• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.19 no.5
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• pp.80-86
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• 2005

Induction motors are a critical component of many industrial processes and are frequently integrated in commercially available equipment. Safety, reliability, efficiency, and performance are some of the major concerns of induction motor applications. Fault tolerant control (FTC) strives to make the system stable and retain acceptable performance under the system faults. All present FTC method can be classified into two groups. The first group is based on fault detection and diagnostics (FDD). The second group is includes of FDD and includes methods such as integrity control, reliable stabilization and simultaneous stabilization. This paper presents the fundamental FDD-based FTC methods, which are capable of on-line detection and diagnose of the induction motors. Therefore, our group has developed the embedded distributed fault tolerant and fault diagnosis system for industrial motor. This paper presents its architecture. These mechanisms are based on two 32-bit DSPs and each TMS320F2407 DSP module processes the stator current, voltage, temperatures, vibration signal of the motor.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.6
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• pp.1106-1118
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• 2006

The Internet has become an important instrument for providing many pieces of information to us. And server systems offer the various services after processing a volume of information, it's network topology also has been complex for providing information. Therefore this expansion means the importance of fast and sustained management of server systems. But most of server systems are located in fire-walls to allow only restricted access. Moreover, due to the difference of management based on the different operating system of each server system, management of server system is not to efficiency. That is, sever administrators have to manage by themselves many kinds of servers by using local-based or socket-based single access applications. Therefore, we design and implement a middleware system which allows to manage many kinds of severs integrally ruling XML-based Web Services which have distributed object technology such as CORBA, Java RMI and DCOM, but are free from platforms or development languages. System also provides location transparency and terminal independence and calls a server system management command to manage systems.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.10
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• pp.2079-2087
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• 2009

This paper describes the iTABLE tabletop tiled display system which is designed for displaying high-resolution scientific visualization. Unlike other tabletop systems that typically use a projection-based single display, iTABLE system is suitable for visualizing and sharing high-resolution data, and it is capable of facilitating group interaction with interactive data visualizations on a table and distributed collaborative visualizations with other tiled displays. First, it surveys prior works on tabletop and tiled display systems as well as scientific visualization, and it describes the design and implementation of iTABLE system, and middleware and an infrared camera-based tangible user interface designed for iTABLE system. It will then discuss some high-resolution scientific visualization applications developed for iTABLE followed by conclusions and future research directions.

• Journal of KIISE:Databases
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• v.35 no.1
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• pp.84-95
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• 2008

Wireless sensor networks have recently emerged as a platform for several applications. By deploying wireless sensor nodes and constructing a sensor network, we can remotely obtain information about the behavior, conditions, and positions of objects in a region. Since sensor nodes operate on batteries, energy-efficient mechanisms for gathering sensor data are indispensable to prolong the lifetime of a sensor network as long as possible. In this paper, we propose a novel clustering algorithm that distributes the energy consumption of a cluster head. First, we analyze the energy consumption if cluster heads and divide each cluster into a collection layer and a transmission layer according to their roles. Then, we elect a cluster head for each layer to distribute the energy consumption of single cluster head. In order to show the superiority of our clustering algorithm, we compare it with the existing clustering algorithm in terms of the lifetime of the sensor network. As a result, our experimental results show that the proposed clustering algorithm achieves about $10%{\sim}40%$ performance improvements over the existing clustering algorithms.

• KIISE Transactions on Computing Practices
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• v.21 no.10
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• pp.651-657
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• 2015

The amount of web traffic has increased as a result of the rapid growth of the use of web-based applications. In order to obtain valuable information from web logs, we need to develop systems that can support interactive, flexible, and efficient ways to analyze and handle large amounts of data. In this paper, we present CERES, a log-based, interactive web analytics system for backbone networks. Since CERES focuses on analyzing web log records generated from backbone networks, it is possible to perform a web analysis from the perspective of a network. CERES is designed for deployment in a server cluster using the Hadoop Distributed File System (HDFS) as the underlying storage. We transform and store web log records from backbone networks into relations and then allow users to use a SQL-like language to analyze web log records in a flexible and interactive manner. In particular, we use the data cube technique to enable the efficient statistical analysis of web log. The system provides users a web-based, multi-modal user interface.

• Journal of KIISE:Computer Systems and Theory
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• v.30 no.7_8
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• pp.359-369
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• 2003

We present efficient generalized algorithms for all-to-all personalized communication operations in a 2D torus. All-to-all personalized communication, or complete exchange, is at the heart of numerous applications, such as matrix transposition, Fast Fourier Transform(FFT), and distributed table lookup. Some algorithms have been Presented when the number of nodes is power-of-2 or multiple-of-four form, but there has been no result for general cases yet. We first present complete exchange algorithm called multiple-Hop-2D when the number of nodes is in the form of multiple-of-two. Then by extending this algorithm, we present two algorithms for an arbitrary number of nodes. Split-and-Merge algorithm first splits the whole network into zones. After each zone performs complete exchange, merge is applied to finish the desired complete exchange. By handling extra steps in Double-Hop-2D algorithm, Modified Double-Hop-2D algorithm performs complete exchange operation for general cases. Finally, we compare the required start-up time for these algorithms.

• The Transactions of the Korean Institute of Power Electronics
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• v.15 no.2
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• pp.159-166
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• 2010

For a grid-connected inverter in distributed generation systems, the current control is essential, and recently, the predictive current control based on a high performance digital signal processors (DSP) to satisfy a fast dynamic response has been widely investigated. However, the performance of predictive current control is degraded by the time delay due to digital implementation, the parameter and measured value errors and the interference of noise, and also theses make system even unstable. Therefore, this paper proposes the predictive current control using grid voltage observer for grid-connected inverter applications. To determine the relevant voltage observer gain, the low-order harmonics of grid voltage are considered, and the effect of filter parameter errors is analyzed. The proposed method has a fast current response capability, the robustness to noise and simple implementation due to voltage sensorless control and the robust current control performance to low-order grid harmonics. The feasibility of the proposed method is verified by simulation and experimental results.

• Journal of Soil and Groundwater Environment
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• v.22 no.6
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• pp.66-73
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• 2017

Empirical erosion models like Universal Soil Loss Equation (USLE) models have been widely used to make spatially distributed soil erosion vulnerability maps. Even if the models detect vulnerable sites relatively well utilizing big data related to climate, geography, geology, land use, etc within study domains, they do not adequately describe the physical process of soil erosion on the ground surface caused by rainfall or overland flow. In other words, such models are still powerful tools to distinguish the erosion-prone areas at large scale, but physics-based models are necessary to better analyze soil erosion and deposition as well as the eroded particle transport. In this study a physics-based soil erosion modeling system was developed to produce both runoff and sediment yield time series at watershed scale and reflect them in the erosion and deposition maps. The developed modeling system consists of 3 sub-systems: rainfall pre-processor, geography pre-processor, and main modeling processor. For modeling system validation, we applied the system for various erosion cases, in particular, rainfall-runoff-sediment yield simulation and estimation of probable maximum sediment (PMS) correlated with probable maximum rainfall (PMP). The system provided acceptable performances of both applications.

• Proceedings of the Korea Water Resources Association Conference
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• 2012.05a
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• pp.39-39
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• 2012

Data assimilation techniques have received growing attention due to their capability to improve prediction in various areas. Despite of their potentials, applicable software frameworks to probabilistic approaches and data assimilation are still limited because the most of hydrologic modelling software are based on a deterministic approach. In this study, we developed a hydrological modelling framework for sequential data assimilation, namely MPI-OHyMoS. MPI-OHyMoS allows user to develop his/her own element models and to easily build a total simulation system model for hydrological simulations. Unlike process-based modelling framework, this software framework benefits from its object-oriented feature to flexibly represent hydrological processes without any change of the main library. In this software framework, sequential data assimilation based on the particle filters is available for any hydrologic models considering various sources of uncertainty originated from input forcing, parameters and observations. The particle filters are a Bayesian learning process in which the propagation of all uncertainties is carried out by a suitable selection of randomly generated particles without any assumptions about the nature of the distributions. In MPI-OHyMoS, ensemble simulations are parallelized, which can take advantage of high performance computing (HPC) system. We applied this software framework for several catchments in Japan using a distributed hydrologic model. Uncertainty of model parameters and radar rainfall estimates is assessed simultaneously in sequential data assimilation.

• Journal of KIISE:Software and Applications
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• v.30 no.11
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• pp.1001-1014
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• 2003

In a feature modeling, problems such as ambiguities, interpretation errors, incompleteness, etc caused by informal specification occur in the modeling phase. Therefore, feature specification method and processes are suggested in this paper to resolve these problems. The structure and language of feature modeling is defined in this paper to specify various features. First, this feature model is abstracted in the meta-level to get predicates and attributes. Formal feature model specification method is proposed using multi-paradigm language. Second, Feature specification process is proposed to describe how to specify feature formally. And third, Feature interaction management is defined to solve the problems caused between specified features. Finally, the proposed feature specification method is applied to Distributed Meeting Scheduler System domain.