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Search Results: 1 - 10 of 43043 matches for " Weihua Xu "
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Lower Approximation Reduction in Ordered Information System with Fuzzy Decision  [PDF]
Xiaoyan Zhang, Weihua Xu
Applied Mathematics (AM) , 2011, DOI: 10.4236/am.2011.27125
Abstract: Attribute reduction is one of the most important problems in rough set theory. This paper introduces the concept of lower approximation reduction in ordered information systems with fuzzy decision. Moreover, the judgment theorem and discernable matrix are obtained, in which case an approach to attribute reduction in ordered information system with fuzzy decision is constructed. As an application of lower approximation reduction, some examples are applied to examine the validity of works obtained in our works..
Rough Computational Approach to UAR based on Dominance Matrix in IOIS  [PDF]
Xiaoyan Zhang, Weihua Xu
Intelligent Information Management (IIM) , 2011, DOI: 10.4236/iim.2011.34016
Abstract: Rough set theory is a new mathematical tool to deal with vagueness and uncertainty. The classical rough set theory based on equivalence relation has made a great progress, while the equivalence relation is too harsh to meet and is extended to dominance relation in real world. It is important to investigate rough computational methods for rough set theory, which is one of the bottleneck problems in the development of rough set theory. In this article, rough computational approach to upper ap-proximation reduction (UAR) is discussed based on dominance matrix in inconsistent ordered information systems (IOIS). The algorithm of upper approximation reduction is obtained, from which we can provide approach to upper approximation reduction operated simply in inconsistent systems based on dominance relations. Finally, an example illustrates the validity of this method, and shows the method is excellent to a complicated information system.
Methods for Lower Approximation Reduction in Inconsistent Decision Table Based on Tolerance Relation  [PDF]
Xiaoyan Zhang, Weihua Xu
Applied Mathematics (AM) , 2013, DOI: 10.4236/am.2013.41024
Abstract: It is well known that most of information systems are based on tolerance relation instead of the classical equivalence relation because of various factors in real-world. To acquire brief decision rules from the information systems, lower approximation reduction is needed. In this paper, the lower approximation reduction is proposed in inconsistent information systems based on tolerance relation. Moreover, the properties are discussed. Furthermore, judgment theorem and discernibility matrix are obtained, from which an approach to lower reductions can be provided in the complicated information systems.

On Starshaped Intuitionistic Fuzzy Sets  [PDF]
Weihua Xu, Yufeng Liu, Wenxin Sun
Applied Mathematics (AM) , 2011, DOI: 10.4236/am.2011.28146
Abstract: Intuitionistic fuzzy starshaped sets (i.f.s.) is a generalized model of fuzzy starshaped set. By the definition of i.f.s., the intuitionistic fuzzy general starshaped sets (i.f.g.s.), intuitionistic fuzzy quasi-starshaped sets (i.f.q-s.) and intuitionistic fuzzy pseudo-starshaped sets (i.f.p-s.) are proposed and the relationships among them are studied. The equivalent discrimination conditions of i.f.q-s. and i.f.p-s. are presented on the basis of their properties which are meaningful for the research of the generalized fuzzy starshaped sets. Moreover, the invariance of the two given fuzzy sets under the translation transformation and linear reversible transformation are discussed.
Ranking for Objects and Attribute Reductions in Intuitionistic Fuzzy Ordered Information Systems
Xiaoyan Zhang,Weihua Xu
Mathematical Problems in Engineering , 2012, DOI: 10.1155/2012/426901
Abstract: We aim to investigate intuitionistic fuzzy ordered information systems. The concept of intuitionistic fuzzy ordered information systems is proposed firstly by introducing an intuitionistic fuzzy relation to ordered information systems. And a ranking approach for all objects is constructed in this system. In order to simplify knowledge representation, it is necessary to reduce some dispensable attributes in the system. Theories of rough set are investigated in intuitionistic fuzzy ordered information systems by defining two approximation operators. Moreover, judgement theorems and methods of attribute reduction are discussed based on discernibility matrix in the systems, and an illustrative example is employed to show its validity. These results will be helpful for decisionmaking analysis in intuitionistic fuzzy ordered information systems.
Synthesis dynamic and developmental profile of prothoracicotropic hormone between diapause- and nondiapause-destined individuals in Helicoverpa armigera
ChengLin Hou,WeiHua Xu
Chinese Science Bulletin , 2007, DOI: 10.1007/s11434-007-0310-1
Abstract: Biosynthesis and secretion of prothoracicotropic hormone (PTTH) of diapause- and nondiapause-destined individuals in Helicoverpa armigera were studied using whole-mount immunocytochemistry and enzyme-linked immunosorbent assay (ELISA). The immunocytochemistry revealed that PTTH is expressed in two pairs of lateral neurosecretory cells of the brain. The presence of immunoreactivity has not significant difference between the brains of the diapause- and nondiapause-destined 6th instar larvae. However, the obvious differences of expressional pattern from day 4 pupae were observed between the two types. PTTH titers in hemolymph from the 6th instar larvae to pharate adults were measured by the ELISA. Although there were similar titer changes between the two types of individuals at the larval stage, a significant difference from developmental expression was detected at the pupal stage, suggesting that the expression and secretion of PTTH does play a crucial role in regulation of pupal diapause of H. armigera.
On Granularity in Information Systems Based on Binary Relation  [PDF]
Weihua Xu, Shihu Liu, Xiaoyan Zhang, Wenxiu Zhang
Intelligent Information Management (IIM) , 2011, DOI: 10.4236/iim.2011.33010
Abstract: In this paper, some important issues of granularity are discussed mainly in information systems (ISs) based on binary relation. Firstly, the vector representation method of knowledge granules is proposed in an infor-mation system based on binary relation to eliminate limitations of set representation method. Secondly, operators among knowledge granularity are introduced and some important properties of them are studied carefully. Thirdly, distance between two knowledge granules is established and granular space is constructed based on it. Fourthly, axiomatic definition of knowledge granularity is investigated, and one can find that some existed knowledge granularities are special cases under the definition. In addition, as an application of knowledge granular space, an example is employed to validate some results in our work.
Estrogen Receptor β of Host Promotes the Progression of Lung Cancer Brain Metastasis of an Orthotopic Mouse Model  [PDF]
Lei Xu, Guang Gao, Jiangong Ren, Fei Su, Zhang Weihua
Journal of Cancer Therapy (JCT) , 2012, DOI: 10.4236/jct.2012.324046
Abstract: Estrogen receptors (ERα and ERβ) in the brain play critical roles in maintaining brain tissue homeostasis and in tissue repair after injury. Growth of cancer metastasis in the brain is a constant damaging process. The role of ERs of the host in the progression of cancer brain metastasis is unknown. To determine the role of ERβ of host in the progression of lung cancer brain metastasis, we used an isogenic murine lung cancer cell line, Lewis lung carcinoma cells (3LL), to produce orthotopic lung cancer brain metastases in wild type and ERβ knockout (ERβ-/-) mice. In the wild type mice, we found that ERα and ERβ appeared in the tumor associated reactive astrocytes at 24hr after injection of tumor cells, and ERβ remained thereafter while ERα disappeared after 1 week. The metastasis bearing ERβ-/- mice survived significantly longer than the wild type mice. To further test the role of ERβ of reactive astrocytes in the survival of cancer cells, we knocked down ERβ in cultured actrocytes using shRNA and performed 3D co-culture with 3LL cells in the presence/absence of chemotherapeutic agents, oxaliplatin and 5-fluorouracil. We found that loss of ERβ in astrocytes significantly reduced the survivability of 3LL cells co-cultured with astrocytes. It is concluded that ERβ of host, especially ERβ in reactive astrocytes, promotes the progression of lung cancer brain metastasis and ERβ might be a potential therapeutic target for lung cancer brain metastasis.
A finite-dimensional integrable system associated with a polynomial eigenvalue problem
Taixi Xu,Weihua Mu,Zhijun Qiao
International Journal of Mathematics and Mathematical Sciences , 2006, DOI: 10.1155/ijmms/2006/13479
Abstract: M. Antonowicz and A. P. Fordy (1988) introduced the second-order polynomial eigenvalue problem Lφ=(∂2
Rough Set Approach to Approximation Reduction in Ordered Decision Table with Fuzzy Decision
Xiaoyan Zhang,Shihu Liu,Weihua Xu
Mathematical Problems in Engineering , 2011, DOI: 10.1155/2011/268929
Abstract: In practice, some of information systems are based on dominance relations, and values of decision attribute are fuzzy. So, it is meaningful to study attribute reductions in ordered decision tables with fuzzy decision. In this paper, upper and lower approximation reductions are proposed in this kind of complicated decision table, respectively. Some important properties are discussed. The judgement theorems and discernibility matrices associated with two reductions are obtained from which the theory of attribute reductions is provided in ordered decision tables with fuzzy decision. Moreover, rough set approach to upper and lower approximation reductions is presented in ordered decision tables with fuzzy decision as well. An example illustrates the validity of the approach, and results show that it is an efficient tool for knowledge discovery in ordered decision tables with fuzzy decision. 1. Introduction Rough set theory, which was first proposed by Pawlak in the early 1980s [1], can describe knowledge via set-theoretic analysis based on equivalence classification for the universe of discourse. It provides a theoretical foundation for inference reasoning about data analysis and has extensive applications in areas of artificial intelligence and knowledge acquisition. A primary use of rough set theory is to reduce the number of attributes in databases thereby improving the performance of applications in a number of aspects including speed, storage, and accuracy. For a data set with discrete attribute values, this can be done by reducing the number of redundant attributes and find a subset of the original attributes that are the most informative. As is well known, an information system may usually has more than one reduct. It means that the set of rules derived from knowledge reduction is not unique. In practice, it is always hoped to obtain the set of the most concise rules. Therefore, people have been attempting to find the minimal reduct of information systems, which means that the number of attributes contained in the reduction is minimal. Unfortunately, it has been proven that finding the minimal reduct of an information system is an NP-hard problem. Recently, some new theories and reduction methods have been developed. Many types of knowledge reduction have been proposed in the area of rough sets [2–8]. Possible rules and reducts have been proposed as a way to deal with inconsistence in an inconsistent decision table [9]. Approximation rules [10] are also used as an alternative to possible rules. On the other hand, generalized decision rules and
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