• Maxillofacial Plastic and Reconstructive Surgery
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• v.14 no.3
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• pp.185-193
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• 1992

The calcifying odontogenic cyst was identified as a pathological entity by Gorlin & his associates in 1962. This lesion is one of the rarest and most disputable cysts in the oral region. The calcifying odontogenic cyst has variable clinical and radiological features. We review the previous literatures and report 2 cases of calcifying odontogenic cyst at Department of Oral and Maxillofacial Surgery, Kyung-Hee University. The 1st case was as follows. The patient vas 22 year old female. The past dental history revealed extraction of prolonged retained #73 tooth about 15days ago. She complained a painful swelling on the lower anterior teeth area. There were chin and vestibular swelling on the lower anterior teeth area, tenderness and missing of #33 tooth. The radiograph revealed well-demarcated unilocular radiolucency containing radiopaque calcific flecks around impacted #33 tooth. The clinical diagnosis was COC, so surgical enucleation was done. There was no recurrence and COC was confirmed by pathologist. The second case was as follows. The patient was 72 year old male. The past history revealed inactive tuberculosis, bronchial asthma and denture construction. The chief complaint was rapidly growing mass on the lower left anterior edentulous area. The clinical findings were chin swelling protruding mass with surface ulceration, fluctuation and a few bloody fluid in aspiration. The radiograph revealed well-demarcated radiolucency mimiking the residual cyst. The biopsy result was COC. The surgical excision was done, but the lesion was recurred 10 months later. The treatment was surgical excision with aggressive peripheral bone grinding and FTSG form groin area. There was no problem during the postoperative period.

• Journal of IKEEE
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• v.24 no.1
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• pp.200-207
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• 2020

In this paper, an area-efficient feature extractor was proposed for security surveillance radar systems and FPGA-based implementation results were presented. In order to reduce the memory requirements, features extracted from Doppler profile for FFT window-size are used, while those extracted from total spectrogram for frame-size are excluded. The proposed feature extractor was design using Verilog-HDL and implemented with Xilinx Zynq-7000 FPGA device. Implementation results show that the proposed design can reduce the logic slice and memory requirements by 58.3% and 98.3%, respectively, compared with the existing research. In addition, security surveillance radar system with the proposed feature extractor was implemented and experiments to classify car, bicycle, human and kickboard were performed. It is confirmed from these experiments that the accuracy of classification is 93.4%.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.9
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• pp.811-819
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• 2014

Activity recognition is a key component in identifying the context of a user for providing services based on the application such as medical, entertainment and tactical scenarios. Instead of applying numerous sensor devices, as observed in many previous investigations, we are proposing the use of smartphone with its built-in multimodal sensors as an unobtrusive sensor device for recognition of six physical daily activities. As an improvement to previous works, accelerometer, gyroscope and magnetometer data are fused to recognize activities more reliably. The evaluation indicates that the IBK classifier using window size of 2s with 50% overlapping yields the highest accuracy (i.e., up to 99.33%). To achieve this peak accuracy, simple time-domain and frequency-domain features were extracted from raw sensor data of the smartphone.

• Smart Structures and Systems
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• v.22 no.4
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• pp.433-440
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• 2018

Pavements porous concrete is a noble structure design in the urban management development generally enabling water to be permeated within its structure. It has also capable in the same time to cater dynamic loading. During the technology development, the quality and quantity of waste materials have led to a waste disposal crisis. Using recycled materials (secondary) instead of virgin ones (primary) have reduced landfill pressure and extraction demanding. This study has reviewed the waste materials (Recycled crushed glass (RCG), Steel slag, Steel fiber, Tires, Plastics, Recycled asphalt) used in the pavement porous concretes and report their respective mechanical, durability and permeability functions. Waste material usage in the partial cement replacement will cause the concrete production cost to be reduced; also, the concretes' mechanical features have slightly affected to eliminate the disposal waste materials defects and to use cement in Portland cement (PC) production. While the cement has been replaced by different industrial wastes, the compressive strength, flexural strength, split tensile strength and different PC permeability mixes have depended on the waste materials' type applied in PC production.

• Maxillofacial Plastic and Reconstructive Surgery
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• v.13 no.1
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• pp.69-76
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• 1991

A 9-year old boy suffering from cleidocranial dysplasia associated with impacted 4 supernumerary teeth and unerupted all permanent teeth is presented with his mother. The pedigree showed autosomal dominant pattern of inheritance, and the raiographic features of them were very similar in clavicle, skull, vertebrae, peivis and extremities. Although almost of the skeleton was involved with this syndrome, they did not recognize any other problem but except dental problem. In mother, who was wearing removable partial dentures leaving 24 impacted teeth in her jaws, the radiographic abnormalities like cystic lesion were not detected. And in the son, who showed impacted 4 supernumerary and all permanent teeth, we have attempted surgical extraction of the supernumerary teeth and periodic surgical opening of the alveolar bone covering the permanent dentition to induce the eruption of permanent teeth at the proper position, Orthodontic treatment has also been combined to correct class III malocclusion state.

• Journal of Digital Contents Society
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• v.18 no.2
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• pp.267-274
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• 2017

Recently, there is a new trend about internet of things (IoT) such as shops with smart mirror around the fashion and beauty industry. Since smart mirror can display a content through a monitor which is attached to back of mirror system while looking through a mirror, it can be applied to various industries such as fashion, beauty and health care. This paper proposes an efficient learning system requiring no assistance from others for the hearing deaf who atrophy verbal skill and are inaccurate in pronunciation by using features of smart mirror. Also, this system proposes an efficient and simple lip reading method which can be applied to an embedded system and improves a learning efficiency by employing previously verified pronunciation training data.

• Journal of the Korean Association of Geographic Information Studies
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• v.5 no.3
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• pp.19-32
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• 2002

Topographic information is indispensable in the applications that require elevational data. These applications are exemplified by watershed partition, extraction of drainage networks, viewshed analysis, derivation of geomorphologic features, quantification of landslide-terrain, and identification of topographic settings susceptible to landsliding. Therefore, we study the accuracy of data on topographic parameters derived from digital elevation models(DEMs). This research wished to analyze the effect that data source and grid size get in topography parameter using gridded DEM. An analysis of topography parameter extract and compared drainage basin, watershed slope, stream network using DEM is constructed by digital map and DTED DEM. Especially, when extract stream network from gridded DEM, received much effects according to threshold value of flowaccumulation regardless of DEM grid size. Therefore, this study applied equal threshold value of flowaccumulation for two data sources, and compare and analyzed stream network.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.5
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• pp.479-493
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• 2016

LiDAR(Light Detection and Ranging) data acquired from ALS(Airborne Laser Scanner) has been intensively utilized to reconstruct object models. Especially, researches for 3D modeling from LiDAR data have been performed to establish high quality spatial information such as precise 3D city models and true orthoimages efficiently. To reconstruct object models from irregularly distributed LiDAR point clouds, sensor calibration, noise removal, filtering to separate objects from ground surfaces are required as pre-processing. Classification and segmentation based on geometric homogeneity of the features, grouping and representation of the segmented surfaces, topological analysis of the surface patches for modeling, and accuracy assessment are accompanied by modeling procedure. While many modeling methods are based on the segmentation process, this paper proposed to extract key points directly for building modeling without segmentation. The method was applied to simulated and real data sets with various roof shapes. The results demonstrate feasibility of the proposed method through the accuracy analysis.

• Journal of the Korea Convergence Society
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• v.11 no.5
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• pp.9-17
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• 2020

Human activity recognition(HAR) using smartphones is a hot research topic in computational intelligence. Smartphones are equipped with a variety of sensors. Fusing the data of these sensors could enable applications to recognize a large number of activities. However, these devices have fewer resources because of the limited number of sensors available, and feature selection and classification methods are required to achieve optimal performance and efficient feature extraction. This paper proposes a smartphone-based HAR scheme according to these requirements. The proposed method in this paper extracts time-domain features from acceleration sensors, gyro sensors, and barometer sensors, and recognizes activities with high accuracy by applying KDA and SVM. This approach selects the most relevant feature of each sensor for each activity. Our comparison results shows that the proposed system outperforms previous smartphone-based HAR systems.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.22 no.7
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• pp.956-962
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• 2018

As the study of the object feature detection from image, we explain methods to identify the species of the tree in forest using the picture taken from dron. Generally there are three kinds of methods, which are GLCM (Gray Level Co-occurrence Matrix) and Gabor filters, in order to extract the object features. We proposed the object extraction method using the statistical properties of trees in this research because of the similarity of the leaves. After we extract the sample images from the original images, we detect the objects using cross correlation techniques between the original image and sample images. Through this experiment, we realized the mean value and standard deviation of the sample images is very important factor to identify the object. The analysis of the color component of the RGB model and HSV model is also used to identify the object.