소결조건이 소결 청동계 마찰재의 마찰특성에 미치는 영향

최병호,박노진,정순욱 金烏工科大學校 1998 論文集 Vol.19 No.-

The effect of sintering conditions(temperature and time) on the frictional properties of sintered bronze-base were investigated. It was observed that with increasing sintering temperature up to 840℃ and sintering time up to 60 min. the hardness, bending strength and coefficient of friction increased continuously, but the wear rate decreased. At sintering temperature of 860℃, however, their mechanical and frictional properties decreased rapidly due to the sweating phenomenon of tin. In our experiments, the optimal sintering condition is that sintering temperature is about 840℃ and sintering time is about 60 min.. Its average grain size is about 14.2㎛.

임상소견에 따른 법랑모세포종의 방사선학적 특징에 관한 임상통계학적 분석

김진수,신상욱,박노부 大韓顎顔面成形再建外科學會 1995 Maxillofacial Plastic Reconstructive Surgery Vol.17 No.4

The author studied on the 115 cases of the ameloblastoma which had been diagnosed with biopsy during the period of 1962 to 1994 at the Kyungpook National University Hospital, Pusan National University Hospital, Youngnam University Hospital, Keimyung University Hospital, Catholic Medical School Hospital, and Maryknol Hospital. This study contains the statistical analysis of the clinico-pathological findings such as sex, age, location, chief complaint, duration, treatment method, size, recurrence and impacted teeth in relation to radiographic findings. The results were as follows : 1. The incidence rate was 60% in .male and 40% in female. 2. At the time of diagnosis, the age of the patients ranged from 9 to 69 years old (average 31.4 years old). The cases of 73% were in the 2nd, 3rd and 4th decades of life. 3. The majority of cases, 88.7% occurred in the mandible, especially 59% in the mandibular angle area. 4. The most prevalent chief complaint of swelling was 56.5%. 5. As regards duration, the cases less than 12 months appeared 49.5%, and average duration is 30.45months. 6. Unilocular radiographic findings showed 43.5%, Multilocular radiographic findings appeared 56.5%. 7. Conservative treatment was performed 40.0%, and radical treatment was employed 60.0%. 8. There was the variation of lesional sizes between 2.0cm and 15cm, average size 6.19cm. 9. Recurrent cases were 28.7%, and impacted teeth were shown 30.43%. 10. The ratiographic finding has no relationship with the factors of age, location, chief complaint, recurrence and impacted teeth, however there is slight indication that the below 30-year-old patient tend to be related to the multilocular type. 11. The multilocular radiographic findings were shown more frequently in the groups of females, over average of 30.45 months, over average size of 6.19cm and radical treatment.

Application of Random Forests to Assessment of Importance of Variables in Multi-sensor Data Fusion for Land-cover Classification

No Wook Park,Kwang Hoon Chi 大韓遠隔探査學會 2006 大韓遠隔探査學會誌 Vol.22 No.3

A random forests classifier is applied to multi-sensor data fusion for supervised land-cover classification in order to account for the importance of variable. The random forests approach is a nonparametric ensemble classifier based on CART-like trees. The distinguished feature is that the importance of variable can be estimated by randomly permuting the variable of interest in all the out-of-bag samples for each classifier. Two different multi-sensor data sets for supervised classification were used to illustrate the applicability of random forests: one with optical and polarimetric SAR data and the other with multi-temporal Radarsat-l and ENVISAT ASAR data sets. From the experimental results, the random forests approach could extract important variables or bands for land-cover discrimination and showed reasonably good performance in terms of classification accuracy.

Predictive Spatial Data Fusion Using Fuzzy Object Representation and Integration: Application to Landslide Hazard Assessment

Park, No-Wook,Chi, Kwang-Hoon,Chung, Chang-Jo,Kwon, Byung-Doo The Korean Society of Remote Sensing 2003 大韓遠隔探査學會誌 Vol.19 No.3

This paper presents a methodology to account for the partial or gradual changes of environmental phenomena in categorical map information for the fusion/integration of multiple spatial data. The fuzzy set based spatial data fusion scheme is applied in order to account for the fuzziness of boundaries in categorical information showing the partial or gradual environmental impacts. The fuzziness or uncertainty of boundary is represented as two kinds of fuzzy membership functions based on fuzzy object concept and the effects of them are quantitatively evaluated with the help of a cross validation procedure. A case study for landslide hazard assessment demonstrates the better performance of this scheme as compared to traditional crisp boundary representation.

Effects of Uncertain Spatial Data Representation on Multi-source Data Fusion: A Case Study for Landslide Hazard Mapping

Park No-Wook,Chi Kwang-Hoon,Kwon Byung-Doo The Korean Society of Remote Sensing 2005 大韓遠隔探査學會誌 Vol.21 No.5

As multi-source spatial data fusion mainly deal with various types of spatial data which are specific representations of real world with unequal reliability and incomplete knowledge, proper data representation and uncertainty analysis become more important. In relation to this problem, this paper presents and applies an advanced data representation methodology for different types of spatial data such as categorical and continuous data. To account for the uncertainties of both categorical data and continuous data, fuzzy boundary representation and smoothed kernel density estimation within a fuzzy logic framework are adopted, respectively. To investigate the effects of those data representation on final fusion results, a case study for landslide hazard mapping was carried out on multi-source spatial data sets from Jangheung, Korea. The case study results obtained from the proposed schemes were compared with the results obtained by traditional crisp boundary representation and categorized continuous data representation methods. From the case study results, the proposed scheme showed improved prediction rates than traditional methods and different representation setting resulted in the variation of prediction rates.

An Overview of Theoretical and Practical Issues in Spatial Downscaling of Coarse Resolution Satellite-derived Products

Park, No-Wook,Kim, Yeseul,Kwak, Geun-Ho The Korean Society of Remote Sensing 2019 大韓遠隔探査學會誌 Vol.35 No.4

This paper presents a comprehensive overview of recent model developments and practical issues in spatial downscaling of coarse resolution satellite-derived products. First, theoretical aspects of spatial downscaling models that have been applied when auxiliary variables are available at a finer spatial resolution are outlined and discussed. Based on a thorough literature survey, the spatial downscaling models are classified into two categories, including regression-based and component decomposition-based approaches, and their characteristics and limitations are then discussed. Second, open issues that have not been fully taken into account and future research directions, including quantification of uncertainty, trend component estimation across spatial scales, and an extension to a spatiotemporal downscaling framework, are discussed. If methodological developments pertaining to these issues are done in the near future, spatial downscaling is expected to play an important role in providing rich thematic information at the target spatial resolution.

The Effects of Spatial Patterns in Low Resolution Thematic Maps on Geostatistical Downscaling

( No Wook Park ) 대한원격탐사학회 2011 大韓遠隔探査學會誌 Vol.27 No.6

This paper investigates the effects of spatial autocorrelation structures in low resolution data on downscaling without ground measurements or secondary data, as well as the potential of geostatistical downscaling. An advanced geostatistical downscaling scheme applied in this paper consists of two analytical steps: the estimation of the point-support spatial autocorrelation structure by variogram deconvolution and the application of area-to-point kriging. Point kriging of block data without variogram deconvolution is also applied for a comparison purpose. Experiments using two low resolution thematic maps derived from remote sensing data showing very different spatial patterns are carried out to discuss the objectives. From the experiments, it is demonstrated that the advanced geostatistical downscaling scheme can generate the downscaling results that well preserve overall patterns of original low resolution data and also satisfy the coherence property, regardless of spatial patterns in input low resolution data. Point kriging of block data can produce the downscaling result compatible to that by area-to-point kriging when the spatial continuity in block data is strong. If heterogeneous local variations are dominant in input block data, the treatment of the low resolution data as point data cannot generate the reliable downscaling result, and this simplification should not be applied to donwscaling.

County-level indoor radon concentration mapping and uncertainty assessment in South Korea using geostatistical simulation and environmental factors

Park, No-Wook,Kim, Yongjae,Chang, Byung-Uck,Kwak, Geun-Ho Elsevier 2019 JOURNAL OF ENVIRONMENTAL RADIOACTIVITY Vol.208 No.-

<P><B>Abstract</B></P> <P>This paper presents a geostatistical simulation approach to not only map the county-level indoor radon concentration (IRC) distributions in South Korea, but also quantify the uncertainty that can be used as decision-supporting information. For county-level IRC mapping in South Korea, environmental factors including geology, radium concentration in surface soil, gravel content in subsoil, and fault line density, which are known to be associated with the source and migration of radon gas, were incorporated into IRC measurements using multi-Gaussian kriging with local means. These four environmental factors could account for about 36% of the variability of noise-filtered IRCs, implying that regional variations of IRCs were affected by these factors. Sequential Gaussian simulation was then applied to generate alternative realizations of county-level IRC distributions. By summarizing the multiple simulation results, we identified some counties that lay on the great limestone series showed elevated IRCs. In addition, there were some counties in which the proportion of grids exceeding the recommended level was high but the uncertainty was also large according to the analysis of several uncertainty measures, which indicates that additional sampling is required for these counties. From the local cluster analysis in conjunction with simulation results, we found that the counties with higher levels of IRC belonged to the statistically significant clusters of high values, and these counties should be the prime targets for radon management and in-depth survey. The geographical distributions of IRC and uncertainty measures presented in this study provide guidance for effective radon management if they are consistently combined with both future IRC measurements and a geogenic radon potential map.</P> <P><B>Highlights</B></P> <P> <UL> <LI> Geostatistical simulation was applied to map county-level indoor radon concentration and uncertainty in South Korea. </LI> <LI> Environmental factors could account for about 36% of the variability of noise-filtered indoor radon concentration. </LI> <LI> Counties with higher indoor radon concentration could be delineated by summarizing multiple simulation results. </LI> <LI> Some counties belonging to clusters of high values with larger reliability were also identified from local cluster analysis. </LI> </UL> </P> <P><B>Graphical abstract</B></P> <P>[DISPLAY OMISSION]</P>

Application of Random Forests to Assessment of Importance of Variables in Multi-sensor Data Fusion for Land-cover Classification

Park No-Wook,Chi kwang-Hoon The Korean Society of Remote Sensing 2006 大韓遠隔探査學會誌 Vol.22 No.3

A random forests classifier is applied to multi-sensor data fusion for supervised land-cover classification in order to account for the importance of variable. The random forests approach is a non-parametric ensemble classifier based on CART-like trees. The distinguished feature is that the importance of variable can be estimated by randomly permuting the variable of interest in all the out-of-bag samples for each classifier. Two different multi-sensor data sets for supervised classification were used to illustrate the applicability of random forests: one with optical and polarimetric SAR data and the other with multi-temporal Radarsat-l and ENVISAT ASAR data sets. From the experimental results, the random forests approach could extract important variables or bands for land-cover discrimination and showed reasonably good performance in terms of classification accuracy.

Geostatistical downscaling of AMSR2 precipitation with COMS infrared observations

Park, No-Wook,Hong, Sungwook,Kyriakidis, Phaedon C.,Lee, Woojoo,Lyu, Sang-Jin TaylorFrancis 2016 International journal of remote sensing Vol.37 No.16

<P>This article presents a geostatistical approach for downscaling precipitation products from passive microwave satellites with geostationary Meteorological Satellite observations. More precisely, the Advanced Microwave Scanning Radiometer 2 (AMSR2) precipitation (daily level 3 product) with 0.25 degrees spatial resolution and the Communication, Ocean and Meteorological Satellite (COMS) infrared (IR) data with 5km spatial resolution were used for the downscaling experiment over the Korean peninsula. Brightness temperature data observed at COMS IR 1 and water vapour channels were incorporated for downscaling via area-to-point residual Kriging with non-linear regression. The evaluation results with densely sampled Automatic Weather Station data revealed that incorporating the COMS IR observations with the AMSR2 precipitation showed similar error statistics to those of the AMSR2 precipitation because of the limitations of IR observations themselves and the inherent errors of the AMSR2 precipitation product over land. However, the area-based evaluation using information entropy indicated that incorporating the COMS observations resulted in more detailed spatial variation in the final product than direct downscaling of the AMSR2 precipitation. In addition, local precipitation patterns could be captured when there were regions with missing precipitation values in the AMSR2 product. Consequently, the downscaling result is useful for understanding the local precipitation patterns with an accuracy similar to that provided by microwave satellite observations. It is also suggested that the spatial variability in the downscaling result and errors in input low-resolution data should be considered when downscaling coarse resolution data using fine resolution auxiliary variables.</P>