• Structural Engineering and Mechanics
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• v.75 no.5
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• pp.633-642
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• 2020

Artificial neural networks (ANNs) are known as intelligent methods for modeling the behavior of physical phenomena because of it is a soft computing technique and takes data samples rather than entire data sets to arrive at solutions, which saves both time and money. ANN is successfully used in the civil engineering applications which are suitable examining the complicated relations between variables. Functionally graded materials (FGMs) are advanced composites that successfully used in various engineering design. The FGMs are nonhomogeneous materials and made of two different type of materials. In the present study, the bending analysis of functionally graded material (FGM) beams presents on theoretical based on combination of mixed-finite element method, Gâteaux differential and Timoshenko beam theory. The main idea in this study is to build a model using ANN with four parameters that are: Young's modulus ratio (E_t/E_b), a shear correction factor (k_s), power-law exponent (n) and length to thickness ratio (L/h). The output data is the maximum displacement (w). In the experiments: 252 different data are used. The proposed ANN model is evaluated by the correlation of the coefficient (R), MAE and MSE statistical methods. The ANN model is very good and the maximum displacement can be predicted in ANN without attempting any experiments.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.300-303
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• 2015

Digital imaging process has been put to practical use in various application sectors due to a rapid advancement such as memory devices, etc. However, noises are being generated due to various reasons during the image processing and a variety of methods are being studied in order to eliminate these noises. Generally, images are damaged due to a mixed noise having different characteristics. In this paper, a filter algorithm which switches according to the noise types was proposed in order to mitigate the influence of mixed noise included in the image. And using the PSNR as the standard for objective decision making of the improvement effect, it was compared with the existing methods.

• Journal of Korean Biological Nursing Science
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• v.23 no.1
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• pp.72-82
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• 2021

Purpose: This study used a mixed methods research design in an attempt to verify the effects of robot-assisted rehabilitation on the gait ability of stroke patients with hemiplegia, and thereby further understand the benefits and challenges of stroke patients' experiences relying on robot-assisted rehabilitation. Methods: An exploratory sequential mixed methods study design was used in order to combine both quantitative and qualitative data. For the quantitative data collection, a total of 30 stroke patients with hemiplegia were recruited from one rehabilitation hospital. Qualitative data were collected through individual interviews using semi-structured questionnaires for a group of 15 patients who were currently undergoing robot-assisted rehabilitation. The data were analyzed through qualitative content analysis. Results: As a result of the quantitative analysis, there were significant differences between the two groups in terms of daily living activity patterns, total number of steps, and average walking speed. As a result of the qualitative analysis, the four main themes derived consisted of, 'curiosity about the usage of robot-assisted rehabilitation,' 'pleasure experienced while using the robots,' 'insufficient information about robots,' and 'a lack of education about robot-assisted rehabilitation.' Conclusions: Robot-assisted rehabilitation had a significant effect on the walking ability of stroke patients with hemiplegia. Additionally, stroke patients with hemiplegia experienced difficulty during the course of their robot-assisted rehabilitation, due to a lack of sufficient information on correct usage techniques. These quantitative and qualitative findings could provide the basic foundation for the development of an educational program on robot-assisted rehabilitation.

• Journal of Korean society of Dental Hygiene
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• v.22 no.3
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• pp.161-170
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• 2022

Objectives: This study aims to conduct in-depth research on the effect of non-surgical periodontal therapy (NSPT) with the application of a comprehensive dental hygiene care (CDHC) process, and provide basic data for the wide application of CDHC. Methods: From May 8, 2021 to September 24, 2021, mixed-methods research was conducted in 36 patients with periodontal diseases. A paired samples t-test was used to analyze the quantitative research data using IBM SPSS program(ver. 22.0; IBM Corp., Armonk, NY, USA) and qualitative research data were analyzed using the thematic analysis method. Results: With NSPT applying the CDHC process, the perception of periodontal health and self-efficacy of periodontal healthcare were increased (p<0.001). Presence of gingivitis, probing pocket depth, bleeding on probing rate, presence of subgingival calculus, and dental plaque index were reduced (p<0.001). Based on 195 meaningful statements, 26 concepts, 12 sub-themes, and 5 themes , , , and were drawn. Conclusions: The perception of periodontal health and the self-efficacy were improved, and substantial change in the clinical index. The CDHC application allowed the study participants to perceive the importance of dental care and professionalism of dental hygienists.

• Journal of Hospice and Palliative Care
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• v.25 no.2
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• pp.85-97
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• 2022

Purpose: This study aimed to describe nurses' perceived needs and barriers to pediatric palliative care (PPC). Methods: Mixed methods with an embedded design were applied. An online survey was conducted for nurses who participated in the End-of-Life Nursing Education Consortium- Pediatric Palliative Care (ELNEC-PPC) train-the-trainer program, of whom 63 responded. Quantitative data were collected with a survey questionnaire developed through the Delphi method. The 47 items for needs and 15 items for barriers to PPC were analyzed with descriptive statistics. Qualitative data were collected through open-ended questions and analyzed with topic modeling techniques. Results: The mean scores of most subdomains of the PPC needs were 3.5 or higher out of 4, and those of PPC barriers ranged from 3.22 to 3.56, indicating the items in the questionnaire developed in this study properly reflect each factor. The needs for PPC were divided into 4 categories: "children and adolescents," "families," "PPC management system," and "community-based PPC." Meanwhile, PPC barriers were divided into 3 categories: "healthcare delivery system," "healthcare provider," and "client." The keywords derived from the topic modeling were perception, palliative, children, and education for necessities and lack, perception, medical care, professional care providers, service, and system for barriers to PPC. Conclusion: In this study, by using mixed-methods, items of nurses' perceived needs and barriers to PPC were identified, categorized, and weighted, and their meanings were explored. For the stable establishment of PPC, the priority should be given to improving perceptions of PPC, establishing an appropriate system, and training professional care providers.

• Journal of applied mathematics & informatics
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• v.7 no.2
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• pp.483-491
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• 2000

In this paper, we use the auxiliary principle technique to suggest and analyze a class of predictor-corrector methods for solving noncoercive mixed variational inequalities. The convergence of the proposed method requires only the partially relaxed strongly monotonicity. which is even weaker than the co-coercivity. As special cases, we obtain a number of new and known results for classical variational inequalities.

• Communications for Statistical Applications and Methods
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• v.12 no.1
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• pp.47-59
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• 2005

Expected mean square(EMS) is an important part of conducting the analysis of variance in the experimental design problem, especially in mixed or random models. We present a set of EMS rules for balanced factorial designs under no restriction on interaction. Also we point out how to use the variance component of SPSS or SAS procedure to obtain EMS.

• Communications for Statistical Applications and Methods
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• v.4 no.1
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• pp.33-39
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• 1997

Tsutakawa(1988) proposed a mixed model for using empirical Bayes method to study the geographic variability in mortality rates of a disease. In particular cases of the analysis in mortality rate, we need to consider the effect of time. If observed data are collected annually for the time period, then time effect will be emphasized. Here, an extended model for estimating the geographic effect and the mortality rates of the disease with time effect is proposed.

• Communications for Statistical Applications and Methods
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• v.19 no.6
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• pp.761-770
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• 2012

We frequently encounter outcomes of count that have extra variation. This paper considers several alternative models for overdispersed count responses such as a quasi-Poisson model, zero-inflated Poisson model and a negative binomial model with a special focus on a generalized linear mixed model. We also explain various goodness-of-fit criteria by discussing their appropriateness of applicability and cautions on misuses according to the patterns of response categories. The overdispersion models for counts data have been explained through two examples with different response patterns.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2002.05a
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• pp.1-8
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• 2002

A Branch-and-Cut algorithm is a branch-and-bound algorithm in which rutting planes are generated throughout the branch-and-bound tree. It is now one of the most widespread and successful methods for solving mixed integer programming problems. In this paper we presents efficient implementation techniques of branch-and-cut algorithm for miked integer programming problems.