Determination of all syzygies for the dependent polynomial invariants of the Riemann Tensor. III. mixed invariants of arbitrary degree in the Ricci Spinor

In this paper, we rigorously prove that the complete set of Riemann tensor invariants given by Sneddon [J. Math. Phys. 40, 5905 (1999)] is both minimal and complete. Furthermore, we provide a two-stage algorithm for the explicit construction of polynomial syzygies relating any dependent Riemann tensor invariant to members of the complete set.

An authorization policy management framework for dynamic medical data sharing

In this paper, we propose a novel feature reduction approach to group words hierarchically into clusters which can then be used as new features for document classification. Initially, each word constitutes a cluster. We calculate the mutual confidence between any two different words. The pair of clusters containing the two words with the highest mutual confidence are combined into a new cluster. This process of merging is iterated until all the mutual confidences between the un-processed pair of words are smaller than a predefined threshold or only one cluster exists. In this way, a hierarchy of word clusters is obtained. The user can decide the clusters, from a certain level, to be used as new features for document classification. Experimental results have shown that our method can perform better than other methods.

Sharing good teaching practice: Practical strategies to integrate ICT into the classroom

Situated in regional areas of Victoria, a group of 16 primary and secondary teachers participated in an intensive program of professional development designed to assist them in embedding lCT into their classroom practice. Most teachers made significant changes to their teaching practice becoming risk-takers and problem solvers.This paper reports on the strategic innovations introduced by the teachers including training, preparation, curriculum planning, software evaluation and selection, classroom management strategies, cooperative learning strategies and embedded assessment tasks. The paper will explore the ways these innovations responded to a variety of constraints including limited resources, time and support.

Sharing and speaking about African music : professional development with Swaziland primary school teachers

The teaching and learning of Indigenous African music is characterised as a holistic integrated experience where music, dance and theatre are inseparable, seen as an integral part of culture. The transmission of this experience is absorbed through participation in cultural activities from childhood in the community. In African societies, both traditional and contemporary, musical arts education and the understanding of culture are fundamental to life, community and society. It is through musical arts, that Africans embrace spiritual, emotional, material and intellectual aspects and knowledge of both the individual and the community. This paper reports on an in-service program (August 2006) offered at the Centre for Indigenous African Instrumental Music and Dance Practices (CIIMDA), Pretoria, South Africa. For the purpose of this paper, the one week professional development course undertaken by generalist primary school teachers from Swaziland is highlighted and proves worthy for these teachers to implement what they learnt in the classroom. As a position paper, I contend that the understanding and participation in indigenous cultural musical arts practices, enlightens learners about their cultural heritage and further enriches their understanding of African music and dance that can be adopted, adapted and applied to primary schools in Swaziland. This paper summaries some key findings of interview data from ten participants in relation to the intensive program. By offering such in-service professional development programs, teachers are able to reach their wider communities where they will continue to share and speak about African music, dance and culture.

Information sharing between heterogeneous uncertain reasoning models in a multi-agent environment : a case study

The issue of information sharing and exchanging is one of the most important issues in the areas of artificial intelligence and knowledge-based systems (KBSs), or even in the broader areas of computer and information technology. This paper deals with a special case of this issue by carrying out a case study of information sharing between two well-known heterogeneous uncertain reasoning models: the certainty factor model and the subjective Bayesian method. More precisely, this paper discovers a family of exactly isomorphic transformations between these two uncertain reasoning models. More interestingly, among isomorphic transformation functions in this family, different ones can handle different degrees to which a domain expert is positive or negative when performing such a transformation task. The direct motivation of the investigation lies in a realistic consideration. In the past, expert systems exploited mainly these two models to deal with uncertainties. In other words, a lot of stand-alone expert systems which use the two uncertain reasoning models are available. If there is a reasonable transformation mechanism between these two uncertain reasoning models, we can use the Internet to couple these pre-existing expert systems together so that the integrated systems are able to exchange and share useful information with each other, thereby improving their performance through cooperation. Also, the issue of transformation between heterogeneous uncertain reasoning models is significant in the research area of multi-agent systems because different agents in a multi-agent system could employ different expert systems with heterogeneous uncertain reasonings for their action selections and the information sharing and exchanging is unavoidable between different agents. In addition, we make clear the relationship between the certainty factor model and probability theory.

Multi-level semantic analysis for sports video

There has been a huge increase in the utilization of video as one of the most preferred type of media due to its content richness for many significant applications including sports. To sustain an ongoing rapid growth of sports video, there is an emerging demand for a sophisticated content-based indexing system. Users recall video contents in a high-level abstraction while video is generally stored as an arbitrary sequence of audio-visual tracks. To bridge this gap, this paper will demonstrate the use of domain knowledge and characteristics to design the extraction of high-level concepts directly from audio-visual features. In particular, we propose a multi-level semantic analysis framework to optimize the sharing of domain characteristics.

A logical framework for knowledge sharing in multi-agent systems

The issue of knowledge sharing has been an important topic in multi-agent research. Knowledge sharing leads to that agents analyze, judge and synthesize the told information so as to make agents’ own knowledge. To match these applications, this paper builds a logical framework for knowledge sharing among agents. We develop a multimodal logic for reasoning about both agents’ knowledge and told information. For formalizing the relationship between knowledge and told information, we present a framework of semantics, with respect to which a sound and complete proof theory is given.

Socio-technical factors influencing channel use for knowledge-sharing in regional SME networks

The economic sustainability of regional areas is dependent on cross-industry innovation and knowledge-sharing among Small and Medium Enterprises (SMEs). The web-based initiatives deployed in regions worldwide to facilitate SME knowledge-sharing have typically been unsuccessful. This paper argues that the main reason for these failures is the lack of understanding of the socio-technical factors which influence the use of web-based channels (websites, online forums and expertise databases) as well as the more conventional channels (face-to-face and e-mail). This paper reports the findings of interpretive case studies of two regional SME business networks. It evaluates the major channels on six socio-technical criteria: link strength; trustworthiness; tacitness; usability; durability and currency. None of the channels were strong against all socio-technical factors. This highlights the importance of achieving an appropriate mix of channels to facilitate SME knowledge-sharing.