• KIEAE Journal
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• v.15 no.3
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• pp.29-36
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• 2015

Purpose: This study is as only basic research for the model Development of the New-Hanok Type Service Facilities in Apartment Housing, which is as a decisive factor used as a planning element for developing the model inherited tradition, There aimed at extracting the genetic factor of Korea's traditional architecture. Method: For this purpose, Consider the concept and regulations of the New-Hanok Type Service Facilities in Apartment Housing and examined the Domestic Application Status of the New-Hanok Type Service Facilities in Apartment Housing. It sets direction of the New-Hanok Type models development based on Expert advice and the literature, and was reviewed a primal reason system of Korea as an extraction base of genetic factors. Result: Then Through the framework of the vertical axis (the form), the horizontal axis (space), It extracted the genetic factors of the Korea Traditional Architecture, classified the genetic factors extracted as the structure(layout, construction, space), features, traditional beauty, investigated the content of the form representation and spatial meaning, and were characterized. Based on the result, It were comprehensive the genetic factors extracted as plan Elements for inheriting of the traditions.

• Journal of Korea Society of Industrial Information Systems
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• v.6 no.1
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• pp.33-38
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• 2001

In this paper, we present an image retrieval system using shape features. The preprocessing to gain shape feature includes edge extraction using chain code. The shape features consist of center of mass, standard deviation, ratio of major axis and minor axis length. The similarity is estimated as comparing the features of query image with the features of images in database. Thus, the candidates of images are retrieved according to the order of similarity. The result of an experimentation is dullness for scale, rotation and translation. We evaluate the performance of shape features for image retrieval on a database with over 170 images. The Recall and the Precision is each 0.72 and 0.83 in the result of average experiment. So the proposed method is presented useful method.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.242-242
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• 2002

The Earth's magnetic field acquired from KOMPSAT-1's TAM (Three-Axis Magnetometer) between June 19th and 21st 2000 was analyzed. The TAM, one of the KOMPSAT-1's Attitude and Orbit Control Subsystems, plays an important role in determining and controlling the satellite's attitude. This also can provide new insight on the Earth's magnetic field. By transforming the satellite coordinate from ECI to ECEF, spherical coordinate of total magnetic field was achieved. These data were grouped into dusk (ascending) and dawn (descending) data sets, based on their local magnetic times. This partitioning is essential for performing 1-D WCA (Wavenumber Correlation Analysis). Also, this enhances the perception of external fields in the Kompsat-1's TAM magnetic maps that were compiled according to different local. The dusk and dawn data are processed independently and then merged to produce a total field magnetic anomaly map. To extract static and dynamic components, the 1-D and 2-D WCAs were applied to the sub-parallel neighboring tracks and dawn-dusk data sets. The static components were compared with the IGRF, the global spherical harmonic magnetic field model. The static and dynamic components were analyzed in terms of corefield, external, and crustal signals based on their origins.

• The korean journal of orthodontics
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• v.31 no.1 s.84
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• pp.1-13
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• 2001

The extraction lot orthodontic treatment can be adopted for aligning crowded dentition, improving facial esthetics and solving a skeletal discrepancy as alternative for a surgical option. Mandibular second premolar extraction was often selected as treatment plan when there we very little or no space shortage in lower arch or limited retraction of the lower incisors was required. The primary object of this study was evaluate a pretreatment condition and examine the amount of tooth movement ior a mandibular second premolar extraction in growing patients. Pretreatment and posttreatment lateral cephalograms of 14 cases that had their four first premolar extracted (4/4 group), 15 cases with upper first and lower second premolar extraction (4/5 group) were selected. Structural method superimposition was conducted to evaluate a difference of dental change between 4/4 and 4/5 group. The results were as follows, 1. Pretreatment factor for 4/4 extraction or 4/5 extraction choice included maxillary incisor axis to occlusal plane, Class II molar relationship, IMPA and interincisal angle. 2. The amount of molar anterior movement in 4/5 group was greater than that of 4/4 group(p<0.05). 3. There was no significant difference between 4/4 group and 4/5 group in aspects of maxillary tooth movement(p<0.05).

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.23 no.1
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• pp.9-17
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• 2005

The objective of the study is to extract information about the road surfaces to be studied by analyzing asphalt concrete-paved road surface images photographed with a digital video camera. To analyze the accuracy of road surface information gained using a digital imagery processing method, it was compared and analyzed with the outcomes of control surveying. As a result, an average error of 0.0427 m in the X-axis direction, that of 0.0527 m in the Y-axis direction, and that of 0.1539 m in the Z-axis direction were found, good enough for mapping at a scale of 1:1,000 or less and GIS data. Besides, information on road surface assessment factors such as crack ratio, the amount of rutting and profile index was gained by analyzing processed digital imagery. This information made it possible to conduct road surface assessment by generating PSI and MCI. As quality digital image information has been gathered from roads and stored, important fundamental data on PMS (Pavement Management System) will become available in the future.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.6
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• pp.76-86
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• 1999

In this paper, it is shown that the car number plate are segmented and extracted more efficiently by using wavelet transform. A car image is decomposed by wavelet transform, and the high frequency image of the decomposed image are selected as feature images. Three selected feature images are synthesized of a single feature image, and a region including the plate is segmented by the correlation coefficient between the feature image and the synthesized image. For segmented plate region, the car plate region is extracted by deciding the Y-axis region composed by vertical region, the car plate region is extracted by deciding the Y-axis region composed by vertical histogram and the X-axis region composed by the variance histogram. Some experiment results of the various image and shown. It has been shown from the results with the high rate of 96% that the car number plates can be segmented and extracted more extractly and efficiently than converntional method.

• The KIPS Transactions:PartD
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• v.9D no.5
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• pp.915-924
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• 2002

Conventional Systems for parcel sorting consist of two sequences as loading the parcel into conveyor belt system and post-code input. Using bar code information, the parcels to be recorded and managed are recognized. This paper describes a 32 $\times$ 32 sized mini-block inspection to extract bar code Region of Interest (ROI) from the line Charged Coupled Device (CCD) camera capturing image of moving parcel at 2m/sec speed. Firstly, the Min-Max distribution of the mini-block has been applied to discard the background of parcel and region of conveying belts from the image. Secondly, the diagonal inspection has been used for the extraction of letters and bar code region. Five horizontal line scanning detects the number of edges and sizes and ROI has been acquired from the detection. The wrong detected area has been deleted by the comparison of group size from labeling processes. To correct excluded bar code region in mini-block processes and for analysis of bar code information, the extracted ROI 8 boundary points and decline distribution have been used with central axis line adjustment. The ROI extraction and central axis creation have become enable within 60～80msec, and the accuracy has been accomplished over 99.44 percentage.

• Journal of the Institute of Convergence Signal Processing
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• v.2 no.4
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• pp.22-30
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• 2001

In this paper we propose three classification algorithms to classify breast tumors that occur in duct into Benign, DCIS(ductal carcinoma in situ) NOS(invasive ductal carcinoma) The general approach for a creating classifier is composed of 2 steps: feature extraction and classification Above all feature extraction for a good classifier is very significance, because the classification performance depends on the extracted features, Therefore in the feature extraction step, we extracted morphology features describing the size of nuclei and texture features The internal structures of the tumor are reflected from wavelet transformed images with 10$\times$ and 40$\times$ magnification. Pariticulary to find the correlation between correct classification rates and wavelet depths we applied 1, 2, 3 and 4-level wavelet transforms to the images and extracted texture feature from the transformed images The morphology features used are area, perimeter, width of X axis width of Y axis and circularity The texture features used are entropy energy contrast and homogeneity. In the classification step, we created three classifiers from each of extracted features using discriminant analysis The first classifier was made by morphology features. The second and the third classifiers were made by texture features of wavelet transformed images with 10$\times$ and 40$\times$ magnification. Finally we analyzed and compared the correct classification rate of the three classifiers. In this study, we found that the best classifier was made by texture features of 3-level wavelet transformed images.

• Journal of Internet Computing and Services
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• v.21 no.4
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• pp.127-135
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• 2020

The purpose of this study is to develop a human activity recognition (HAR) system, which distinguishes 13 activities, including five activities commonly dealt with in conventional HAR researches and eight activities from the Eastern-Asian culture. The eight special activities include floor-sitting/standing, chair-sitting/standing, floor-lying/up, and bed-lying/up. We used a 3-axis accelerometer sensor on the wrist for data collection and designed a machine learning model for the activity classification. Data clustering through preprocessing and feature extraction/reduction is performed. We then tested six machine learning algorithms for recognition accuracy comparison. As a result, we have achieved an average accuracy of 99.7% for the 13 activities. This result is far better than the average accuracy of current HAR researches based on a smartwatch (89.4%). The superiority of the HAR system developed in this study is proven because we have achieved 98.7% accuracy with publically available 'pamap2' dataset of 12 activities, whose conventionally met the best accuracy is 96.6%.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2001.06a
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• pp.285-288
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• 2001

In this paper, we proposed new method of speech feature extraction using ICA(Independent Component Analysis) which minimized the dependency and correlation among speech signals on purpose to separate each component in the speech signal. ICA removes the repeating of data after finding the axis direction which has the greatest variance in input dimension. We verified improvement of speech recognition ability with training and recognition experiments when ICA compared with conventional mel-cepstrum features using HMM. Also, we can see that ICA dealt with the situation of recognition ability decline that is caused by environmental noise.