• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.805-825
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• 2017

Correlation Filter-based Trackers (CFTs) gained popularity recently for their effectiveness and efficiency. To deal with the size changes of the target which may degenerate the tracking performance, scale estimation has been introduced in existing CFTs. However, the variations of the aspect ratio were usually neglected, which also influence the size of the target. In this paper, Size Aware Correlation Filter Trackers (SACFTs) are proposed to deal with this problem. The SACFTs not only determine the translation and scale variations, but also take the aspect ratio changes into consideration, thus a better estimation of the size of the target can be realized, which improves the overall tracking performance. And competing results can be achieved compared with state-of-the-art methods according to the experiments conducted on two large scale datasets.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.27 no.12
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• pp.767-775
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• 2014

New material design has obtained tremendous attention in material science community as the performance of new materials, especially in nano length scale, could be greatly improved to applied in modern industry. In certain conditions limiting experimental synthesis of these new materials, new approach by computer simulation has been proposed to be applied, being able to save time and cost. Recent development of computer systems with high speed, large memory, and parallel algorithms enables to analyze individual atoms using first principle calculation to predict quantum phenomena. Beyond the quantum level calculations, mesoscopic scale and continuum limit can be addressed either individually or together as a multi-scale approach. In this article, we introduced current endeavors on material design using analytical theory and computer simulations in multi-length scales and on multi-physical properties. Some of the physical phenomena was shown to be interconnected via a cross-link rule called 'cross-property relation'. It is suggested that the computer simulation approach by multi-physics analysis can be efficiently applied to design new materials for multi-functional characteristics.

• Nuclear Engineering and Technology
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• v.55 no.2
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• pp.493-505
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• 2023

Comprehensive condition monitoring of large industry systems such as nuclear power plants (NPPs) is essential for safety and maintenance. In this study, we developed novel system-scale diagnostic technology based on deep-learning and IR thermography that can efficiently and cost-effectively classify system conditions using compact Raspberry Pi and IR sensors. This diagnostic technology can identify the presence of an abnormality or accident in whole system, and when an accident occurs, the type of accident and the location of the abnormality can be identified in real-time. For technology development, the experiment for the thermal image measurement and performance validation of major components at each accident condition of NPPs was conducted using a thermal-hydraulic integral effect test facility with compact infrared sensor modules. These thermal images were used for training of deep-learning model, convolutional neural networks (CNN), which is effective for image processing. As a result, a proposed novel diagnostic was developed that can perform diagnosis of components, whole system and accident classification using thermal images. The optimal model was derived based on the modern CNN model and performed prompt and accurate condition monitoring of component and whole system diagnosis, and accident classification. This diagnostic technology is expected to be applied to comprehensive condition monitoring of nuclear power plants for safety.

• Journal of applied mathematics & informatics
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• v.25 no.1_2
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• pp.293-304
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• 2007

In this paper, we present a Krylov subspace based projection method for reduced-order modeling of large scale bilinear multi-input multi-output (MIMO) systems. The reduced-order bilinear system is constructed in such a way that it can match a desired number of moments of multi-variable transfer functions corresponding to the kernels of Volterra series representation of the original system. Numerical examples report the effectiveness of this method.

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 2008.11a
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• pp.99-104
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• 2008

The combustion properties of sandwich panels were tested and analyzed according to ISO 13784-1(Room Corner Test for Sandwich panel building systems) test method for the purpose of establishing the classification of reaction to fire performance. Several variables including heat release rate, smoke production rate, FIGRA, SMOGRA, and so on, were analyzed for specific four materials about sandwich panel systems on each 5 times, totally 20 times. Finally, elements for Classification system were suggested and evaluations for those elements were made.

• Proceedings of the Korean Society for Quality Management Conference
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• 1998.11a
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• pp.393-403
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• 1998

The advent of very large scale integration(VLSI) has had a tremendous impact on the design of fault-tolerant circuits and systems. The increasing density, decreasing power consumption, and decreasing costs of integrated circuits, due in part to VLSI, have made it possible and practical to implement the redundancy approaches used in fault-tolerant computing. The purpose of this paper is to study the many aspects of designing fault-tolerant systems in a VLSI environment. First, we expound upon the opportunities and problemes presented by VLSI technology. Second, we consider in detail the importance of design mistakes, common-mode failures, and transient faults in VLSI. Finally, we examine the techniques available to implement redundancy using VLSI and the problems associated with these techniques.

• 시스템엔지니어링워크숍
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• s.4
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• pp.155-158
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• 2004

In executing the large scale national project, such as development of space launch vehicle, it is most important to guarantee the technological reliability. However the reliability analysis of launch vehicle is different from other mass product goods because of the limitation of budget and number of tests. In this study, the reliability analysis technique of the propulsion system, which is one of the major sub-systems of launch vehicle is illustrated applied to the liquid rocket engine of KSR-Ⅲ.Ȁ

• Proceedings of the Korea Society for Industrial Systems Conference
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• 1998.10a
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• pp.827-834
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• 1998

This paper describes a multi-level simulation technique and its implementation, which accurately solve voltages and currents of circuits descreibed at mixed levels of abstractions. A metho to form a tightly coupled simulation environment is proposed and, starting from a description of a circuit, simulation set-up and analysis procedure of the multi-level simulator for a transient response are presented. Circuit and behavioral simulation techniques and their implementations composing the multi-level simulation are explained in detail. Most of the algorithms implemented in the simulation are based upon the standard simulation techniques in order to obtain the reliability and accuracy of conventinoal simulators. Simulation examples show that the multi-level simulator can analyze circuits containing highly nonlinear behavioral models without loss of accuracy provided the behavioral models are accurate enough.

• Proceedings of the Korea Water Resources Association Conference
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• 2006.05a
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• pp.354-359
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• 2006

The analysis of large-scale water resources systems is often complicated by the presence of multiple reservoirs and diversions, the uncertainty of unregulated inflows and demands, and conflicting objectives. Reinforcement learning is presented herein as a new approach to solving the challenging problem of stochastic optimization of multi-reservoir systems. The Q-Learning method, one of the reinforcement learning algorithms, is used for generating integrated monthly operation rules for the Keum River basin in Korea. The Q-Learning model is evaluated by comparing with implicit stochastic dynamic programming and sampling stochastic dynamic programming approaches. Evaluation of the stochastic basin-wide operational models considered several options relating to the choice of hydrologic state and discount factors as well as various stochastic dynamic programming models. The performance of Q-Learning model outperforms the other models in handling of uncertainty of inflows.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.193-198
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• 2001

In the large scale B2B transaction like buying Express-Train or selling Daewoo Motor, a tremendous amount of variables and factors of chaos functionate in it directly or indirectly. To get effective information processing on the so called complex system like this, it should be possible to unite the global insight power of the human being and the local computing power of the machine. In this paper, we suggested a union model of human being and machine using Hugent concept. Hugent is defined as an agent model which allows us to chemically unite the human's component and the machine's component in terms of information processing. In this paper, we showed that some typical problems contained in the complex system can be treated more easily through the suggested Hugent concept.