• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.26 no.4
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• pp.355-362
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• 2000

Neoplastic growth is characterized by alterations of oncogenes and antioncogenes. The interaction between activated oncogenes and functional deletion of antioncogene appears to be the driving force directing normal cells to uncontrolled growth resulting in tumor. In addition to those genes mentioned, other genes controlling the entry of cells into the cell cycle have recently been implicated in cancer development. The overexpression of the cyclin D1 gene, which has been mapped to 11q13, either by gene rearrangement or amplification has been noted in various malignant tumors. The product of the cyclin D1 gene forms a complex with cyclin-dependent protein kinases(CDK4) that governs a key transition in the cell cycle. The relationships between the overexpression of cyclin D1 assessed by immunihistochemistry and the amplification of the cyclin D1 gene by differential polymerase chain reaction(DPCR) using primers for dopamin D2 receptor gene in 13 cases of squamous cell carcinomas of the oral cavity have been studied. The semiquantitative assay of cyclin D1 amplification has been made by cyclin D1/dopamin D2 receptor(CD/DR) ratio. The results were as follows; 1. In the normal tissue and the tumor, the CD/DR ratios were 0.82 and 1.36 respectively. This implicates 1.65-fold amplification of cyclin D1 gene in tumor compared to that in normal tissue. 2. The tumor tissue which showed overexpression of cyclin D1 by immunohistochemistry revealed 2-fold amplification of cyclin D1 compared to the normal tissue. 3. The tumor tissue which showed mild expression of cyclin D1 by immunihistochemistry revealed 1.7-fold amplification of cyclin D compared to the normal tissue. 4. The cyclin D1 was overexpressed in the tumor tissue at the rate of 38%. Above results suggest that cyclin D1 has close correlation with the development of carcinoma in the oral cavity. But further studies were needed to elucidate the carcinogeneic mechanisms by comparative studies among cyclin D1, pRb and p53.

• The KIPS Transactions:PartD
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• v.12D no.1 s.97
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• pp.165-178
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• 2005

A product classification scheme is the foundation on which product databases are designed, and plays a central role in almost all aspects of management and use of product information. It needs to meet diverse user views to support efficient and convenient use of product information. It needs to be changed and evolved very often without breaking consistency in the cases of introduction of new products, extinction of existing products, class reorganization, and class specialization. It also needs to be merged and mapped with other classification schemes without information loss when B2B transactions occur. For these requirements, a classification scheme should be so dynamic that it takes in them within right time and cost. The existing classification schemes widely used today such as UNSPSC and eCl@ss, however, have a lot of limitations to meet these requirements for dynamic features of classification. Product information implies a plenty of semantics such as class attributes like material, time, place, etc., and integrity constraints. In this Paper, we analyze the dynamic features of product databases and the limitation of existing code based classification schemes, and describe the semantic classification model proposed in [1], which satisfies the requirements for dynamic features of product databases. It provides a means to explicitly and formally express more semantics for product classes and organizes class relationships into a graph.

• Journal of the Korean Geographical Society
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• v.48 no.6
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• pp.897-913
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• 2013

The main purpose of the paper is to examine the spatial characteristics of school choice through residential mobility by conducting a correlation analysis on the relationships between the middle schools' entrance rates to special high schools and the elementary schools' net transfer rates. Analyses are done at both the individual school level and the school catchment area level. Prior to the calculation, the two variables involved in the correlation analysis are transformed via a standardization equation, and the standardized scores are mapped and explored. Both the global and local correlation analyses are done for the standardized variables. Main findings are twofold. First, the global correlation analysis reports that there exists a statistically significant correlation between the two variables at both the analytical levels. Second, albeit the prominent positive correlation at the global level, the local analysis reveals the existence of a considerable level of spatial heterogeneity in terms of bivariate association. While several school catchment areas with very high local correlation coefficients (the HH association type) are popped up, other areas with various types of bivariate association including ones even opposite to the global trend are also observed.

• Korean Journal of Breeding Science
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• v.41 no.3
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• pp.236-243
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• 2009

This study was conducted to develop a japonica-type rice cultivar with brown planthopper (BPH) resistance using DNA markers. A doubled haploid (DH) population consisting of 120 pure-lines was established by anther culture of $F_1$ hybrids between 'Samgang', a Tongil type BPH resistance cultivar, and 'Nagdong', a japonica cultivar. To determine the map position of genes responsible for BPH resistance in rice, a genetic map was constructed based on 120 DH lines. A total of 162 molecular markers were classified into 12 linkage groups, covering 1,884 Kosami centimorgan (cM) with an average of 11.6 cM. Five QTLs (qBPR3, qBPR6, qBPR7, qBPR8, and qBPR12) associated with BPH resistance were identified and mapped on chromosomes 3, 6, 7, 8, and 12, respectively, using the genetic map constructed in this study. To analyze the relationship between BPH resistance and agronomic traits, a total of eight QTLs related to the agronomic traits were detected on 12 rice chromosomes. In an analysis of relationships, three QTLs (qBPR3, qBPR7, and qBPR8) showed a linkage with tested agronomic traits. A QTL (qBPR3) located on chromosome 3 (RM282-3023) was closely linked to culm length (qCL3). The QTL (qBPR8) for BPH resistance on the short arm of chromosome 8 also overlapped the region detected in culm length (qCL8).

• Geophysics and Geophysical Exploration
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• v.8 no.1
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• pp.78-85
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• 2005

This study, combining geophysical and environmental approaches, was undertaken to investigate the causes of secondary salinity in the Goondoola basin, in southwestern Queensland. Airborne radiometric, electromagnetic and ground electromagnetic datasets were acquired, along with data on soils and subsurface materials and groundwater. Relationships established between radiometric, elevation data, and measured material properties allowed us to generate predictive maps of surface materials and recharge potential. Greatest recharge to the groundwater is predicted to occur on the weathered bedrock rises surrounding the basin. Electromagnetic data (airborne, ground, and downhote), used in conjunction with soil and drillhole measurements, were used to quantify regolith salt store and to define the subsurface architecture. Conductivity measurements reflect soil salt distribution. However, deeper in the regolith, where the salt content is relatively constant, the AEM signal is influenced by changes in porosity or material type. This allowed the lateral distribution of bedrock weathering zones to be mapped. Salinisation in this area occurs because of local-andintermediate-scale processes, controlled strongly by regolith architecture. The present surface outbreak is the result of evaporative concentration above shallow saline groundwater, discharging at break of slope. The integration of surficial and subsurface datasets allowed the identification of similar landscape settings that are most at risk of developing salinity with groundwater rise. This information is now being used by local land managers to refine management choices that prevent excess recharge and further salt mobilisation.

• Korean Journal of Remote Sensing
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• v.35 no.6_1
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• pp.919-932
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• 2019

Fine particulate matter (PM2.5) is not only affected by anthropogenic emissions, but also intensifies, migrates, decreases by hydrometeorological factors. Therefore, it is essential to understand relationships between the hydrometeorological factors and PM2.5 concentration. In Korea, PM2.5 concentration is measured at the ground observatories and estimated data are given to locations where observatories are not present. In this way, the data is not suitable to represent an area, hence it is impossible to know accurate concentration at such locations. In addition, it is hard to trace migration, intensification, reduction of PM2.5. In this study, we analyzed the relationships between hydrometeorological factors, acquired from Global Land Data Assimilation System (GLDAS), and PM2.5 by means of Bayesian Model Averaging (BMA). By BMA, we also selected factors that have meaningful relationship with the variation of PM2.5 concentration. 4 PM2.5 concentration models for different seasons were developed using those selected factors, with Aerosol Optical Depth (AOD) from MODerate resolution Imaging Spectroradiometer (MODIS). Finally, we mapped the result of the model, to show spatial distribution of PM2.5. The model correlated well with the observed PM2.5 concentration (R ~0.7; IOA ~0.78; RMSE ~7.66 ㎍/㎥). When the models were compared with the observed PM2.5 concentrations at different locations, the correlation coefficients differed (R: 0.32-0.82), although there were similarities in data distribution. The developed concentration map using the models showed its capability in representing temporal, spatial variation of PM2.5 concentration. The result of this study is expected to be able to facilitate researches that aim to analyze sources and movements of PM2.5, if the study area is extended to East Asia.

• Journal of KIISE:Databases
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• v.33 no.1
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• pp.102-116
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• 2006

Electronic catalogs (or e-catalogs) hold information about the goods and services offered or requested by the participants, and consequently, form the basis of an e-commerce transaction. Catalog management is complicated by a number of factors and product classification is at the core of these issues. Classification hierarchy is used for spend analysis, custom3 regulation, and product identification. Classification is the foundation on which product databases are designed, and plays a central role in almost all aspects of management and use of product information. However, product classification has received little formal treatment in terms of underlying model, operations, and semantics. We believe that the lack of a logical model for classification Introduces a number of problems not only for the classification itself but also for the product database in general. It needs to meet diverse user views to support efficient and convenient use of product information. It needs to be changed and evolved very often without breaking consistency in the cases of introduction of new products, extinction of existing products, class reorganization, and class specialization. It also needs to be merged and mapped with other classification schemes without information loss when B2B transactions occur. For these requirements, a classification scheme should be so dynamic that it takes in them within right time and cost. The existing classification schemes widely used today such as UNSPSC and eClass, however, have a lot of limitations to meet these requirements for dynamic features of classification. In this paper, we try to understand what it means to classify products and present how best to represent classification schemes so as to capture the semantics behind the classifications and facilitate mappings between them. Product information implies a plenty of semantics such as class attributes like material, time, place, etc., and integrity constraints. In this paper, we analyze the dynamic features of product databases and the limitation of existing code based classification schemes. And describe the semantic classification model, which satisfies the requirements for dynamic features oi product databases. It provides a means to explicitly and formally express more semantics for product classes and organizes class relationships into a graph. We believe the model proposed in this paper satisfies the requirements and challenges that have been raised by previous works.