The Language Policy for Higher Education （2002） and University of Cape Town＇s Language Plan （2001） suggest that language is central to our social and academic engagement at every level： to our communication with...The Language Policy for Higher Education （2002） and University of Cape Town＇s Language Plan （2001） suggest that language is central to our social and academic engagement at every level： to our communication with those around us, to our learning, and to our identities. The purpose of this paper is to show how the medical school, after making progress towards implementing the University of Cape Town＇s Language Plan of 2001, is compelled to encourage isiXhosa language developers to develop the necessary and relevant vocabulary responding to the needs of the target users. In some cases, there is a need to adopt terms that are already available and being used by the speech community to align them in the curriculum. Research conducted by analyzing field notes, having plenary discussions with students, observations during clinical practice, reflecting on the curriculum and study materials material. Results indicated the significance of teaching isiXhosa drawing from the medical jargon understood amongst patients, doctors, and nurses. This paper discusses the status enjoyed by isiXhosa to date, language teaching and teaching matters pertaining to isiXhosa, and reflection on whether there is benefit in learning isiXhosa.展开更多
The sign algorithm has been extensively investigated for digital echo cancellation application and other adaptive filtering applications. In this paper, we use the blind averaging Sign-regressor (SR) algorithm for ada...The sign algorithm has been extensively investigated for digital echo cancellation application and other adaptive filtering applications. In this paper, we use the blind averaging Sign-regressor (SR) algorithm for adaptive multiuser detection. It is another least mean square (LMS) algorithm and eliminates the need for multiplication in the adaptive algorithm. The new algorithm not only reduces the calculation complexity but also has good convergence character. Simulations indicate that this algorithm can adapt to the changes of the environment quickly and improve the stability of the SIR.展开更多
Social tagging systems are widely applied in Web 2.0.Many users use these systems to create,organize,manage,and share Internet resources freely.However,many ambiguous and uncontrolled tags produced by social tagging s...Social tagging systems are widely applied in Web 2.0.Many users use these systems to create,organize,manage,and share Internet resources freely.However,many ambiguous and uncontrolled tags produced by social tagging systems not only worsen users' experience,but also restrict resources' retrieval efficiency.Tag clustering can aggregate tags with similar semantics together,and help mitigate the above problems.In this paper,we first present a common co-occurrence group similarity based approach,which employs the ternary relation among users,resources,and tags to measure the semantic relevance between tags.Then we propose a spectral clustering method to address the high dimensionality and sparsity of the annotating data.Finally,experimental results show that the proposed method is useful and efficient.展开更多
文摘The Language Policy for Higher Education （2002） and University of Cape Town＇s Language Plan （2001） suggest that language is central to our social and academic engagement at every level： to our communication with those around us, to our learning, and to our identities. The purpose of this paper is to show how the medical school, after making progress towards implementing the University of Cape Town＇s Language Plan of 2001, is compelled to encourage isiXhosa language developers to develop the necessary and relevant vocabulary responding to the needs of the target users. In some cases, there is a need to adopt terms that are already available and being used by the speech community to align them in the curriculum. Research conducted by analyzing field notes, having plenary discussions with students, observations during clinical practice, reflecting on the curriculum and study materials material. Results indicated the significance of teaching isiXhosa drawing from the medical jargon understood amongst patients, doctors, and nurses. This paper discusses the status enjoyed by isiXhosa to date, language teaching and teaching matters pertaining to isiXhosa, and reflection on whether there is benefit in learning isiXhosa.
文摘The sign algorithm has been extensively investigated for digital echo cancellation application and other adaptive filtering applications. In this paper, we use the blind averaging Sign-regressor (SR) algorithm for adaptive multiuser detection. It is another least mean square (LMS) algorithm and eliminates the need for multiplication in the adaptive algorithm. The new algorithm not only reduces the calculation complexity but also has good convergence character. Simulations indicate that this algorithm can adapt to the changes of the environment quickly and improve the stability of the SIR.
基金supported by the National Natural Science Foundation of China(Nos.61273292,61303131,51474007,and 51374114)the MOE Humanities and Social Science Research on Youth Foundation of China(No.13YJCZH077)
文摘Social tagging systems are widely applied in Web 2.0.Many users use these systems to create,organize,manage,and share Internet resources freely.However,many ambiguous and uncontrolled tags produced by social tagging systems not only worsen users' experience,but also restrict resources' retrieval efficiency.Tag clustering can aggregate tags with similar semantics together,and help mitigate the above problems.In this paper,we first present a common co-occurrence group similarity based approach,which employs the ternary relation among users,resources,and tags to measure the semantic relevance between tags.Then we propose a spectral clustering method to address the high dimensionality and sparsity of the annotating data.Finally,experimental results show that the proposed method is useful and efficient.
