• Atmosphere
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• v.22 no.1
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• pp.1-12
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• 2012

The Atmospheric motion vectors (AMVs) derived using infrared (IR) channel imagery of geostationary satellites have been utilized widely for real-time weather analysis and data assimilation into global numerical prediction model. As the horizontal resolution of sensors on-board satellites gets higher, it becomes possible to identify atmospheric motions induced by convective clouds ($meso-{\beta}$ and $meso-{\gamma}$ scales). The National Institute of Meteorological Research (NIMR) developed the high resolution visible (HRV) AMV algorithm to detect mesoscale atmospheric motions including ageostrophic flows. To retrieve atmospheric motions smaller than $meso-{\beta}$ scale effectively, the target size is reduced and the visible channel imagery of geostationary satellite with 1 km resolution is used. For the accurate AMVs, optimal conditions are decided by investigating sensitivity of algorithm to target selection and correction method of height assignment. The results show that the optimal conditions are target size of 32 km ${\times}$ 32 km, the grid interval as same as target size, and the optimal target selection method. The HRV AMVs derived with these conditions depict more effectively tropical cyclone OMAIS than IR AMVs and the mean speed of HRV AMVs in OMAIS is slightly faster than that of IR AMVs. Optimized mesoscale AMVs are derived for 6 months (Feb. 2010-Jun. 2010) and validated with radiosonde observations, which indicates NIMR's HRV AMV algorithm can retrieve successfully mesoscale atmospheric motions.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.4
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• pp.676-683
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• 2011

In this paper, we propose a robust method which can detect and track a high-speed small approaching target in a cluttered environment for Korean Active Protection System. The proposed method uses a temporal and spatial filter, tracking filter to detect and track a single target in consecutive order. And it is comprised of a candidate target detection step, a prior target selection step and a target tracking. Field tests on real infrared image sequences show that the proposed method could stably track a high speed and small target in complex background and target occlusion.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.28 no.9
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• pp.733-739
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• 2017

This paper is a study on PRF selection method to accurately detect the target in the target tracking mode of airborne radar. The proposed methods are an 'optimization' method to select the closest to the center of the allowable zone considering the uncertainty of the target distance and velocity prediction and a 'quasi-optimization' method to improve the real time performance. In addition, the characteristics of the proposed methods are compared and analyzed through cost function and calculation time.

• Industrial Engineering and Management Systems
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• v.14 no.2
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• pp.210-219
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• 2015

A classification task requires an exponentially growing amount of computation time and number of observations as the variable dimensionality increases. Thus, reducing the dimensionality of the data is essential when the number of observations is limited. Often, dimensionality reduction or feature selection leads to better classification performance than using the whole number of features. In this paper, we study the possibility of utilizing the Markov blanket discovery algorithm as a new feature selection method. The Markov blanket of a target variable is the minimal variable set for explaining the target variable on the basis of conditional independence of all the variables to be connected in a Bayesian network. We apply several Markov blanket discovery algorithms to some high-dimensional categorical and continuous data sets, and compare their classification performance with other feature selection methods using well-known classifiers.

• Journal of Korea Society of Industrial Information Systems
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• v.5 no.2
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• pp.56-61
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• 2000

The quality of English to Korean Machine Translation depends on how well it deals with target word selection of verbs containing enormous ambiguity. Verb sense disambiguation can be done by using collocation, but the construction of verb collocations costs a lot of efforts and expenses. So, existing methods should be examined in the practical view points. This paper describes the practical method of target word selection using existing collocation and semantic distance computed from minimum semantic features of nouns.

• Journal of the Ergonomics Society of Korea
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• v.34 no.1
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• pp.19-27
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• 2015

Objective: The aim of this study is to investigate how well eye movement times in visual target selection tasks by an eye input device follows the typical Fitts' Law and to compare vertical and horizontal eye movement times. Background: Typically manual pointing provides excellent fit to the Fitts' Law model. However, when an eye input device is used for the visual target selection tasks, there were some debates on whether the eye movement times in can be described by the Fitts' Law. More empirical studies should be added to resolve these debates. This study is an empirical study for resolving this debate. On the other hand, many researchers reported the direction of movement in typical manual pointing has some effects on the movement times. The other question in this study is whether the direction of eye movement also affects the eye movement times. Method: A cursor movement times in visual target selection tasks by both input devices were collected. The layout of visual targets was set up by two types. Cursor starting position for vertical movement times were in the top of the monitor and visual targets were located in the bottom, while cursor starting positions for horizontal movement times were in the right of the monitor and visual targets were located in the left. Results: Although eye movement time was described by the Fitts' Law, the error rate was high and correlation was relatively low ($R^2=0.80$ for horizontal movements and $R^2=0.66$ for vertical movements), compared to those of manual movement. According to the movement direction, manual movement times were not significantly different, but eye movement times were significantly different. Conclusion: Eye movement times in the selection of visual targets by an eye-gaze input device could be described and predicted by the Fitts' Law. Eye movement times were significantly different according to the direction of eye movement. Application: The results of this study might help to understand eye movement times in visual target selection tasks by the eye input devices.

• Proceedings of the IEEK Conference
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• 2009.05a
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• pp.264-266
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• 2009

A skill is defined as the special ability to do something well, especially as acquired by learning and practice. To learn a skill, a Bayesian network model for representing the skill is first learned. We will regard the Bayesian network for a skill as an affordance. We propose a soft Behavior Motivation(BM) switch as a method for ordering affordances to accomplish a task. Then, a skill is constructed as a combination of an affordance and a soft BM switch. To demonstrate the validity of our proposed method, some experiments were performed with GENIBO(Pet robot) performing a task using skills of Search-a-target-object, Approach-a-target-object, Push-up-in front of -a-target-object.

• The Journal of the Acoustical Society of Korea
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• v.31 no.1
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• pp.39-50
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• 2012

A voice transformation (VT) method that can make the utterance of a source speaker mimic that of a target speaker is described. Speaker individuality transformation is achieved by altering three feature parameters, which include the LPC cepstrum, pitch period and gain. The main objective of this study involves construction of an optimal sequence of features selected from a target speaker's database, to maximize both the correlation probabilities between the transformed and the source features and the likelihood of the transformed features with respect to the target model. A set of two-pass conversion rules is proposed, where the feature parameters are first selected from a database then the optimal sequence of the feature parameters is then constructed in the second pass. The conversion rules were developed using a statistical approach that employed a maximum likelihood criterion. In constructing an optimal sequence of the features, a hidden Markov model (HMM) was employed to find the most likely combination of the features with respect to the target speaker's model. The effectiveness of the proposed transformation method was evaluated using objective tests and informal listening tests. We confirmed that the proposed method leads to perceptually more preferred results, compared with the conventional methods.

• Communications for Statistical Applications and Methods
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• v.9 no.3
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• pp.809-824
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• 2002

we propose two methods which separate the variable selection step and the split-point selection step. We call these two algorithms as CHITES method and F&CHITES method. They adapted some of the best characteristics of CART, CHAID, and QUEST. In the first step the variable, which is most significant to predict the target class values, is selected. In the second step, the exhaustive search method is applied to find the splitting point based on the selected variable in the first step. We compared the proposed methods, CART, and QUEST in terms of variable selection bias and power, error rates, and training times. The proposed methods are not only unbiased in the null case, but also powerful for selecting correct variables in non-null cases.

• Journal of the Earthquake Engineering Society of Korea
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• v.15 no.5
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• pp.1-10
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• 2011

This paper proposes an efficient method for selecting ground motions with the mean response spectrum matching a target spectrum. Since former studies reported that the shape and amplitude of the response spectra can be treated independently for selecting ground motions, this study first selects ground motions such that the shape of their mean response spectrum matches that of the target spectrum, then scales the ground motions. To select the ground motions best matching the shape of the target response spectrum, the standard deviation of the difference between the target response spectrum and the mean response spectrum of the selected ground motions needs to be minimized. Unlike the existing procedure, the scaling factor can be computed without iteration. Based on the selection results of 7 ground motions from a library of 40 ground motions, the proposed method is verified as an accurate and efficient method.