• Korean Membrane Journal
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• v.6 no.1
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• pp.55-60
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• 2004

In recent years, an increasing interest in membrane technology has been observed in chemical and environmental industry. Membrane technology has advantages of low cost, energy saving and environmental clean technology comparing to conventional separation processes. Pervaporation is one of new advanced membrane technology applied for separation of azeotropic mixtures, aqueous organic mixtures, organic solvent and petrochemical mixtures. Sodium alginate composite membranes were prepared for the enhancement of long-term stability of pervaporation performance of water-ethanol mixture using pervaporation. Sodium alginate membranes were crosslinked with CaCl$_2$ and coated with polyelectrolyte chitosan to protect washing out of calcium ions from the polymer. The surface structures of PAN and hydrolysed PAN membrane were confirmed by ATR Fourier transform infrared (FT-IR). A field emission scanning electron microscopy (FE-SEM; Jeol 6340F) operated at 15 kV. Concentration profiles for Ca in the membrane surface and membrane cross-section were taken by an energy dispersive X-ray (EDX) analyser (Jeol) attached to the field emission scanning electron microscopy (Jeol 6340F). Pervaporation experiments were done with several operation run times to investigate long-term stability of the membranes.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.10 no.3
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• pp.343-347
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• 1998

The objective of this study is to manufacture the low temperature waterless container that is compact and low cost for a live fish transportation. Using the low temperature water container, it makes observations on the optimal conditions such as the amount of dissolved oxygen, total ammonia and nitrite in seawater for determining the survival rate of live fish in short and long-term transportation. Using a sole as a live fish, the temperatures of $0^{\circ}C$, 3$^{\circ}C$, 5$^{\circ}C$, 7$^{\circ}C$, 15$^{\circ}C$ were controled for there effects. The results of this investigation show that as the seawater temperature increased, the amount of oxygen decreased and there was a low temperature shock below 3$^{\circ}C$. It was observed that the fish was died with 30$m\ell/\ell$of ammonia. The optimal temperature is about 5$^{\circ}C$ for live fish transportation to maintain best survival rate.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 1999.10a
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• pp.73-81
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• 1999

Inchon Port is the second largest import-export port of Korea, and has the point ant issue such as the excessive logistics cost because of the limits of handing capacity and the chronic demurrage. There is few research activities on the analysis and improvement of the whole port operation, because Inchon Port not only has the dual dock system and various facilities but also handles a various kind of cargo. The purpose of this paper is to develop the simulation program as a long-term strategic support tool, considering the dual dock system and the TOC(terminal operation company) system executed from March, 1997 in Inchon Port. The basic input parameters such as arrival intervals, cargo tons, service rates are analyzed and the probability density function for this parameters are estimated. The main mechanism of simulation model is the discrete event-driven simulation and the next-event time advancing. The program is executed based on the knowledge base and database, and is constructed using VISUAL BASIC and ACCESS database. From the simulation model, it is possible to estimate the demurrage status through analyzing scenarios such as the variation of cargo ton and cargo handing level, the increase of service rate, and so on, and to establish the long-term port strategic plan.

• Proceedings of the KIEE Conference
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• 2004.11b
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• pp.261-265
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• 2004

This paper proposes a fuzzy dual method for analyzing long-term transmission system expansion planning problem considering ambiguities of the power system using fuzzy lineal programming. Transmission expansion planning problem can be formulated integer programming or linear programming with minimization total cost subject to reliability (load balance). A long-term expansion planning problem of a grid is very complex, which have uncertainties fur budget, reliability criteria and construction time. Too much computation time is asked for actual system. Fuzzy set theory can be used efficiently in order to consider ambiguity of the investment budget (economics) for constructing the new transmission lines and the delivery marginal rate (reliability criteria) of the system in this paper. This paper presents formulation of fuzzy dual method as first step for developing a fuzzy Ford-Fulkerson algorithm in future and demonstrates sample study. In application study, firstly, a case study using fuzzy integer programming with branch and bound method is presented for practical system. Secondly, the other case study with crisp Ford Fulkerson is presented.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.10
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• pp.3554-3570
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• 2021

With the rapid development of the Chinese water project, the safety monitoring of dams is urgently needed. Many drawbacks exist in dams, such as high monitoring costs, a limited equipment service life, long-term monitoring difficulties. MEMS sensors have the advantages of low cost, high precision, easy installation, and simplicity, so they have broad application prospects in engineering measurements. This paper designs intelligent monitoring based on the collaborative measurement of dual MEMS sensors. The system first determines the endpoint coordinates of the sensor array by the coordinate transformation relationship in the monitoring system and then obtains the dam settlement according to the endpoint coordinates. Next, this paper proposes a dual-MEMS sensor collaborative measurement algorithm that builds a mathematical model of the dual-sensor measurement. The monitoring system realizes mutual compensation between sensor measurement data by calculating the motion constraint matrix between the two sensors. Compared with the single-sensor measurement, the dual-sensor measurement algorithm is more accurate and can improve the reliability of long-term monitoring data. Finally, the experimental results show that the dam subsidence monitoring system proposed in this paper fully meets the engineering monitoring accuracy needs, and the dual-sensor collaborative measurement system is more stable than the single-sensor monitoring system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.8
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• pp.2993-3010
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• 2021

The job shop scheduling problem (JSSP) plays a critical role in smart manufacturing, an effective JSSP scheduler could save time cost and increase productivity. Conventional methods are very time-consumption and cannot deal with complicated JSSP instances as it uses one optimal algorithm to solve JSSP. This paper proposes an effective scheduler based on deep learning technology named self-supervised long-short term memory (SS-LSTM) to handle complex JSSP accurately. First, using the optimal method to generate sufficient training samples in small-scale JSSP. SS-LSTM is then applied to extract rich feature representations from generated training samples and decide the next action. In the proposed SS-LSTM, two channels are employed to reflect the full production statues. Specifically, the detailed-level channel records 18 detailed product information while the system-level channel reflects the type of whole system states identified by the k-means algorithm. Moreover, adopting a self-supervised mechanism with LSTM autoencoder to keep high feature extraction capacity simultaneously ensuring the reliable feature representative ability. The authors implemented, trained, and compared the proposed method with the other leading learning-based methods on some complicated JSSP instances. The experimental results have confirmed the effectiveness and priority of the proposed method for solving complex JSSP instances in terms of make-span.

• Asia-Pacific Journal of Business
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• v.9 no.3
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• pp.71-82
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• 2018

This study verifies whether the sustainable tax strategy provides unique information on earnings persistence and brings about the difference of value relevance of accounting information. Sustainability is measured by the 5-year coefficient of variation in cash ETR, such as in McGuire et al.(2013), which measures variability in long-term performance of tax avoidance. The value relevance of accounting information in this study is modified by the Ohlson model(1995), which explains the value of the firm by using accounting information such as net assets and net income and other non-accounting information. The samples of this study are the firms listed on the securities market from 2004 to 2015 and the final samples are 3,133 firm-year. The results of this empirical analysis show that the value relevance of accounting information increases as firms have long-term and sustainable tax strategies. Most of the prior studies on tax strategies have examined the tax minimization strategy that minimizes the tax cost. However, this study is different in that the sustainability of the tax strategy affects the value relevance of accounting information. The results of this study will be useful for the users to make decision using the value relevance of accounting information.

• Journal of the Korean Solar Energy Society
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• v.39 no.2
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• pp.45-55
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• 2019

More than 76% of the detached houses in Korea are over 20 years old. These old detached houses have poor energy efficiency. According to the 2017 Housing Census (Statistics Korea), more than 50% of low-income families live in detached houses. Therefore, the improvement of energy efficiency in old detached houses is needed from the viewpoint of energy welfare. The general method of building energy modelling for the verification of energy efficiency is based on the construction year data of "Building Design Criteria for Energy Saving" due to the cost and time involved in collecting the thermal performance data of buildings. There is poor accuracy with the deterioration of long-term aging of building materials. Also, the selection of alternatives for energy performance improvement is based on the items to be applied, not a performance improvement goal. It is difficult to calculate energy performance that reflects variations in various parameters with dynamic energy simulations. In this study, the influence of long-term aging is used to accurately predict the energy performance of old detached houses. The building energy modelling method is called ENERGY#, which is a static analysis method based on ISO13790. Energy performance is evaluated by a combination of input variables including building orientation, insulation of walls and roof, thermal performance of windows and window/wall ratio, and infiltration rate. Finally, this study provides a way to determine alternatives that meet energy performance improvement goals.

• Journal of Korean Academic Society of Home Health Care Nursing
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• v.28 no.2
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• pp.111-123
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• 2021

Purpose: This study aimed to present the management strategies necessary to improve the operational efficiency of visiting nurse centers and evaluate their effectiveness. Methods: The subjects of this study were visiting nurse centers registered as long-term care centers. Based on value chain analysis, cost information analysis, and data envelope analysis, the study was carried out according to the Magerison's management consulting procedure, for six months. This procedure comprised eight sub-steps of approach and application. Results: The following management strategies were agreed upon: establishment of a cooperative network with other visiting care centers, creation of high satisfaction of external customers by providing practical training to care workers, and making rehabilitation and exercise services as the core nursing activities to be focused on. Conclusion: The management consulting process and analysis method applied in this study can referred to as a useful methodological framework for revitalizing visiting nursing centers in the future.

• Nuclear Engineering and Technology
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• v.54 no.10
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• pp.3682-3694
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• 2022

The expansion of a country's ecological footprint generates resources for economic development. China's import bill and carbon footprint can be reduced by investing in green transportation and energy technologies. A sustainable environment depends on the cessation of climate change; the current study investigates nuclear energy efficiency, economic complexity, air transportation, and industrial improvement for reducing environmental footprint. Using data spanning the years 1983-2016, the dynamic autoregressive distributed lag simulation method has demonstrated the short- and long-term variability in the impact of regressors on the ecological footprint. The study findings revealed that economic complexity in China had been found to have a statistically significant impact on the country's ecological footprint. Moreover, the industrial improvement process is helpful for the ecological footprint in China. In the short term, air travel has a negative impact on the ecological footprint, but this effect diminishes over time. Additionally, energy innovation is negative and substantial both in the short and long run, thus demonstrating its positive role in reducing the ecological footprint. Policy implications can be extracted from a wide range of issues, including economic complexity, industrial improvement, air transportation, energy innovation, and ecological impact to achieve sustainable goals.