• Journal of Intelligence and Information Systems
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• v.28 no.1
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• pp.1-28
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• 2022

In recent years, many Internet giants have begun providing their own content services, which attract online users by offering personalized services based on artificial intelligence technologies. This study investigates the role of two firms' content services within the firms' online service network. We examine the role of Naver Webtoon, which can be characterized as a professional-generated content, within Naver's service portfolio, and that of Google YouTube, which can be characterized as a user-generated content, within Google's service portfolio. Using survey data on viewers' use of the two services, we analyze a valued directed service network, where a node denotes an online service and a relationship between two nodes denotes a sequential use of two services. We found that both Webtoon and YouTube show higher out-degree centrality than in-degree centrality, which implies these content services are more likely to be starting services rather than arriving services within the firms' interactive network. The gap between the out-degree and in-degree centrality of YouTube is much smaller than that of Webtoon. The high centrality of YouTube, a user-generated content service, within the Google service network shows that YouTube's initial role of providing specific-content videos (e.g., entertainment) has expanded into a general search service for users.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.6 no.12
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• pp.55-67
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• 2016

Purpose: The aims of this were to analyse the quantitative research trends and describe the factors influencing health related to quality of life (HRQoL) and instruments used to HRQoL after Intensive care units (ICU) discharge. Methods: This study were included 84 published papers regarding HRQoL after ICU discharge from initial data to December 2015. Results: The majority of papers were performed abroad. Only 4 papers with regard to HRQoL of ICU survivors were performed by nurses. 36 studies (42.8%) were used to measure HRQoL ICU survivors using the SF-36. 29 studies (34.5%) were used to measure HRQoL at 3~6 months after ICU discharge. Older age, longer length of stay at ICU, severity of illness, anxiety and depression were main risk factors to lower HRQoL in ICU patients. Conclusions: This study provides a better understanding of quality of life follwing critical illness. Therefore, further stduy is needed to develop patient centered intervention considered patients'health status and recovery phase. Additionally, large prospective multicenter cohort studies should be required.

• 한국체육학회지인문사회과학편
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• v.55 no.1
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• pp.221-233
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• 2016

The purpose of this study was to prove a development and initial validation of the korean version of coach-athlete relationship maintenance scale that originated from the work of Rhind & Jowett(2012) in pro baseball. The items were then administered to 132 Participants(29 coaches and 103 athletes) completed the questionnaires of the coach-athlete relationship maintenance in First preliminary investigation. Maximum likelihood estimate was used to identify the latent underlying structure. In order to verify the validity of Korean version of coach-athlete relationship maintenance was administered to an independent sample of 273 coaches and athletes. Pro baseball coach-athlete relationship maintenance is consisted of six factors(25 items) with conflict management, motivational, preventative, openness/assurance, support, and social network. SPSS18.0 and AMOS16.0 were used to analyze the exploratory factor analysis, confirmatory factory analysis and internal consistency, test-retest with bootstrapping using of the data in this study. The results of the pro baseball coach-athlete relationship maintenance scale had six factors with 25 items, and each six factor was positively correlated. Overall, this study verified pro baseball coach-athlete relationship maintenance questionnaire. Thus, suggest that path of comparing the differences between the first division and farm team by using the test of the structural model invariance across the groups.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.3C
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• pp.179-186
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• 2008

Pressuremeter test estimates the deformational properties of soil from the relationship between applied pressure and the displacement of cavity wall. It is general to utilize the reloading curve for the estimation of deformational properties of soil because the initial loading curve can be affected by the disturbance caused by boring. On the other hand, the instrumental resolution or the variation of measured data makes it hard to estimate the maximum shear modulus from pressuremeter test results. This study suggested the methodology estimating the maximum shear modulus from pressuremeter test directly, based on the curve fitting of reloading curve. In addition, the difference was taken into account between the stress state around the probe in reloading and that of the in-situ state. Pressuremeter tests were conducted for 15 cases using a large calibration chamber, together with a number of reference tests. The maximum shear moduli taken from suggested method were compared with those from empirical correlation and bender element test.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3C
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• pp.201-207
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• 2006

Soil tests are generally conducted using a membrane to measure a pore water pressure. However, it has also been recognized that the membrane penetrates into the specimen by the change of the confining pressure, and it results in the erroneous measurement in the pore water pressure and the volumetric strain. This study examined the effectiveness of the correction equation of the membrane penetration on the basis of the experimental data acquired during the isotropic unloading and the cyclic shear process using the hollow cylindrical shear test equipment. The results showed that the membrane penetration by the correction equation could be overestimated when the mean effective stress was lower than 20kPa in this study. The limitations originated from the sudden increase near the zero effective stress, and in order to prevent the overestimation in low effective stress condition, the use of the constant a was proposed in this study. Furthermore, the correction equation for the membrane penetration had to be applied carefully when the initial relative density was high and the density changes were occurred by the relocation of the soil particle by the liquefaction.

• The Korean Journal of Applied Statistics
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• v.36 no.5
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• pp.447-455
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• 2023

COVID-19 is an emerging infectious disease that is hard to predict in terms of fatality rate, treatments, and the timing of its end. World is developing treatments and vaccines for COVID-19. Several treatments and vaccines currently have emergency use authorization, but the treatments are only allowed for critically ill patients with COVID-19. Therefore, the aim of this study is to analyze the confirmed cases of COVID-19, including mortality and testing, in OECD countries and to assess the effect of vaccination on mortality. Looking at the confirmed cases, mortality, and vaccination rates of COVID-19, the number of confirmed cases was lower than previously reported cases after full vaccination. In early 2022, with Omicron, the confirmed cases increased sharply, while mortality dropped, and the mortality showed a gentle curve as the cumulative fully vaccinated exceeded 50%. This indicates that COVID-19 vaccines have an effect on reducing mortality. However, the duration of effectiveness of vaccines was considerably short, which decreased the initial inoculation effect and increased the monthly mortality. As this study was carried out during the COVID-19 pandemic, there was not enough data to analyze comprehensively. However, it is meaningful to compare and analyze the impact of COVID-19 by country.

• Journal of Internet Computing and Services
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• v.24 no.6
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• pp.73-80
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• 2023

The recent steep increase in the minimum hourly wage has increased the burden of labor costs, and the share of unmanned stores is increasing in the aftermath of COVID-19. As a result, theft crimes targeting unmanned stores are also increasing, and the "Just Walk Out" system is introduced to prevent such thefts, and LiDAR sensors, weight sensors, etc. are used or manually checked through continuous CCTV monitoring. However, the more expensive sensors are used, the higher the initial cost of operating the store and the higher the cost in many ways, and CCTV verification is difficult for managers to monitor around the clock and is limited in use. In this paper, we would like to propose an AI image processing fusion algorithm that can solve these sensors or human-dependent parts and detect customers who perform abnormal behaviors such as theft at low costs that can be used in unmanned stores and provide cloud-based notifications. In addition, this paper verifies the accuracy of each algorithm based on behavior pattern data collected from unmanned stores through motion capture using mediapipe, object detection using YOLO, and fusion algorithm and proves the performance of the convergence algorithm through various scenario designs.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.4
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• pp.1-16
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• 2023

In 2005, the selection of 10 innovation cities was completed, and since 2013, public institutions began relocating to innovation cities. As a policy aimed at promoting balanced regional development, there were significant expectations from the regions. However, although the population moving to innovation cities has increased, it remains to be seen how much inflow is from the capital region and what spatial characteristics exist nationwide. Therefore, this study aims to analyze whether the innovation cities are fulfilling their roles by examining the patterns of inflow from the capital region and the spatial characteristics, and to reassess the policy direction for future innovation cities. We utilized the Microdata Integrated Service (MDIS) provided by Statistics Korea from 2013 to 2021. For the data collection reasons, we focused on analyzing the three cities. The results showed that in the initial stages of innovation city development, there was a significant influx of population from the capital region, leading to some effects on population dispersion and balanced regional development. However, over time, a phenomenon emerged where more people started to move back to the capital region, indicating a problematic trend. Furthermore, the Gyeongbuk Innovation City and Gwangju-Jeonnam Innovation City showed similarities in terms of reasons for migration, age of householder, and number of household members. However, the Gyeongnam Innovation City exhibited distinct characteristics compared to the other two cities. While the reasons for this phenomenon may be diverse, the current situation suggests that the goal of achieving "balanced national development" has reached its limits. Therefore, urgent measures need to be taken for improvement that take regional characteristics into account. Furthermore, in designing the second phase of the public institution relocation plan is required to avoid repeating the same issues and ensure a more thoughtful approach.

• Journal of Korean Society of Rural Planning
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• v.30 no.1
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• pp.57-66
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• 2024

This study aimed to develop a precise vegetation cover classification model for small streams using the combination of drone remote sensing and support vector machine (SVM) techniques. The chosen study area was the Idong stream, nestled within Geosan-gun, Chunbuk, South Korea. The initial stage involved image acquisition through a fixed-wing drone named ebee. This drone carried two sensors: the S.O.D.A visible camera for capturing detailed visuals and the Sequoia+ multispectral sensor for gathering rich spectral data. The survey meticulously captured the stream's features on August 18, 2023. Leveraging the multispectral images, a range of vegetation indices were calculated. These included the widely used normalized difference vegetation index (NDVI), the soil-adjusted vegetation index (SAVI) that factors in soil background, and the normalized difference water index (NDWI) for identifying water bodies. The third stage saw the development of an SVM model based on the calculated vegetation indices. The RBF kernel was chosen as the SVM algorithm, and optimal values for the cost (C) and gamma hyperparameters were determined. The results are as follows: (a) High-Resolution Imaging: The drone-based image acquisition delivered results, providing high-resolution images (1 cm/pixel) of the Idong stream. These detailed visuals effectively captured the stream's morphology, including its width, variations in the streambed, and the intricate vegetation cover patterns adorning the stream banks and bed. (b) Vegetation Insights through Indices: The calculated vegetation indices revealed distinct spatial patterns in vegetation cover and moisture content. NDVI emerged as the strongest indicator of vegetation cover, while SAVI and NDWI provided insights into moisture variations. (c) Accurate Classification with SVM: The SVM model, fueled by the combination of NDVI, SAVI, and NDWI, achieved an outstanding accuracy of 0.903, which was calculated based on the confusion matrix. This performance translated to precise classification of vegetation, soil, and water within the stream area. The study's findings demonstrate the effectiveness of drone remote sensing and SVM techniques in developing accurate vegetation cover classification models for small streams. These models hold immense potential for various applications, including stream monitoring, informed management practices, and effective stream restoration efforts. By incorporating images and additional details about the specific drone and sensors technology, we can gain a deeper understanding of small streams and develop effective strategies for stream protection and management.

• Korean Journal of Radiology
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• v.22 no.11
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• pp.1850-1857
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• 2021

Objective: The purpose of this study was to assess whether a deep learning (DL) algorithm could enable simultaneous noise reduction and edge sharpening in low-dose lumbar spine CT. Materials and Methods: This retrospective study included 52 patients (26 male and 26 female; median age, 60.5 years) who had undergone CT-guided lumbar bone biopsy between October 2015 and April 2020. Initial 100-mAs survey images and 50-mAs intraprocedural images were reconstructed by filtered back projection. Denoising was performed using a vendor-agnostic DL model (ClariCT.AI^TM, ClariPI) for the 50-mAS images, and the 50-mAs, denoised 50-mAs, and 100-mAs CT images were compared. Noise, signal-to-noise ratio (SNR), and edge rise distance (ERD) for image sharpness were measured. The data were summarized as the mean ± standard deviation for these parameters. Two musculoskeletal radiologists assessed the visibility of the normal anatomical structures. Results: Noise was lower in the denoised 50-mAs images (36.38 ± 7.03 Hounsfield unit [HU]) than the 50-mAs (93.33 ± 25.36 HU) and 100-mAs (63.33 ± 16.09 HU) images (p < 0.001). The SNRs for the images in descending order were as follows: denoised 50-mAs (1.46 ± 0.54), 100-mAs (0.99 ± 0.34), and 50-mAs (0.58 ± 0.18) images (p < 0.001). The denoised 50-mAs images had better edge sharpness than the 100-mAs images at the vertebral body (ERD; 0.94 ± 0.2 mm vs. 1.05 ± 0.24 mm, p = 0.036) and the psoas (ERD; 0.42 ± 0.09 mm vs. 0.50 ± 0.12 mm, p = 0.002). The denoised 50-mAs images significantly improved the visualization of the normal anatomical structures (p < 0.001). Conclusion: DL-based reconstruction may enable simultaneous noise reduction and improvement in image quality with the preservation of edge sharpness on low-dose lumbar spine CT. Investigations on further radiation dose reduction and the clinical applicability of this technique are warranted.