• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.9C
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• pp.1258-1268
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• 2004

We propose a new fast, algorithm which is used for detecting frontal face in the frequency domain based on human skin-color using OCT coefficient of dynamic image compression and skin color information. The region where each pixel has a value of skin-color were extracted from U and V value based on DCT coefficient obtained in the process of Image compression using skin-color map in the Y, U, V color space A morphological filter and labeling method are used to eliminate noise in the resulting image We propose the algorithm to detect fastly human face that estimate the directional feature and variance of luminance block of human skin-color Then Extraction of face was completed adaptively on both background have the object analogous to skin-color and background is simple in the proposed algorithm The performance of face detection algorithm is illustrated by some simulation results earned out on various races We confined that a success rate of 94 % was achieved from the experimental results.

• The Journal of the Acoustical Society of Korea
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• v.22 no.7
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• pp.603-611
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• 2003

This paper proposes an effective feature compensation scheme based on speech model for achieving robust speech recognition. Conventional model-based method requires off-line training with noisy speech database and is not suitable for online adaptation. In the proposed scheme, we can relax the off-line training with noisy speech database by employing the parallel model combination technique for estimation of correction factors. Applying the model combination process over to the mixture model alone as opposed to entire HMM makes the online model combination possible. Exploiting the availability of noise model from off-line sources, we accomplish the online adaptation via MAP (Maximum A Posteriori) estimation. In addition, the online channel estimation procedure is induced within the proposed framework. For more efficient implementation, we propose a selective model combination which leads to reduction or the computational complexities. The representative experimental results indicate that the suggested algorithm is effective in realizing robust speech recognition under the combined adverse conditions of additive background noise and channel distortion.

• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1407-1418
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• 2014

Korean youth spend tremendous time in school for preparing for college admissions. Their academic achievement and overall satisfaction with their lives are affected by how well they adapt to life in school. Successful adaptation to school is important enough to affect a student's future social life. One of the factors that affect adaptation to school is the psychological condition of adolescent anxiety. Anxiety is one of the common mental disorders that appear in people who are not familiar with new environments. Anxiety is known to be related to behavioral problems, and problems with psychological and emotional adaptation. This condition is dramatically increased in adolescents.Parental conflict in particular is known to be a major factor in affecting youth anxiety. As parental conflict became more severe, children felt more negative emotions such as anger, sadness and worry. Moreover, when a child's issue caused the parental conflict, there were more side effects in the emotional condition of the child. This study shows how parental conflict affects a child's anxiety and a child's school life.This problem is analyzed through structural equation modeling.

• Journal of the Korean Society of Child Welfare
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• no.58
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• pp.231-262
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• 2017

South Korea has long been a culturally homogenous society, yet the increasing number of immigrants has turned the country into a multicultural society. Therefore, many empirical studies have investigated the way immigrants adapt to the Korean society and its associated factors. However, examining the overall process of migration (from family separation to reunification and cultural adaptation to the host society) that immigrant youth usually experience has been understudied. Previous empirical research and theoretical work have identified prominent factors that predict immigrant youth's mental health: experiences of family separation, living with others rather than primary caretakers during the separation, the length of residency in the host society, and family and peer support. In this respect, this exploratory and preliminary study that examined whether the experience of migration process and post-migration are related to Korean immigrant youth's mental health problems (depression, anxiety, and suicidal ideation). The result indicated that longer duration of family separation; living with relatives, siblings; and friends rather than primary caretakers during the separation; receiving less support from family and peer after migration; and a lower degree of cultural adaptation to Korean culture were associated with depression, anxiety, and suicidal ideation. Drawing upon the results, this study discussed implications for policy and practice.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.61-71
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• 2004

Recently, various techniques for face detection are studied, but most of them still have problems on processing in real-time. Therefore, in this paper, we propose novel techniques for real-time detection of human faces in sequential images using motion and chroma information. First, background model is used to find a moving area. In this procmoving area. edure, intensity values for reference images are averaged, then skin-color are detected in We use HCr color-space model and adaptive threshold method for detection. Second, binary image labeling is applied to acquire candidate regions for faces. Candidates for mouth and eyes on a face are obtained using differences between green(G) and blue(B), intensity(I) and chroma-red(Cr) value. We also considered distances between eye points and mouth on a face. Experimental results show effectiveness of real-time detection for human faces in sequential images.

• Journal of the Institute of Convergence Signal Processing
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• v.9 no.1
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• pp.1-9
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• 2008

One of the problems for implementing the spot detection phase in the 2-DE gel image analysis program is the eliminating noises in the image. Remained noises after the preprocessing phase cause the over-segmented regions by the segmentation phase. To identify and exclude the over-segmented background regions, if we use the fixed thresholding method that is choosing an intensity value for the threshold, the spots that is invisible by the eyes but mean a very small amount proteins which have important role in the biological samples could be eliminated. This paper propose an adaptive thresholding method that come from an idea that is got on statistical analysing for the prominences of the peaks. The adaptive thresholding method works as following. Firstly we calculate an average prominence value curve and fit it to exponential function curve, as a result we get parameters for the exponential function. And then we calculate a threshold value by using the parameters and probability distribution of errors. Lastly we apply the threshold value to the region for determining the region is a noise or not. According to the probability distribution of errors, the reliability is 99.85% and we show the correctness of the proposed method by representing experiment results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.9C
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• pp.863-870
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• 2009

Bilateral filter (BF) is a nonlinear filter for sharpness enhancement and noise removal. The BF performs the function by the two Gaussian filters, the domain filter and the range filter. To apply the BF to infrared (IR) small target detection, the standard deviation of the two Gaussian filters need to be changed adaptively between the background region and the target region. This paper presents a new BF with the adaptive standard deviation based on the analysis of the edge component of the local window, also having the variable filter size. This enables the BF to perform better and become more suitable in the field of small target detection Experimental results demonstrate that the proposed method is robust and efficient than the conventional methods.

• The Journal of the Acoustical Society of Korea
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• v.39 no.3
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• pp.179-190
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• 2020

In this paper, we estimated the Direction of Arrival (DOA) using Conventional BeamForming (CBF), adaptive beamforming and compressive beamforming. Minimum Variance Distortionless Response (MVDR) and Multiple Signal Classification (MUSIC) are used as the adaptive beamforming, and grid-free compressive sensing is applied for the compressive sensing beamforming. Theoretical background and limitations of each technique are introduced, and the performance of each technique is compared through simulation and real experiments. The real experiments are conducted in the presence of reflected signal, transmitting a sound using two speakers and receiving acoustic data through a linear array consisting of eight microphones. Simulation and experimental results show that the adaptive beamforming and the grid-free compressive beamforming have a higher resolution than conventional beamforming when there are uncorrelated signals. On the other hand, the performance of the adaptive beamforming is degraded by the reflected signals whereas the grid-free compressive beamforming still improves the conventional beamforming resolution regardless of reflected signal presence.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.39 no.2
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• pp.69-78
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• 2002

This paper addresses a method to automatically detect out a person's face from a given image that consists of a hair and face view of the person and a complex background scene. Out method involves an effective detection algorithm that exploits the spatial distribution characteristics of human skin color via an adaptive fuzzy color classifier (AFCC), The universal skin-color map is derived on the chrominance component of human skin color in Cb, Cr and their corresponding luminance. The desired fuzzy system is applied to decide the skin color regions and those that are not. We use RGB model for extracting the hair color regions because the hair regions often show low brightness and chromaticity estimation of low brightness color is not stable. After some preprocessing, we apply convex-hull to each region. Consequent face detection is made from the relationship between a face's convex-hull and a head's convex-hull. The algorithm using the convex-hull shows better performance than the algorithm using pattern method. The performance of the proposed algorithm is shown by experiment. Experimental results show that the proposed algorithm successfully and efficiently detects the faces without constrained input conditions in color images.

• Explosives and Blasting
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• v.35 no.1
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• pp.34-42
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• 2017

It is very difficult to clearly define the damages caused by blasting-induced noise and vibration, because the damages depend on, besides the level of noise and vibration, the response of the object, environmental conditions, subjective feeling, and mental condition. Especially, it is more difficult when the fish is concerned, because that experimental approach is not easy and that we lack of the reasonable criterion for the acceptance level of noise and vibration. In Korea, the acceptance level for damage due to underwater noise is 140 dB re $1{\mu}Pa$, and the difference from the underwater background sound level is defined as more than 20 dB re $1{\mu}Pa$. It is however, appropriate for continuous noise not for transient sound. The authors compared the relationship between vibration velocity and underwater noise measured from the test blasting around Marphysa sanguinea farm. This paper presents the measurement results and suggestions the acceptance level for damage due to underwater noise from explosive blasting.