• Journal of Korean Society for Geospatial Information Science
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• v.13 no.3 s.33
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• pp.41-52
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• 2005

The high density of population and building; can cause catastrophe in urban areas when natural or artificial disasters break out. The aim of this paper is to assess comprehensive disasters risk of urban areas by Geospatial Information System. For this purpose, we classified disasters risk of urban areas into low categories: flood, fire, building-collapse, and shelter, and then determined factors for hazard risk assessment respectively. The results of hazard assessment can be applied to minimize the demage of disasters in establishing the urban management planning. For more systematic and professional approach the further research is need to consider more disaster assessment factors and join with related experts.

• Korean Institute of Interior Design Journal
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• v.19 no.3
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• pp.22-29
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• 2010

Recent days, transition to ecological thought is being accelerating by environmental impact with a sustainable development. This symptom is no exception in architecture area. So is vernacular design affecting on modern architecture in many ways in terms of economical aspect and eco-friendly environment as well. Natural energy like solar power, environment, and terrestrial heat that applied in vernacular architecture is also widely accepted in name of 'sustainable energy' of which a design applied with ventilation and airing of natural wind is very useful & pragmatic in terms of economical reason. Accordingly, this study examined a relation between vernacular architecture and natural wind and compared it with traditional type and its feature of ventilation & airing. Ventilation & airing applied in the past can be divided into three categories: methods by convection, natural element, and architectural type. All these methods gave some pleasant felling indoors when there were no artificial energies. Even in modern age, such a ventilation & airing is being used with traditional type in different variety of materials, and it will be developed with modern technology without any extra cost in terms of sustainable expansion, and opened for further researches.

• Health Policy and Management
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• v.28 no.3
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• pp.272-279
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• 2018

Since the introduction of new health technology assessment in 2007, benefit coverage process of health insurance related to new health technology has become an upgraded system through the evidence-based decisions. As a result of enforcing this system for 10 years, however, there have been several rising concerns. It needs to support the insufficient evidence of medical technologies, introduce reassessment system for post management of market entry technologies, and improve evaluation methods and process. In addition, there is the possibility of emerging an unheard-of medical technology, fused various categories like artificial intelligence, robot, information technology, physics and life science in the fourth industrial revolution. Now, new updated system introduced to improve new technology assessment, such as 'limited health technology assessment system,' 'system for postponement of new health technology assessment,' 'one-stop service system,' and 'integrated operation of approval for medical devices and new health technology assessment.' Therefore it needs to prepare the improvement plan for new health technology assessment to be established more advanced system, and we have to resolve concerns by communication with various healthcare experts and patients now and for ever.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.17 no.2
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• pp.149-158
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• 2010

Purpose: This study was done to gain understanding of what career and related experience mean to individuals undergoing hemodialysis. Methods: Ten male patients receiving hemodialysis participated in the study. Data collection took place between November 18, 2008 and February 10, 2010, via unstructured interviews. Data collection and analysis were conducted simultaneously, and Colaizzi's phenomenological method (1978) was used for the analysis. Results: The significance the participants found in their "dual" life as worker and dialysis patients was classified into five categories: 'Recognition of self-existence value', 'My health comes before my work', 'Being afraid of stigma', 'Limitation of restricted work', and 'Difficulty with time management.' Conclusion: It was found that the dialysis patients showed ambivalent feelings towards their careers, hoping they will be able to continue to work yet fearing that the continued work might break balance the between their livelihood and healing. Therefore, it is recommended that hours for hemodialysis be more flexible to ensure that patients can keep their jobs and better manage their time while undergoing treatment.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.64 no.2
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• pp.74-78
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• 2015

With the improvement of living standards and economic development, electricity consumption continues to grow. The electricity is a special energy which is hard to store, so its supply must be consistent with the demand. The objective of electricity demand forecasting is to make best use of electricity energy and provide balance between supply and demand. Hence, it is very important work to forecast electricity demand with higher precision. So, various forecasting methods have been developed. They can be divided into five broad categories such as time series models, regression based model, artificial intelligence techniques and fuzzy logic method without considering special-day effects. Electricity demand patterns on holidays can be often idiosyncratic and cause significant forecasting errors. Such effects are known as special-day effects and are recognized as an important issue in determining electricity demand data. In this research, we developed the power demand forecasting method using ELM(Extreme Learning Machine) for special day, particularly, lunar new year and Chuseok holiday.

• Proceedings of the Korean Vacuum Society Conference
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• 2013.08a
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• pp.93-93
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• 2013

To make the rationale design of interface between cell and artificial surface, many studies have been controlled influencing cue which can typically be divided into two central categories: chemical cues based on modification surface chemical properties containing attractive/repulsive molecules, and physical cues that may include applied tension/stress, electrical polarization, magnetic field, and topography. Recently, researches have been focused on physical cue, especially topography. The surface topography may influence cellular responses for example, cell adhesion, cell morphology and gene expression. However, there were few systematic studies about these nanotopographical effects on neuronal developments in a feature size-dependent manner. Herein, we report a nanoscale-resolved study of nanotopographical effects on cellular adhesion and growth. In this study, we use substrates with packed glass beads by rubbing method for generating highly periodic nanotopographies with various sizes. We found that acceleration of neuritogenesis appeared only on the beads larger than 200 nm in diameter, and observed that filopodial thickness was comparable with this scale. This study is expected to be essential to elucidate the nanotopographical effect on cellular adhesion and growth.

• Journal of Information Processing Systems
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• v.17 no.6
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• pp.1057-1070
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• 2021

Case-related news filtering is crucial in legal text mining and divides news into case-related and case-unrelated categories. Because case-related news originates from various fields and has different writing styles, it is difficult to establish complete filtering rules or keywords for data collection. In addition, the labeled corpus for case-related news is sparse; therefore, to train a high-performance classification model, it is necessary to annotate the corpus. To address this challenge, we propose topic-enhanced positive-unlabeled learning, which selects positive and negative samples guided by topics. Specifically, a topic model based on a variational autoencoder (VAE) is trained to extract topics from unlabeled samples. By using these topics in the iterative process of positive-unlabeled (PU) learning, the accuracy of identifying case-related news can be improved. From the experimental results, it can be observed that the F1 value of our method on the test set is 1.8% higher than that of the PU learning baseline model. In addition, our method is more robust with low initial samples and high iterations, and compared with advanced PU learning baselines such as nnPU and I-PU, we obtain a 1.1% higher F1 value, which indicates that our method can effectively identify case-related news.

• International conference on construction engineering and project management
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• 2022.06a
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• pp.245-252
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• 2022

Risk identification for bridge projects is a knowledge-based and labor-intensive task involving several procedures and stakeholders. Presently, risk information of bridge projects is unstructured and stored in different sources and formats, hindering knowledge sharing, reuse, and automation of the risk identification process. Consequently, there is a need to develop structured and formalized risk information for bridge projects to aid effective risk identification and automation of the risk management processes to ensure project success. This study proposes a semantic risk breakdown structure (SRBS) to support risk identification for bridge projects. SRBS is a searchable hierarchical risk breakdown structure (RBS) developed with python programming language based on a semantic modeling approach. The proposed SRBS for risk identification of bridge projects consists of a 4-level tree structure with 11 categories of risks and 116 potential risks associated with bridge projects. The contributions of this paper are threefold. Firstly, this study fills the gap in knowledge by presenting a formalized risk breakdown structure that could enhance the risk identification of bridge projects. Secondly, the proposed SRBS can assist in the creation of a risk database to support the automation of the risk identification process for bridge projects to reduce manual efforts. Lastly, the proposed SRBS can be used as a risk ontology that could aid the development of an artificial intelligence-based integrated risk management system for construction projects.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.147-149
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• 2021

Recently, the rapid growth of the media market and the expectations of users have been increasing. In this research, tags are extracted through media-derived audio and classified into specific categories using artificial intelligence. This category is a type of emotion including joy, anger, sadness, love, hatred, desire, etc. We use JupyterNotebook to conduct the corresponding study, analyze voice data using the LiBROSA library within JupyterNotebook, and use Neural Network using keras and layer models.

• Journal of the Korea Society of Computer and Information
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• v.28 no.7
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• pp.39-46
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• 2023

The purpose of this study is to design and develop the test standard to measure AI literacy abilities. First, we selected key areas of AI literacy through the related studies and expert FGI and designed detailed standard. The area of the test standard is divided into three categories: AI concept, practice, and impact. In order to confirm the validity of the test standard, we conducted twice expert validity tests and then modified and supplemented the test index. To confirm the validity of the test standard, we conducted an expert validity test twice and then modified and supplemented the test standard. The final AI literacy test standard consisted of a total of 30 questions. The AI literacy test standard developed in this study can be an important tool for developing self-checklists or AI competency test questions for measuring AI literacy ability.