• KIPS Transactions on Software and Data Engineering
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• v.13 no.1
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• pp.35-49
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• 2024

Video captioning technology, as a significant outcome of the integration between computer vision and natural language processing, has emerged as a key research direction in the field of artificial intelligence. This technology aims to achieve automatic understanding and language expression of video content, enabling computers to transform visual information in videos into textual form. This paper provides an initial analysis of the research trends in deep learning-based video captioning and categorizes them into four main groups: CNN-RNN-based Model, RNN-RNN-based Model, Multimodal-based Model, and Transformer-based Model, and explain the concept of each video captioning model. The features, pros and cons were discussed. This paper lists commonly used datasets and performance evaluation methods in the video captioning field. The dataset encompasses diverse domains and scenarios, offering extensive resources for the training and validation of video captioning models. The model performance evaluation method mentions major evaluation indicators and provides practical references for researchers to evaluate model performance from various angles. Finally, as future research tasks for video captioning, there are major challenges that need to be continuously improved, such as maintaining temporal consistency and accurate description of dynamic scenes, which increase the complexity in real-world applications, and new tasks that need to be studied are presented such as temporal relationship modeling and multimodal data integration.

• Journal of Ginseng Research
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• v.48 no.2
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• pp.202-210
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• 2024

Background: Panax ginseng Meyer polysaccharides exhibit various biological functions, like antagonizing galectin-3-mediated cell adhesion and migration. Galectin-8 (Gal-8), with its linker-joined N- and C-terminal carbohydrate recognition domains (CRDs), is also crucial to these biological processes, and thus plays a role in various pathological disorders. Yet the effect of ginseng-derived polysaccharides in modulating Gal-8 function has remained unclear. Methods: P. ginseng-derived pectin was chromatographically isolated and enzymatically digested to obtain a series of polysaccharides. Biolayer Interferometry (BLI) quantified their binding affinity to Gal-8, and their inhibitory effects on Gal-8 was assessed by hemagglutination, cell migration and T-cell apoptosis. Results: Our ginseng-derived pectin polysaccharides consist mostly of rhamnogalacturonan-I (RG-I) and homogalacturonan (HG). BLI shows that Gal-8 binding rests primarily in RG-I and its β-1,4-galactan side chains, with sub-micromolar K_D values. Both N- and C-terminal Gal-8 CRDs bind RG-I, with binding correlated with Gal-8-mediated function. Conclusion: P. ginseng RG-I pectin β-1,4-galactan side chains are crucial to binding Gal-8 and antagonizing its function. This study enhances our understanding of galectin-sugar interactions, information that may be used in the development of pharmaceutical agents targeting Gal-8.

• Journal of Internet Computing and Services
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• v.25 no.1
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• pp.57-67
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• 2024

This research investigates training methods for large language models to accurately identify sentiments and comprehend information about increasing and decreasing fluctuations in the financial domain. The main goal is to identify suitable datasets that enable these models to effectively understand expressions related to financial increases and decreases. For this purpose, we selected sentences from Wall Street Journal that included relevant financial terms and sentences generated by GPT-3.5-turbo-1106 for post-training. We assessed the impact of these datasets on language model performance using Financial PhraseBank, a benchmark dataset for financial sentiment analysis. Our findings demonstrate that post-training FinBERT, a model specialized in finance, outperformed the similarly post-trained BERT, a general domain model. Moreover, post-training with actual financial news proved to be more effective than using generated sentences, though in scenarios requiring higher generalization, models trained on generated sentences performed better. This suggests that aligning the model's domain with the domain of the area intended for improvement and choosing the right dataset are crucial for enhancing a language model's understanding and sentiment prediction accuracy. These results offer a methodology for optimizing language model performance in financial sentiment analysis tasks and suggest future research directions for more nuanced language understanding and sentiment analysis in finance. This research provides valuable insights not only for the financial sector but also for language model training across various domains.

• Journal of Korean Society of Archives and Records Management
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• v.24 no.2
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• pp.41-63
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• 2024

This study investigated research trends in digital curation indexed in a prominent domestic academic information database. A systematic literature review was conducted on 39 academic papers published from 2009 to 2023. The review examined indexing status according to publication year, venue, academic discipline, research area distribution, research affiliation and occupation, and research types. In addition, network centrality analysis and cohesive group analysis were performed on 69 author keywords. The findings revealed several key points. First, digital curation research peaked in 2015 and 2016 with 5 publications each year, followed by a slight decrease, and then consistently produced 4 or more publications annually since 2019. Second, among the 39 studies, 25 were conducted in interdisciplinary fields, including library and information science, while 11 were in the humanities, such as miscellaneous humanities. The most prominent research areas were theoretical and infrastructural aspects, information management and services, and institutional domains. Third, digital curation research was predominantly led by university-affiliated professors and researchers, with collaborative research more prevalent than solo research. Lastly, analysis of author keywords revealed that "digital curation," "institution," and "content" were the most influential central keywords within the overall network.

• Therapeutic Science for Rehabilitation
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• v.13 no.2
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• pp.27-40
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• 2024

Objective : This study aimed to conduct a systematic review of the assessment tools used to assess the housing environment of older adults. Methods : Data were collected from January 2015 to August 31st, 2023, by searching databases including the Cochrane Library, PubMed, and ProQuest. From the 267 articles, nine assessment tools were selected for analysis based on their original instruments. These tools were categorized and systematically organized for analysis based on their frequency of use, assessment purposes, sub-domains, scales, and other relevant criteria. Results : Among the nine tools, HOME FAST and IPAQ-E were the most frequently used (20% each). The objectives of these tools are to assess friendliness, physical barriers, fall prevention, dementia-friendly environments, physical activity, and accessibility. The measurement scope encompassed various factors, such as outdoor spaces, buildings, transportation, housing, and community support. Conclusion : When considering the suitability of housing for the older adults population, providing foundational data for the rational selection of evaluation tools with logical validity is important. This includes factors such as the objectives and measurement scopes of housing environment assessment tools.

• Journal of the Korean GEO-environmental Society
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• v.25 no.4
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• pp.13-20
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• 2024

In this paper, a parallel analysis algorithm for Smoothed Particle Hydrodynamics (SPH), one of the numerical methods for fluidic materials, is introduced. SPH, which is a meshless method, can represent the behavior of a continuum using a particle-based approach, but it demands substantial computational resources. Therefore, parallel analysis algorithms are essential for SPH simulations. The domain decomposition algorithm, which divides the computational domain into partitions to be independently analyzed, is the most representative method among parallel analysis algorithms. In Discrete Element Method (DEM) and Molecular Dynamics (MD), the Cartesian coordinate-based domain decomposition method is popularly used because it offers advantages in quickly and conveniently accessing particle positions. However, in SPH, it is important to share particle information among partitioned domains because SPH particles are defined based on information from nearby particles within the smoothing length. Additionally, maintaining CPU load balance is crucial. In this study, a highly parallel efficient algorithm is proposed to dynamically minimize the size of orthogonal domain partitions to prevent excess CPU utilization. The efficiency of the proposed method was validated through numerical analysis models. The parallel efficiency of the proposed method is evaluated for up to 30 CPUs for fluidic models, achieving 90% parallel efficiency for up to 28 physical cores.

• Korean Journal of Radiology
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• v.22 no.2
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• pp.263-280
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• 2021

Percutaneous transthoracic needle biopsy (PTNB) is one of the essential diagnostic procedures for pulmonary lesions. Its role is increasing in the era of CT screening for lung cancer and precision medicine. The Korean Society of Thoracic Radiology developed the first evidence-based clinical guideline for PTNB in Korea by adapting pre-existing guidelines. The guideline provides 39 recommendations for the following four main domains of 12 key questions: the indications for PTNB, pre-procedural evaluation, procedural technique of PTNB and its accuracy, and management of post-biopsy complications. We hope that these recommendations can improve the diagnostic accuracy and safety of PTNB in clinical practice and promote standardization of the procedure nationwide.

• Journal of Science Education
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• v.48 no.1
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• pp.1-14
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• 2024

The Korean Science Education Standards (KSES) were developed to support the establishment of a domestic national science curriculum to respond to future social and environmental changes as an action plan to improve scientific literacy in the context of science education. In this study, we analyzed the relationship between KSES and the 2022 revised middle science curriculum focusing its learning contents and learning objectives and sought effects of the successful implementation of the curriculum. As a result, the content system of the 2022 revised middle science curriculum was highly related to the categories of knowledge in KSES. Attempts to deal with the content related to the nature of science was also confirmed through content elements in science and society domains. In the case of achievement standards, it was focused on some areas of the performance expectations in KSES, but the level of statement of the achievement standards closely matched the level of middle school students as suggested by KSES. From these results, it was possible to confirm the high relationship between the 2022 revised middle science curriculum and KSES, as well as the possibility of using KSES as an international indicator for establishing future science education plans.

• Journal of Science Education
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• v.48 no.1
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• pp.31-46
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• 2024

This study analyzes the academic achievement characteristics of Korean fourth graders on the problem solving and inquiry tasks (PSIs) introduced in TIMSS 2019. TIMSS 2019 conducted a computer-based assessment in addition to the traditional paper-based assessment. The PSIs were included only in the computer-based assessment, so 30 countries participated in the PSIs of the computer-based assessment. PSIs consist of integrating multiple content and cognitive domains, including 10 or fewer items. Most of the items are constructed in an open-ended format rather than multiple-choice. The analysis results showed that there were differences in student achievement across countries depending on the inclusion of PSIs. Korea's average achievement score decreased by 1 point. The analysis of individual items showed that students' achievement was somewhat low, and the correct answer rate for male students was generally higher than that for female students in many items. Furthermore, item-by-item analysis revealed that there were items where countries such as England and Finland had higher correct answer rates than traditional high-achieving countries, i.e. Singapore, Taiwan, and Korea. Considering the recent emphasis on integrated education, it seems necessary to review the use of PSIs in assessments in Korea as well.

• Journal of the International Relations & Interdisciplinary Education
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• v.4 no.1
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• pp.85-111
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• 2024

Since the release of the 2000 PISA results, Finland's education has consistently been regarded as a competitor or benchmark for South Korea's educational system. However, recent indicators of division, opposition, and discontent within our educational sphere suggest a considerable departure from Finland's ethos of happiness in education. Against this backdrop, this study aims to analyze the trends in Finnish education-related research appearing in Korean academic journals. Utilizing network text analysis, we examined 160 papers indexed in RISS with titles containing "Finland" and "education". Key findings are as follows. Firstly, research on Finnish education has been steadily increasing, albeit showing recent signs of decline. Secondly, the majority of research topics were micro-level, with literature review-based methodologies predominating. Thirdly, a minority of researchers accounted for one-third of the total research output. Fourthly, countries compared with Finland predominantly included neoliberal states such as Japan, the United States, the United Kingdom, Australia, and Singapore. Fifthly, research themes and subjects primarily focused on primary and secondary education, particularly in domains such as mathematics and science, influenced by PISA. Future research on Finnish education should transcend localized and fragmented areas of inquiry, undertaking comprehensive investigations into the processes and history of Finland's happiness-oriented education. Such endeavors are essential for deriving insights crucial for our learning. Particularly, consideration should be given to moving beyond literature-based methodologies, fostering international collaborative discussions facilitated online, and linking the Finnish education community with educators, parents, students, local councils, and governmental stakeholders to collectively discuss and research.