• Journal of Korean Dental Science
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• v.16 no.2
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• pp.128-148
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• 2023

Dementia is an umbrella term that describes the loss of thinking, memory, attention, logical reasoning, and other mental abilities to the extent that it interferes with the activities of daily living. More than 50 million individuals worldwide live with dementia, which is expected to increase to 131 million by 2050. Recent research has shown that poor oral health increases the risk of dementia, while oral health declines with cognitive decline. In this narrative review, the literature was based on the "hypothesis" that dementia and oral health have a close relationship, and appropriate oral health and occlusal rehabilitation treatment can improve the quality of life of patients with dementia and prevent progression. We conducted a literature search in PubMed and Google Scholar databases, using the search terms "dementia," "major neurocognitive disorder," "dentition," "occlusion," "tooth loss," "dental prosthesis," "dental implant," and "occlusal rehabilitation" in the title field over the past 30 years. A total of 131 studies that scientifically addressed dementia, oral health, and/or oral rehabilitation were included. In a meta-analysis, the random effect model demonstrated significant tooth loss increasing the dementia risk 3.64-fold (pooled odds ratio=3.64, 95% confidence interval [2.50~5.32], P-value=0.0348). Tooth loss can be an important indicator of cognitive function decline. As the number of missing teeth increases, the risk of dementia increases. Loss of teeth can lead to a decrease in the ascending information to the brain and reduced masticatory ability, cerebral blood flow, and psychological atrophy. Oral microbiome dysbiosis and migration of key bacterial species to the brain can also cause dementia. Additionally, inflammation in the oral cavity affects the inflammatory response of the brain and the complete body. Conversely, proper oral hygiene management, the placement of dental implants or prostheses to replace lost teeth, and the restoration of masticatory function can inhibit symptom progression in patients with dementia. Therefore, improving oral health can prevent dementia progression and improve the quality of life of patients.

• Journal of the Korea Society for Simulation
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• v.32 no.4
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• pp.19-26
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• 2023

The increase in the dropout rate of college students nationwide has a serious negative impact on universities and society as well as individual students. In order to proactive identify students at risk of dropout, this study built a decision tree, random forest, logistic regression, and deep learning-based dropout prediction model using academic data that can be easily obtained from each university's academic management system. Their performances were subsequently analyzed and compared. The analysis revealed that while the logistic regression-based prediction model exhibited the highest recall rate, its f-1 value and ROC-AUC (Receiver Operating Characteristic - Area Under the Curve) value were comparatively lower. On the other hand, the random forest-based prediction model demonstrated superior performance across all other metrics except recall value. In addition, in order to assess model performance over distinct prediction periods, we divided these periods into short-term (within one semester), medium-term (within two semesters), and long-term (within three semesters). The results underscored that the long-term prediction yielded the highest predictive efficacy. Through this study, each university is expected to be able to identify students who are expected to be dropped out early, reduce the dropout rate through intensive management, and further contribute to the stabilization of university finances.

• Phonetics and Speech Sciences
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• v.15 no.4
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• pp.109-118
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• 2023

Cardiac arrest is a critical medical emergency where immediate response is essential for patient survival. This is especially true for Out-of-Hospital Cardiac Arrest (OHCA), for which the actions of emergency medical services in the early stages significantly impact outcomes. However, in Korea, a challenge arises due to a shortage of dispatcher who handle a large volume of emergency calls. In such situations, the implementation of a machine learning-based OHCA detection program can assist responders and improve patient survival rates. In this study, we address this challenge by developing a machine learning-based OHCA detection program. This program analyzes transcripts of conversations between responders and callers to identify instances of cardiac arrest. The proposed model includes an automatic transcription module for these conversations, a text-based cardiac arrest detection model, and the necessary server and client components for program deployment. Importantly, The experimental results demonstrate the model's effectiveness, achieving a performance score of 79.49% based on the F1 metric and reducing the time needed for cardiac arrest detection by 15 seconds compared to dispatcher. Despite working with a limited dataset, this research highlights the potential of a cardiac arrest detection program as a valuable tool for responders, ultimately enhancing cardiac arrest survival rates.

• Composites Research
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• v.36 no.6
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• pp.441-447
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• 2023

Recently, as demand for high-strength, lightweight materials has increased, there has been great interest in joining with metals. In the case of mechanical bonding, such as bolting and riveting, chemical bonding using adhesives is attracting attention as stress concentration, cracks, and peeling occur. In this paper, surface treatment was performed to improve the adhesive strength, and the change in adhesive strength was analyzed. For the adhesive strength test were conducted with Carbon Fiber Reinforced Plastic(CFRP), CR340(Steel), and Al6061(Aluminum), and laser and plasma surface treatment were used. After plasma surface treatment, the adhesive strength improved by 7.3% and 39.2% in CFRP-CR340 and CFRP-Al6061, respectively. CR340-Al6061 was improved by 56.2% in laser surface treatment. Surface free energy(SFE) was measured by contact angle after plasma treatment, and it is thought that the adhesion strength was improved by minimizing damage through a chemical reaction mechanism. For laser surface treatment, it is thought that creates a rough bonding surface and improves adhesive strength due to the mechanical interlocking effect. Therefore, surface treatment is effect to improve adhesive strength, and based on this paper, the long-term fatigue test will be conducted to prevent fatigue failure, which is a representative cause of actual structural damage.

• Journal of the Korea Society of Computer and Information
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• v.29 no.6
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• pp.121-130
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• 2024

In this paper, we propose and design an NCS-based job matching system for individuals with disabilities. This system allows users with disabilities to access it, input basic information (personal and disability-related details), and take a simple test related to job performance. The system then provides NCS job-related information appropriate to their type and degree of disability. To effectively link various NCS-based jobs, it is essential to consider the degree of disability for each type of disability. However, most evaluation tools target specific types of disabilities or assess the vocational abilities of individuals with disabilities in a limited manner, focusing only on cognitive levels or certain physical functions. This makes it challenging to apply these tools to an NCS-based job matching system for individuals with disabilities. Therefore, in this paper, we utilize the ICF coresets for VR to assess the cognitive levels or physical functions required for performing specific jobs. Additionally, we use the NCS vocational competency evaluation tools to determine the levels of vocational competencies required for performing specific jobs. By doing so, we match NCS-based jobs according to the type and degree of disability. The proposed NCS-based job matching system relies on the user's interaction with the system, which may pose challenges for visually impaired individuals or those with intellectual and autism spectrum disabilities who have low literacy levels. Enhancing the accessibility of this system could enable individuals with disabilities to receive recommendations for NCS-based jobs that suit their vocational abilities.

• Journal of The Korean Association For Science Education
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• v.27 no.4
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• pp.354-365
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• 2007

The purpose of this study was to understand the undergraduate students' response characteristics by their cognitive conflict levels and result predictions when they were confronted with the learning tasks of action & reaction and electric circuits. The 147 engineering college students who were enrolled at the introductory physics classes were selected as the subjects for this study. The students were grouped by cognitive levels and result predictions. First, in action and reaction task, the trend of suspecting experimental results and finding the reasons was dominant; however, in electric circuits, the trend of accepting the results was dominant. Second, the reasons for the responses on the subcategories of cognitive conflict were different by the level of cognitive conflict. The responses were influenced by students' preexisting knowledge, former experiences, learning habits, learning motivation, and epistemological beliefs, etc. The high conflict group recognized what they do not consider and was positive to reappraise their preconceptions, while the low conflict group showed the tendency of accepting the situation without doubt and low interest on learning physics. In conclusion, students responses showed differences in cognitive conflict levels, result predictions and presented conflict tasks. The research results, especially the response characteristics, suggest that more research on effective cognitive conflict strategies appropriate for different tasks and students' conflicts are necessary for effective physics teaching.

• Journal of the Korean Geotechnical Society
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• v.40 no.1
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• pp.5-14
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• 2024

PHC piles demonstrate superior resistance to compression and bending moments, and their factory-based production enhances quality assurance and management processes. Despite these advantages that have resulted in widespread use in civil engineering and construction projects, the design process frequently relies on empirical formulas or N-values to estimate the soil-pile friction, which is crucial for bearing capacity, and this reliance underscores a significant lack of experimental validation. In addition, environmental factors, e.g., the pH levels in groundwater and the effects of seawater, are commonly not considered. Thus, this study investigates the influence of vibrating machine foundations on PHC pile models in consideration of the effects of varying pH conditions. Concrete model piles were subjected to a one-month conditioning period in different pH environments (acidic, neutral, and alkaline) and under the influence of seawater. Subsequent repeated direct shear tests were performed on the pile-soil interface, and the disturbed state concept was employed to derive parameters that effectively quantify the dynamic behavior of this interface. The results revealed a descending order of shear stress in neutral, acidic, and alkaline conditions, with the pH-influenced samples exhibiting a more pronounced reduction in shear stress than those affected by seawater.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.18 no.6
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• pp.159-172
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• 2023

This study aims to empirically investigate the relative effects of business-to-business (vs. business-to-consumer) business model innovation (BMI) on innovation performance. The research examines the impact of three key components of BMI: 1. value creation, 2. value proposition, and 3. value capture, on innovation performance. The 2022 Entrepreneurship Survey data by the Korean Entrepreneurship Foundation was used to analyze 2,879 companies. An exploratory data analysis (EDA) including various categories such as industry, firm, CEO, and technology chracteristics was conducted to show the latest startup status in Korea. The results show that value creation of B2B (vs. B2C) firms has a more positive and significant impact on innovation performance. Whereas, value proposition of B2C (vs. B2B) firms was found to have a more positive and significant effect on innovation performance. Interestingly, value capture did not show any effects for either type of firms. Additionally, the study employed seemingly unrelated regression (SUR) analysis for robustness checks. These findings provide important insights about the relative effects of B2B-BMI (vs. B2C-BMI).

• Journal of the Korean Applied Science and Technology
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• v.40 no.4
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• pp.856-867
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• 2023

Due to the increase in fine dust caused by environmental pollution, oxidative damage and aging of the skin are accelerated. In this study, the antioxidant, hyaluronic acid, filaggrin, MMP-1, and ROS level of selected herbal extracts were evaluated to confirm the protective efficacy of keratinocytes treated PM10. As a result, the antioxidant capacity of 1,1-diphenyl-2-picrylhydrazyl(DPPH), 2,2'-azinobis (3-ethylbenzothiazoline-6-sulfonic acid(ABTS), and FRAP assay increased in a concentration-dependent manner. Keratinocytes the group treated with 300 ㎍/ml of PM10, hyaluronic acid and filaggrin decreased by more than 50%, and increased in the group treated with extracts of Alpinia officinarum, Ulmus macrocarpa, and Ulmus macrocarpa but decreased when the extract was treated, which is evaluated as inhibiting the degradation of collagen and elastin. In addition, in the case of ROS measurement using zebrafish embryos, it was confirmed that the extract was reduced when the extract was treated 25 ㎍/ml, the intensity of fluorescence similar to the negative control was shown, confirming that the production of ROS was significantly reduced. Through this study, the selected oriental medicinal materials, Alpinia officinarum, Ulmus macrocarpa, and Ulmus macrocarpa, protect the skin from fine dust. It is thought that it can be used as an anti-aging product for skin improvement as a material that can be improved or improved.

• Information Systems Review
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• v.20 no.4
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• pp.59-78
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• 2018

With the advent of the various device types and marketing communication, customer's search and purchase behavior have become more complex and segmented. However, extant research on multichannel marketing effects of the purchase funnel has not reflected the specific features of device User Interface (UI) and User Experience (UX). In this study, we analyzed the marketing channel effects of multi-device shoppers using a unique click stream dataset from global online retailers. We examined device types that activate online shopping and compared the differences between marketing channels that promote visits. In addition, we estimated the direct and indirect effects on visits and purchase revenue through customer's accumulated experience and channel conversions. The findings indicate that the same customer selects a different marketing channel according to the device selection. These results can help retailers gain a better understanding of customers' decision-making process in multi-marketing channel environment and devise the optimal strategy taking into account various device types. Our empirical analyses yield business implications based on the significant results from global big data analytics and contribute academically meaningful theoretical framework using an economic model. We also provide strategic insights attributed to the practical value of an online marketing manager.