Supporting adaptive learning in hypertext environments : a high level timed Petri net-based approach

A problem for hypertext-based learning application is to control learning paths for different learning activities. This paper first introduces related concepts of hypertext learning state space and high level Petri Nets (PNs), then proposes a high level timed PN based approach used to providing kinds of adaptation for learning activities by adjusting time attributes of targeted learning state space. Examples are given while explaining ways to realising adaptive instructions. Possible future directions are also discussed at the end of this paper.

Layered dynamic probabilistic networks for spatio-temporal modelling

In applications such as tracking and surveillance in large spatial environments, there is a need for representing dynamic and noisy data and at the same time dealing with them at different levels of detail. In the spatial domain, there has been work dealing with these two issues separately, however, there is no existing common framework for dealing with both of them. In this paper, we propose a new representation framework called the Layered Dynamic Probabilistic Network (LDPN), a special type of Dynamic Probabilistic Network (DPN), capable of handling uncertainty and representing spatial data at various levels of detail. The framework is thus particularly suited to applications in wide-area environments which are characterised by large region size, complex spatial layout and multiple sensors/cameras. For example, a building has three levels: entry/exit to the building, entry/exit between rooms and moving within rooms. To avoid the problem of a relatively large state space associated with a large spatial environment, the LDPN explicitly encodes the hierarchy of connected spatial locations, making it scalable to the size of the environment being modelled. There are three main advantages of the LDPN. First, the reduction in state space makes it suitable for dealing with wide area surveillance involving multiple sensors. Second, it offers a hierarchy of intervals for indexing temporal data. Lastly, the explicit representation of intermediate sub-goals allows for the extension of the framework to easily represent group interactions by allowing coupling between sub-goal layers of different individuals or objects. We describe an adaptation of the likelihood sampling inference scheme for the LDPN, and illustrate its use in a hypothetical surveillance scenario.

A probabilistic framework for tracking in wide-area environments

Surveillance in wide-area spatial environments is characterised by complex spatial layouts, large state space, and the use of multiple cameras/sensors. To solve this problem, there is a need for representing the dynamic and noisy data in the tracking tasks, and dealing with them at different levels of detail. This requirement is particularly suited to the Layered Dynamic Probabilistic Network (LDPN), a special type of Dynamic Probabilistic Network (DPN). In this paper, we propose the use of LDPN as the integrated framework for tracking in wide-area environments. We illustrate, with the help of a synthetic tracking scenario, how the parameters of the LDPN can be estimated from training data, and then used to draw predictions and answer queries about unseen tracks at various levels of detail.

Face recognition via incremental 2DPCA

Recently, the Two-Dimensional Principal Component Analysis (2DPCA) model is proposed and proved to be an efficient approach for face recognition. In this paper, we will investigate the incremental 2DPCA and develop a new constructive method for incrementally adding observation to the existing eigen-space model. An explicit formula for incremental learning is derived. In order to illustrate the effectiveness of the proposed approach, we performed some typical experiments and show that we can only keep the eigen-space of previous images and discard the raw images in the face recognition process. Furthermore, this proposed incremental approach is faster when compared to the batch method (2DPCD) and the recognition rate and reconstruction accuracy are as good as those obtained by the batch method.

Wal-Mart’s trade union in China

In 2007–8, more than 100 Wal-Mart stores in China established trade unions, which were praised by labour organizations and scholars throughout the world. This article questions these positive assessments and evaluations through an empirical study. The empirical findings reveal a dark and unpleasant picture of a double cooptation in that both the Chinese government and Wal-Mart have successfully coopted a few more or less independent unions. Although the presence of the trade union seems to challenge Wal-Mart’s neoliberal corporate ideology and governance, the compromise and tacit agreement between Wal-Mart and the party-state not only reflects a marriage of convenience but also indicates some deeper compatibility, the compatibility between China’s state corporatist model and the neoliberal approach taken by Wal-Mart. This study finds that China continues to move in a ‘state corporatist’ direction and that the transition towards civil society and ‘societal corporatism’ has been stymied.

Supporting personalised content management in smart health information portals

Information portals are seen as an appropriate platform for personalised healthcare and wellbeing information provision. Efficient content management is a core capability of a successful smart health information portal (SHIP) and domain expertise is a vital input to content management when it comes to matching user profiles with the appropriate resources. The rate of generation of new health-related content far exceeds the numbers that can be manually examined by domain experts for relevance to a specific topic and audience. In this paper we investigate automated content discovery as a plausible solution to this shortcoming that capitalises on the existing database of expert-endorsed content as an implicit store of knowledge to guide such a solution. We propose a novel content discovery technique based on a text analytics approach that utilises an existing content repository to acquire new and relevant content. We also highlight the contribution of this technique towards realisation of smart content management for SHIPs.

Freshwater influences on hydrology and seagrass dynamics of intermittent estuaries

Many temperate estuaries have intermittently open and closed mouths, a feature that is often related to intermittent freshwater input. These systems, often overlooked due to their small size, can have large hydrological variability over medium-term time scales.

This variability presents potential difficulties for estuarine species particularly where anthropogenic alterations to freshwater flows can cause large deviations from natural patterns of tidal influence and inundation of habitat.

Influences of natural and hydrological variability on seagrasses were examined in two central Victorian estuaries with anthropogenically-modified but naturally-intermittent freshwater flows and mouth openings. Comparisons were focused on differences between an estuary with artificially-augmented freshwater inflow and an adjacent system, in which the volume and timing of inflows were altered by a reservoir. Eight additional estuaries in the region were also used to provide a context for these two main sites.

Hydrological changes during the three-year field component were affected by the ending of a drought and then a major flood a year later as well as by ongoing anthropogenic flow reduction and augmentation. These influences on hydrology were associated with an initially high seagrass coverage that was substantially reduced and showed signs of recovery only in the system that was affected by lower inflows. Such influences and responses also changed seasonally but to a much lesser extent than the responses to stochastic climatic events.

Natural flows were intermittent and varied substantially between years. Flooding flows represented up to 89% of the long-term annual average flow. Water quality was broadly typical of the region, with the exception of low pH in some tributaries, especially those of Anglesea estuary. Anthropogenic changes to flow were most evident at times of low natural flows and resulted in longer and more frequent periods of zero inflow to Painkalac estuary and a continual base flow to Anglesea. This base flow, from ponds containing coal ash, neutralised waters flowing from upstream and increased conductivity, except at times of high natural flow.

A three-state conceptual model of the magnitude and variability of water levels, based largely on the degree of tidal influence was identified and quantitatively assessed for the two estuaries that were the main focus of the study. These states in turn had a large influence on the area and inundation of benthic habitat. Floods tended to open the mouths of estuaries, which then remained tidal given sufficient flow to overcome sedimentary processes at the mouths. Low and zero inflow was a precondition for closure of the mouths of the estuaries. When closed, differences in inflow resulted in different endpoints in salinity patterns. From an initial pattern similar to a classic ‘salt wedge’, Painkalac estuary, with reduced inflow, quickly destratified and gradually became more saline, at times hypersaline. Anglesea estuary, with augmented flow, tended to remain stratified for longer until becoming completely fresh, given a long enough period of closure.

Episodic changes in the water quality of the estuaries were associated with different components of the freshwater flow regimes. At high flows, fresh waters of low pH with a high metal load entered Anglesea estuary. Except during the largest flood, when the estuary was completely flushed, this water was neutralised at the halocline and resulting in precipitation of metals. High flows into Painkalac were associated with elevated concentrations of clay-sourced suspended solids. During a closed period, with zero flow, a release of sediment-bound nutrients triggered by anoxia was observed in Painkalac, followed by an algal bloom.

The large decline in seagrass extent that was observed in both estuaries was closely related to floods and the subsequent reductions in potential habitat associated with the tidal states that followed. Analysis of historical patterns of extent against rainfall records suggested that periods of drought and extended mouth closures were related to establishment and expansion of beds. This model was similar to that described for South African estuaries and contrasted with more-seasonal patterns reported for local marine embayments.

Rates of in situ decomposition of seagrass detritus showed a mix of seasonal and disturbance-driven patterns of change, depending on estuary. Variability of these rates on a scale of 100s of metres was typically not significant, but there were a few episodes that were highly significant. A negative correlation between decomposition rate and seagrass extent was also observed. A novel technique for assessing cellulose decomposition potential in sediment, adapted from soil science, proved to be a useful tool for estuarine research. Results from this component of the study highlighted both small-scale variability that was inconsistent through time, and also stable differences in decomposition potential between depths and estuaries that were consistent with differences in hydrological state and salinity.

Given the relative lack of knowledge about processes in intermittent estuaries, particularly those relating to changes in freshwater inflow, results from this study will be of value both locally and for similar systems elsewhere. Locally, it is likely that flow regimes to both Anglesea and Painkalac estuaries will be reduced, following closure of the mine power station at Anglesea and due to increased demand from the reservoir above Painkalac. There is potential to manage flows from each of these sources to minimise downstream effects. Regionally, and globally, there are many intermittent estuaries in areas with Mediterranean-type climates. It has been predicted that the climates of these regions will become drier but with an increase in intensity of storm events, both of which have ramifications for flow regimes to estuaries. It is hoped that results of this study will contribute to more informed management of intermittent estuaries in the context of these likely changes.

Diving deeper into individual foraging specializations of a large marine predator, the southern sea lion

Despite global declines in the abundance of marine predators, knowledge of foraging ecology, necessary to predict the ecological consequences of large changes in marine predator abundance, remains enigmatic for many species. Given that populations suffering severe declines are of conservation concern, we examined the foraging ecology of southern sea lions (SSL) (Otaria flavescens)-one of the least studied otariids (fur seal and sea lions)-which have declined by over 90 % at the Falkland Islands since the 1930s. Using a combination of biologging devices and stable isotope analysis of vibrissae, we redress major gaps in the knowledge of SSL ecology and quantify patterns of individual specialization. Specifically, we revealed two discrete foraging strategies, these being inshore (coastal) and offshore (outer Patagonian Shelf). The majority of adult female SSL (72 % or n = 21 of 29 SSL) foraged offshore. Adult female SSL that foraged offshore travelled further (92 ± 20 vs. 10 ± 4 km) and dived deeper (75 ± 23 vs. 21 ± 8 m) when compared to those that foraged inshore. Stable isotope analysis revealed long-term fidelity (years) to these discrete foraging habitats. In addition, we found further specialization within the offshore group, with adult female SSL separated into two clusters on the basis of benthic or mixed (benthic and pelagic) dive behavior (benthic dive proportion was 76 ± 9 vs. 51 ± 8 %, respectively). We suggest that foraging specialization in depleted populations such as SSL breeding at the Falkland Islands, are influenced by foraging site fidelity, and could be independent of intraspecific competition. Finally, the behavioral differences we describe are crucial to understanding population-level dynamics, impediments to population recovery, and threats to population persistence.

Pyrolysis of municipal green waste: a modelling, simulation and experimental analysis

Pyrolysis is the thermo-chemical conversion of carbonaceous feedstock in the absence of oxygen to produce bio-fuel (bio-oil, bio-char and syn-gas). Bio-fuel production from municipal green waste (MGW) through the pyrolysis process has attracted considerable attention recently in the renewable energy sector because it can reduce greenhouse gas emissions and contribute to energy security. This study analyses properties of MGW feedstock available in Rockhampton city of Central Queensland, Australia, and presents an experimental investigation of producing bio-fuel from that MGW through the pyrolysis process using a short sealed rotary furnace. It was found from the experiment that about 19.97% bio-oil, 40.83% bio-char and 29.77% syn-gas can be produced from the MGW. Then, a four-stage steady state simulation model is developed for pyrolysis process performance simulation using Aspen Plus software. In the first stage, the moisture content of the MGW feed is reduced. In the second stage, the MGW is decomposed according to its elemental constituents. In the third stage, condensate material is separated and, finally, the pyrolysis reactions are modelled using the Gibbs free energy minimisation approach. The MGW's ultimate and proximate analysis data were used in the Aspen Plus simulation as input parameters. The model is validated with experimentally measured data. A good agreement between simulation and experimental results was found. More specifically, the variation of modelling and experimental elemental compositions of the MGW was found to be 7.3% for carbon, 15.82% for hydrogen, 7.04% for nitrogen and 5.56% for sulphur. The validated model is used to optimise the biofuel production from the MGW as a function of operating variables such as temperature, moisture content, particle size and process heat air-fuel ratio. The modelling and optimisation results are presented, analysed and discussed.

Characteristics evaluation of a μ-Synthesis H∞ controller for a grid-connected three-phase photovoltaic system

This paper presents a μ-Synthesis H∞ Controller for regulating the switching signal of the inverter connected with a three-phase photovoltaic (PV) system. To facilitate the control design, the system is represented in terms of state space realization with uncertainties. The control design involves selecting proper weighting functions and performing synthesis. The controller order is reduced by Henkel-norm method. Simulations are carried out to evaluate the characteristics of the controller under parametric uncertainties. It is found out that the proposed controller is inherently stable, possesses significantly small tracking error, and preserves nominal performance, robust stability and robust performance for the grid-connected three-phase PV system.

Characteristics evaluation of an LMI-synthesis H∞ controller for a superconducting magnetic energy systems applied in power systems

© 2015 IEEE.This paper presents an H« controller synthesised based on linear matrix inequalities (LMI) for a current source converter based superconducting magnetic energy systems (SMESs) connected to a node of power systems where the regulation of grid current has considered as a control objective. To facilitate the control design, the system is represented in terms of state space realization with uncertainties. The control design involves selecting proper weighting functions and performing LMI-synthesis. The controller order is reduced by Henkel-norm method. Simulations are carried out to evaluate the characteristics of the controller under parametric uncertainties. It is found out that the proposed controller is inherently stable, possesses significantly small tracking error, and preserves robust performance for the SMES.