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A scalable and adaptive method for finding semantically equivalent cue words of uncertainty
Chen, Chaomei,Song, Min,Heo, Go Eun Elsevier 2018 Journal of Informetrics Vol.12 No.1
<P><B>Abstract</B></P> <P>Scientific knowledge is constantly subject to a variety of changes due to new discoveries, alternative interpretations, and fresh perspectives. Understanding uncertainties associated with various stages of scientific inquiries is an integral part of scientists’ domain expertise and it serves as the core of their meta-knowledge of science. Despite the growing interest in areas such as computational linguistics, systematically characterizing and tracking the epistemic status of scientific claims and their evolution in scientific disciplines remains a challenge. We present a unifying framework for the study of uncertainties explicitly and implicitly conveyed in scientific publications. The framework aims to accommodate a wide range of uncertainty types, from speculations to inconsistencies and controversies. We introduce a scalable and adaptive method to recognize semantically equivalent cues of uncertainty across different fields of research and accommodate individual analysts’ unique perspectives. We demonstrate how the new method can be used to expand a small seed list of uncertainty cue words and how the validity of the expanded candidate cue words is verified. We visualize the mixture of the original and expanded uncertainty cue words to reveal the diversity of expressions of uncertainty. These cue words offer a novel resource for the study of uncertainty in scientific assertions.</P> <P><B>Highlights</B></P> <P> <UL> <LI> A generalized framework of uncertainty is presented to accommodate uncertainties. </LI> <LI> A scalable and adaptive method selects semantically equivalent words. </LI> <LI> The method advances the selection of scientific assertions involving uncertainties. </LI> <LI> The study offers new resources for studying the role of uncertainty in science. </LI> </UL> </P>
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Chen, Chaomei Korea Institute of Science and Technology Informat 2018 Journal of Information Science Theory and Practice Vol.6 No.2
Digital Science's Dimensions is envisaged as a next-generation research and discovery platform for more efficient access to cross-referenced scholarly publications, grants, patents, and clinical trials. As a new addition to the growing open citation resources, it offers opportunities that may benefit a wide variety of stakeholders of scientific publications, from researchers and policy makers to the general public. In this article, we explore and demonstrate some of the practical potentials in terms of cascading citation expansions. Given a set of publications, the cascading citation expansion process can be iteratively applied to a set of articles so as to extend the coverage to more and more relevant articles through citation links. Although the conceptual origin can be traced back to Garfield's citation indexing, it has been largely limited, until recently, to the few who have unrestricted access to a citation database that is large enough to sustain such iterative expansions. Building on the open application program interface of Dimensions, we integrate cascading citation expansion functions in CiteSpace and demonstrate how one may benefit from these new capabilities. In conclusion, cascading citation expansion has the potential to improve our understanding of the structure and dynamics of scientific knowledge.
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Commutativity and hyponormality of Toeplitz operators on the weighted Bergman space
Yufeng Lu,Chaomei Liu 대한수학회 2009 대한수학회지 Vol.46 No.3
In this paper we give necessary and sufficient conditions that two Toeplitz operators with monomial symbols acting on the weighted Bergman space commute. We also present necessary and sufficient conditions for the hyponormality of Toeplitz operators with some special symbols on the weighted Bergman space. All the results are stated in terms of the Mellin transform of the symbol. In this paper we give necessary and sufficient conditions that two Toeplitz operators with monomial symbols acting on the weighted Bergman space commute. We also present necessary and sufficient conditions for the hyponormality of Toeplitz operators with some special symbols on the weighted Bergman space. All the results are stated in terms of the Mellin transform of the symbol.
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COMMUTATIVITY AND HYPONORMALITY OF TOEPLITZ OPERATORS ON THE WEIGHTED BERGMAN SPACE
Lu, Yufeng,Liu, Chaomei Korean Mathematical Society 2009 대한수학회지 Vol.46 No.3
In this paper we give necessary and sufficient conditions that two Toeplitz operators with monomial symbols acting on the weighted Bergman space commute. We also present necessary and sufficient conditions for the hyponormality of Toeplitz operators with some special symbols on the weighted Bergman space. All the results are stated in terms of the Mellin transform of the symbol.
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Image Denoising Based on Adaptive Fractional Order Anisotropic Diffusion
( Jimin Yu ),( Lijian Tan ),( Shangbo Zhou ),( Liping Wang ),( Chaomei Wang ) 한국인터넷정보학회 2017 KSII Transactions on Internet and Information Syst Vol.11 No.1
Recently, the method based on fractional order partial differential equation has been used in image processing. Usually, the optional order of fractional differentiation is determined by a lot of experiments. In this paper, a denoising model is proposed based on adaptive fractional order anisotropic diffusion. In the proposed model, the complexity of the local image texture is reflected by the local variance, and the order of the fractional differentiation is determined adaptively. In the process of the adaptive fractional order model, the discrete Fourier transform is applied to compute the fractional order difference as well as the dynamic evolution process. Experimental results show that the peak signal-to-noise ratio (PSNR) and structural similarity index measurement (SSIM) of the proposed image denoising algorithm is better than that of other some algorithms. The proposed algorithm not only can keep the detailed image information and edge information, but also obtain a good visual effect.
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