factors: walking, balance, isometric strength and hand tremors. Potential independet variables were extracted through correlation analysis of the sub-variables and dependent variables, Hoehn & Yahr scale. And then, a stepwise multiple regression analysis using the potential independent variables was performed to identify predictor of Hoehn & Yahr scale. Results: First, the results of the study showed that physical composition and gait had a relatively more correlated with the progression of the disease, compared to balance and hand tremor. Second, Parkinson's functional performance is characterized by dynamic pattern of walking, such as foot clearance and turning angle (TA) of walking, and a high-explained regression model is completed. Conclusion: The study emphasized the importance of walking variables and body composition in minor pathological features compared to Parkinson's patient's balancing ability and hand tremor. Specifically, it revealed that dynamic walking patterns functionally characterize patients. The results are worth considering when assessing functional performance related to the progression of the disease at the site.