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Search Results: 1 - 10 of 54069 matches for " CHANG Chun-Ping "
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Numerical Investigation of Laser-Assisted Nanoimprinting on a Copper Substrate from a Perspective of Heat Transfer Analysis
Chun-Ping Jen
Computer Science , 2008,
Abstract: The technique of laser-assisted nanoimprinting lithography (LAN) has been proposed to utilize an excimer laser to irradiate through a quartz mold and melts a thin polymer film on the substrate for micro- to nano-scaled fabrications. In the present study, the novel concept of that copper was adopted as the substrate instead of silicon, which is conventionally used, was proposed. The micro/nano structures on the copper substrate could be fabricated by chemical/electrochemical etching or electroforming ; following by the patterns have been transferred onto the substrate using LAN process. Alternatives of the substrate materials could lead versatile applications in micro/nano-fabrication. To demonstrate the feasibility of this concept numerically, this study introduced optical multiple reflection theory to perform both analytical and numerical modeling during the process and to predict the thermal response theoretically.
Current research status and developing trends of wave process analysis in sedimentary basins

LIU Chun-ping,JIN Zhi-jun,LIN Juan-hua,LI Jing-chang,

地球物理学进展 , 2009,
Abstract: Wave process analysis is one of the newly introduced methods for studying sedimentary basins. It is theoretically based on the wave theory of geophysics which regards the crust motion in the way of wave process. The basic concepts, developments, principles and methods of the wave process analysis in sedimentary basins are presented in this paper. We introduce the four main aspects of current research status of the wave process analysis in detail and discuss its developing trends.
New Method for Template Detection and Location Under Complex Background

WANG Jian-hu,ZHU Yuan-chang,WANG Chun-ping,WANG Jian-hu,ZHU Yuan-chang,WANG Chun-ping,WANG Jian-hu,ZHU Yuan-chang,WANG Chun-ping,

中国图象图形学报 , 2007,
Abstract: Sensor calibration is a necessary and key step before applying photics sensor to measurement. While applying template in calibration, the first task is to detect and locate the template in complex background. At present, manual detection is used widely, whose efficiency is very low. To solve this problem, a new method for template detection and location under complex background is provided in this paper, which consists of two steps, template detection and precise location. The former implements the template detection using image segmentation and Hough transformation, and the later locates the four key corners on template using SUSAN technique. The experiment result shows that the proposed method is simple and reliable and it can be applied in any complex scene.
Domain-oriented semantic integration method using virtual views

LI Hua-yu,HU Chang-jun,OUYANG Chun-ping,YE Yin-zhu,

计算机应用研究 , 2010,
Abstract: For heterogeneous data sources of oil engineering domain, this paper presented a semantic-based virtual view integration method. By ontology extraction and merging process, built local ontology of data sources and global ontology to achieve semantic-based data access view. Using mapping information among these ontologies and data sources, could convert semantic search statement to queries on underlying data sources. This method provided a unified and transparent data access view and could avoid the problem of frequent data loading and updating. Through applying in well decision support data-integration-platform, this method achieves a good application effect.
Research and Implementation of Domain-specific Virtual Data Center Based on Semantics

LI Hua-yu,HU Chang-jun,OUYANG Chun-ping,YE Yin-zhu,

计算机科学 , 2011,
Abstract: The data involved in the field of oil-well-engineering are distributed, heterogeneous and autonomous, and there is also a complex semantic association among them Under this circumstance, effective global support for decisionmaking is difficult to ensure. Using integration technology of ontology and virtual view, this paper presented a virtual data center solution for oil-well data integration. Through global-ontology construction, ontology extraction, ontology mapping and query conversion, the data in oil-well engineering field can be semantically integrated. Consequently, a unified and semanti}based data query and shared services were achieved. By practical application, this virtual data center is able to supply production decision with comprehensive and real-time data services.
Approach of Ontology Learning from Relational Database Based on FCA

OUYANG Chun-ping,HU Chang-jun LI Yang LIU Zhen-yu,

计算机科学 , 2011,
Abstract: Ontology learning is a process,which extracts semantic information from the existing data model and generates ontology using a set of predefined mapping rules. Relational database is the main model of data access and management,and extracting ontology from relational database is one of the research hotspots in ontology engineering field. A common method adopted by the domestic and foreign scholars is that ontology is constructed by using mapping rules between E-R model and ontology elements. But this method is subjective and it goes against the application of ontology. To address this issue, an approach of ontology learning from relational database based on formal concept analysis was proposed,which could obtain the hierarchical relation of concept and semantic relation of data objectively. The proposed method not only keeps the semantic information of relational data tables, but also shows the advantage of FCA in automatic extraction of semantic information. Thus the quality of final ontology is improved and the application field of ontology is extended. A case study of the proposed method combined with materials service safety database was also presented.
Hepatopoietin Cn suppresses apoptosis of human hepatocellular carcinoma cells by up-regulating myeloid cell leukemia-1
Jing Chang, Yang Liu, Dong-Dong Zhang, Da-Jin Zhang, Chu-Tse Wu, Li-Sheng Wang, Chun-Ping Cui
World Journal of Gastroenterology , 2010,
Abstract: AIM: To investigate the role of hepatopoietin Cn (HPPCn) in apoptosis of hepatocellular carcinoma (HCC) cells and its mechanism.METHODS: Two human HCC cell lines, SMMC7721 and HepG2, were used in this study. Immunostaining, Western blotting and enzyme linked immunosorbent assay were conducted to identify the expression of HPPCn and the existence of an autocrine loop of HPPCn/HPPCn receptor in SMMC7721 and HepG2. Apoptotic cells were detected using fluorescein isothiocyanate (FITC)-conjugated Annexin V and propidium iodide.RESULTS: The HPPCn was highly expressed in human HCC cells and secreted into culture medium (CM). FITC-labeled recombinant human protein (rhHPPCn) could specifically bind to its receptor on HepaG2 cells. Treatment with 400 ng/mL rhHPPCn dramatically increased the viability of HCC-derived cells from 48.1% and 36.9% to 85.6% and 88.4%, respectively (P < 0.05). HPPCn silenced by small-interfering RNA reduced the expression and secretion of HPPCn and increased the apoptosis induced by trichostatin A. Additionally, HPPCn could up-regulate the expression of myeloid cell leukemia-1 (Mcl-1) in HCC cells via mitogen-activated protein kinase (MAPK) and sphingosine kinase-1.CONCLUSION: HPPCn is a novel hepatic growth factor that can be secreted to CM and suppresses apoptosis of HCC cells by up-regulating Mcl-1 expression.
Multisource image classification method based on information fusion in remote sensing

LIU Chun-ping,

计算机应用 , 2007,
Abstract: A new classification and fusion method for multi-source of remote sensing images was put forward based on the D-S evidence theory. Select the interesting region of class by experience and obtain basic probability assignment function by extracting feature at first, then combine multi-source image to be grouped with Dempster's orthogonal rule to get the result of classification. Experiments show that the proposed method is superior to the K-mean. The uncertainty in classification is effectively decreased, as well as the classification accuracy is improved.
Comparison of clustering methods based on Kohonen neural network in remote sensing classification

LIU Chun-ping,

计算机应用 , 2006,
Abstract: Three kinds of clustering methods,including KCN(Kohonen Clustering Network), FKCN(Fuzzy c-Means based Kohonen Clustering Network) and EPKCN(Evolutionary Programming based Kohonen Clustering Network) that were applied in the classification of remote sensing image,were discussed.Experiments show that these unsupervised learning methods had different characters in classifying land use/cover of remote sensing.To EPKCN,the vision effect of classification is best and the rate of single iteration is fastest;To FKCN,when the training process trends to convergence,the total training rate is fastest.However,taking into count the demand of land use/cover classification in remote sensing,EPKCN is the best one in these three algorithms,and can be applied in unsupervised classification of remote sensing land use/cover.
Study on the electronic structures of CsI crystal with F-type color center

Pu Chun-Ying,Liu Ting-Yu,Liu Chang-Jie,Bai Xiao-Ming,Li Chun-Ping,She Hui,

物理学报 , 2010,
Abstract: 运用以密度泛函理论为基础的相对论性离散变分方法(DV-Xα)模拟计算了完整的和含有F心、F+心以及F2心的碘化铯(CsI)晶体的电子结构,得到了含F心和F+心以及F2心的CsI晶体电子态密度分布以及它们可能产生的光学跃迁模式.计算结果表明,含F心和F2心的CsI晶体的禁带宽度明显变窄,F心和F2心的能级都出现在禁带中并且作为施主能级位于导带底部,利用过渡态理论计算得到其能级向
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