• 한국정보처리학회:학술대회논문집
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• 한국정보처리학회 2010년도 추계학술발표대회
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• pp.1050-1052
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• 2010

Locator and Identifier Split is considered as the solution to the scalability problem Internet is facing today. The separation approach of Locator and Identifier requires a third party called mapping system. The mapping system enables the inter-domain routing between two different edge networks. The design of this third party has generated many proposals, among them one approach use Border Gateway Protocol (BGP) for effective mapping information updates distribution. In this paper, we take advantage of this approach by considering the scalability in term of mapping information storage. Our goal is to provide scalability in term of mapping information storage as well as effective mapping information updates distribution.

• Computers and Concrete
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• 제22권3호
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• pp.261-267
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• 2018

Long-term deformation of a steel-reinforced concrete (SRC) column is different from that of a reinforced concrete (RC) column due to the different moisture distribution. Wide-flange steel in an SRC column obstructs diffusion and makes long-term deformation slower. Previous studies analyzed the characteristics of long-term deformation of SRC columns. In this study, an additional experiment is conducted to more precisely investigate the effect of wide-flange steel on the long-term deformation of SRC columns. Long-term deformation, especially creep of SRC columns with various types of wide-flange steel, is tested. Wide-flange steel for the experiment is made of thin acrylic panels that can block diffusion but does not have strength, because the main purpose of this study is to exclusively demonstrate the long-term deformation of concrete caused by moisture diffusion, not by the reinforcement ratio. Experimental results show that the long-term deformation of a SRC column develops slower than that in a RC column, and it is slower as the wide-flange steel hinders diffusion more. These experimental results can be used for analytical prediction of long-term deformation of various SRC columns. An example of the analytical prediction is provided. According to the experimental and analytical results, it is clear that a new prediction model for long-term deformation of SRC columns should be developed in further studies.

• 천문학회보
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• 제44권1호
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• pp.52.3-52.3
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• 2019

We investigate a relative contribution from short to long-term flaring rate to predicting M and X-class flare probabilities. In this study, we consider magnetic parameters summarizing distribution and non-potentiality by Solar Dynamics Observatory/Helioseimic and Magnetic Imager and flare list by Geostationary Operational Environmental Satellites. A short-term rate is the number of major flares that occurred in an given active region (AR) within one day before the prediction time. A mid-term rate is a mean flaring rate from the AR appearance day to one day before the prediction time. A long-term rate is a rate determined from a relationship between magnetic parameter values of ARs and their flaring rates from 2010 May to 2015 April. In our model, the predicted rate is given by the combination of weighted three rates satisfying that their sum of the weights is 1. We calculate Brier skill scores (BSSs) for investigating weights of three terms giving the best prediction performance using ARs from 2015 April to 2018 April. The BSS (0.22) of the model with only long-term is higher than that with only short-term or mid-term. When short or mid-term are considered additionally, the BSSs are improved. Our model has the best performance (BSS = 0.29) when all three terms are considered, and their relative contribution from short to long-term rate are 19%, 23%, and 58%, respectively. This model seems to be more effective when predicting active solar ARs having several major flares.

• 간호행정학회지
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• 제11권1호
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• pp.67-77
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• 2005

Purpose: Needs of health-welfare-medical service for the elderly is rapidly increasing in Korea. The purpose of this study was to evaluate the needs of health-welfare-medical service for the long-term care elderly in the community and to compare differences by their characteristics. Method: Needs assessment was completed in the homes of 598 persons over 65 years by using the tool of needs assessment, between November and December, 2003. We examined all the health-welfare-medical service of elderly in the community. Data were analyzed using SAS program. Result: The needs of the long-term care elderly in community was largest 'home visiting service of visiting nurse(87.5%)', and then 'religious, psychological and emotional support(73.9%)', 'home visiting therapy of physician(58.5%)', 'social support service(55.7%)', 'health improvement program of public health center and social welfare center(51.8%)', 'health examination(48.8%)' followed. The difference of health-welfare-medical service needs among characteristics(age, medical security, caregiver existence, and regions) was statistically significant by service contents(p<0.05 or p<0.01). Conclusion: We can apply it in the distribution of community resource and the development of service providing programs by figure out the needs assessment for the long-term care elderly in the community, and consequently, through this, realizing the health maintenance and promotion of the long-term care elderly.

• 생약학회지
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• 제44권2호
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• pp.200-208
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• 2013

The aim of this study was to evaluate the shelf-life of Bojungikgi-tang (Buzhongyiqi-tang in Chinese) by long-term storage test. Experiments were performed to evaluate the stability such as the selected physicochemical, pH, identification, heavy metal, microbiological experiment, and amount of marker compounds under a long-term storage test of Bojungikgi-tang decoction. The significant change was not showed in pH, heavy metal, microbiological, and identification test based on long-term storage test. Furthermore, the HPLC analysis was performed for the determinations of liquiritin, glycyrrhizin, nodakenin, and hesperidin in Bojungikgi-tang by long-term storage test. We were calculated shelf-life of Bojungikgi-tang decoction based on the amount change of four constituents. Consequently, Shelf-life by four compounds at room temperature was predicted 23 month. The suggested shelf-life would be helpful on the storage and distribution of herbal medicine.

• 한국해양공학회지
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• 제24권6호
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• pp.97-102
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• 2010

This paper deals with the variability of short term creep rupture time based on previous creep rupture tests and the statistical methodology of the creep life prediction. The results of creep tests performed using constant uniaxial stresses at 600, 650, and $700^{\circ}C$ elevated temperatures were used for a statistical analysis of the inter-specimen variability of the short term creep rupture time. Even under carefully controlled identical testing conditions, the observed short-term creep rupture time showed obvious inter-specimen variability. The statistical aspect of the short term creep rupture time was analyzed using a Weibull statistical analysis. The effect of creep stress on the variability of the creep rupture time was decreased with an increase in the stress level. The effect of the temperature on the variability also decreased with increasing temperature. A long term creep life prediction method that considers this statistical variability is presented. The presented method is in good agreement with the Lason-Miller Parameter (LMP) life prediction method.

• 생약학회지
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• 제43권3호
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• pp.257-264
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• 2012

The purpose of this study was to estimate the shelf-life of Ssanghwa-tang by long-term storage test. Experiments were conducted to evaluate the stability such as the selected physicochemical, pH, identification, heavy metal, microbiological experiment under a long-term storage test of Ssanghwa-tang. The significant change was not showed in pH, heavy metal, microbiological, identification test and quantitative analysis based on long-term storage test. The contents of albiflorin, paeoniflorin, cinnamic acid, liquiritin, and glycyrrhizin in long-term storage test were 66.8-93.1 ${\mu}g/mL$, 429.0-495.0 ${\mu}g/mL$, 3.8-4.4 ${\mu}g/mL$, 32.0-38.1 ${\mu}g/mL$, and 66.8-71.7 ${\mu}g/mL$, respectively. Shelf-lifes by 5 compounds about 3 lots at room temperature were predicted 21-37, 14-21, and 16-72 months, respectively. The suggested shelf-life would be helpful on the storage and distribution of herbal medicine.

• 디지털산업정보학회논문지
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• 제15권1호
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• pp.1-7
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• 2019

The objective of this study is to examine the trends in big data. Research abstracts were extracted from 4,019 articles, published between 1995 and 2018, on Web of Science and were analyzed using topic modeling and time series analysis. The 20 single-term topics that appeared most frequently were as follows: model, technology, algorithm, problem, performance, network, framework, analytics, management, process, value, user, knowledge, dataset, resource, service, cloud, storage, business, and health. The 20 multi-term topics were as follows: sense technology architecture (T10), decision system (T18), classification algorithm (T03), data analytics (T17), system performance (T09), data science (T06), distribution method (T20), service dataset (T19), network communication (T05), customer & business (T16), cloud computing (T02), health care (T14), smart city (T11), patient & disease (T04), privacy & security (T08), research design (T01), social media (T12), student & education (T13), energy consumption (T07), supply chain management (T15). The time series data indicated that the 40 single-term topics and multi-term topics were hot topics. This study provides suggestions for future research.

• 대한치과기공학회지
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• 제46권2호
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• pp.21-27
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• 2024

Purpose: This study aimed to analyze the stress distribution and deformation in implant abutments made from titanium (Ti-6Al-4V), zirconia, and polyetheretherketone (PEEK), including their screws and fixtures, under various loading conditions using finite element analysis (FEA). Methods: Three-dimensional models of the mandible with implant abutments were created using Siemens NX software (NX10.0.0.24, Siemens). FEA was conducted using Abaqus to simulate occlusal loads and assess stress distribution and deformation. Material properties such as Young's modulus and Poisson's ratio were assigned to each component based on literature and experimental data. Results: The FEA results revealed distinct stress distribution patterns among the materials. Titanium alloy abutments exhibited the highest stress resistance and the most uniform stress distribution, making them highly suitable for long-term stability. Zirconia abutments showed strong mechanical properties with higher stress concentration, indicating potential vulnerability to fracture despite their aesthetic advantages. PEEK abutments demonstrated the least stress resistance and higher deformation compared to other abutment materials, but offered superior shock absorption, though they posed a higher risk of mechanical failure under high load conditions. Conclusion: The study emphasizes the importance of selecting appropriate materials for dental implants. Titanium offers durability and uniform stress distribution, making it highly suitable for long-term stability. Zirconia provides aesthetic benefits but has a higher risk of fracture compared to titanium. PEEK excels in shock absorption but has a higher risk of mechanical failure compared to both titanium and zirconia. These insights can guide improved implant designs and material choices for various clinical needs.

• 산업경영시스템학회지
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• 제47권2호
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• pp.155-167
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• 2024

Distribution and logistics industries contribute some of the biggest GDP(gross domestic product) in South Korea and the number of related companies are quarter of the total number of industries in the country. The number of retail tech companies are quickly increased due to the acceleration of the online and untact shopping trend. Furthermore, major distribution and logistics companies try to achieve integrated data management with the fulfillment process. In contrast, small and medium distribution companies still lack of the capacity and ability to develop digital innovation and smartization. Therefore, in this paper, a deep learning-based demand forecasting & recommendation model is proposed to improve business competitiveness. The proposed model is developed based on real sales transaction data to predict future demand for each product. The proposed model consists of six deep learning models, which are MLP(multi-layers perception), CNN(convolution neural network), RNN(recurrent neural network), LSTM(long short term memory), Conv1D-BiLSTM(convolution-long short term memory) for demand forecasting and collaborative filtering for the recommendation. Each model provides the best prediction result for each product and recommendation model can recommend best sales product among companies own sales list as well as competitor's item list. The proposed demand forecasting model is expected to improve the competitiveness of the small and medium-sized distribution and logistics industry.