• Journal of Korean Society of Industrial and Systems Engineering
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• v.27 no.4
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• pp.170-178
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• 2004

As quality becomes a primary leading factor of organizational success, various management strategies have been introduced to improve quality competitiveness. Quality competitiveness, however, is difficult to measure and numerous organizations are struggling to set realistic improvement objectives. The primary purpose of this research is to propose a systematic approach to help the practitioners develop an improvement plan for their organizational quality competitiveness. This approach employs DEA(Data Envelopment Analysis) to evaluate relative efficiency among companies which make efforts to improve their quality competitiveness. It presents an integer programming model to elicit an optimal improvement plan for meeting a target level. A decision support system is also developed for the managers to plan a sequential improvement plan based on both DEA model and the integer programming model.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.47 no.5
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• pp.403-406
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• 2021

The dilemma regarding the management of condylar fractures generally revolves around the surgical approach, implant design, and the surgeon's experience. Zide and Kent's guidelines streamlined the decision making process for condylar fractures. However, there exists no standardized protocol for reduction and fixation of condylar fractures. Here, we have described a detailed and stepwise protocol, common to any surgical approach, that would lead to predictable, reproducible, and repeatable results in every surgeon's hands.

• Korean Journal of Applied Biomechanics
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• v.26 no.4
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• pp.353-360
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• 2016

Objective: The aim of this study was to investigate the relationship between aiming patterns and scores in archery shooting. Method: Four (N = 4) elementary-level archers from middle school participated in this study. Aiming pattern was defined by averaged acceleration data measured from accelerometers attached on the body during the aiming phase in archery shooting. Stepwise multiple regression analysis was used to test whether a model incorporating aiming patterns from all nine accelerometers could predict the scores. In order to extract period of interest (POI) data from raw data, a Dynamic Time Warping (DTW)-based extraction method was presented. Results: Regression models for all four subjects are conducted with different significance levels and variables. The significance levels of the regression models are 0.12%, 1.61%, 0.55%, and 0.4% respectively; the $R^2$ of the regression models is 64.04%, 27.93%, 72.02%, and 45.62% respectively; and the maximum significance levels of parameters in the regression models are 1.26%, 4.58%, 5.1%, and 4.98% respectively. Conclusion: Our results indicated that the relationship between aiming patterns and scores was described by a regression model. Analysis of the significance levels, variables, and parameters of the regression model showed that our approach - regression analysis with DTW - is an effective way to raise scores in archery shooting.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.3
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• pp.553-561
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• 2019

This study examined the relationship between professional self-concept, interpersonal relationship, coping, and clinical practice satisfaction of nursing college students. This was a descriptive study. The survey participants were 355 students in M city and I city. The data were collected from May 29 to June 16, 2017 and self-report questionnaires, including the Professional Self-concept Scale, Interpersonal Relationship Scale, Coping Scale, and Clinical Practice Satisfaction Scale. The data were analyzed by descriptive statistics, independent-samples t-test, ANOVA, and stepwise multiple regression. Professional self-concept showed significant differences according to religion, income, and school records. Interpersonal relationships showed significant differences according to gender, income, and school records. Coping showed significant differences according to the school records. Professional self-concept had a statistically positive correlation with interpersonal relationship, clinical practice satisfaction, and approach coping. Stepwise multiple regression analysis showed that the predictor of professional self-concept was interpersonal relationships, approach coping, religion, school records, and avoidant coping, which accounted for 45.2% of the variance. These results highlight the need for enhancement programs of nursing college students' professional self-concept that consider their interpersonal relationships, coping, religion, and school records.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 1999.10a
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• pp.365-373
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• 1999

Recently, numerous studies have demonstrated that artificial intelligence such as neural networks can be an alternative methodology for classification problems to which traditional statistical methods have long been applied. In building neural network model, the selection of independent and dependent variables should be approached with great care and should be treated as a model construction process. Irrespective of the efficiency of a learning procedure in terms of convergence, generalization and stability, the ultimate performance of the estimator will depend on the relevance of the selected input variables and the quality of the data used. Approaches developed in statistical methods such as correlation analysis and stepwise selection method are often very useful. These methods, however, may not be the optimal ones for the development of neural network models. In this paper, we propose a genetic algorithms approach to find an optimal or near optimal input variables for neural network modeling. The proposed approach is demonstrated by applications to bankruptcy prediction modeling. Our experimental results show that this approach increases overall classification accuracy rate significantly.

• Journal of Korean Academy of Nursing
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• v.14 no.2
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• pp.84-92
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• 1984

This article examined relationships between selected variables, such as demographic background, care, treatment variables, environmental characteristics, and patient's daily behavior and mood change. Relationship were determined between independent variabltherapeutic-rapeutie approach, demographic data, environmental management approach-,and dependent variable-patient's daily behavioral and mood change. 35 patients selected within some criteria in a psychiatric ward, were obserbed during 5 weeks by use of Wyatt's Behavior & Mood Rating Scale ac-cording to the object of the study. At the same time, the frequence of the care and treatment were collected. Criteria for sample selection and independent variables as an influential factor to the patient behavioral change, based on a literature revienw and clinical experiences. Pearson's correlation and multiple regression analysis were used to determine the influfntial factors to the patient behavioral change. Systematic reading (r=.8324), Psychiatrist's individual interview (r=.5764), tranquilizer (r=.3441) and hospitalization processing date (r=.4143) were related with patient's behavioral change. That is these 4 variables can be said to influence to the patient's behavior and mood. A stepwise multiple regression analysis of the effect of the independent varibles of systematic reading, psychintrists individual interview, tranquilizer and hospitalization processing date on the dependent variable, patient's behavioral change was carried out. Systematic reading with on R²of. 69 revealed to be the main influential factor to the patient's behavior and mood change, as the next factor psychiatrist individual interview. A total inclusion of these factors revealed a 73% prediction for the patient's behavior and mood change. But the most influential factor was the interaction of the systematic reading and psychiatrist's individual interview.

• The Journal of Korean Association of Computer Education
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• v.5 no.4
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• pp.53-60
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• 2002

Typical Apriori-like methods for mining sequential patterns have some problems such as generating of many candidate patterns and repetitive searching of a large database. And PrefixSpan constructs the prefix projected databases which are stepwise partitioned in the mining process. It can reduce the searching space to estimate the support of candidate patterns, but the construction cost of projected databases is still high. For efficient sequential pattern mining, we need to reduce the cost to generate candidate patterns and searching space for the generated ones. To solve these problems, we proposed SuffixSpan(Suffix checked Sequential Pattern mining), a new method for sequential pattern mining, and show a formal approach to our method.

• Journal of Families and Better Life
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• v.21 no.2
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• pp.87-101
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• 2003

The purposes of this study were to analyze causes of wife abuse through married couples as the research subject. The study employed ecological perspective to the study of wife abuse as an multiple dimensional and integrated paradigm combined with isolated theories of other research. The subjects were 369 married couples who live in Gwangju area. Data were analyzed with Cronbach'α, factor analysis, basic statistics, paired-t test, 1-test, ANOVA, Duncan's test, correlation analysis, stepwise multiple regression analysis. and hierarchical regression analysis using the SPSS 10.0 for windows. The major findings were as follows; 1. The psychological abuse score, physical abuse score, and sexual abuse score were lower than median without exception. Hut prevalence rates of wife abuse were considerably serious; 91.9% psychological abuse, 44.4% physical abuse, and 53.7% sexual abuse. 2. The results of the hierarchical regression analysis indicated that the marital conflict had the strongest impact on wife abuse. And the attitude toward wife abuse of husband, hostility of husband, exposure experience of domestic violence during a growth period of husband, perception toward social violence of husband, exposure experience of domestic violence during a growth period of wife, drinking problem of husband, and interpersonal relationships stress of husband had influenced on wife abuse. These variables accounted for 49.5% of variance of wife abuse behaviors. As the result of the study, it concludes that the ecological systemic approach on the cause of wife abuse is useful as a theoretical instrument. Suggestions and implications are made for further research and practical application.

• IEMEK Journal of Embedded Systems and Applications
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• v.18 no.6
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• pp.277-283
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• 2023

Vital signals provide essential information regarding the health status of individuals, thereby contributing to health management and medical research. Present monitoring methods, such as ECGs (Electrocardiograms) and smartwatches, demand proximity and fixed postures, which limit their applicability. To address this, Non-contact vital signal measurement methods, such as CW (Continuous-Wave) radar, have emerged as a solution. However, unwanted signal components and a stepwise processing approach lead to errors and limitations in heart rate detection. To overcome these issues, this study introduces an integrated neural network approach that combines noise removal, demodulation, and dominant-frequency detection into a unified process. The neural network employed for signal processing in this research adopts a MLP (Multi-Layer Perceptron) architecture, which analyzes the in-phase and quadrature signals collected within a specified time window, using two distinct input layers. The training of the neural network utilizes CW radar signals and reference heart rates obtained from the ECG. In the experimental evaluation, networks trained on different datasets were compared, and their performance was assessed based on loss and frequency accuracy. The proposed methodology exhibits substantial potential for achieving precise vital signals through non-contact measurements, effectively mitigating the limitations of existing methodologies.

• Asia-Pacific Journal of Business
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• v.14 no.4
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• pp.1-21
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• 2023

Purpose - The study investigates the role of authenticity of B2B salespersons has on their consultative selling competence. The study also examines the mediating effect of customer orientation between the authenticity of B2B salespersons and their consultative selling competence, as well as the moderating role of trust in the buyer-seller exchange. Design/methodology/approach - This research utilized a covariance-based structural equation model technique. The study assessed the research model's moderation effects through a stepwise approach, which allowed for an examination of the moderating effect of trust in the buyer-seller relationship. Findings - As a result of structural equation analysis, this study found that the authenticity of B2B salespersons influences their consultative selling competence by mediating their customer orientation significantly. In addition, trust in the buyer-seller exchange plays a significant role as a moderating variable between customer orientation and competitive selling competence, but it is not significant as a moderating variable between the authenticity and customer orientation of B2B salespersons. Research implications or Originality - This research proposed the role of authenticity of the B2B salesperson as a key factor in the trust-based relationship and a key variable of consultative selling competence. The study has taken the research on the authenticity of the B2B salesperson one step further from the study of authenticity of the brand and the company's leadership.