• Proceedings of the Korea Information Processing Society Conference
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• 2007.05a
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• pp.741-744
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• 2007

데스크탑 그리드 시스템에서 각 자원에서 수행한 작업 결과에 대한 정확성 검증은 중요한 문제이다. 작업 결과에 대한 정확성을 보장하기 위해서 결과 검증 기법으로 투표기반 기법이나 신뢰기반 기법이 사용되어 왔다. 그러나 이러한 기법들은 동적인 연산 환경에 효과적으로 대처하지 못하여 낮은 확장성과 높은 연산 지연을 초래할 수 있는 단점을 갖고 있다. 이러한 단점을 해결하고자 본 논문에서는 자원제공자에 의해 초래될 수 있는 잘못된 연산 결과에 대해 각 자원제공자의 신용도(credibility)를 동적으로 평가하여 연산 결과의 정확성을 판단하는 적응적 결과 검증 메커니즘(Adaptive Result Verification Mechanism: ARVM)을 제안한다. 또한, 제안하는 ARVM 은 자원제공자의 가용성(availability) 정보를 이용하여 결과 검증 시에 요구되는 연산 지연을 최소화한다.

• Geophysics and Geophysical Exploration
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• v.13 no.1
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• pp.118-127
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• 2010

Resistivity logging instruments are designed to measure the electrical resistivity of a formation, and this can be directly interpreted to provide a water-saturation profile. However, resistivity logs are sensitive to borehole and shoulder-bed effects, which often result in misinterpretation of the results. These effects are emphasised more in the presence of tool eccentricity. For precise interpretation of short- and long-normal logging measurements in the presence of tool eccentricity, we simulate and analyse eccentricity effects by combining the use of a Fourier series expansion in a new system of coordinates with a 2D goal-oriented high-order self-adaptive hp finite-element refinement strategy, where h denotes the element size and p the polynomial order of approximation within each element. The algorithm automatically performs local mesh refinement to construct an optimal grid for the problem under consideration. In addition, the proper combination of h and p refinements produces highly accurate simulations even in the presence of high electrical resistivity contrasts. Numerical results demonstrate that our algorithm provides highly accurate and reliable simulation results. Eccentricity effects are more noticeable when the borehole is large or resistive, or when the formation is highly conductive.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.5
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• pp.84-95
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• 2011

In this paper, we present a deblocking algorithm that removes grid and staircase noises, which are called "blocking artifacts", occurred in the compressed satellite images. Particularly, the given satellite images are compressed with equal quantization coefficients in row according to region complexity, and more complicated regions are compressed more. However, this approach has a problem that relatively less complicated regions within the same row of complicated regions have blocking artifacts. Removing these artifacts with a general deblocking algorithm can blur complex and undesired regions as well. Additionally, the general filter lacks in preserving the curved edges. Therefore, the proposed algorithm presents an adaptive filtering scheme for removing blocking artifacts while preserving the image details including curved edges using the given quantization step size and content analysis. Particularly, WLFPCA (weighted lowpass filter using principle component analysis) is employed to reduce the artifacts around edges. Experimental results showed that the proposed method outperforms SA-DCT in terms of subjective image quality.

• Journal of the Korea Computer Graphics Society
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• v.19 no.3
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• pp.1-11
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• 2013

Fluid Implicit Particle (FLIP) method is used in Visual Effect(VFX) industries frequently because FLIP based simulation show high performance with good visual quality. However in large-scale fluid simulations, the efficiency of FLIP method is low because it requires many particles to represent large volume of water. In this papers, we propose a novel hybrid method of simulating fluids to supplement this drawback. To improve the performance of the FLIP method by reducing the number of particles, particles are deployed inside thin layers of the inner surface of water volume only. The coupling between less-disspative solutions of FLIP method and viscosity solution of level set method is achieved by introducing a new surface reconstruction method motivated by surface reconstruction method[1] and moving least squares(MLS) method[2]. Our hybrid method can generate high quality of water simulations efficiently with various multiscale features.

• Journal of Electrical Engineering and Technology
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• v.12 no.6
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• pp.2099-2105
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• 2017

In a power system that has a high wind penetration, the output power fluctuation of a large-scale wind turbine generator (WTG) caused by the varying wind speed increases the maximum frequency deviation, which is an important metric to assess the quality of electricity, because of the reduced system inertia. This paper proposes a stable power-smoothing scheme of a doubly-fed induction generator (DFIG) that can suppress the maximum frequency deviation, particularly for a power system with a high wind penetration. To do this, the proposed scheme employs an additional control loop relying on the system frequency deviation that operates in combination with the maximum power point tracking control loop. To improve the power-smoothing capability while guaranteeing the stable operation of a DFIG, the gain of the additional loop is modified with the rotor speed and frequency deviation. The gain is set to be high if the rotor speed and/or frequency deviation is large. The simulation results based on the IEEE 14-bus system demonstrate that the proposed scheme significantly lessens the output power fluctuation of a WTG under various scenarios by modifying the gain with the rotor speed and frequency deviation, and thereby it can regulate the frequency deviation within a narrow range.

• Journal of Electrical Engineering and Technology
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• v.11 no.1
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• pp.86-92
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• 2016

Upon detecting a frequency event in a power system, the stepwise inertial control (SIC) of a wind turbine generator (WTG) instantly increases the power output for a preset period so as to arrest the frequency drop. Afterwards, SIC rapidly reduces the WTG output to avert over-deceleration (OD). However, such a rapid output reduction may act as a power deficit in the power system, and thereby cause a second frequency dip. In this paper, a hybrid reference function for the stable SIC of a doubly-fed induction generator is proposed to prevent OD while improving the frequency nadir (FN). To achieve this objective, a reference function is separately defined prior to and after the FN. In order to improve the FN when an event is detected, the reference is instantly increased by a constant and then maintained until the FN. This constant is determined by considering the power margin and available kinetic energy. To prevent OD, the reference decays with the rotor speed after the FN. The performance of the proposed scheme was validated under various wind speed conditions and wind power penetration levels using an EMTP-RV simulator. The results clearly demonstrate that the scheme successfully prevents OD while improving the FN at different wind conditions and wind power penetration levels. Furthermore, the scheme is adaptive to the size of a frequency event.

• Journal of The Korean Society of Agricultural Engineers
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• v.62 no.3
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• pp.71-83
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• 2020

Resilience is the capacity to maintain essential services under a range of circumstances from normal to extreme. It is achieved through the ability of assets, networks, systems and management to anticipate, absorb and recover from disturbance. It requires adaptive capacity in respect of current and future risks and uncertainties as well as experience to date. The agricultural infrastructures with high resilience can not only reduce the size of the disaster relatively, but also minimize the loss by reducing the time required for recovery. This study aims to evaluate the most suitable drought countermeasures with the analysis of various resilience indices by predicting future agricultural water shortage under land use and climate change scenarios for agricultural areas in Jeju Island. The results showed that the permanent countermeasure is suitable than the temporary countermeasures as drought size and the cost required for recovery increase. Wide-area water supply system, which is a kind of water grid system, is identified as the most advantageous among countermeasures. It is recommended to evaluate the capability of agricultural infrastructure against drought with the various Resilience Indices for reliable assessment of long-term effect.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.9
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• pp.2605-2625
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• 2024

Siamese-based segmentation and tracking algorithms improve accuracy and stability for video object segmentation and tracking tasks simultaneously. Although effective, variability in target appearance and background clutter can still affect segmentation accuracy and further influence the performance of tracking. In this paper, we present a memory propagation-based target-aware and mask-attention decision network for robust object segmentation and tracking. Firstly, a mask propagation-based attention module (MPAM) is constructed to explore the inherent correlation among image frames, which can mine mask information of the historical frames. By retrieving a memory bank (MB) that stores features and binary masks of historical frames, target attention maps are generated to highlight the target region on backbone features, thus suppressing the adverse effects of background clutter. Secondly, an attention refinement pathway (ARP) is designed to further refine the segmentation profile in the process of mask generation. A lightweight attention mechanism is introduced to calculate the weight of low-level features, paying more attention to low-level features sensitive to edge detail so as to obtain segmentation results. Finally, a mask fusion mechanism (MFM) is proposed to enhance the accuracy of the mask. By utilizing a mask quality assessment decision network, the corresponding quality scores of the "initial mask" and the "previous mask" can be obtained adaptively, thus achieving the assignment of weights and the fusion of masks. Therefore, the final mask enjoys higher accuracy and stability. Experimental results on multiple benchmarks demonstrate that our algorithm performs outstanding performance in a variety of challenging tracking tasks.

• Journal of KIISE:Databases
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• v.30 no.5
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• pp.451-463
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• 2003

Recently, there have been various research efforts to develop strategies for accelerating OLAP operations on huge amounts of spatio-temporal data. Most of the work is based on multi-tree structures which consist of a single R-tree variant for spatial dimension and numerous B-trees for temporal dimension. The multi~tree based frameworks, however, are hardly applicable to spatio-temporal OLAP in practice, due mainly to high management cost and low query efficiency. To overcome the limitations of such multi-tree based frameworks, we propose a new approach called Hilbert Cube(H-Cube), which employs fractals in order to impose a total-order on cells. In addition, the H-Cube takes advantage of the traditional Prefix-sum approach to improve Query efficiency significantly. The H-Cube partitions an embedding space into a set of cells which are clustered on disk by Hilbert ordering, and then composes a cube by arranging the grid cells in a chronological order. The H-Cube refines cells adaptively to handle regional data skew, which may change its locations over time. The H-Cube is an adaptive, total-ordered and prefix-summed cube for spatio-temporal data warehouses. Our approach focuses on indexing dynamic point objects in static spatial dimensions. Through the extensive performance studies, we observed that The H-Cube consumed at most 20% of the space required by multi-tree based frameworks, and achieved higher query performance compared with multi-tree structures.

• The KIPS Transactions:PartD
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• v.11D no.6
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• pp.1221-1230
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• 2004

In mobile environments, the locations of moving objects such as vehicles, airplanes and users of wireless devices continuously change over time. For efficiently processing moving object information, the database system should be able to deal with large volume of data, and manage indexing efficiently. However, previous research on indexing method mainly focused on query performance, and did not pay attention to update operation for moving objects. In this paper, we propose a novel moving object indexing method, named ACAR-Tree. For processing efficiently frequently updating of moving object location information as well as query performance, the proposed method is based on fixed grid structure with auxiliary R-Tree. This hybrid structure is able to overcome the poor update performance of R-Tree which is caused by reorganizing of R-Tree. Also, the proposed method is able to efficiently deal with skewed-. or gaussian distribution of data using auxiliary R-Tree. The experimental results using various data size and distribution of data show that the proposed method has reduced the size of index and improve the update and query performance compared with R-Tree indexing method.