• Journal of The Korean Society of Integrative Medicine
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• v.12 no.1
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• pp.109-124
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• 2024

Purpose : The purpose of this study was to examine the effects of a virtual reality-based complex cognitive training program for depression, cognitive function, and digital divide reduction in the elderly who have not been diagnosed with dementia or MCI. Methods : We enrolled 16 participants who were over 65 years old and not been diagnosed with dementia or MCI. We randomly divided into three groups (A, B, C). Participants underwent an 8-week virtual reality-based complex cognitive training program (60 minutes each session, twice per week). At a baseline, all participants completed questionnaires on general features, depression and cognitive function. After four weeks, all participants completed questionnaires on depression and cognitive function. After the end of the last program, participants conducted questionnaires on depression, cognitive function, and usability evaluation. Results : At the 8-week follow-up, 16 participants completed the program. Compared to the baseline, the average score of cognitive function was increased (from 26.5 to 28.5), although it was not statistically significant (p<.061). There were no significant differences between baseline and post-training evaluations on depression scores. The average score of usability evaluation was 75.56, which corresponds to good. Conclusion : Even though the results showed no statistically significant findings in cognitive function and depression after the virtual reality-based complex cognitive training intervention, this pilot study proposed the possibility of utilizing the virtual reality program as a tool that provides active learning opportunities for the elderly and helps improve their cognitive function through multi-sensory components. Also, the findings of this study suggested a positive reevaluation of the elderly's digital access capabilities while reducing the digital divide. A virtual reality-based complex cognitive training program improved the social network of the elderly. We expect that it will expand in size and help with their social participation of the elderly.

• International Journal of Knowledge Content Development & Technology
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• v.14 no.3
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• pp.39-57
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• 2024

Plagiarism detection software is beneficial in detecting plagiarism in research works of postgraduate students. Despite the benefits of using plagiarism detection software, studies have revealed that most students, including postgraduates, do not use plagiarism detection software as expected. This could depend on the provision of facilitating conditions like internet connectivity, training opportunities and electricity. Thus, this study examined facilitating conditions and the use of plagiarism detection software among postgraduates of the University of Ibadan, Nigeria. A descriptive survey research design of the correlational type was used for this study, with a population of 2143 postgraduates. The multi-stage random sampling technique was used to determine the sample size of 242. The questionnaire was the research instrument, and data was analysed using descriptive statistics. Results showed that most postgraduates agreed that the university provided facilitating conditions like internet connectivity. The majority of the respondents noted that they used Turnitin monthly. Most of the respondents noted that they used plagiarism detection software to paraphrase their work and check the correctness of the grammar in their documents. The most prominent challenges confronting plagiarism detection software use by most respondents were their inability to afford subscription payment to use the plagiarism detection software and slow internet connectivity. There was a significant positive relationship between facilitating conditions and the use of plagiarism detection software by the postgraduates of the University of Ibadan, Nigeria. Some of the recommendations for the institution's management include leveraging the vast network of alumni willing to give back to the institution and intervening in the provision of internet connectivity and electricity.

• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.113-118
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• 2024

In this paper, we propose an optimal wavelet in a system for canceling background noise of acoustic signals. This system performed Discrete Wavelet Transform(DWT) instead of the existing Short Time Fourier Transform(STFT) and then improved noise cancellation performance through a deep learning process. DWT functions as a multi-resolution band-pass filter and obtains transformation parameters by time-shifting the parent wavelet at each level and using several wavelets whose sizes are scaled. Here, the noise cancellation performance of several wavelets was tested to select the most suitable mother wavelet for analyzing the speech. In this study, to verify the performance of the noise cancellation system for various wavelets, a simulation program using Tensorflow and Keras libraries was created and simulation experiments were performed for the four most commonly used wavelets. As a result of the experiment, the case of using Haar or Daubechies wavelets showed the best noise cancellation performance, and the mean square error(MSE) was significantly improved compared to the case of using other wavelets.

• Quality Improvement in Health Care
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• v.29 no.2
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• pp.2-14
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• 2023

Purpose: This study aimed to identify strategies to enhance the competencies of patient safety coordinators in Korea. Methods: Fourteen participants from nine hospitals were interviewed between May and November 2022. Qualitative content analysis was used to analyze the data. Results: As for the strategies to enhance patient safety management competency, 3 themes and 11 sub-themes were derived. The first theme was 'Having individual competence as a patient safety coordinator', and the sub-themes were 'Communication skills with members', 'Flexible thinking from multiple perspectives', and 'Preparing for administrative work competencies that they had not experienced as a nurse.' The second theme was 'Responding strategically to promote improvement activities', and the sub-themes for it were 'Multi-angle approach to the problem', 'A careful approach so as not to be taken as criticism in the field', 'Increasing the possibility of improvement activities through awareness', 'Activating the network between patient safety coordinators', and 'Expanding learning opportunities through patient safety case analysis.' The third theme was 'Obtaining support to facilitate patient safety activities', and the sub-themes for this were 'Improving staff awareness of patient safety', 'Providing a training course for nurse professional of patient safety', and 'Expanding the manpower allocation standard of patient safety coordinators.' Conclusion: This study explored personal competencies such as document writing and computer utilization capabilities, focused on ways to improve the field of patient safety management, and emphasized the need for organizational and political support.

• The Transactions of the Korea Information Processing Society
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• v.13 no.3
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• pp.122-129
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• 2024

Though programming education has been stressed recently, the elementary, middle, and high school students are having trouble in programming education. Most programming environments for them are based on block coding, which hinders them from moving to text coding. The traditional PC environment has also troubles such as maintenance problems. In this situation, mobile applications can be considered as alternative programming environments. This paper addresses the design and implementation of coding applications for mobile devices. As a prototype, a Scheme interpreter mobile app is proposed, where Scheme is used for programming courses at MIT since it supports multi-paradigm programming. The implementation has the advantage of not consuming the network bandwidth since it is designed as a standalone application. According to the benchmark result, the execution time on Android devices, relative to that on a desktop, was 131% for the Derivative and 157% for the Tak. Further, the maximum execution times for the benchmark programs on the Android device were 19.8ms for the Derivative and 131.15ms for the Tak benchmark. This confirms that when selecting an Android device for programming education purposes, there are no significant constraints for training.

• Steel and Composite Structures
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• v.51 no.4
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• pp.441-456
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• 2024

This paper aims to develop Machine Learning (ML) algorithms to predict the buckling resistance of cold-formed steel (CFS) channels with restrained flanges, widely used in typical CFS sheathed wall panels, and provide practical design tools for engineers. The effects of cross-sectional restraints were first evaluated on the elastic buckling behaviour of CFS channels subjected to pure axial compressive load or bending moment. Feedforward multi-layer Artificial Neural Networks (ANNs) were then trained on different datasets comprising CFS channels with various dimensions and properties, plate thicknesses, and restraining conditions on one or two flanges, while the elastic distortional buckling resistance of the elements were determined according to the Finite Strip Method (FSM). To develop less biased networks and ensure that every observation from the original dataset has the chance of appearing in the training and test set, a K-fold cross-validation technique was implemented. In addition, the hyperparameters of the ANNs were tuned using a grid search technique to provide ANNs with optimum performances. The results demonstrated that the trained ANNs were able to predict the elastic distortional buckling resistance of CFS flange-restrained elements with an average accuracy of 99% in terms of coefficient of determination. The developed models were then used to propose a simple ANN-based design formula for the prediction of the elastic distortional buckling stress of CFS flange-restrained elements. Finally, the proposed formula was further evaluated on a separate set of unseen data to ensure its accuracy for practical applications.

• Journal of the Korea Computer Graphics Society
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• v.30 no.3
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• pp.51-59
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• 2024

Collecting a dataset with a corresponding labeled gaze vector requires a high cost in the gaze estimation field. In this paper, we suggest a data augmentation of manipulating the gaze of an original image, which improves the accuracy of the gaze estimation model when the number of given gaze labels is restricted. By conducting multi-class gaze bin classification as an auxiliary task and adjusting the latent variable of the diffusion model, the model semantically edits the gaze from the original image. We manipulate a non-binary attribute, pitch and yaw of gaze vector to a desired range and uses the edited image as an augmented train data. The improved gaze accuracy of the gaze estimation network in the semi-supervised learning validates the effectiveness of our data augmentation, especially when the number of gaze labels is 50k or less.

• Archives of design research
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• v.18 no.4 s.62
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• pp.53-64
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• 2005

The emergence of new communication media, digital, is something of a wonder, as well as a cultural tension. The industrial technologies that dramatically expand human abilities are being developed much faster than the speed of adaptation by humans. Without an exception, it creates new contents and form of the culture by shaking the very foundation of the notion about human beings. Korean broadcasting environment has stepped into the era of multi-media, multi-channel as the digital technology separated the media into network, cable, satellite and internet. In this digital culture, broadcasting, as a medium of information delivering and communication, has bigger influence than ever. Such changes in broadcasting environment turned the TV viewers into new consumers who participate and play the main role in active communication by choosing and using the media. This study is trying to systemize the question about the core identity of broadcasting through brand as the consumers stand in the center of broadcasting with the power to select channel. The story schema theory can be applied as a cognitive psychological tool to approach the active consumers in order to explain the cognitive processes that are related to information processing. It is a design with stories, which comes up as a case of a brand's story telling. The range of this study covers the current issue and educational programs in network TV during the period of May and August of year 2005. The cases of Korean and foreign programs were compared by the station each program is broadcasted. This study concludes that it is important to take the channel identity into the consideration in the brand strategy of each program. Especially, the leading programs of a station must not be treated as a separate program that has nothing to do with the station's identity. They must be treated to include the contents and form that builds the identity of the channel. Also, this study reconfirmed that building a brand of the anchor person can play as an important factor in the identity of the program's brand.

• Journal of Environmental Impact Assessment
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• v.24 no.2
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• pp.134-153
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• 2015

When making urban planning, it is important to understand climate effect caused by urban structural changes. Seoul city applies UPIS(Urban Plan Information System) which provides information on urban planning scenario. Technology for analyzing climate effect resulted from urban planning needs to developed by linking urban planning scenario provided by UPIS and climate analysis model, CAS(Climate Analysis Seoul). CAS develops for analyzing urban climate conditions to provide realistic information considering local air temperature and wind flows. Quantitative analyses conducted by CAS for the production, transportation, and stagnation of cold air, wind flow and thermal conditions by incorporating GIS analysis on land cover and elevation and meteorological analysis from MetPhoMod(Meteorology and atmospheric Photochemistry Meso-scale model). In order to reflect land cover and elevation of the latest information, CAS used to highly accurate raster data (1m) sourced from LiDAR survey and KOMPSAT-2(KOrea Multi-Purpose SATellite) satellite image(4m). For more realistic representation of land surface characteristic, DSM(Digital Surface Model) and DTM(Digital Terrain Model) data used as an input data for CFD(Computational Fluid Dynamics) model. Eight inflow directions considered to investigate the change of flow pattern, wind speed according to reconstruction and change of thermal environment by connecting green area formation. Also, MetPhoMod in CAS data used to consider realistic weather condition. The result show that wind corridors change due to reconstruction. As a whole surface temperature around target area decreases due to connecting green area formation. CFD model coupled with CAS is possible to evaluate the wind corridor and heat environment before/after reconstruction and connecting green area formation. In This study, analysis of climate impact before and after created the green area, which is part of 'Connecting green network across the north and south in Seoul' plan, one of the '2020 Seoul master plan'.

• Korean Journal of Remote Sensing
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• v.36 no.6_2
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• pp.1509-1521
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• 2020

Experiments for validation of surface reflectance produced by Korea Multi-Purpose Satellite (KOMPSAT-3A) were conducted using Chinese Baotou (BTCN) data among four sites of the Radical Calibration Network (RadCalNet), a portal that provides spectrophotometric reflectance measurements. The atmosphere reflectance and surface reflectance products were generated using an extension program of an open-source Orfeo ToolBox (OTB), which was redesigned and implemented to extract those reflectance products in batches. Three image data sets of 2016, 2017, and 2018 were taken into account of the two sensor model variability, ver. 1.4 released in 2017 and ver. 1.5 in 2019, such as gain and offset applied to the absolute atmospheric correction. The results of applying these sensor model variables showed that the reflectance products by ver. 1.4 were relatively well-matched with RadCalNet BTCN data, compared to ones by ver. 1.5. On the other hand, the reflectance products obtained from the Landsat-8 by the USGS LaSRC algorithm and Sentinel-2B images using the SNAP Sen2Cor program were used to quantitatively verify the differences in those of KOMPSAT-3A. Based on the RadCalNet BTCN data, the differences between the surface reflectance of KOMPSAT-3A image were shown to be highly consistent with B band as -0.031 to 0.034, G band as -0.001 to 0.055, R band as -0.072 to 0.037, and NIR band as -0.060 to 0.022. The surface reflectance of KOMPSAT-3A also indicated the accuracy level for further applications, compared to those of Landsat-8 and Sentinel-2B images. The results of this study are meaningful in confirming the applicability of Analysis Ready Data (ARD) to the surface reflectance on high-resolution satellites.