• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.1
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• pp.25-30
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• 2016

It is critical to forecast the maximum daily and monthly demand for power with as little error as possible for our industry and national economy. In general, long-term forecasting of power demand has been studied from both the consumer's perspective and an econometrics model in the form of a generalized linear model with predictors. Time series techniques are used for short-term forecasting with no predictors as predictors must be predicted prior to forecasting response variables and containing estimation errors during this process is inevitable. In previous researches, seasonal exponential smoothing method, SARMA (Seasonal Auto Regressive Moving Average) with consideration to weekly pattern Neuron-Fuzzy model, SVR (Support Vector Regression) model with predictors explored through machine learning, and K-means clustering technique in the various approaches have been applied to short-term power supply forecasting. In this paper, SARMA and intervention model are fitted to forecast the maximum power load daily, weekly, and monthly by using the empirical data from 2011 through 2013. $ARMA(2,\;1,\;2)(1,\;1,\;1)_7$ and $ARMA(0,\;1,\;1)(1,\;1,\;0)_{12}$ are fitted respectively to the daily and monthly power demand, but the weekly power demand is not fitted by AREA because of unit root series. In our fitted intervention model, the factors of long holidays, summer and winter are significant in the form of indicator function. The SARMA with MAPE (Mean Absolute Percentage Error) of 2.45% and intervention model with MAPE of 2.44% are more efficient than the present seasonal exponential smoothing with MAPE of about 4%. Although the dynamic repression model with the predictors of humidity, temperature, and seasonal dummies was applied to foretaste the daily power demand, it lead to a high MAPE of 3.5% even though it has estimation error of predictors.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.9
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• pp.4108-4122
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• 2016

To address challenges of an unprecedented growth in mobile data traffic, the ultra-dense network deployment is a cost efficient solution to off-load the traffic over other small cells. However, the real traffic is often much lower than the peak-hour traffic and certain small cells are superfluous, which will not only introduce extra energy consumption, but also impose extra interference onto the radio environment. In this paper, an elastic energy efficient cell management scheme is proposed based on flow scheduling among multi-layer ultra-dense cells by a SDN controller. A significant power saving was achieved by a cell-level energy manager. The scheme is elastic for energy saving, adaptive to the dynamic traffic distribution in the office or campus environment. In the end, the performance is evaluated and demonstrated. The results show substantial improvements over the conventional method in terms of the number of active BSs, the handover times, and the switches of BSs.

• The Journal of Information Technology
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• v.4 no.1
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• pp.39-54
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• 2001

Knowledge can be characterized in many ways. We have categorized internal and external knowledge by its position, tacit and explicit knowledge by the degree of formalization, and general and innovative knowledge by the power of competitive advantage. They is, often, mixed in real world. Under New Economy, firms must conduct the analysis of various knowledge embodied employee's skill, its products and business process, and create a new added value. Knowledge is the important strategic resource and the ability to capture, organize, store and apply is the critical capability for substantial competitive advantage. For establishing the steps of knowledge management strategy, we described below - the identification of intellectual capital, value analysis, the building of knowledge infrastructure, the knowledge organization, value creation, and the knowledge evaluation and dynamic knowledge management.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.6
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• pp.1321-1326
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• 2015

The amount of smart phones has increased exponentially. Due to the periodic release of high-performance smart phones and upgraded operating system, new smart phones become out-dated over 1 or 2 years. In order to solve environmental constraints of these smart phones, virtualization technology using Thin-Client terminal has been developed. However, in the case of Virtual Machine(VM), the applications associated with sensors and a GPS device can not run because they are not included. In this paper, by implementing the device driver for Android running in a virtual machine in the x86-based systems, it is to provide Android virtualization capabilities such as using the latest smart phones in the virtual machine environment. It would like to propose a method that the virtual device driver receives sensors and GPS information from the old Android smart phones(Thin-Client) that actually work and run as if the real device exists.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.6B
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• pp.534-543
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• 2006

As the topology frequently varies, more cluster reconstructing is needed and also management overheads increase in the wireless ad hoc/sensor networks. In this paper, we propose a multi-hop clustering algorithm for wireless sensor network topology management using dynamic pre-clusterhead scheme to solve cluster reconstruction and load balancing problems. The proposed scheme uses weight map that is composed with power level and mobility, to choose pre-clusterhead and construct multi-hop cluster. A clusterhead has a weight map and threshold to hand over functions of clusterhead to pre-clusterhead. As a result of simulation, our algorithm can reduce overheads and provide more load balancing well. Moreover, our scheme can maintain the proper number of clusters and cluster members regardless of topology changes.

• Journal of KIISE:Computing Practices and Letters
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• v.13 no.7
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• pp.454-461
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• 2007

Portable embedded systems have recently become smaller in size and offer a variety of junctions for users. These systems require high performance processors to handle the many functions and also a small battery to fit inside the system. However, due to its size, the battery life has become a major issue. It is important to have both efficient power design and management for each function, while optimizing processor voltage and clock frequency in order to extend the battery life of the system. In this paper, we calculated the efficiency of power in optimizing power rail. This system has two microprocessors. One is used to play music and movie files while the other is for DMB. In order to reduce power consumption, the DMB microprocessor is turned of while music or videos are played. Lastly, DVFS is applied to the processor in the system to reduce power consumption. Experimental results of the implemented system have resulted in reduced power consumption.

• Journal of IKEEE
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• v.20 no.2
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• pp.188-191
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• 2016

In this paper, we propose energy-efficient automatic power controller which can power on and off the signboard at the specified light intensity using the Illuminance Detector. By using segmented section Classification algorithm, light intensity setup system propose variable resistor method which makes users more easy to control. Automatic light on-off system set a standard by measured illuminance data. Measured light-intensity through the Illuminance Detector are communicated with the signboard power controller with wireless communication, and it controls lighting system. In this paper, we evaluated the Energy-Efficient Automatic Power Controller of The Signboard using illuminance detector. Experimental results in lightless environment shows that the error rate is less than 3% by Accredited Testing Laboratories.

• Environmental and Resource Economics Review
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• v.25 no.2
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• pp.229-253
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• 2016

To achieve the socially optimum level of renewable generation, governments should design renewable policies to induce renewable technologies competitive with conventional generation technologies. And to do that, it is needed to understand how each policy has been effective in promoting renewables for power sector. In most of the literatures, there are two key limitations that they did not considered autocorrelation problem using the amount of generation from renewables as a dependent variable and technology innovation which needs to be preceded technology adoption. In this study, I try to overcome these two problems by using dynamic panel model and adding an additional variable for technology innovation. According to the result, FIT has been effective rather than RPS in promoting renewables for generation and I found the possibility that the counterintuitive results which commonly appeared in existing studies might be due to the two limitations mentioned above.

• Journal of KIISE:Computer Systems and Theory
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• v.30 no.5_6
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• pp.307-318
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• 2003

In this paper, we design and construct a TMO object group that provides the guaranteed real-time services in the distributed object computing environments, and verify execution power of its model for the correct distributed real-time services. The TMO object group we suggested is based on TINA's object group concept. This model consists of TMO objects having real-time properties and some components that support the object management service and the real-time scheduling service in the TMO object group. Also TMO objects can be duplicated or non-duplicated on distributed systems. Our model can execute the guaranteed distributed real-time service on COTS middlewares without restricting the specially ORB or the of operating system. For achieving goals of our model. we defined the concepts of the TMO object and the structure of the TMO object group. Also we designed and implemented the functions and interactions of components in the object group. The TMO object group includes the Dynamic Binder object and the Scheduler object for supporting the object management service and the real-time scheduling service, respectively The Dynamic Binder object supports the dynamic binding service that selects the appropriate one out of the duplicated TMO objects for the clients'request. And the Scheduler object supports the real-time scheduling service that determines the priority of tasks executed by an arbitrary TMO object for the clients'service requests. And then, in order to verify the executions of our model, we implemented the Dynamic Binder object and the Scheduler object adopting the binding priority algorithm for the dynamic binding service and the EDF algorithm for the real-time scheduling service from extending the existing known algorithms. Finally, from the numerical analyzed results we are shown, we verified whether our TMO object group model could support dynamic binding service for duplicated or non-duplicated TMO objects, also real-time scheduling service for an arbitrary TMO object requested from clients.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.9
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• pp.1199-1208
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• 2013

In recent years, the development of application programs for distribution system analysis and control has been essential part for distribution management system (DMS). In this paper, we propose the common database for application programs of distribution management system. The proposed database model has several characteristics as followings. First, the proposed database model is designed for the common use of almost the whole distribution application software. The static equipment model and dynamic type tables are mixed and the parallel table structure is applied. Second, the linked list structure of database are used for the fast processing of applications. The database model includes the hierarchy and non-hierarchy distribution system structure. Third, the reduction method of distribution database is applied. For this, we present the network reduction rules. The basic concept of reduction rules are the electrical unification of successive line section which has not lateral branches and the removal of simple lateral branches which has no devices and other laterals. Proposed database model is tested for the Jeju system of Korea Electric Power Corporation (KEPCO). Through the test, we verified that the proposed database structure can be effectively used to accomplish the distribution system operation.