• Proceedings of the Korean Institute of Building Construction Conference
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• 2008.05a
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• pp.35-41
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• 2008

Qualitative enhancement of dwelling life has changing the recognition for the environment friendly wood which is being highlighted for its usage as an interior materials. This trend may prove the excellent performance of wood whose inherent characteristics has its comfortable, mild feeling of material, sound resistance and stabilities and the market of interior woods including floor, moulding and wooden panel as finishing interior materials is growing sustainably. However, since this materials is vulnerable to humidity and flame, waterproofing and flame retarding stability, an essential condition for interior materials, together with maintenance, are the main topics to be resolved. From the above-mentioned results, as a result of waterdrop contact angle, wood absorption volume and water content percentage test and the performance test of the processed materials after flame retardant, though there was some submerging time changes among types of woods for ensuring waterproofing performance improvement but as time passes, similar tendency was noticed to be formulated. As the submerging time is increased, so does the absorption volume and accordingly optimal level of range is judged to be drawn in order to ensure excellent performance, taking optimal economy into consideration. Therefore, it is considered that above-mentioned woods could be utilized for waterproof and flame retardant processed interior materials using uniform microwave and in order to put this technology into practical application, a research by way of diversified performance proving is required to be carried out.

• Journal of the Korea Society of Computer and Information
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• v.16 no.8
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• pp.137-146
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• 2011

In order to support increased consumer awareness regarding energy consumption, we present new ways of monitoring and predicting with energy in electric appliances. The proposed system is a design of a common electrical power outlet called smart plug that measures the amount of current passing through current sensor at 0.5 second. To acquire data for training and testing the proposed neural network, weather parameters used include average temperature of day, min and max temperature, humidity, and sunshine hour as input data, and power consumption as target data from smart plug. Using the experimental data for training, the neural network model based on Back-Propagation algorithm was developed. Multi layer perception network was used for nonlinear mapping between the input and the output data. It was observed that the proposed neural network model can predict the power consumption quite well with correlation coefficient was 0.9965, and prediction mean square error was 0.02033.

• KEPCO Journal on Electric Power and Energy
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• v.2 no.2
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• pp.211-221
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• 2016

The increase of world's population and economic development are the keys drivers behind growing demand for energy. Especially the demand for electricity would eventually result in an increase of coal usage. Therefore ultra supercritical circulating fluidized bed boiler has been developed as solutions of economic eco-friendly technologies for coal and of increasing supplies of low grade fuels. Ultra supercritical circulating fluidized bed boiler has an once through type of steam cycle different from drum type in subcritical circulating fluidized bed boiler. Also, the duplication of a proven commercial module with 100-300 MWe subcritical circulating fluidized bed might be the key for design of 500~800 MWe ultra supercritical circulating fluidized bed boiler. After 2017, ultra supercritical circulating fluidized bed boiler might become standard model over subcritical circulating fluidized bed boiler. Therefore, this paper will help you to understand ultra super critical circulating fluidized bed (USC-CFB) through describing the background, status and prospect of the CFB technology.

• Journal of the Korean Institute of Gas
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• v.18 no.4
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• pp.35-43
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• 2014

Usage of the inorganic floor finishing material can be advantageous to overcome some problems of traditional organic-based floor finishing material used for hazardous material storage facilities. A spark can be produced by physical impact between the flooring and the flooring disposal equipment while removing the existing flooring. In order to prevent a fire hazard, which may be caused the spark, it is feasible that a construction can be implemented without removing the existing flooring. Moreover, the top coating material containing an antistatic agent is effective to prevent secondary damage caused by static electricity after finishing the construction of the flooring. Therefore, the inorganic floor finishing material of the this study is expected to be beneficial for safety management and economical aspect for inspectors.

• Journal of KIBIM
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• v.5 no.4
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• pp.53-62
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• 2015

Korea has been at the forefront of green growth initiatives. In 2008, the government declared the new vision toward 'low-carbon society and green growth'. The government subsidies and Feed-in Tariff (FIT) increased domestic usage of solar power by supplying photovoltaic housing and photovoltaic generation systems. Since 2000, solar power industry has been the world's fastest growing source with the annual growth rate of 52.5%. Especially, BIPV(Building Integrated Photovoltaic) systems are capturing a growing portion of the renewable energy market due to several reasons. BIPV consists of photovoltaic cells and modules integrated into the building envelope such as a roof or facades. By avoiding the cost of conventional materials, the incremental cost of photovoltaics is reduced and its life-cycle cost is improved. When it comes to atypical building, numerous problems occur because PV modules are flat, stationary, and have its orientation determined by building surface. However, previous studies mainly focused on improving installations of solar PV technologies on ground and rooftop photovoltaic array and developing prediction model to estimate the amount of produced electricity. Consequently, this paper discusses the problem during a planning and design stage of BIPV systems and suggests the method to select optimal design of the systems by applying the national strategy and economic policies. Furthermore, the paper aims to develop BIM tool based on the engineering knowledge from experts in order for non-specialists to design photovoltaic generation systems easily.

• Advances in environmental research
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• v.3 no.2
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• pp.173-183
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• 2014

A comprehensive mathematical model was developed for this study to estimate on-site and off-site GHG emissions from wastewater treatment plants (WWTPs). The model was applied to three different hybrid WWTPs (S-WWTP, J-WWTP, and T-WWTP) including anaerobic, anoxic, and aerobic process, located in Seoul City, South Korea. Overall on-site and off-site GHG emissions from S-WWTP, J-WWTP, and T-WWTP were $305,253kgCO_2e/d$, $282,682kgCO_2e/d$, and $117,942kgCO_2e/d$, respectively. WWTP treating higher amounts of wastewater produced more on-site and off-site GHG emissions. On average, the percentage contribution of on-site and off-site emissions was 3.03% and 96.97%. The highest amount of on-site GHG emissions was generated from anoxic process and the primary on-site GHG was nitrous oxide ($N_2O$). Off-site GHG emissions related to electricity consumption for unit operation was much higher than that related to production of chemicals for on-site usage. Recovery and reuse of biogas significantly reduced the total GHG emissions from WWTPs. The results obtained from this study can provide basic knowledge to understand the source and amount of GHG emissions from WWTPs and strategies to establish lower GHG emitting WWTPs.

• Journal of IKEEE
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• v.23 no.1
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• pp.120-126
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• 2019

Recently, accurate prediction of power consumption based on machine learning techniques in Internet of Energy (IoE) has been actively studied using the large amount of electricity data acquired from advanced metering infrastructure (AMI). In this paper, we propose a deep learning model based on Gated Recurrent Unit (GRU) as an artificial intelligence (AI) network that can effectively perform pattern recognition of time series data such as the power consumption, and analyze performance of the prediction based on real household power usage data. In the performance analysis, performance comparison between the proposed GRU-based learning model and the conventional learning model of Long Short Term Memory (LSTM) is described. In the simulation results, mean squared error (MSE), mean absolute error (MAE), forecast skill score, normalized root mean square error (RMSE), and normalized mean bias error (NMBE) are used as performance evaluation indexes, and we confirm that the performance of the prediction of the proposed GRU-based learning model is greatly improved.

• The Transactions of the Korean Institute of Power Electronics
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• v.27 no.5
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• pp.376-383
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• 2022

The improved performance of computer parts, such as graphic card, CPU, and main board, has led to the need for power supplies with a high power output. The dynamic load profile rapidly changes the usage of power consumption depending on load operations, such as PC power and air conditioner. Under dynamic load profile conditions, power consumption can be classified into maximum, normal, and standby power. Several problems arise in the case of maximum power. Peak power is generated at the system power source in the maximum-power situation. Frequent generation of peak power can cause high-frequency problems and reduce the life of high-pressure parts (especially high-pressure capacitors). For example, when a plurality of PCs are used, system overload occurs due to peak power generation and causes problems, such as power failure and increase in electricity bills due to exceeded contract power. To solve this problem, a system peak power limit/compensation power circuit is proposed for a power supply under dynamic load profile conditions. The proposed circuit detects the system current to determine the power situation of the load. When the system current is higher than the set level, the circuit recognizes that the system current generates peak power and compensates for the load power through a converter using a super capacitor as the power source. Thus, the peak power of loads with a dynamic load profile is limited and compensated for, and problems, such as high-frequency issues, are solved. In addition, the life of high-pressure parts is increased.

• KNOM Review
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• v.24 no.1
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• pp.1-12
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• 2021

VM (Virtual Machine) live migration is a server virtualization technique for deploying a running VM to another server node while minimizing downtime of a service the VM provides. Currently, in cloud data centers, VM live migration is widely used to apply load balancing on CPU workload and network traffic, to reduce electricity consumption by consolidating active VMs into specific location groups of servers, and to provide uninterrupted service during the maintenance of hardware and software update on servers. It is critical to use VMlive migration as a prevention or mitigation measure for possible failure when its indications are detected or predicted. In this paper, we propose two VNF live migration methods; one for predictive load balancing and the other for a proactive measure in failure. Both need machine learning models that learn periodic monitoring data of resource usage and logs from servers and VMs/VNFs. We apply the second method to a vEPC (Virtual Evolved Pakcet Core) failure scenario to provide a detailed case study.

• KOREAN JOURNAL OF PACKAGING SCIENCE & TECHNOLOGY
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• v.28 no.2
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• pp.143-149
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• 2022

PCS needs to freely switch AC and DC to connect the battery, external AC loads and renewable energy in both directions for energy efficiency. Whenever converting happens, power loss inevitably occurs. Minimization of the power loss to save electricity and convert it for usage is a very critical function in PCS. PCS plays an important role in the ESS(Energy Storage System) but the importance of stabilizing semiconductors on PCB(Printed Circuit Board) should be empathized with a risk of failure such as a fire explosion. In this study, the temperature variation inside PCS was reviewed by cooling fan on top of PCS, and the vibration characteristics of PCS were analyzed during truck transportation for reliability of the product. In most cases, a cooling fan is mounted to control the inner temperature at the upper part of the PCS and components generating the heat placed on the internal aluminum cooling plate to apply the primary cooling and the secondary cooling system with inlet fans for the external air. Results of CFD showed slightly lack of circulating capacity but simulated temperatures were durable for components. The resonance points of PCS were various due to the complexity of components. Although they were less than 40 Hz which mostly occurs breakage, it was analyzed that the vibration displacement in the resonance frequency band was very insufficient. As a result of random-vibration simulation, the lower part was analyzed as the stress-concentrated point but no breakage was shown. The steel sheet could be stable for now, but for long-term domestic transportation, structural coupling may occur due to accumulation of fatigue strength. After the test completed, output voltage of the product had lost so that extra packaging such as bubble wrap should be considered.