• Journal of Ginseng Research
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• v.48 no.2
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• pp.149-162
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• 2024

Ginseng, the roots of Panax species, is an important medicinal herb used as a tonic. As ginsenosides are key bioactive components of ginseng, holistic chemical profiling of them has provided many insights into understanding ginseng. Mass spectrometry has been a major methodology for profiling, which has been applied to realize numerous goals in ginseng research, such as the discrimination of different species, geographical origins, and ages, and the monitoring of processing and biotransformation. This review summarizes the various applications of ginsenoside profiling in ginseng research over the last three decades that have contributed to expanding our understanding of ginseng. However, we also note that most of the studies overlooked a crucial factor that influences the levels of ginsenosides: genetic variation. To highlight the effects of genetic variation on the chemical contents, we present our results of untargeted and targeted ginsenoside profiling of different genotypes cultivated under identical conditions, in addition to data regarding genome-level genetic diversity. Additionally, we analyze the other limitations of previous studies, such as imperfect variable control, deficient metadata, and lack of additional effort to validate causation. We conclude that the values of ginsenoside profiling studies can be enhanced by overcoming such limitations, as well as by integrating with other -omics techniques.

• Journal of the Korean Geotechnical Society
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• v.40 no.1
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• pp.47-54
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• 2024

In current slope stability analysis techniques, slope stability is evaluated based on the saturated-soil theory. However, soil-water characteristics change frequently depending on the climate. Therefore, because the saturated soil theory has limitations, the application of the unsaturated soil theory is necessary for slope stability. It is also important to evaluate the engineering properties of unsaturated soil because the capillary absorption capacity is reduced due to heavy rain, thereby causing a reduction in slope stability. In this study, soil-water characteristic tests were performed using four samples with different fine contents (0%, 10%, 20%, and 30%) using granite-weathered soil in domestic production areas. In particular, to consider the previously conducted drying process as well as the evaluation of stability due to heavy rain on the actual slope, a wetting process was conducted, in which the water content was increased. In addition, the van Genuchten (1980) model, which is the most consistent theoretical equation for the experiment, was used with various theoretical equations, and the parameters were analyzed according to the fine content of the granite-weathered soil for the drying and wetting processes.

• The Journal of the Acoustical Society of Korea
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• v.25 no.8
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• pp.383-388
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• 2006

This Paper presents a novel approach to single channel microphone speech enhancement in noisy environments. Widely used noise reduction techniques based on the spectral subtraction are generally expressed as a spectral gam depending on the signal-to-noise ratio (SNR). The well-known decision-directed(DD) estimator of Ephraim and Malah efficiently reduces musical noise under the background noise conditions, but generates the delay of the a prioiri SNR because the DD weights the speech spectrum component of the Previous frame in the speech signal. Therefore, the noise suppression gain which is affected by the delay of the a priori SNR, which is estimated by the DD matches the previous frame rather than the current one, so after noise suppression. this degrades the noise reduction performance during speech transient periods. We propose a computationally simple but effective speech enhancement technique based on the sigmoid type function for the weight Parameter of the DD. The proposed approach solves the delay problem about the main parameter, the a priori SNR of the DD while maintaining the benefits of the DD. Performances of the proposed enhancement algorithm are evaluated by ITU-T p.862 Perceptual Evaluation of Speech duality (PESQ). the Mean Opinion Score (MOS) and the speech spectrogram under various noise environments and yields better results compared with the fixed weight parameter of the DD.

• Korean Journal of Construction Engineering and Management
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• v.25 no.1
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• pp.32-41
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• 2024

In the construction industry, not only safety accidents, but also various complex risks such as construction delays, cost increases, and environmental pollution occur, and management technologies are needed to solve them. Among them, process risk management, which directly affects the project, lacks related information compared to its importance. This study tried to develop a MATM tunnel process risk classification system to solve the difficulty of risk information retrieval due to the use of different classification systems for each project. Risk collection used existing literature review and experience mining techniques, and DB construction utilized the concept of natural language processing. For the structure of the classification system, the existing WBS structure was adopted in consideration of compatibility of data, and an RBS linked to the work species of the WBS was established. As a result of the research, a risk classification system was completed that easily identifies risks by work type and intuitively reveals risk characteristics and risk factors linked to risks. As a result of verifying the usability of the established classification system, it was found that the classification system was effective as risks and risk factors for each work type were easily identified by user input of keywords. Through this study, it is expected to contribute to preventing an increase in cost and construction period by identifying risks according to work types in advance when planning and designing NATM tunnels and establishing countermeasures suitable for those factors.

• Korean Journal of Environment and Ecology
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• v.38 no.1
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• pp.67-78
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• 2024

The term ecosystem services refers to natural ecosystems' benefits to humans. Various models have been developed and applied to quantify ecosystem services. Habitat quality assessment is a widely used leading InVEST ecosystem service model. In Korea, habitat quality assessment is conducted for national parks. For habitat quality assessment, the initial value of habitat quality must be used to assess the sensitivity to threats, which varies depending on the country and application field. Therefore, an expert survey (AHP) was conducted based on previous habitat quality assessments in national parks to adjust the sensitivity, the initial value for the habit quality assessment. As a result of the AHP, 18 items were adjusted, including 10 items, such as natural grassland and unarranged fields, upward and 8 items, such as rivers and ponds, downward. Based on the adjusted sensitivity results, the habitat quality of Bukhansan National Park and Gyeryongsan National Park (urban type), Gyeongju National Park (historic type), Hallyeohaesang National Park (ocean type), and Jirisan National Park and Seoraksan National Park (mountain type) were adjusted. The results of the analysis showed that the habitat quality of urban dry areas and water bodies distributed in the national parks was reflected in the habitat quality assessment. In the future, it will be possible to evaluate the habitat quality of natural parks using this standard.

• Information Systems Review
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• v.22 no.4
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• pp.21-39
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• 2020

Recently, deep learning has shown high performance in various applications such as pattern analysis and image classification. Especially known as a difficult task in the field of machine learning research, stock market forecasting is an area where the effectiveness of deep learning techniques is being verified by many researchers. This study proposed a deep learning Convolutional Neural Network (CNN) model to predict the direction of stock prices. We then used the feature selection method to improve the performance of the model. We compared the performance of machine learning classifiers against CNN. The classifiers used in this study are as follows: Logistic Regression, Decision Tree, Neural Network, Support Vector Machine, Adaboost, Bagging, and Random Forest. The results of this study confirmed that the CNN showed higher performancecompared with other classifiers in the case of feature selection. The results show that the CNN model effectively predicted the stock price direction by analyzing the embedded values of the financial data

• Journal of Oriental Neuropsychiatry
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• v.35 no.2
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• pp.205-216
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• 2024

Objectives: To evaluate the effectiveness of Mindfulness & Loving Beingness (M&L) psychotherapy combined with traditional Korean medicine in treating acute sleep disorders in patients hospitalized following traffic accidents. Methods: We applied traditional Korean medicine treatments in conjunction with various mindfulness meditation techniques from M&L therapy, including Resource Mindfulness and Nourishment Brief Therapy. This study was conducted on three patients who reported acute sleep disorder symptoms on the first day of hospitalization following a traffic accident. The effectiveness of these interventions was assessed using the PTSD Checklist for DSM-5 (PCL-5-K), Insomnia Severity Index (ISI), EuroQol 5-Dimension (EQ-5D), Numerical Rating Scale (NRS), and Patient Global Impression of Change (PGIC). Results: ISI and PCL-5-K scores showed significant improvements after treatment, indicating reduced sleep disturbances and stress symptoms. Additionally, EQ-5D and PGIC scores were enhanced, reflecting an overall improvement in quality of life. Conclusions: This study suggests that integrating M&L therapy with traditional Korean medicine could significantly improve symptoms in patients with acute sleep disorders following traffic accidents.

• Journal of Navigation and Port Research
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• v.48 no.3
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• pp.155-163
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• 2024

As the demand for reducing carbon emissions increases, efforts to reduce the usage of fossil fuels and research on renewable energy are also increasing. Among the various renewable energy harvesting techniques, the floating offshore wind turbine has several advantages. Compared to other technologies, it has fewer installation limitations due to interference with human activity. Additionally, a large wind turbine farm can be constructed in the open ocean. Therefore, it is important to conduct motion analysis of floating offshore wind turbines in waves during the initial stage of conceptual design. In this study, a frequency motion analysis was conducted on a semi-submersible type floating offshore wind turbine. The analysis focused on the effects of varying trim on the motion characteristics. Specifically, motion response analysis was performed on heave, roll, and pitch. Natural period analysis confirmed that changing the trim angle did not significantly affect the heave and pitch motions, but it did have a regular impact on the roll motion.

• Korean Journal of Clinical Laboratory Science
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• v.55 no.4
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• pp.244-252
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• 2023

The timeliness and accuracy of test results are crucial factors for clinicians to decide and promptly administer effective and targeted antimicrobial therapy, especially in life-threatening infections or when vital organs and functions, such as sight, are at risk. Further research is needed to refine and optimize matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS)-based assays to obtain accurate and reliable results in the shortest time possible. MALDI-TOF MS-based bacterial identification focuses primarily on techniques for isolating and purifying pathogens from clinical samples, the expansion of spectral libraries, and the upgrading of software. As technology advances, many MALDI-based microbial identification databases and systems have been licensed and put into clinical use. Nevertheless, it is still necessary to develop MALDI-TOF MS-based antimicrobial-resistance analysis for comprehensive clinical microbiology characterization. The important applications of MALDI-TOF MS in clinical research include specific application categories, common analytes, main methods, limitations, and solutions. In order to utilize clinical microbiology laboratories, it is essential to secure expertise through education and training of clinical laboratory scientists, and database construction and experience must be maximized. In the future, MALDI-TOF mass spectrometry is expected to be applied in various fields through the use of more powerful databases.

• Journal of the Korea Institute of Building Construction
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• v.24 no.1
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• pp.157-168
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• 2024

The frequent occurrence of structural failures at building construction sites in Korea has underscored the critical role of rigorous oversight in the inspection and management of construction projects. As mandated by prevailing regulations and standards, onsite supervision by designated supervisors encompasses thorough documentation of construction quality, material standards, and the history of any reconstructions, among other factors. These reports, predominantly consisting of unstructured data, constitute approximately 80% of the data amassed at construction sites and serve as a comprehensive repository of quality-related information. This research introduces the SL-QPA model, which employs text mining techniques to preprocess supervision reports and establish a sentiment dictionary, thereby enabling the quantification of quality performance. The study's findings, demonstrating a statistically significant Pearson correlation between the quality performance scores derived from the SL-QPA model and various legally defined indicators, were substantiated through a one-way analysis of variance of the correlation coefficients. The SL-QPA model, as developed in this study, offers a supplementary approach to evaluating the quality performance of building construction projects. It holds the promise of enhancing quality inspection and management practices by harnessing the wealth of unstructured data generated throughout the lifecycle of construction projects.