• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.11
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• pp.5522-5536
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• 2017

In this paper, a video based smoke detection method using dynamic texture feature extraction with volume local binary patterns is studied. Block based method was used to distinguish smoke frames in high definition videos obtained by experiments firstly. Then we propose a method that directly extracts dynamic texture features based on irregular motion regions to reduce adverse impacts of block size and motion area ratio threshold. Several general volume local binary patterns were used to extract dynamic texture, including LBPTOP, VLBP, CLBPTOP and CVLBP, to study the effect of the number of sample points, frame interval and modes of the operator on smoke detection. Support vector machine was used as the classifier for dynamic texture features. The results show that dynamic texture is a reliable clue for video based smoke detection. It is generally conducive to reducing the false alarm rate by increasing the dimension of the feature vector. However, it does not always contribute to the improvement of the detection rate. Additionally, it is found that the feature computing time is not directly related to the vector dimension in our experiments, which is important for the realization of real-time detection.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.10
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• pp.1516-1522
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• 2017

We propose a novel monitoring system for diagnosing crack faults of the wind turbine using image information. The proposed method classifies a normal state and a abnormal state for the blade parts of the wind turbine. Specifically, the images are input to the proposed system in various states of wind turbine rotation. according to the blade condition. Then, the video of rotating blades on the wind turbine is divided into several image frames. Motion vectors are estimated using the previous and current images using the motion estimation, and the change of the motion vectors is analyzed according to the blade state. Finally, we determine the final blade state using the Support Vector Machine (SVM) classifier. In SVM, features are constructed using the area information of the blades and the motion vector values. The experimental results showed that the proposed method had high classification performance and its $F_1$ score was 0.9790.

• Structural Monitoring and Maintenance
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• v.6 no.2
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• pp.125-145
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• 2019

Bridge scour is one of the predominant causes of bridge failure. Current climate deterioration leads to increase of flooding frequency and severity and thus poses a higher risk of bridge scour failure than before. Recent studies have explored extensively the vibration-based scour monitoring technique by analyzing the structural modal properties before and after damage. However, the state-of-art of this area lacks a systematic approach with sufficient robustness and credibility for practical decision making. This paper attempts to develop a data-driven methodology for bridge scour monitoring using support vector machines. This study extracts features from the bridge dynamic responses based on a generic sensitivity study on the bridge's modal properties and selects the features that are significantly contributive to bridge scour detection. Results indicate that the proposed data-driven method can quantify the bridge scour damage with satisfactory accuracy for most cases. This paper provides an alternative methodology for bridge scour evaluation using the machine learning method. It has the potential to be practically applied for bridge safety assessment in case that scour happens.

• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.422-424
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• 1997

In this paper, we characterize the whole class of vector fields that can be linearized by a given nominal state transformation and a feedback linearizing controller. The necessary and sufficient condition for a given uncertain vector field to be so-called "completely linearizable by the nominal coordinate transformation" is given in terms of Lie Bracket of uncertain vector fields and some suitable vector fields of the nominal system.

• Journal of Korean Society of Forest Science
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• v.77 no.2
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• pp.199-207
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• 1988

Three clones of Populus alba ${\times}$ P. grandidentata have been tested for susceptibility to Agrobacterium tumefaciens strains A281 and A348. We determined the optimum concentration of kanamycin sulfate for effective selection of leaf disc-derived, transgenic tissues transformed using Agrobacterium binary vector pGA472 containing a neomycin phosphotransferase gene (NPT-II) which confers kanamycin resistance. Of the wild type Ti plasmids contained by the two Agrobacterium strains, pTiBo542 of strain A281 appears to be best suited to serve as a helper plasmid for binary vector systems. A relatively low concentration (10mg/l) of kanamycin sulfate inhibited adventitious shoot initiation from leaf discs on regeneration medium. Transformed kanamycin-resistant calli were obtained by culturing Agrobacterium inoculated leaf discs on selective regeneration medium. The transformed kanamycin-resistant calli continued to grow on regeneration media supplemented with kanamycin sulfate to levels of 50 and 200mg/l. The growth of non-co-cultivated control calli was severely inhibited on regeneration medium containing 50mg/l kanamycin sulfate.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.3
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• pp.1-7
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• 2004

We demonstrate in this paper that the level crossing technique can be applied to such a system that not only the state vector is two-dimensional but Its two components are heterogeneous. As an example system, we use the GI-G/c/K queue whose state vector consists of the number of customers in the system and the total unfinished work.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.7 no.4
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• pp.7-13
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• 1998

The gloval model is developed by combining this actuator formular with robot manipulator which is reported previously . The model initially represented in the form of coupled time-varying nonlinear dynamic system. It then decomposed into the decoupled linear model using nonlinear feedback and state transformation techniques. The new model employes the pole replacement method to improve the stability of the system. Using this new model, an robust control algorithm is developed. The proposed algorithm takes two state variables, position vector and velocity vector, and one input variable from actuator, input voltage.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1993.04a
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• pp.75-79
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• 1993

본 연구에서는 원통형 셀을 Donnell-Mushitari의 Thin Shell로 모델링하고, 유체의 거동은 Hankel 함수를 배제하고 유한차분법(Finite Difference Method)으로 모델링하여, 상태 벡터(State Vector)해석법, 전달 행렬 및 푸리 에 변환(Fourier Transform)을 사용, 무한 원통형 몰수체의 강제 진동을 해 석하였다.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.12
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• pp.1594-1600
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• 1988

In this paper, an effective method in analyzing a class of bilinear systems via Taylor polynomials is proposed. The result derived by Yang and Chen shows an implicit form for unknown state vector and requires to solve a linear algebraic equation with large dimension when the number of terms used increase. In comparison to the result of Yang and Chen, the method in this paper gives a closed form for unknown state vector and does not need to solve any linear algebraic equation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.2976-2990
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• 2022

The adaptive adjustment of reference or weight vectors in decomposition-based methods has been a hot research topic in the evolutionary community over the past few years. Although various methods have been proposed regarding this issue, most of them aim to diversify solutions in the objective space to cover the true Pareto fronts as much as possible. Different from them, this paper proposes a knee point-based reference vector adaptive adjustment strategy to concurrently balance the convergence and diversity. To be specific, the knee point-based reference vector adaptive adjustment strategy firstly utilizes knee points to construct the adaptive reference vectors. After that, a new fitness function is defined mathematically. Then, this paper further designs a many-objective evolutionary algorithm with knee point-based reference vector adaptive adjustment strategy, where the mating operation and environmental selection are designed accordingly. The proposed method is extensively tested on the WFG test suite with 8, 10 and 12 objectives and MPDMP with state-of-the-art optimizers. Extensive experimental results demonstrate the superiority of the proposed method over state-of-the-art optimizers and the practicability of the proposed method in tackling practical many-objective optimization problems.