• Journal of Digital Convergence
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• v.20 no.2
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• pp.277-287
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• 2022

ZEB is a building that increases the energy independence of the building itself, and new and renewable elements that can produce energy are essential, and BIPV is the most notable technology. In ZEB's design, BIPV should be planned early in the design, but BIPV plans are insufficient in the early stages. Therefore, this study derived elements for theoretical consideration of BIM and ZEB and analysis of ZEB independence rate based on BIM, a convergence design technology, and analyzed BIPV energy production and building energy consumption. Finally, by calculating the energy independence rate and reviewing the rating criteria in the project model, a basic research method for calculating the energy independence rate of ZEB at the beginning of the design was presented. Through this, it is expected that design productivity can be improved by supporting the decision of ZEB subjects.

• Journal of Digital Convergence
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• v.13 no.12
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• pp.235-244
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• 2015

This study was done to identify convergence factors influencing the HPV vaccination in female university students. The subjects of this study were 546 female university students. The data were collected through interviews using a structured questionnaire from 5 to 30th of October, 2013. 138(25.3%) reported that they were vaccinated. Religion, ever heard cervical cancer, HPV and cervical cancer vaccination, ever had a pap test, knowledge about HPV vaccination, health beliefs(total), perceived benefit, perceived barrier, cancer preventive behavior(total) and cervical cancer preventive behavior were associated with being vaccinated. In logistic regression analysis showed that the predictors are ever had a pap test(OR=34.67, 95% CI=17.19~ 69.92), perceived benefit(OR=1.45, 95% CI=1.17~1.81) and perceived barrier(OR=1.44, 95% CI=1.27~1.63). It was recommended to make convergence policy supports and education programs reinforcing a pap test and perceived benefit and reducing perceived barriers about HPV vaccination.

• Journal of Digital Convergence
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• v.13 no.4
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• pp.295-302
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• 2015

The purpose of this study was to evaluate the effects of convergence-based reeducation of core basic nursing skills (subcutaneous injection, indwelling catheterization) on competence, knowledge, attitude and confidence for nursing students. Subjects were 34 nursing students and 3rd grade. Experimental treatment and data collection was conducted from December 14 to 29, 2013. Skills for subcutaneous injection including simple blood glucose test and indwelling catheterization were evaluated before and after intervention. Knowledge, attitude and confidence were measured using structured questionnaires. Data were analyzed by the frequency, descriptive statistics and paired t-test using SPSS version 21. As a result, after reeducation, significant improvement was found in competence (p<.001), knowledge (p<.001) and confidence (p<.001) in subcutaneous injection and indwelling catheterization. Convergence-Based reeducation program was found effective to enhance the competence of core basic nursing skills before graduating nursing students. Therefore, it is necessary to continue to develop program and to evaluate the effects with further research.

• Journal of Korean society of Dental Hygiene
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• v.24 no.3
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• pp.197-208
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• 2024

Objectives: Extended reality technology offers an innovative opportunity to enhance self-directed learning through interactive processes in healthcare education. This study aims to analyze research trends in the application of extended reality technology-based educational content in the field of healthcare. Methods: Through literature search, selection, and exclusion processes based on predefined criteria, we conducted an analysis of domestic healthcare studies employing extended reality technology, ultimately selecting and examining 39 relevant publications. Results: The analysis reveals diverse applications of extended reality across various fields such as medicine, dentistry, and nursing. Positive effects, including increased academic satisfaction, immersion, and interest, are observed, alongside challenges like media usage difficulties and cybersickness. Conclusions: Future research should focus on the development and application of extended reality-based educational content in diverse healthcare curricula, emphasizing both educational approaches and continuous technological advancements.

• Journal of the Korea Convergence Society
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• v.9 no.5
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• pp.33-41
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• 2018

The purpose of this study is to develop more accurate and robust emotion prediction neural network (EPNN) model by combining heart rate variability (HRV) and neural network. For the sake of improving the prediction performance more reliably, the proposed EPNN model is based on various types of activation functions like hyperbolic tangent, linear, and Gaussian functions, all of which are embedded in hidden nodes to improve its performance. In order to verify the validity of the proposed EPNN model, a number of HRV metrics were calculated from 20 valid and qualified participants whose emotions were induced by using money game. To add more rigor to the experiment, the participants' valence and arousal were checked and used as output node of the EPNN. The experiment results reveal that the F-Measure for Valence and Arousal is 80% and 95%, respectively, proving that the EPNN yields very robust and well-balanced performance. The EPNN performance was compared with competing models like neural network, logistic regression, support vector machine, and random forest. The EPNN was more accurate and reliable than those of the competing models. The results of this study can be effectively applied to many types of wearable computing devices when ubiquitous digital health environment becomes feasible and permeating into our everyday lives.

• Journal of Institute of Convergence Technology
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• v.4 no.2
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• pp.1-9
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• 2014

This paper examines feature-based reconstruction algorithm using feature-based modeling and based on topology optimization technology, which aims to achieve a minimal volume weight and to satisfy user-defined constraints such as stress, deformation related conditions. The finite element model after topology optimization allows us to remove some region of a solid model for predefined volume requirement. The stress or deformation distribution resulted from finite element analysis enables us to add some material to the solid model for a robust structure. For this purpose, we propose a feature-based redesign algorithm which inserts negative features to the solid model for material removal and positive features for material addition, and we introduce a bisection method which searches an optimal structure by iteratively applying the feature-based redesign algorithm. Several examples are considered to illustrate the proposed algorithms and to demonstrate the effectiveness of the present approach.

• Journal of Institute of Convergence Technology
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• v.4 no.2
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• pp.11-15
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• 2014

Magnet gear transfers a high speed torque of the driving side to a low speed following side. Of course, the torque is amplified as much as a ratio between pole number of magnet gears constituting both sides through ferromagnet modulator. However, the parameters of the overall magnetic system influence the transmitting torque strongly. They include a pole number of permanent magnet, magnet thickness, reducing ratio, harmonic modulator thickness, and open ratio etc. In this paper, the influences of the parameters are analyzed using finite element method tool. By comparison, a desirable design specification is proposed, including a recommended modulator pattern.

• Journal of Institute of Convergence Technology
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• v.9 no.1
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• pp.1-6
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• 2019

Matrix multiplication is a fundamental mathematical operation that has numerous applications across most scientific fields. In this paper, we presents a parallel GPU computation algorithm for dense matrix-matrix multiplication using OpenGL compute shader, which can play a very important role as a fundamental building block for many high-performance computing applications. Experimental results on NVIDIA Quad 4000 show that the proposed algorithm runs about 208 times faster than previous CPU algorithm and achieves performance of 75 GFLOPS in single precision for dense matrices with matrix size 4,096. Such performance proves that our algorithm is practical for real applications.

• Journal of Institute of Convergence Technology
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• v.6 no.1
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• pp.27-30
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• 2016

In recent years, manufacturing industry takes a lot of significant change - such as Industry4.0, SMART factory, and IoT(Internet of things). To satisfy their requirements, many cutting-edge machineries are provided to enhance manufacturing industry's productivity. Also, IT technologies are applied to many machinery part and improve their functions. In Korea, Chung-buk plays an important role in machinery part industry. In this paper, we survey, analyze and summarize the current machinery part industry focused on Chunk-buk Area.

• Journal of Institute of Convergence Technology
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• v.8 no.1
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• pp.15-20
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• 2018

Recently a GPU has acquired programmability to perform general purpose computation fast by running thousands of threads concurrently. This paper presents a parallel GPU computation algorithm for dense matrix-matrix addition and scalar multiplication using OpenGL compute shader. It can play a very important role as a fundamental building block for many high-performance computing applications. Experimental results on NVIDIA Quad 4000 show that the proposed algorithm runs 21 times faster than CPU algorithm and achieves performance of 16 GFLOPS in single precision for dense matrices with size 4,096. Such performance proves that our algorithm is practical for real applications.