• Proceedings of the KSME Conference
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• 2008.11b
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• pp.2423-2428
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• 2008

A turbo classifier having a rotating rotor of two stage classification region has been developed to have a cut size of 1 micro meter. Particle number concentrations were counted using Aerosol Particle Sizer (APS, TSI co., USA) at inlet and outlet of the classifier. Partial classification efficiency was obtained at various rotation speeds, total flow rates, and feed rates of powders, and classification characteristic depending on design parameters was discussed. Classification performance was enhanced as rotation speed of rotor increased and total flow rate decreased.

• Geomechanics and Engineering
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• v.35 no.1
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• pp.67-80
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• 2023

Due to the nature of the conjunctive Cone Penetration Test(CPT), which does not verify the actual sample directly, geotechnical engineers commonly classify the underground geomaterials using CPT results with the classification diagrams proposed by various researchers. However, such classification diagrams may fail to reflect local geotechnical characteristics, potentially resulting in misclassification that does not align with the actual stratification in regions with strong local features. To address this, this paper presents an objective method for more accurate local CPT soil classification criteria, which utilizes C4.5 decision tree models trained with the CPT results from the clay-dominant southern coast of Korea and the sand-dominant region in South Carolina, USA. The results and analyses demonstrate that the C4.5 algorithm, in conjunction with oversampling, outlier removal, and pruning methods, can enhance and optimize the decision tree-based CPT soil classification model.

• The Journal of Korean Physical Therapy
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• v.26 no.5
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• pp.315-323
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• 2014

Purpose: This study was conducted in order to investigate the effect of motor ability on mastery motivation in children with cerebral palsy. Methods: Sixty children with cerebral palsy (5~12 years) and their parents participated in the study. Data on general characteristics and disability condition, Gross Motor Functional Classification System, Manual Ability Classification System, and The Dimensions of Mastery questionnaire were collected for this study. Independent t-test, and ANOVA were used for analysis of the effect of The Dimensions of Mastery questionnaire according to general and disability condition, Gross Motor Functional Classification System, and Manual Ability Classification System. Linear regression analysis was performed to determine the effects of Gross Motor Functional Classification System and Manual Ability Classification System on The Dimensions of Mastery questionnaire. SPSS win. 22.0 was used and Tukey was used for post hoc analysis, level of statistical significance was less than 0.05. Results: The Dimensions of Mastery questionnaire score showed statistically significant difference according to gender, region, type, disability rating, Gross Motor Functional Classification System, and Manual Ability Classification System (p<0.05). Gross Motor Functional Classification System and Manual Ability Classification System were the effect factor on The Dimensions of Mastery questionnaire significantly (p<0.05). Conclusion: These results suggest that motor ability of children with cerebral palsy was an important factor having an effect on The Dimensions of Mastery questionnaire.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.12
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• pp.547-552
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• 2014

As social multimedia sites are getting popular such as Flickr and Facebook, the amount of image information has been increasing very fast. So there have been many studies for accurate social image retrieval. Some of them were web image classification using semantic relations of image tags and BoVW(Bag of Visual Words). In this paper, we propose a method to detect salient region in images using GBVS(Graph Based Visual Saliency) model which can eliminate less important region like a background. First, We construct BoVW based on SIFT algorithm from the database of the preliminary retrieved images with semantically related tags. Second, detect salient region in test images using GBVS model. The result of image classification showed higher accuracy than the previous research. Therefore we expect that our method can classify a variety of images more accurately.

• Journal of Service Research and Studies
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• v.5 no.2
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• pp.103-110
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• 2015

Recently, Classification of characters in a 3D FPS game has emerged as a very significant issue. In this study, We propose the game character Classification method using Image Region Segmentation of the extracting meaningful object in a simple operation. In this method, first used a non-linear RGB color model and octree color quantization scheme. The input image represented a less than 20 quantized color and uses a small number of meaningful color histogram. And then, the image divided into small blocks, calculate the degree of similarity between the color histogram intersection and adjacent block in block units. Because, except for the block boundary according to the texture and to extract only the boundaries of the object block. Set a region by these boundary blocks as a game object and can be used for FPS game play. Through experiment, we obtain accuracy of more than 80% for Classification method using each feature. Thus, using this property, characters could be classified effectively and it draws the game more speed and strategic actions as a result.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.15 no.5
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• pp.103-114
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• 2012

The purpose of this research is classifying stream into different types depending on various factor from the perspective of stream corridor restoration and using it as basic data, which are used to consider efficient management and planning for the healthy stream according to the characteristic by types. In this study, 130 points of location of the Nakdong river basin which consist of various geographic factors have been chosen and hierarchical cluster analysis has been carried out in these points by using biological and physiochemical factors whose health can be considered to be predicted and evaluated. As a result of cluster analysis, there were three divided types. Type A whose biology and water quality are considered the best was the highest in forest area percentage so that it was classified into natural stream. Type B was classified into a rural region stream with a mixture of urban and agricultural region. Type C, with the most damaged water quality and biology health had the most urban region surface area and was named as urban region stream. Moreover, an overall restoration strategy according to characteristic by stream types was set. By the results of correlation analysis on factors, water quality showed a high correlation with biological properties and was affected by surrounding land usage. In evaluation of streams, it proves the need to consider not only other habitat's geographical and biological factors but also the water quality and land usage factors. There needs to be further research on stream ecosystem functionality factors and structural aspects by using a more objective and total evaluation result in selecting additional index and various other specific classification methods by stream types and its restoration strategies.

• Journal of Urban Science
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• v.9 no.2
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• pp.21-30
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• 2020

The purpose of this study is to present a plan to distinguish 229 local governments nationwide by taking into account various characteristics such as population, employment, housing, and industry of the region for customized urban policies in the era of metropolitan areas. The National Statistical Portal (KOSIS) collected and standardized data related to population, housing, industry, and finance by region from 2000 to 2015 for the classification of regional types necessary for customized urban policies, and this was used to classify them into regional types that considered population, employment, housing and industry. The summary of the analysis results is as follows. First, as a result of the regional type classification, 10 key employment sites (4.4%), 5 employment centers (2.2%), 38 residential centers (16.6%), 20 growth areas (8.7%), 26 industrial cities (11.4%), 35 low-fertile farming and fishing villages (15.3%) and 95 stagnant areas (41.5%). Second, the Seoul metropolitan area is the most diverse type of metropolitan area in the country, with most of its core employment sites inside Seoul, residential centers inside and outside Seoul, and growth areas in the southeastern part of the country (Busan, Ulsan, and Gyeongsangnam-do) are mixed with industrial and growth areas centered around Busan, Ulsan and surrounding areas, while the rest of the local governments are found to be low-fertile farming villages or stagnant areas. Daegu (Daegu, Gyeongbuk) is an industrial city in Daegu, and the rest of the local governments are either low-density farming and fishing villages or stagnant areas. The Honam region (Gwangju and Jeolla) was found to be a low-mill farming and fishing village or stagnant area except for Gwangju, while the Chungcheong region (Daejeon, Sejong, and Chungcheong) was seen as a growth area with areas adjacent to Daejeon, Sejong, and the Seoul metropolitan area, and some industrial cities were included. Finally, the Gangwon area was mostly classified as low-density farming and fishing villages and stagnant areas.

• Journal of the Korean Geographical Society
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• v.50 no.5
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• pp.485-503
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• 2015

This study aims at evaluating geomorphological classification systems to predict the occurrence of landslides in mountainous region in Korea. Geomorphological classification systems used in this study are Catena, TPI, and Geomorphons. Study sites are Gapyeong-gun, Hoengseong-gun, Gimcheon-si, Yeoju-si/Yicheon-si in which landslide occurrence data were collected by local governments from 2001-2014. Catena method has objective classification standard to compare among regions objectively and understand the result intuitively. However, its procedure is complicated and hard to be automated for the general public to use it. Both TPI and Geomorphons have simple procedure and GIS-extension, therefore it has high accessibility. However, the results of both systems are highly dependent on the scale, and have low relevance to geomorphological formation process because focusing on shape of terrain. Three systems have low compatibility, therefore unified concept are required for broad use of landform classification. To assess the effectiveness of prediction on landslide by each geomorphological classification system, 50% of geomorphological classes with higher landslide occurrence are selected and the total landslide occurrence in selected classes are calculated and defined as 'predictive ability'. The ratio of terrain categorized by 'predictive ability' to whole region is defined as 'vulnerable area ratio'. An indicator to compare three systems which is predictive ability divided by vulnerable area ratio was developed to make a comprehensive judgment. As a result, Catena ranked the highest in suitability.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.849-850
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• 2008

Region adaptive demosaicing scheme based on the spectral spatial correlation is prosed in this paper. Region classification and adaptive demosaicing makes the decision of the edge direction more accurately.

• Proceedings of the IEEK Conference
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• 2002.06a
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• pp.195-198
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• 2002

One-dimensional radar signature, such as range profile, is highly dependent on the aspect angle. Therefore, radar target recognition over wide angular region is a very difficult task. In this paper, we propose the Bayes classifier with Gaussian mixture model for radar target recognition over wide-angular region and compare performances of proposed technique and radar target recognition with subclasses concept in the literature of probability of correct classification ratio.