Journal of the Korea Society of Computer and Information
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v.28
no.11
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pp.53-63
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2023
This study developed a cognitive impairment predictive model as one of the screening tests for preventing dementia in the elderly by using Automated Machine Learning(AutoML). We used 'Wearable lifelog data for high-risk dementia patients' of National Information Society Agency, then conducted using PyCaret 3.0.0 in the Google Colaboratory environment. This study analysis steps are as follows; first, selecting five models demonstrating excellent classification performance for the model development and lifelog data analysis. Next, using ensemble learning to integrate these models and assess their performance. It was found that Voting Classifier, Gradient Boosting Classifier, Extreme Gradient Boosting, Light Gradient Boosting Machine, Extra Trees Classifier, and Random Forest Classifier model showed high predictive performance in that order. This study findings, furthermore, emphasized on the the crucial importance of 'Average respiration per minute during sleep' and 'Average heart rate per minute during sleep' as the most critical feature variables for accurate predictions. Finally, these study results suggest that consideration of the possibility of using machine learning and lifelog as a means to more effectively manage and prevent cognitive impairment in the elderly.
Journal of the Korea Society of Computer and Information
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v.28
no.11
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pp.73-80
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2023
In this paper, a technology to protect important information from access in order to revitalize the cloud service market. A technology is proposed to solve the risk of leakage of important confidential and personal information stored in cloud systems, which is one of the various obstacles to the cloud service market. To protect important information, access control rights to cloud resources are granted to cloud service providers and general users. The system administrator has superuser authority to maintain and manage the system. Client computing services are managed by an external cloud service provider, and information is also stored in an external system. To protect important in-house information within the company, all users, it was designed to provide access authority with users including cloud service providers, only after they are authenticated. It is expected that the confidentiality of cloud computing resources and service reliability achieved through the proposed access control technology will contribute to revitalizing the cloud service market.
Journal of the Korean Society of Clothing and Textiles
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v.47
no.5
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pp.779-803
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2023
The growth of digital news media and the stock price index has resulted in economic fluctuations in the fashion industry. This study examines the impact of fashion industry news and macroeconomic changes on the Textile & Wearing Apparel KOSPI over the past five years. An auto-regressive integrated moving average exogenous time series model was conducted using the fashion industry stock market index, the news topic index, and macro-economic indicators. The results indicated the topics of "Cosmetic business expansion" and "Digital innovation" impacted the Textile & Wearing Apparel KOSPI after one week, and the topics of "Pop-up store," "Entry into the Chinese fashion market," and "Fashion week and trade show" affected it after two weeks. Moreover, the topics of "Cosmetic business expansion" and "Entry into the Chinese fashion market" were statistically significant in the macroeconomic environment. Regarding the effect relation of Textile & Wearing Apparel KOSPI, "Cosmetic business expansion," "Entry into the Chinese fashion market," and consumer price fluctuation showed negative effects, while the private consumption change rate, producer price fluctuation, and unemployment change rate had positive effects. This study analyzes the impact of media framing on fashion industry business cycles and provides practical insights into managing stock market risk for fashion companies.
International conference on construction engineering and project management
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2011.02a
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pp.413-419
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2011
Corporate governance is a system articulating the division of responsibilities among different company members, and defining the running rules and procedures for making decisions on corporate affairs. The separation of ownership and management in modern enterprises brings agency problems to the company shareholders, and it is wildly believed that good practice on corporate governance is essential to prevent managers from taking actions by which profiteering their own benefits but compromising the interests of shareholders. This research investigates the level of companies' compliance with the corporate governance codes to find whether significant differences in corporate governance practice exist between the listed construction companies and the national leading companies in Taiwan. Further exploration focuses on the correlation between the compliance level and the industrial features. The investigation finds that: (1)Construction companies display lower levels of corporate governance compliance; (2)Construction companies display lower levels of structural board independence and respect for stakeholders; (3)Compliance levels of construction companies are correlated with the number of employees and the ownership concentration; (4)Compliance levels of the whole sample companies are correlated with the factors representing firm size, such as turnover, capital and number of employees, but are independent of profitability as well as stock price volatility. The above empirical evidence characterizes the features of corporate governance in Taiwan listed construction companies, including: (1)Large companies lurking high risk of agency problems have more willingness to conduct corporate governance and meanwhile can afford higher costs for the conduction, so that their compliance level would be higher than smaller companies; (2)Construction companies in Taiwan have higher ownership concentration, on account of the industrial tradition of family business, and therefore pay less attention to the compliance with structural board independence and respect for stakeholders. However, the conclusions indicate that further studies are essential to clarify whether the above disparities would lead to a negative cycle of corporate governance practice in construction industry. The benefits of corporate governance should unfold more evidently to convince construction companies for improving their investment environment and stimulating their healthy growth.
Journal of the Korean Society of Industry Convergence
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v.27
no.3
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pp.601-607
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2024
The discharge of oily wastewater into water bodies and soil poses a serious hazard to the environment and public health. Various conventional techniques have been employed to treat oil-water mixtures and emulsions; Unfortunately, these approaches are frequently expensive, time-consuming, and unsatisfactory outcomes. Porous materials and adsorbents are commonly used for purification, but their use is limited by low separation efficiencies and the risk of secondary contamination. Recent advancements in nanotechnology have driven the development of innovative materials and technologies for oil-contaminated wastewater treatment. Nanomaterials can offer enhanced oil-water separation properties due to their high surface area and tunable surface chemistry. The fabrication of nanofiber membranes with precise pore sizes and surface properties can further improve separation efficiency. Notably, novel technologies have emerged utilizing nanomaterials with special surface wetting properties, such as superhydrophobicity, to selectively separate oil from oil-water mixtures or emulsions. These special wetting surfaces are promising for high-efficiency oil separation in emulsions and allow the use of materials with relatively large pores, enhancing throughput and separation efficiency. In this study, we introduce a facile and scalable method for fabrication of superhydrophobic-superoleophilic felt fabrics for oil/water mixture and emulsion separation. AlN nanopowders are hydrolyzed to create the desired microstructures, which firmly adhere to the fabric surface without the need for a binder resin, enabling specialized wetting properties. This approach is applicable regardless of the material's size and shape, enabling efficient separation of oil and water from oil-water mixtures and emulsions. The oil-water separation materials proposed in this study exhibit low cost, high scalability, and efficiency, demonstrating their potential for broad industrial applications.
The Journal of Korea Institute of Information, Electronics, and Communication Technology
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v.17
no.1
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pp.67-75
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2024
Crosswalks play an important role for the safe movement of pedestrians in a complex urban environment. However, for the visually impaired, crosswalks can be a big risk factor. Although assistive tools such as braille blocks and acoustic traffic lights exist for safe walking, poor management can sometimes act as a hindrance to safety. This paper proposes a method to improve accuracy in a deep learning-based real-time crosswalk detection model that can be used in applications for pedestrian assistance for the disabled at the beginning. The image was binarized by utilizing the characteristic that the white line of the crosswalk image contrasts with the road surface, and through this, the crosswalk could be better recognized and the location of the crosswalk could be more accurately identified by using two models that learned the whole and the middle part of the crosswalk, respectively. In addition, it was intended to increase accuracy by creating a boundary box that recognizes crosswalks in two stages: whole and part. Through this method, additional frames that the detection model did not detect in RGB image learning from the crosswalk image could be detected.
Importance: The emergence and rapid increase in the incidence of multidrug-resistant (MDR) bacteria in pig farms has become a serious concern and reduced the choice of effective antibiotics. Objective: This study analyzed the phylogenetics and diversity of antibiotic resistance genes (ARGs) and molecularly identified the source of ARGs in antibiotic-resistant Escherichia coli isolated from pig farms in Banten Province, Indonesia. Methods: Forty-four antibiotic-resistant E. coli isolates from fecal samples from 44 pig farms in Banten Province, Indonesia, were used as samples. The samples were categorized into 14 clusters. Sequencing was performed using the Oxford Nanopore Technologies MinION platform, with barcoding before sequencing with Nanopore Rapid sequencing gDNA-barcoding (SQK-RBK110.96) according to manufacturing procedures. ARG detection was conducted using ResFinder, and the plasmid replicon was determined using PlasmidFinder. Results: Three phylogenetic leaves of E. coli were identified in the pig farming cluster in Banten Province. The E. coli isolates exhibited potential resistance to nine classes of antibiotics. Fifty-one ARGs were identified across all isolates, with each cluster carrying a minimum of 10 ARGs. The ant(3'')-Ia and qnrS1 genes were present in all isolates. ARGs in the E. coli pig farming cluster originated mainly from plasmids, accounting for an average of 89.4%. Conclusions and Relevance: The elevated potential for MDR events, coupled with the dominance of ARGs originating from plasmids, increases the risk of ARG spread among bacterial populations in animals, humans, and the environment.
The United States (US) National Science Foundation's (NSF's) National Ecological Observatory Network (NEON) is a continental-scale observation facility, constructed and operated by Battelle, that collects long-term ecological data to better understand and forecast how US ecosystems are changing. All data and samples are collected using standardized methods at 81 field sites across the US and are freely and openly available through the NEON data portal, application programming interface (API), and the NEON Biorepository. NSF led a decade-long design process with the research community, including numerous workshops to inform the key features of NEON, culminating in a formal final design review with an expert panel in 2009. The NEON construction phase began in 2012 and was completed in May 2019, when the observatory began the full operations phase. Full operations are defined as all 81 NEON sites completely built and fully operational, with data being collected using instrumented and observational methods. The intent of the NSF is for NEON operations to continue over a 30-year period. Each challenge encountered, problem solved, and risk realized on NEON offers up lessons learned for constructing and operating distributed ecological data collection infrastructure and data networks. NEON's construction phase included offices, labs, towers, aquatic instrumentation, terrestrial sampling plots, permits, development and testing of the instrumentation and associated cyberinfrastructure, and the development of community-supported collection plans. Although colocation of some sites with existing research sites and use of mostly "off the shelf" instrumentation was part of the design, successful completion of the construction phase required the development of new technologies and software for collecting and processing the hundreds of samples and 5.6 billion data records a day produced across NEON. Continued operation of NEON involves reexamining the decisions made in the past and using the input of the scientific community to evolve, upgrade, and improve data collection and resiliency at the field sites. Successes to date include improvements in flexibility and resilience for aquatic infrastructure designs, improved engagement with the scientific community that uses NEON data, and enhanced methods to deal with obsolescence of the instrumentation and infrastructure across the observatory.
Purpose This paper examines the role of local market-based communities in driving regional revitalization, using detailed analysis of online networks. We aim to dissect a local community's communication network, highlighting members with high engagement levels and exploring their characteristics. Our goal is to identify the conditions that allow local community networks to grow independently and to demonstrate how the activation of these networks contributes to regional revitalization. Design/methodology/approach We employ a mixed-methods approach, combining social network analysis with statistical techniques to investigate the structure of online communication networks. Specifically, we use ANOVA to determine the statistical significance of our findings, ensuring their reliability. To complement our quantitative data, we include qualitative insights from interviews, adding depth and context to our analysis. Findings Our results show that individuals with high centrality in the online network are crucial for maintaining active local communities. We find that leveraging local resources to create a supportive and adaptable environment is essential for the communities' sustainability and expansion. Importantly, our research draws a direct connection between the vitality of local community networks and the broader process of regional revitalization. We argue that energizing local communities is an effective way to address the risk of regional decline. By integrating quantitative analysis with qualitative feedback, this study contributes to the understanding of local market-based communities as key drivers of regional development. It emphasizes the importance of building vibrant, resourceful community networks to revitalize areas experiencing socio-economic challenges.
Journal of the korean academy of Pediatric Dentistry
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v.51
no.1
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pp.80-87
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2024
Silver diamine fluoride, which can arrest dental caries, is alkaline and may cause mild soft tissue irritation. Water-based silver fluoride has a neutral pH, which is closer to the physiological range, and is biocompatible for use in the oral environment. This study aimed to evaluate the effect of water-based silver fluoride on remineralizing early enamel lesions by comparing it with other fluoride agents through microhardness and quantitative light-induced fluorescence measurements. An in vitro study with intact bovine incisors was performed. Artificial enamel lesions were induced and subjected to microhardness and quantitative light-induced fluorescence testing. Specimens were randomly divided into 4 groups for treatment. The specimens in group I were treated with water-based silver fluoride and potassium iodide, group II with silver diamine fluoride and potassium iodide, group III with sodium fluoride varnish, and group IV with distilled water. After 8 days of pH cycling, the specimens were subjected to microhardness and quantitative light-induced fluorescence testing. Water-based silver fluoride and silver diamine fluoride showed the greatest increases in microhardness and quantitative light-induced fluorescence, with no significant differences between the two. Sodium fluoride varnish also exhibited a significant increase in microhardness and quantitative light-induced fluorescence, but the differences were smaller than those for water-based silver fluoride and silver diamine fluoride. Water-based silver fluoride is considered useful in a clinical setting for remineralizing enamel lesions, with the advantages of no risk of tissue burn and improved taste and smell.
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