Designing learning object repositories : a thesis presented in partial fulfilment of the requirements for the degree of Master of Information Science in Information Sciences at Massey University

Learning object repositories are expanding rapidly into the role of independent educational systems that not only are a supplement to a traditional way of learning, but also allow users to search, exchange and re-use learning objects. The intention of this innovative technology is to have such repositories to collect a database of learning objects catalogued by the learning content management system. However, for users to perform an efficient search, these learning objects would need to use metadata standards or specifications to describe their properties. For learning objects stored within the repositories, metadata standards are often used to descibe them so users of the respositories are able to find the accurate resources they required, hence metadata standards are important elements of any learning object repository. In this paper, a courseware example is used to demonstrate how to define a set of characteristics that we want to describe for our courseware, and attempt to map the data schema in the database with the available metadata standards. The outcome is to identify a set of metadata elements that would fully describe our learning objects stored within the learning object repository, and these metadata elements will also assist instructors to create adaptable courseware that can be reused by different instructors. Metadata standard is known as a critical element for the management of learning objects, not only will it increase the accuracy of the search results, it will also provide more relevant and descriptive information about the learning objects to the searchers

Exchange-Correlation Energy from Pairing Matrix Fluctuation and the Particle-Particle Random Phase Approximation

We formulate an adiabatic connection for the exchange-correlation energy in terms of pairing matrix fluctuation. This connection opens new channels for density functional approximations based on pairing interactions. Even the simplest approximation to the pairing matrix fluctuation, the particle-particle Random Phase Approximation (pp-RPA), has some highly desirable properties. It has no delocalization error with a nearly linear energy behavior for systems with fractional charges, describes van der Waals interactions similarly and thermodynamic properties significantly better than particle-hole RPA, and eliminates static correlation error for single-bond systems. Most significantly, the pp-RPA is the first known functional that has an explicit and closed-form dependence on the occupied and unoccupied orbitals and captures the energy derivative discontinuity in strongly correlated systems. These findings illlustrate the potential of including pairing interactions within a density functional framework

The Flagellar Motility of \u3cem\u3eChlamydomonas pf25\u3c/em\u3e Mutant Lacking an AKAP-binding Protein Is Overtly Sensitive to Medium Conditions

Radial spokes are a conserved axonemal structural complex postulated to regulate the motility of 9 + 2 cilia and flagella via a network of phosphoenzymes and regulatory proteins. Consistently, a Chlamydomonas radial spoke protein, RSP3, has been identified by RII overlays as an A-kinase anchoring protein (AKAP) that localizes the cAMP-dependent protein kinase (PKA) holoenzyme by binding to the RIIa domain of PKA RII subunit. However, the highly conserved docking domain of PKA is also found in the N termini of several AKAP-binding proteins unrelated to PKA as well as a 24-kDa novel spoke protein, RSP11. Here, we report that RSP11 binds to RSP3 directly in vitro and colocalizes with RSP3 toward the spoke base near outer doublets and dynein motors in axonemes. Importantly, RSP11 mutant pf25 displays a spectrum of motility, from paralysis with flaccid or twitching flagella as other spoke mutants to wild-typelike swimming. The wide range of motility changes reversibly depending on the condition of liquid media without replacing defective proteins. We postulate that radial spokes use the RIIa/AKAP module to regulate ciliary and flagellar beating; absence of the spoke RIIa protein exposes a medium-sensitive regulatory mechanism that is not obvious in wild-type Chlamydomonas

Application of EOS-ELM with binary Jaya-based feature selection to real-time transient stability assessment using PMU data

Recent studies show that pattern-recognition-based transient stability assessment (PRTSA) is a promising approach for predicting the transient stability status of power systems. However, many of the current well-known PRTSA methods suffer from excessive training time and complex tuning of parameters, resulting in inefficiency for real-time implementation and lacking the online model updating ability. In this paper, a novel PRTSA approach based on an ensemble of OS-extreme learning machine (EOSELM) with binary Jaya (BinJaya)-based feature selection is proposed with the use of phasor measurement units (PMUs) data. After briefly describing the principles of OS-ELM, an EOS-ELM-based PRTSA model is built to predict the post-fault transient stability status of power systems in real time by integrating OS-ELM and an online boosting algorithm, respectively, as a weak classifier and an ensemble learning algorithm. Furthermore, a BinJaya-based feature selection approach is put forward for selecting an optimal feature subset from the entire feature space constituted by a group of system-level classification features extracted from PMU data. The application results on the IEEE 39-bus system and a real provincial system show that the proposal has superior computation speed and prediction accuracy than other state-of-the-art sequential learning algorithms. In addition, without sacrificing the classification performance, the dimension of the input space has been reduced to about one-third of its initial value.Comment: Accepted by IEEE Acces