• Journal of Korean Society on Water Environment
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• v.29 no.3
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• pp.400-408
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• 2013

Total phosphorus was set as a target indicator to prevent eutrophication and algae growth, etc., in three major rivers (Nakdong River, Geum River and Yeongsang/Seomjin River) for the second phase (2011 ~ 2015) in total maximum daily loads (TMDLs) system. However, total phosphorus management was restrictively introduced, i.e., upstream of the Lake Daechung, in the Geum River watershed. Total phosphorus concentration and trophic levels in downstream of the Lake Daechung (include Mangyeong and Dongjin rivers) were increased more than upstream. Therefore, it is necessary to expand total phosphorus management in all watersheds of the Geum River. If total phosphorus was managed in all area of the Geum River watershed, it is possible to decrease total phosphorus concentration and trophic levels, and solve the unbalanced water quality between up and downstream of the Lake Daechung.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.9
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• pp.417-424
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• 2002

This paper presents an industrial peak load management system for the peak demand control. Kohonen neural network and wavelet transform based techniques are adopted for industrial peak load forecasting that will be used as input data of the peak demand control. Firstly, one year of historical load data of a steel company were sorted and clustered into several groups using Kohonen neural network and then wavelet transforms are applied with Biorthogonal 1.3 mother wavelet in order to forecast the peak load of one minute ahead. In addition, for the peak demand control, composite fuzzy model is proposed and implemented in this work. The results are compared with those of conventional model, fuzzy model and composite model, respectively. The outcome of the study clearly indicates that the composite fuzzy model approach can be used as an attractive and effective means of the peak demand control.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.1
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• pp.41-47
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• 2015

In recent years, energy supply cases to take advantage of EMS(Energy Management System) are increasing according to high interest of energy efficiency. The important factor for essential and economical EMS operation is the supply and demand plan the hourly power demand of building load using the hierarchical clustering method of variety statistical techniques, and use the real historical data of target load. Also the estimated results of study are obtained the reliability through separate tests of validity.

• Journal of Environmental Science International
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• v.12 no.3
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• pp.345-358
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• 2003

Jindong bay at the northwestern part of Jinhae bay suffers from the occurrence of red tides in summer every year. In order to study the management methods of coastal environments, an ecological numerical model has been developed. The model experiments was forecasted that the load of nutrients from the land and field concentration will be cut down per 10% each. When we cut down 57.2% nitrogen load in the inner bay and 38.4% phosphorous load in the outer bay of bottom layer of the nutrients load from land and field concentration, the seawater quality standard levels up first grade. When we cut down 86.5% nutrients in the inner bay and 93.0% nutrients in the outer bay, the concentration of chlorophyll a decreases below 3.2 $\mu\textrm{g}$/(equation omitted)(an individual concentration of phytoplankton : 10,000cel1/ml), i.e. the red tides do not occur.

• Journal of Communications and Networks
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• v.10 no.1
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• pp.38-43
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• 2008

In this paper, adaptive channel borrowing approach fuzzy neural networks for load balancing (ACB-FNN) is presented to maximized the number of served calls and the depending on asymmetries traffic load problem. In a wireless network, the call's arrival rate, the call duration and the communication overhead between the base station and the mobile switch center are vague and uncertain. A new load balancing algorithm with cell involved negotiation is also presented in this paper. The ACB-FNN exhibits better learning abilities, optimization abilities, robustness, and fault-tolerant capability thus yielding better performance compared with other algorithms. It aims to efficiently satisfy their diverse quality-of-service (QoS) requirements. The results show that our algorithm has lower blocking rate, lower dropping rate, less update overhead, and shorter channel acquisition delay than previous methods.

• Journal of the Korea Safety Management & Science
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• v.12 no.3
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• pp.101-106
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• 2010

The purposes of this paper are to investigate an effect of weight of material and gender on postural stability and to introduce formulas for those. There were five levels of weights 0, 9, 18, 27 and 36 kg, and two levels of genders were conducted. Eight male and five female subjects participated in this experiment, ten tests were performed for each level of weights to measure the postural stability by using the stability platform. The effect of the genders and the load on the postural stability were statistically analysed by the two way ANOVA test and the regression analysis. The ANOVA test showed that the effect of weights was statistically significant on postural stability to the both male and female subjects. And the postural stability of female subjects was better than that of male subjects. A linear regression formula for the balancing time and the load and a formula for the reduction rate postural stability and the relative load were introduced by the regression analysis.

• Journal of Industrial Technology
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• v.30 no.A
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• pp.9-15
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• 2010

Recently, Smart Grid is a emerging topic in power and communication industry. Smart Grid refers to a evolution of the electricity supply infrastructure that monitors, protects, and intelligently optimize the operation of the interconnected elements including various type of generators, power grid, building/home automation system and end-use consumers. In order to successful implementation of Smart Grid, energy management function will be the key factor that coordinates and optimally controls the various loads according to the operating condition and environments, and the load patterns in residential and commercial building will be required as fundamental element for load management. In this study, we collects many types of energy usage data of electric appliances, analyze their load curves, and make the general load patterns for electrical appliance.

• Journal of Information Processing Systems
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• v.5 no.2
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• pp.69-76
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• 2009

Self healing systems are considered as cognation-enabled sub form of fault tolerance system. But our experiments that we report in this paper show that self healing systems can be used for performance optimization, configuration management, access control management and bunch of other functions. The exponential complexity that results from interaction between autonomic systems and users (software and human users) has hindered the deployment and user of intelligent systems for a while now. We show that if that exceptional complexity is converted into self-growing knowledge (policies in our case), can make up for initial development cost of building an intelligent system. In this paper, we report the application of AHSEN (Autonomic Healing-based Self management Engine) to in OKKAM Project infrastructure backbone cluster that mimics the web service based architecture of u-Zone gateway infrastructure. The 'blind' load division on per-request bases is not optimal for distributed and performance hungry infrastructure such as OKKAM. The approach adopted assesses the active threads on the virtual machine and does resource estimates for active processes. The availability of a certain server is represented through worker modules at load server. Our simulation results on the OKKAM infrastructure show that the self healing significantly improves the performance and clearly demarcates the logical ambiguities in contemporary designs of self healing infrastructures proposed for large scale computing infrastructures.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.5
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• pp.351-360
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• 2016

Rapid population growth with high living standards and high electronics use for personal comfort has raised the electricity demand exponentially. To fulfill this elevated demand, conventional energy sources are shifting towards low production cost and long term usable alternative energy sources. Hybrid renewable energy systems (HRES) are becoming popular as stand-alone power systems for providing electricity in remote areas due to advancement in renewable energy technologies and subsequent rise in prices of petroleum products. Wind and solar power are considered feasible replacement to fossil fuels as the prediction of the fuel shortage in the near future, forced all operators involved in energy production to explore this new and clean source of power. Presented paper proposes fuzzy logic based Energy Management System (EMS) for Wind Turbine (WT), Photo Voltaic (PV) and Diesel Generator (DG) hybrid micro-grid configuration. Battery backup system is introduced for worst environmental conditions or high load demands. Dump load along with dump load controller is implemented for over voltage and over speed protection. Fuzzy logic based supervisory control system performs the power flow control between different scenarios such as battery charging, battery backup, dump load activation and DG backup in most intellectual way.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2007.05a
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• pp.397-399
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• 2007

This paper presents multiple regression analysis and data update to improve present spatial electric load forecasting algorithm of the DISPLAN. Spatial electric load forecasting considers a local economy, the number of local population and load characteristics. A Case study is performed for Jeon-Ju and analyzes a trend of the spatial load for the future 20 years. The forecasted information can contribute to an asset management of distribution systems.