• The Journal of KAIRB
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• v.6 no.1
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• pp.17-31
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• 2024

Purpose: This study aims to develop preliminary items for measuring the perceived service quality of clinical trials among participants and to verify content validity. Methods: This study was designed as a methodological study. A conceptual framework was established based on Brady and Cronin's hierarchical model, and preliminary items were prepared through translation-back-translation, a review of existing instruments, and in-depth interviews with clinical trial participants and clinical research coordinators. The final items were completed through content validity testing by experts and a review of items by clinical trial participants for the prepared preliminary items. Results: Through this study, a set of 58 items across four domains (quality of interaction with researchers, the physical environment, performance procedures, and performance results) and 9 components (information·education·communication, trust, respect for participant preferences, securing facilities and space, accessibility, comfortability, informed consent, coordination of care, subjective understanding of clinical trials) on the service quality of clinical trials were completed. The scale content validity index of all preliminary items was 0.96, meeting the recommended standards. The individual-item content validity index also meets the recommended criteria for most items, excluding four items. Conclusion: This study holds significance in developing items to measure the quality of clinical trial execution from the perspective of participants. By verifying the reliability and validity of these items through subsequent research, it is expected that they can be utilized as a valuable instrument to devise strategies for improving the quality of clinical trials.

• Journal of Internet Computing and Services
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• v.25 no.2
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• pp.79-92
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• 2024

ChatGPT, as a representative chatbot leveraging generative artificial intelligence technology, is used valuable not only in scientific and technological domains but also across diverse sectors such as society, economy, industry, and culture. This study conducts an explorative analysis of user sentiments and needs for ChatGPT by examining global social media discourse on Reddit. We collected 10,796 comments on Reddit from December 2022 to August 2023 and then employed keyword analysis, sentiment analysis, and need-mining-based topic modeling to derive insights. The analysis reveals several key findings. The most frequently mentioned term in ChatGPT-related comments is "time," indicative of users' emphasis on prompt responses, time efficiency, and enhanced productivity. Users express sentiments of trust and anticipation in ChatGPT, yet simultaneously articulate concerns and frustrations regarding its societal impact, including fears and anger. In addition, the topic modeling analysis identifies 14 topics, shedding light on potential user needs. Notably, users exhibit a keen interest in the educational applications of ChatGPT and its societal implications. Moreover, our investigation uncovers various user-driven topics related to ChatGPT, encompassing language models, jobs, information retrieval, healthcare applications, services, gaming, regulations, energy, and ethical concerns. In conclusion, this analysis provides insights into user perspectives, emphasizing the significance of understanding and addressing user needs. The identified application directions offer valuable guidance for enhancing existing products and services or planning the development of new service platforms.

• Journal of Korean Library and Information Science Society
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• v.54 no.4
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• pp.85-104
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• 2023

The purpose of this study is to analyze the examination questions used in the librarian teacher recruitment exam, including the domains, content, and evaluation factors, and to propose improvements for the recruitment exam. To achieve this, examination questions for librarian teacher recruitment exams since 2002, provided by the Korea Institute for Curriculum and Evaluation, were collected and analyzed the frequency of appearances by section. The analysis revealed that, 106 questions (21.95%) on school library administration, 63 questions (13.04%) on classification and information retrieval 59 questions (12.22%) on library computerization, 58 questions (12.01%) on reading education, 56 questions (11.59%) cataloging and information service, and 18 questions (3.73%) on information media were examined. Next, analyzed the frequency of appearances in the last 10 years (2014-2023) by dividing the examination areas into specialty of librarian and school library practice, and found that there were a total of 149 questions (66.22%) related to specialty of librarian and 76 questions (33.78%) related to school library practice. Based on these findings, recommendations have been made for update assessment areas and factors, expanding the field of information media, and suggested the need for a stable and continuous teacher recruitment policy.

• The Journal of the Acoustical Society of Korea
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• v.43 no.2
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• pp.243-252
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• 2024

Among the Foley sound generation models that have recently begun to be studied, a sound generation technique using the Vector Quantized-Variational AutoEncoder (VQ-VAE) structure and generation model such as Pixelsnail are one of the important research subjects. On the other hand, in the field of deep learning-based acoustic signal compression, residual vector quantization technology is reported to be more suitable than the conventional VQ-VAE structure. Therefore, in this paper, we aim to study whether residual vector quantization technology can be effectively applied to the Foley sound generation. In order to tackle the problem, this paper applies the residual vector quantization technique to the conventional VQ-VAE-based Foley sound generation model, and in particular, derives a model that is compatible with the existing models such as Pixelsnail and does not increase computational resource consumption. In order to evaluate the model, an experiment was conducted using DCASE2023 Task7 data. The results show that the proposed model enhances about 0.3 of the Fréchet audio distance. Unfortunately, the performance enhancement was limited, which is believed to be due to the decrease in the resolution of time-frequency domains in order to do not increase consumption of the computational resources.

• Korean Journal of Radiology
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• v.21 no.12
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• pp.1345-1354
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• 2020

Objective: To evaluate radiomics analysis in studies on mild cognitive impairment (MCI) and Alzheimer's disease (AD) using a radiomics quality score (RQS) system to establish a roadmap for further improvement in clinical use. Materials and Methods: PubMed MEDLINE and EMBASE were searched using the terms 'cognitive impairment' or 'Alzheimer' or 'dementia' and 'radiomic' or 'texture' or 'radiogenomic' for articles published until March 2020. From 258 articles, 26 relevant original research articles were selected. Two neuroradiologists assessed the quality of the methodology according to the RQS. Adherence rates for the following six key domains were evaluated: image protocol and reproducibility, feature reduction and validation, biologic/clinical utility, performance index, high level of evidence, and open science. Results: The hippocampus was the most frequently analyzed (46.2%) anatomical structure. Of the 26 studies, 16 (61.5%) used an open source database (14 from Alzheimer's Disease Neuroimaging Initiative and 2 from Open Access Series of Imaging Studies). The mean RQS was 3.6 out of 36 (9.9%), and the basic adherence rate was 27.6%. Only one study (3.8%) performed external validation. The adherence rate was relatively high for reporting the imaging protocol (96.2%), multiple segmentation (76.9%), discrimination statistics (69.2%), and open science and data (65.4%) but low for conducting test-retest analysis (7.7%) and biologic correlation (3.8%). None of the studies stated potential clinical utility, conducted a phantom study, performed cut-off analysis or calibration statistics, was a prospective study, or conducted cost-effectiveness analysis, resulting in a low level of evidence. Conclusion: The quality of radiomics reporting in MCI and AD studies is suboptimal. Validation is necessary using external dataset, and improvements need to be made to feature reproducibility, feature selection, clinical utility, model performance index, and pursuits of a higher level of evidence.

• Information Systems Review
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• v.25 no.1
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• pp.93-110
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• 2023

Recently, attempts have been made to convert unstructured text into vectors and to analyze vast amounts of natural language for various purposes. In particular, the demand for analyzing texts in specialized domains is rapidly increasing. Therefore, studies are being conducted to analyze specialized and general-purpose documents simultaneously. To analyze specific terms with general terms, it is necessary to align the embedding space of the specific terms with the embedding space of the general terms. So far, attempts have been made to align the embedding of specific terms into the embedding space of general terms through a transformation matrix or mapping function. However, the linear transformation based on the transformation matrix showed a limitation in that it only works well in a local range. To overcome this limitation, various types of nonlinear vector alignment methods have been recently proposed. We propose a vector alignment model that matches the embedding space of specific terms to the embedding space of general terms through end-to-end learning that simultaneously learns the autoencoder and regression model. As a result of experiments with R&D documents in the "Healthcare" field, we confirmed the proposed methodology showed superior performance in terms of accuracy compared to the traditional model.

• Journal of the Korea Institute of Building Construction
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• v.24 no.1
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• pp.145-156
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• 2024

In an era where construction projects are becoming increasingly large and complex, the Korean construction industry faces the challenge of implementing systematic and cohesive schedule management practices. This study initially delineates the concept of schedule management capabilities, systematically categorizing them into five distinct domains: law and regulations, requirements of project owners, capabilities of professionals and organizations, task capability, and the adoption of smart construction technologies for schedule management. Through a survey targeting industry professionals, this research assesses the perceived importance and the actual proficiency level in schedule management across these categories, employing an Importance Performance Analysis(IPA) to scrutinize these capabilities. The findings underscore the acknowledged significance of diverse aspects of schedule management, yet reveal discrepancies between the current proficiency levels and their perceived importance, pinpointing areas necessitating enhancement. Critical improvement needs identified encompass the planning of budgets for schedule management, development of regulations for assessing construction periods, deployment of specialized on-site staff for schedule management, and investment in advanced schedule management software solutions. Consequently, this study offers a nuanced analysis and strategic insights for enhancing schedule management practices, aiming to facilitate their effective implementation in the field.

• Journal of Korean Society of Rural Planning
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• v.30 no.2
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• pp.13-24
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• 2024

This study conducts an analysis of social media big data pertaining to island tourism resources, aiming to discern the diverse forms and categories of island tourism favored by consumers, ascertain predominant resources, and facilitate objective decision-making grounded in scientific methodologies. To achieve this objective, an examination of blog posts published on Naver from 2022 to 2023 was undertaken, utilizing keywords such as 'Island tourism', 'Island travel', and 'Island backpacking' as focal points for analysis. Text mining techniques were applied to sift through the data. Among the resources identified, the port emerged as a significant asset, serving as a pivotal conduit linking the island and mainland and holding substantial importance as a focal point and resource for tourist access to the island. Furthermore, an analysis of the disparity between existing island tourism resources and those acknowledged by tourists who actively engage with and appreciate island destinations led to the identification of 186 newly emerging resources. These nascent resources predominantly clustered within five regions: Incheon Metropolitan City, Tongyeong/Geoje City, Jeju Island, Ulleung-gun, and Shinan-gun. A scrutiny of these resources, categorized according to the tourism resource classification system, revealed a notable presence of new resources, chiefly in the domains of 'rural landscape', 'tourist resort/training facility', 'transportation facility', and 'natural resource'. Notably, many of these emerging resources were previously overlooked in official management targets or resource inventories pertaining to existing island tourism resources. Noteworthy examples include ports, beaches, and mountains, which, despite constituting a substantial proportion of the newly identified tourist resources, were not accorded prominence in spatial information datasets. This study holds significance in its ability to unearth novel tourism resources recognized by island tourism consumers through a gap analysis approach that juxtaposes the existing status of island tourism resource data with techniques utilizing social media big data. Furthermore, the methodology delineated in this research offers a valuable framework for domestic local governments to gauge local tourism demand and embark on initiatives for tourism development or regional revitalization.

• Korean Journal of Radiology
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• v.24 no.11
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• pp.1102-1113
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• 2023

Objective: To elucidate the use of radiological studies, including nuclear medicine, and biopsy for the diagnosis and staging of prostate cancer (PCA) in clinical practice and understand the current status of PCA in Asian countries via an international survey. Materials and Methods: The Asian Prostate Imaging Working Group designed a survey questionnaire with four domains focused on prostate magnetic resonance imaging (MRI), other prostate imaging, prostate biopsy, and PCA backgrounds. The questionnaire was sent to 111 members of professional affiliations in Korea, Japan, Singapore, and Taiwan who were representatives of their working hospitals, and their responses were analyzed. Results: This survey had a response rate of 97.3% (108/111). The rates of using 3T scanners, antispasmodic agents, laxative drugs, and prostate imaging-reporting and data system reporting for prostate MRI were 21.6%-78.9%, 22.2%-84.2%, 2.3%-26.3%, and 59.5%-100%, respectively. Respondents reported using the highest b-values of 800-2000 sec/mm² and fields of view of 9-30 cm. The prostate MRI examinations per month ranged from 1 to 600, and they were most commonly indicated for biopsy-naïve patients suspected of PCA in Japan and Singapore and staging of proven PCA in Korea and Taiwan. The most commonly used radiotracers for prostate positron emission tomography are prostate-specific membrane antigen in Singapore and fluorodeoxyglucose in three other countries. The most common timing for prostate MRI was before biopsy (29.9%). Prostate-targeted biopsies were performed in 63.8% of hospitals, usually by MRI-ultrasound fusion approach. The most common presentation was localized PCA in all four countries, and it was usually treated with radical prostatectomy. Conclusion: This survey showed the diverse technical details and the availability of imaging and biopsy in the evaluation of PCA. This suggests the need for an educational program for Asian radiologists to promote standardized evidence-based imaging approaches for the diagnosis and staging of PCA.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.2
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• pp.85-93
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• 2024

In this paper, we propose a method for establishing a state-space equation model for the motion analysis of floating structures subjected to wave loads, by applying system-identification techniques. Traditionally, the motion of floating structures has been analyzed in the time domain by integrating the Cummins equation over time, which utilizes a convolution integral term to account for the effects of the retardation function. State-space equation models have been studied as a way to efficiently solve floating-motion equations in the time domain. The proposed approach outlines a procedure to derive the target transfer function for the load-displacement input/output relationship in the frequency domain and subsequently determine the state-space equation that closely approximates it. To obtain the state-space equation, the method employs the N4SID system-identification method and an optimization approach that treats the coefficients of the numerator and denominator polynomials as design variables. To illustrate the effectiveness of the proposed method, we applied it to the analysis of a single-degree-of-freedom model and the motion of a six-degree-of-freedom barge. Our findings demonstrate that the presented state-space equation model aligns well with the existing analysis results in both the frequency and time domains. Notably, the method ensures computational accuracy in the time-domain analysis while significantly reducing the calculation time.