• The Journal of Engineering Geology
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• v.32 no.3
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• pp.377-388
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• 2022

Recently, several studies have utilized machine learning to efficiently and accurately analyze seismic data that are exponentially increasing. In this study, we expand earthquake information such as occurrence time, hypocentral location, and magnitude to produce a dataset for applying to machine learning, reducing the dimension of the expended data into dominant features through principal component analysis. The dimensional extended data comprises statistics of the earthquake information from the Global Centroid Moment Tensor catalog containing 36,699 seismic events. We perform data preprocessing using standard and max-min scaling and extract dominant features with principal components analysis from the scaled dataset. The scaling methods significantly reduced the deviation of feature values caused by different units. Among them, the standard scaling method transforms the median of each feature with a smaller deviation than other scaling methods. The six principal components extracted from the non-scaled dataset explain 99% of the original data. The sixteen principal components from the datasets, which are applied with standardization or max-min scaling, reconstruct 98% of the original datasets. These results indicate that more principal components are needed to preserve original data information with even distributed feature values. We propose a data processing method for efficient and accurate machine learning model to analyze the relationship between seismic data and seismic behavior.

• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.285-288
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• 2002

Compression of magnetic resonance images (MRI) has proved to be more difficult than other medical imaging modalities. In an average sized hospital, many tora bytes of digital imaging data (MRI) are generated every year, almost all of which has to be kept. The medical image compression is currently being performed by using different algorithms. In this paper, Fuzzy C-Means (FCM) algorithm is used for the Vector Quantization (VQ). First, a digital image is divided into subblocks of fixed size, which consists of 4${\times}$4 blocks of pixels. By performing 2-D Discrete Cosine Transform (DCT), we select six DCT coefficients to form the feature vector. And using FCM algorithm in constructing the VQ codebook. By doing so, the algorithm can make good time quality, and reduce the processing time while constructing the VQ codebook.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.6 no.2
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• pp.10-18
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• 1997

This paper presents the development of real-time estimation and control details for a computer vision-based robot control method. This is accomplished using a sequential estimation scheme that permits placement of these points in each of the two-dimensional image planes of monitoring cameras. Estimation model is developed based on a model that generalizes know 4-axis Scorbot manipulator kinematics to accommodate unknown relative camera position and orientation, etc. This model uses six uncertainty-of-view parameters estimated by the iteration method. The method is tested experimentally in two ways : First the validity of estimation model is tested by using the self-built test model. Second, the practicality of the presented control method is verified in performing 4-axis manipulator's assembly task. These results show that control scheme used is precise and robust. This feature can open the door to a range of application of multi-axis robot such as deburring and welding.

• Journal of information and communication convergence engineering
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• v.9 no.5
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• pp.505-509
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• 2011

This paper attempts to classify known facial expressions and to establish the correlations between two regions (eye + eyebrows and mouth) in identifying the six prototypic expressions. Covariance is used to describe region texture that captures facial features for classification. The texture captured exhibit the pattern observed during the execution of particular expressions. Feature matching is done by simple distance measure between the probe and the modeled representations of eye and mouth components. We target JAFFE database in this experiment to validate our claim. A high classification rate is observed from the mouth component and the correlation between the two (eye and mouth) components. Eye component exhibits a lower classification rate if used independently.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1995.10a
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• pp.1114-1119
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• 1995

This paper presents the development of estimation model and control method based on the new computer vision. This proposed control method is accomplished using a sequential estimation scheme that permits placement of the rigid body in each of the two-dimensional image planes of monitoring cameras. Estimation model with six parameters is developed based on a model that generalizes known 4-axis scara robot kinematics to accommodate unknown relative camera position and orientation, etc. Based on the estimated parameters,depending on each camers the joint angle of robot is estimated by the iteration method. The method is tested experimentally in two ways, the estimation model test and a three-dimensional rigid body placement task. Three results show that control scheme used is precise and robust. This feature can open the door to a range of application of multi-axis robot such as assembly and welding.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2000.04a
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• pp.366-369
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• 2000

This paper examines three algorithms to recognize speaker's emotion using the speech signals. Target emotions are happiness, sadness, anger, fear, boredom and neutral state. MLB(Maximum-Likeligood Bayes), NN(Nearest Neighbor) and HMM (Hidden Markov Model) algorithms are used as the pattern matching techniques. In all cases, pitch and energy are used as the features. The feature vectors for MLB and NN are composed of pitch mean, pitch standard deviation, energy mean, energy standard deviation, etc. For HMM, vectors of delta pitch with delta-delta pitch and delta energy with delta-delta energy are used. We recorded a corpus of emotional speech data and performed the subjective evaluation for the data. The subjective recognition result was 56% and was compared with the classifiers' recognition rates. MLB, NN, and HMM classifiers achieved recognition rates of 68.9%, 69.3% and 89.1% respectively, for the speaker dependent, and context-independent classification.

• Journal of Korean Medical classics
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• v.18 no.4 s.31
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• pp.145-154
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• 2005

The SangHanIlJeGeum(傷寒-提金) explain the six channel of disease. The Greater Yang controls the construction and defence, and governs the exterior of the body, which serves as the body's external barrier. Accordingly, many of the signs associated with greater yang appear in the early stages of disease. The essential features of greater yang disease are a pulse that is floating, headache, stiffness and pain of the head and nape, heateffusion, and aversion to cold. The main feature of Yang brightness disease is yang hyperactivity and heat exuberance. An evil can directly enter the yang brightness channel from the exterior, but it usually passes into the channel from the greater yang. Yang brightness disease is generally characterized by generalized heat effusion, spontaneous sweating, aversion not to cold but to heat, and a pulse that is large. Distinction is made between a heat patter and a repletion pattern.

• Proceedings of the Korea Contents Association Conference
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• 2004.11a
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• pp.505-510
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• 2004

This paper suggests a new CT-image segmentation algorithm. This algorithm uses morphological filters and the watershed algorithms. The proposed CT-image segmentation algorithm consists of six parts: preprocessing, image simplification, feature extraction, decision making, region merging, and postprocessing. By combining spatial and temporal information, we can get more accurate segmentation results. The simulation results illustrate not only the segmentation results of the conventional scheme but also the results of the proposed scheme; this comparison illustrates the efficacy of the proposed technique. Furthermore, we compare the various medical images of the structuring elements. Indeed, to illustrate the improvement of coding efficiency in postprocessing, we use differential chain coding for the shape coding of results.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2001.09a
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• pp.231-234
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• 2001

When constructing subsurface structures and/or wells, the precise estimates of hydraulic parameters must be obtained for operating safety and/or for developing necessary quantity of groundwater. Hydraulic conductivity is mainly subjected to the characteristics of fracture network in the fractured media such as fracture orientation and angle, fracture aperture and frequency, fracture length, interconnectivity of fractures, and filling material, feature of fracture plane. In this study we conducted water injection test at afferent depths on six boreholes drilled in granite of Mt. Geumjeong. hydraulic conductivity was calculated using Moye and Hvorslev methods. The relation between hydraulic conductivity and fracture frequency data obtained from acoustic televiewer and core log were analyzed. The result shows that the correlation between the hydraulic conductivity and the fracture frequency data obtained from acoustic televiewer is better than that with the core log.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.5 no.1
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• pp.1-6
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• 2005

In this paper, we propose an emotion recognition method using the facial images and speech signals. Six basic emotions including happiness, sadness, anger, surprise, fear and dislike are investigated. Facia] expression recognition is performed by using the multi-resolution analysis based on the discrete wavelet. Here, we obtain the feature vectors through the ICA(Independent Component Analysis). On the other hand, the emotion recognition from the speech signal method has a structure of performing the recognition algorithm independently for each wavelet subband and the final recognition is obtained from the multi-decision making scheme. After merging the facial and speech emotion recognition results, we obtained better performance than previous ones.