• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.1
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• pp.272-287
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• 2016

Recently, various and effective contrast based salient object detection models to focus on a single target have been proposed. However, there is a lack of research on detection of multiple objects, and also it is a more challenging task than single target process. In the multiple target problem, we are confronted by new difficulties caused by distinct difference between properties of objects. The characteristic of existing models depending on the global maximum distribution of data point would become a drawback for detection of multiple objects. In this paper, by analyzing limitations of the existing methods, we have devised three main processes to detect multiple salient objects. In the first stage, regional features are extracted from over-segmented regions. In the second stage, the regional features are categorized into homogeneous cluster using the mean-shift algorithm with the kernel function having various sizes. In the final stage, we compute saliency scores of the categorized regions using only spatial features without the contrast features, and then all scores are integrated for the final salient regions. In the experimental results, the scheme achieved superior detection accuracy for the SED2 and MSRA-ASD benchmarks with both a higher precision and better recall than state-of-the-art approaches. Especially, given multiple objects having different properties, our model significantly outperforms all existing models.

• Smart Structures and Systems
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• v.13 no.3
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• pp.389-406
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• 2014

Optimal sensor placement techniques play a significant role in enhancing the quality of modal data during the vibration based health monitoring of civil structures, where many degrees of freedom are available despite a limited number of sensors. The literature has shown a shift in the trends for solving such problems, from expansion or elimination approach to the employment of heuristic algorithms. Although these heuristic algorithms are capable of providing a global optimal solution, their greatest drawback is the requirement of high computational effort. Because a highly efficient optimisation method is crucial for better accuracy and wider use, this paper presents an improved simulated annealing (SA) algorithm to solve the sensor placement problem. The algorithm is developed based on the sensor locations' coordinate system to allow for the searching in additional dimensions and to increase SA's random search performance while minimising the computation efforts. The proposed method is tested on a numerical slab model that consists of two hundred sensor location candidates using three types of objective functions; the determinant of the Fisher information matrix (FIM), modal assurance criterion (MAC), and mean square error (MSE) of mode shapes. Detailed study on the effects of the sensor numbers and cooling factors on the performance of the algorithm are also investigated. The results indicate that the proposed method outperforms conventional SA and Genetic Algorithm (GA) in the search for optimal sensor placement.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.2
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• pp.240-244
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• 2007

Non-intrusive methods based on active remote IR illumination fur eye tracking is important for many applications of vision-based man-machine interaction. One problem that has plagued those methods is their sensitivity to lighting condition change. This tends to significantly limit their scope of application. In this paper, we present a new real-time eye detection and tracking methodology that works under variable and realistic lighting conditions. Based on combining the bright-pupil effect resulted from IR light and the conventional appearance-based object recognition technique, our method can robustly track eyes when the pupils are not very bright due to significant external illumination interferences. The appearance model is incorporated in both eyes detection and tracking via the use of support vector machine and the mean shift tracking. Additional improvement is achieved from modifying the image acquisition apparatus including the illuminator and the camera.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.10a
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• pp.281-284
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• 2010

In this paper, we present Hand-gesture recognition for actual computing into color images from camera. Color images are binarization and labeling by using the YCbCr Color model. Respectively label area seeks the center point of the hand from to search Maximum Inscribed Circle which applies Voronoi-Diagram. This time, searched maximum circle and will analyze the elliptic ingredient which is contiguous so a hand territory will be able to extract. we present the presentation contral system using elliptic element and Maximum Inscribed Circle. This algorithm is to recognize the various environmental problems in the hand gesture recognition in the background objects with similar colors has the advantage that can be effectively eliminated.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2006.05a
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• pp.92-100
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• 2006

In many common control charting situations, the statistic to be charted can be viewed as the output of a linear filter applied to the sequence of process measurement data. In recent work that has generalized this concept, the charted statistic is the output of a general linear filter in impulse response form, and the filter is designed by selecting its impulse response coefficients in order to optimize its average run length performance. In this work, we restrict attention to the class of all second-order linear filters applied to the residuals of a time series model of the process data. We present an algorithm for optimizing the design of the second-order filter that is more computationally efficient and robust than the algorithm for optimizing the general linear filter. We demonstrate that the optimal second-order filter performs almost as well as the optimal general linear filter in many situations. Both methods share a number of interesting characteristics and are tuned to detect any distinct features of the process mean shift, as it manifests itself in the residuals.

• Journal of Mechanical Science and Technology
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• v.15 no.8
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• pp.1181-1187
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• 2001

The radiation driven response function (R$\_$q/) for AP and HMX propellant was obtained and compared with experimental results by using a simple $\alpha$$\beta$γ flame model rather than with detailed chemistry. For an AP propellant, the profile of heat release was assumed by the experimental data. The calculated R$\_$q/ shows a frequency shift of the peak amplitude to the higher frequency and a decrease in the maximum amplitude as radiation increases. In addition, it was found the increase in the total flux could enhance the mean burning rate γ$\_$b/ while the phase differences between the radiation and resulting conduction could consequently reduce the fluctuating amplitude Δγ$\_$b/. Fortunately, this is the qualitative duplication of the behavior recently observed in the experiments of RDX propellants. For HMX, the response function R$\_$q/ has been calculated and showed a quite good agreement with the experimental data. Even though the fairly good agreement of R$\_$q/ with experimental ones, the unsteady behavior of HMX was not reproduced as the radiation input increased. This is due to lack of the material properties of HMX or the physical understanding of HMX burning at high pressure.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.8 no.2
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• pp.456-463
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• 2004

Non-intrusive methods based on active remote IR illumination for eye tracking is important for many applications of vision-based man-machine interaction. One problem that has plagued those methods is their sensitivity to lighting condition change. This tends to significantly limit their scope of application. In this paper, we present a new real-time eye detection and tacking methodology that works under variable and realistic lighting conditions. Based on combining the bright-Pupil effect resulted from IR light and the conventional appearance-based object recognition technique, our method can robustly track eyes when the pupils ale not very bright due to significant external illumination interferences. The appearance model is incorporated in both eyes detection and tacking via the use of support vector machine and the mean shift tracking. Additional improvement is achieved from modifying the image acquisition apparatus including the illuminator and the camera.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.1
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• pp.75-83
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• 2008

We propose a welfare interface using multiple fecial features tracking, which can efficiently implement various mouse operations. The proposed system consist of five modules: face detection, eye detection, mouth detection, facial feature tracking, and mouse control. The facial region is first obtained using skin-color model and connected-component analysis(CCs). Thereafter the eye regions are localized using neutral network(NN)-based texture classifier that discriminates the facial region into eye class and non-eye class, and then mouth region is localized using edge detector. Once eye and mouth regions are localized they are continuously and correctly tracking by mean-shift algorithm and template matching, respectively. Based on the tracking results, mouse operations such as movement or click are implemented. To assess the validity of the proposed system, it was applied to the interface system for web browser and was tested on a group of 25 users. The results show that our system have the accuracy of 99% and process more than 21 frame/sec on PC for the $320{\times}240$ size input image, as such it can supply a user-friendly and convenient access to a computer in real-time operation.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.36 no.2
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• pp.112-126
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• 1991

The atmospheric carbon dioxide concentration is ever-increasing and expected to reach about 600 ppmv some time during next century. Such an increase of $CO_2$ may cause a warming of the earth's surface of 1.5 to 4.5$^{\circ}C$, resulting in great changes in natural and agricultural ecosystems. The climatic scenario under doubled $CO_2$ projected by general circulation model of Goddard Institute for Space Studies(GISS) was adopted to evaluate the potential impact of climate change on agroclimatic resources, net primary productivity and rice productivity in Korea. The annual mean temperature was expected to rise by 3.5 to 4.$0^{\circ}C$ and the annual precipitation to vary by -5 to 20% as compared to current normal climate (1951 to 1980), resulting in the increase of possible duration of crop growth(days above 15$^{\circ}C$ in daily mean temperature) by 30 to 50 days and of effective accumulated temperature(EAT=∑Ti, Ti$\geq$1$0^{\circ}C$) by 1200 to 150$0^{\circ}C$. day which roughly corresponds to the shift of its isopleth northward by 300 to 400 km and by 600 to 700 m in altitude. The hydrological condition evaluated by radiative dryness index (RDI =Rn/ $\ell$P) is presumed to change slightly. The net primary productivity under the 2$\times$$CO_2$ climate was estimated to decrease by 3 to 4% when calculated without considering the photosynthesis stimulation due to $CO_2$ enrichment. Empirical crop-weather model was constructed for national rice yield prediction. The rice yields predicted by this model under 2 $\times$ $CO_2$ climatic scenario at the technological level of 1987 were lower by 34-43% than those under current normal climate. The parameters of MACROS, a dynamic simulation model from IRRI, were modified to simulate the growth and development of Korean rice cultivars under current and doubled $CO_2$ climatic condition. When simulated starting seedling emergence of May 10, the rice yield of Hwaseongbyeo(medium maturity) under 2 $\times$ $CO_2$ climate in Suwon showed 37% reduction compared to that under current normal climate. The yield reduction was ascribable mainly to the shortening of vegetative and ripening period due to accelerated development by higher temperature. Any simulated yields when shifted emergence date from April 10 to July 10 with Hwaseongbyeo (medium maturity) and Palgeum (late maturity) under 2 $\times$ $CO_2$ climate did not exceed the yield of Hwaseongbyeo simulated at seedling emergence on May 10 under current climate. The imaginary variety, having the same characteristics as those of Hwaseongbyeo except growth duration of 100 days from seedling emergence to heading, showed 4% increase in yield when simulated at seedling emergence on May 25 producing the highest yield. The simulation revealed that grain yields of rice increase to a greater extent under 2$\times$ $CO_2$-doubled condition than under current atmospheric $CO_2$ concentration as the plant type becomes more erect.

• The Journal of the Acoustical Society of Korea
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• v.40 no.5
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• pp.479-487
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• 2021

In this paper, we propose an Sound Event Detection (SED) model using self-training based on a noisy student model. The proposed SED model consists of two stages. In the first stage, a mean-teacher model based on an Residual Convolutional Recurrent Neural Network (RCRNN) is constructed to provide target labels regarding weakly labeled or unlabeled data. In the second stage, a self-training-based noisy student model is constructed by applying different noise types. That is, feature noises, such as time-frequency shift, mixup, SpecAugment, and dropout-based model noise are used here. In addition, a semi-supervised loss function is applied to train the noisy student model, which acts as label noise injection. The performance of the proposed SED model is evaluated on the validation set of the Detection and Classification of Acoustic Scenes and Events (DCASE) 2020 Challenge Task 4. The experiments show that the single model and ensemble model of the proposed SED based on the noisy student model improve F1-score by 4.6 % and 3.4 % compared to the top-ranked model in DCASE 2020 challenge Task 4, respectively.