• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2017.05a
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• pp.641-644
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• 2017

Usage of LTE(Long Term Evolution) technology is expanded to industrial an emergency service field beyond commercial communications of mobile internet focused on smartphone. In this paper, transmission performance of LTE technology be supplied to various service area is analyzed on the level of application traffics. Performance is evaluated with compter simulation based NS(Network Simulator)-2, CBR(Constant Bit Rate), VBR(Variable Bit Rate File) traffic is used as simulation target. Results and methods of this paper can be used for research and developmemt of LTE based networks.

• Steel and Composite Structures
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• v.2 no.2
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• pp.85-98
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• 2002

The aim of the paper is to present some results about the influence of rheological phenomena on steel-concrete composite beams. Both the cases of slab with normal and high performance concrete for one and two-span beams are analysed. A new finite element model that allows taking into account creep, shrinkage and cracking in tensile zones for concrete, along with non-linear behaviour of connection, steel beam and reinforcement, has been used. The main parameters that affect the response of the composite beam under the service load are highlighted. The influence of shrinkage on the slip over the supports is analysed, together with the cracking along the beam. At last, by performing a collapse analysis after a long-term analysis, the influence of rheological phenomena on the ductility demand of connection and reinforcement is analysed.

• Journal of the Korean Institute of Gas
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• v.11 no.3
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• pp.40-43
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• 2007

The performance of PEMFC stack can be improved significantly by optimizing the design and operating conditions. As a result, the performance of daily operation showed slight deviation (0.02-0.9%) after accumulated DSS operation for 500 hrs but the stack performance was stable. Therefore, it is confirmed that it would be improved the life-time of stack and operation reliability for the commercialization of PEMFC system.

• Journal of Integrative Natural Science
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• v.11 no.4
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• pp.204-208
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• 2018

Comparison of different optimizer performance in photovoltaic power modeling using artificial neural deep learning techniques is described in this paper. Six different deep learning optimizers are tested for Long-Short-Term Memory networks in this study. The optimizers are namely Adam, Stochastic Gradient Descent, Root Mean Square Propagation, Adaptive Gradient, and some variants such as Adamax and Nadam. For comparing the optimization techniques, high and low fluctuated photovoltaic power output are examined and the power output is real data obtained from the site at Mokpo university. Using Python Keras version, we have developed the prediction program for the performance evaluation of the optimizations. The prediction error results of each optimizer in both high and low power cases shows that the Adam has better performance compared to the other optimizers.

• International Journal of High-Rise Buildings
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• v.9 no.4
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• pp.343-349
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• 2020

This research aimed to clarify the long-term mechanical performance of a steel truss member strengthened by a carbon fiber-reinforced polymer (CFRP) without protective coating through exposure testing. Strengthening and repair methods using CFRP have been developed in recent years; however, there is a lack of durability research for CFRP-strengthened members, especially mechanical performance investigation according to actual exposure testing. In this study, 10 CFRP-strengthening steel specimens were created in 2015, and elastic bending tests were conducted biannually. Eventually, although resin loss occurred due to environmental effects, the mechanical performance of CFRP-strengthened steel was not degraded, and we propose a calculation method of bending stiffness to evaluate the lower value of stiffness for design.

• Composites Research
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• v.19 no.1
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• pp.43-48
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• 2006

High performance fiber reinforced cement composites have better performances than traditional cement based materials, therefore, have been expected as new construction applications such as the materials for construction & bridge structure, repair and rehabilitation applications, anti-collapse applications, anti-noise applications etc. However, they have lots of the problems such as material design, fabrication method and structural analysis. Also, the most serious problems of High performance fiber reinforced cement composites have been expensive initial cost, lack of long-term exposure data. As a result, it is needed that the efforts for lowering the initial cost and accumulation of long-term exposure. There has been hardly assessment results of life cycle cost for HPFRCC in construction field, but some papers showed that total life cycle cost could be profitable if the initial cost could be reduced.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.133-133
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• 2021

The performance of radar Quantitative Precipitation Estimation (QPE) using Long Short-Term Memory (LSTM) networks in hydrological applications depends on either the quality of data or the three-dimensional CAPPI structure from the weather radar. While radar data quality is controlled and enhanced by the more and more modern radar systems, the effect of CAPPI structure still has not yet fully investigated. In this study, three typical and important types of CAPPI structure including inverse-pyramid, cubic of grids 3x3, cubic of grids 4x4 are investigated to evaluate the effect of CAPPI structures on the performance of radar QPE using LSTM networks. The investigation results figure out that the cubic of grids 4x4 of CAPPI structure shows the best performance in rainfall estimation using the LSTM networks approach. This study give us the precious experiences in radar QPE works applying LSTM networks approach in particular and deep-learning approach in general.

• Journal of Korean society of Dental Hygiene
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• v.17 no.5
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• pp.791-803
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• 2017

Objectives: Oral health management is important to improve the quality of life among the elderly. This study investigated the performance of elderly oral health management among some care workers in long-term-care hospitals. Methods: The study subjects were 174 care workers in 10 long-term-care hospitals. Data on general characteristics of care workers, attitude, recognition and knowledge of elderly health, performance of elderly oral health management were collected by a self-administered questionnaire. Data were analyzed through descriptive analysis, t-test, ANOVA, correlation and multiple regression analysis by using a SPSS version 23.0 statistical program. Results: The performance score of oral health management was $4.34{\pm}0.64$ on the 5-point Likert scale. The subjects who exercised more than 2 times a month were significantly higher in their performance of elderly oral health management compared to subjects who did not exercise (${\beta}=0.232$, p=0.035). And, the subjects who cared 10-19 persons were significantly higher in performance of elderly oral health management compared to subjects who cared more than 20 elderly (${\beta}=0.246$, p=0.020). The oral health behavior of care worker (${\beta}=0.271$, p<0.001) and the knowledge of oral health care (${\beta}=0.055$, p=0.008) were positively related to the performance of elderly oral health management. Conclusions: The educational program designed to improve knowledge of care workers in accordance with the standard textbook for training care workers should be developed, and the long term education program should be reinforced to improve the performance for elderly oral health care. If care workers can care a proper number of old persons, they will give oral health care to them.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.3
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• pp.1073-1081
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• 2021

When firms have higher environmental performance, they can provide sustainable business that allows firms to build the value of credibility and ethics, higher reputation, higher productivity, and lower costs. The advantages of environmental responsibilities help firms to maintain their earnings level over a long-term period. This research aims to examine the effect of environmental performance on earnings persistence. Research samples include 413 manufacturing firms-years listed in the Indonesian Stock Exchange and the PROPER evaluation in 2013-2019. Environmental performance is measured by PROPER evaluation rating. The result shows that environmental performance has a positive effect on earnings persistence. The advantage of environmental responsibilities allows firms to enjoy performance sustainability and persistence in a long-term period, not only periodically. Also, the positive effect of environmental performance on earnings persistence occurs more in the environmentally sensitive industry than non-sensitive ones. Since an environmentally-sensitive industry brings more environmental damage, higher environmental performance is more valuable to provide sustainability. This research has limitations to use all the Indonesian Stock Exchange-listed firms since not all firms participate in the PROPER evaluation. This research implies firms' management should maintain earnings persistence and sustainability by implementing higher-quality environmental responsibility, especially for firms in an environmentally-sensitive industry.

• Journal of Korean Society for Quality Management
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• v.47 no.3
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• pp.497-508
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• 2019

Purpose: The purpose of this study is to overcome limitations of conventional studies that to predict Baltic Dry Index (BDI). The study proposed applications of Artificial Neural Network (ANN) named Long Short-Term Memory (LSTM) to predict BDI. Methods: The BDI time-series prediction was carried out through eight variables related to the dry bulk market. The prediction was conducted in two steps. First, identifying the goodness of fitness for the BDI time-series of specific ANN models and determining the network structures to be used in the next step. While using ANN's generalization capability, the structures determined in the previous steps were used in the empirical prediction step, and the sliding-window method was applied to make a daily (one-day ahead) prediction. Results: At the empirical prediction step, it was possible to predict variable y(BDI time series) at point of time t by 8 variables (related to the dry bulk market) of x at point of time (t-1). LSTM, known to be good at learning over a long period of time, showed the best performance with higher predictive accuracy compared to Multi-Layer Perceptron (MLP) and Recurrent Neural Network (RNN). Conclusion: Applying this study to real business would require long-term predictions by applying more detailed forecasting techniques. I hope that the research can provide a point of reference in the dry bulk market, and furthermore in the decision-making and investment in the future of the shipping business as a whole.