• Journal of Korean Society for Quality Management
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• v.51 no.4
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• pp.573-588
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• 2023

Purpose: This study presents a research approach that utilizes deep reinforcement learning to construct optimal portfolios based on the business cycle for stocks and other assets. The objective is to develop effective investment strategies that adapt to the varying returns of assets in accordance with the business cycle. Methods: In this study, a diverse set of time series data, including stocks, is collected and utilized to train a deep reinforcement learning model. The proposed approach optimizes asset allocation based on the business cycle, particularly by gathering data for different states such as prosperity, recession, depression, and recovery and constructing portfolios optimized for each phase. Results: Experimental results confirm the effectiveness of the proposed deep reinforcement learning-based approach in constructing optimal portfolios tailored to the business cycle. The utility of optimizing portfolio investment strategies for each phase of the business cycle is demonstrated. Conclusion: This paper contributes to the construction of optimal portfolios based on the business cycle using a deep reinforcement learning approach, providing investors with effective investment strategies that simultaneously seek stability and profitability. As a result, investors can adopt stable and profitable investment strategies that adapt to business cycle volatility.

• Smart Structures and Systems
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• v.30 no.6
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• pp.571-582
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• 2022

Optimal life-cycle management is a challenging issue for deteriorating regional bridges. Due to the complexity of regional bridge structural conditions and a large number of inspection and maintenance actions, decision-makers generally choose traditional passive management strategies. They are less efficiency and cost-effectiveness. This paper suggests a deep reinforcement learning framework employing double-deep Q-networks (DDQNs) to improve the life-cycle management of deteriorating regional bridges to tackle these problems. It could produce optimal maintenance plans considering restrictions to maximize maintenance cost-effectiveness to the greatest extent possible. DDQNs method could handle the problem of the overestimation of Q-values in the Nature DQNs. This study also identifies regional bridge deterioration characteristics and the consequence of scheduled maintenance from years of inspection data. To validate the proposed method, a case study containing hundreds of bridges is used to develop optimal life-cycle management strategies. The optimization solutions recommend fewer replacement actions and prefer preventative repair actions when bridges are damaged or are expected to be damaged. By employing the optimal life-cycle regional maintenance strategies, the conditions of bridges can be controlled to a good level. Compared to the nature DQNs, DDQNs offer an optimized scheme containing fewer low-condition bridges and a more costeffective life-cycle management plan.

• Journal of the Korean Applied Science and Technology
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• v.31 no.2
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• pp.197-202
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• 2014

Positive plate was composed of lead hydroxide via reaction between lead oxide and $H_2O$ and lead sulfate was formed of the reaction of lead hydroxide with sulfuric acid. And its density is $3.8g/cm^3$, $4.0g/cm^3$, $4.2g/cm^3$ and $4.4g/cm^3$ by controlling volume of refined water. Curing of positive plate is done for low ($45^{\circ}C$, 40hr, over 95% of relative humidity) & high ($80^{\circ}C$, 40hr, over 95% of relative humidity) temperature, which created 3BS & 4BS active materials. Experimental result of DOD with 100% life cycle test shows that it was not related to the density of active materials but to the low & high temperature aging of active materials. The test makes us to understand that the crystallization which is made by curing of active materials is a more of a main factor than density of active materials under the deep cycle using circumstances. The active materials which were from the high temperature curing are better for deep cycle performance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.11
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• pp.3780-3797
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• 2022

The estimation of radio map (RM) is a fundamental and critical task for the network planning and optimization performance of mobile communication. In this paper, a RM estimation method is proposed based on a deep dual learning structure. This method can simultaneously and accurately reconstruct the urban building map (UBM) and estimate the RM of the whole cell by only part of the measured reference signal receiving power (RSRP). Our proposed method implements UBM reconstruction task and RM estimation task by constructing a dual U-Net-based structure, which is named RadioCycle. RadioCycle jointly trains two symmetric generators of the dual structure. Further, to solve the problem of interference negative transfer in generators trained jointly for two different tasks, RadioCycle introduces a dynamic weighted averaging method to dynamically balance the learning rate of these two generators in the joint training. Eventually, the experiments demonstrate that on the UBM reconstruction task, RadioCycle achieves an F1 score of 0.950, and on the RM estimation task, RadioCycle achieves a root mean square error of 0.069. Therefore, RadioCycle can estimate both the RM and the UBM in a cell with measured RSRP for only 20% of the whole cell.

• Journal of Power System Engineering
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• v.20 no.2
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• pp.79-84
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• 2016

The thermodynamic performance of ocean thermal energy conversion with 1 kg/s geothermal water flow rate as a heat source was evaluated to obtain the basic data for the optimal design of cycle with respect to the classification of the working fluid. The basic thermodynamic model for cycle is rankine cycle and the geothermal water and deep seawater were adapted for the heat source of evaporator and condenser, respectively. R245fa, R134a are better to use as a working fluid than others in view of the use of geothermal water. It is important to select the proper working fluid to operate the ocean thermal energy conversion. So, this paper can be used as the basic data for the design of ocean thermal energy conversion with geothermal water and deep seawater.

• Journal of Ocean Engineering and Technology
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• v.25 no.1
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• pp.80-84
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• 2011

The cycle performance of closed ocean thermal energy conversion (OTEC) system with 50 kW gross power was evaluated to obtain the basic data for the optimal design of OTEC using waste heat such as solar power, discharged heat from condenser of power plant. The basic thermodynamic model for OTEC is Rankine cycle, and the surface seawater and deep seawater were used for the heat source of evaporator and condenser, respectively. The cycle performance such as efficiency, heat exchanger capacity, etc. was analyzed on the variation of temperature increase by waste heat. The cycle efficiency increased and necessary capacity of evaporator and condenser decreased under 50kW gross power with respect to the temperature increase of working fluid. Also, when the temperature increase is about $13.5^{\circ}C$, the heat which can be used is generated. By generator with 0.9 effectiveness under the simulated condition, the cycle efficiency was improved approximately 3.0% comparing with the basic cycle.

• Journal of the Korean Ceramic Society
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• v.39 no.6
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• pp.570-575
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• 2002

The present tendency of electrical and electronics is concentrated on MEMS devices for advantage of miniaturization, intergration, low electric power and low cost. Therefore it is essential that high aspect ratio and high etch rate by HDP technology development, so that silicon deep trench etching reactions was studied by ICP equipment. Deep trench etching of silicon was investigated as function of platen power, etch step time of etch/passivation cycle time and SF$\_$6/:C$_4$F$\_$8/ flow rate. Their effects on etch profile, scallops, etch rate, uniformity and selectivity were also studied.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 1994.06a
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• pp.69-78
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• 1994

A rotating disk is introduced to be applied to the deep drawing press. Several characteristics are summarized to see the basics of deep drawing of sheet metal in terms of load-stroke relationship and formability. Many conventional drawing presses, which are mostly link-type presses, are also shown to be compared with the rotating disk-type press. Performances of the new press are kinematically analyzed it terms of load-main gear angle relationship, stroke-gear angle relationship, and slide velocity-gear angle relationship and they are compared with those of conventional types', e. g. crank press and so on. The comparison show kinematically better performance of rotating disk-type press than that of conventional ones. Also, the new press are proven to be one of the best press for mass production in terms of cycle time. Applicability of the rotating disk press to deep drawing and cold forging work is introduced. The new press is described in terms of economy such that the cost of new press would be much lower than those of conventional types'.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.809-812
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• 2005

Battery is an energetic collector of solar cell system. Battery which is used in the system must have many qualities in the followings. The battery must be "Deep Cycle Battery" type. In addition, the battery is Cleary indicated the percentage of DOD. The indication of DOD is used for calculation other valve used in solar cell system. Currently, the percentage of DOD of battery is fixed by battery manufacture. If users would like to calculate is introduced % DOD, the users have to check the battery at least 12 months. This article is introduced battery deep of discharge meter by using theory of lead acid battery under deep cycle type and including the theory of DC. Current and internal resistance of battery. The data used for analyzing are collected according to the theories. The data will be calculated by monitor unit and controller systems.

• PNF and Movement
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• v.6 no.1
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• pp.21-25
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• 2008

Purpose : The purpose of this study was conducted to find out observation at gait analysis of the stroke patient with proprioceptive neuromuscular facilitation(PNF) concept. Methods : This is a literature study with books, seminar note and international PNF course book. Results : Stroke patient gait was poor initial contact by weakness of tibialis anterior or weakness of contralateral plantar flexor, poor loading response by loss of deep sensation, poor mid stance by loss of deep sensation, weakness of tibialis anterior and weakness of plantar flexors eccentric control, poor terminal stance, pre-swing, initial swing by loss of deep sensation and stiffness fo deep toe flexors. Conclusion : Stroke patient gait determine on loss of mobility, pain, fear, trunk muscle weakness, loss of coordination, loss of deep sensation, neglect and apraxia. Therefore observational gait analysis of the stroke patient focus on gait cycle and take out hypotheses from the gait cycle. These hypotheses have to define accept or not by parameters. Treatment plan made with the hypotheses.