Managed fund attributes and performance : Australian evidence

This cross-sectional study goes beyond the traditional performance evaluation of managed funds and extends the literature to consider fund-specific attributes that influence performance. Using a sample of 168 Australian open-ended equity funds, the risk adjusted performance is measured using three alternative evaluation techniques. We find that funds with higher management fees and long fund history have contributed to the underperformance. Along with the traditional attributes identified by the literature, market capitalisation of the security held by the fund is included as a unique attribute with significant results, indicating that funds targeting small capitalisation companies display superior performance.

Modelling regulatory change V's volume of trading effects in HSIF and HSI volatility

In an earlier paper, we adopted a bi-variate BEKK–GARCH framework and employed a systematic approach to examine structural breaks in the Hang Seng Index and Index Futures market volatility. Switching dummy variables were included and tested in the variance equations to check for any structural changes in the autoregressive volatility structure due to the events that have taken place in the Hong Kong market surrounding the Asian markets crisis. In this paper, we include measures of daily trading volume from both markets in the estimation. Likelihood ratio tests indicate the switching dummy variables become insignificant and the GARCH effects diminish but remain significant. There is some evidence that the Sequential Arrival of Information Model (SIM) provides a platform to explain these market induced effects when volume of trade is accounted for.

Age and productivity of academics: A case study of a public university in Malaysia

This study examines the relationship between age and productivity measured based on key performance indicators (KPI) amongst academic staff at Universiti Sains Malaysia (USM). Three models were used in the analysis: linear, quadratic and piece-wise spline. The linear model indicates that age is negatively related to KPI. The quadratic model shows an inverted-U shaped relationship where KPI peaks at age 41 years. The piece-wise spline model indicates academic staff reach the peak of their productivity between ages 46-50 years with another productive age interval between 36-40 years implying 10 golden years when KPI could be harvested fruitfully. There is a significant downtrend in the KPI after 50 years of age. Other factors that have significant influence on KPI are gender, academic rank and discipline. The sub-models show that the influence of age on KPI is more significant amongst academic staff in the arts compared to the science stream. Age influence on KPI is significant amongst female staff but not male staff. We conclude that assessing performance in the workplace with regard to age requires complex methodological engagement and also needs to be based on a wider lens which recognises and includes within the discussion, the intangible and social dimensions of performance.

Habitat characteristics for New Holland mouse Pseudomys novaehollandiae in Victoria

Pseudomys novaehollandiae is 'Endangered' in Victoria, where it is presently considered to be extant at only three localities Loch Sport, Providence Ponds, and Wilsons Promontory. This study aimed to determine indicators of suitable habitat for the species that could assist in identifying potential habitat and sites for planned re-introductions as part of a recovery program. Vegetation and site data (soils, topography, rainfall, fire age-time since fire) were assessed at localities where P. novaehollandiae was recorded. The species occurred in five structural vegetation groups - open-forest, woodland, heathland, shrubland, grassland, with the most common being open-forest and woodland. Grassland and shmbland were restricted to coastal sand-dunes in south Gippsland. Understorey vegetation at most sites was dominated by sclerophyllous shrubs ranging in cover from 10 - 70%. Classification of quadrats produced eight floristic groups in which the trend was for quadrats to cluster according to geographical location. Ordination confirmed the classification pattern and vector-fitting produced significant correlations between vector points and five variables: species richness, latitude, longitude, fire age and annual rainfall. The study identified a range of vegetation communities where P. novaehollandiae occurs and provided evidence that the species is not restricted to floristically rich and diverse heathlands. The findings can be used to determine further localities with suitable habitat. However, factors other than vegetation are also likely to be important in predicting suitable habitat.

Marine benthic habitat mapping using multibeam data, georeferenced video and image classification techniques in Victoria, Australia

This paper contributes to a better understanding of geophysical characteristics and benthic communities in the Hopkins site in Victoria, Australia. An automated decision tree classification system was used to classify substrata and dominant biota communities. Geophysical sampling and underwater video data collected in this study reveals a complex bathymetry and biological structure which complements the limited information of benthic marine ecosystems in coastal waters of Victoria. The technique of combining derivative products from the backscatter and the bathymetry datasets was found to improve separability for broad biota and substrata categories over the use of either of these datasets alone.

Bayesian clustering with AutoClass explicitly recognises uncertainties in landscape classification

Clustering of multivariate data is a commonly used technique in ecology, and many approaches to clustering are available. The results from a clustering algorithm are uncertain, but few clustering approaches explicitly acknowledge this uncertainty. One exception is Bayesian mixture modelling, which treats all results probabilistically, and allows comparison of multiple plausible classifications of the same data set. We used this method, implemented in the AutoClass program, to classify catchments (watersheds) in the Murray Darling Basin (MDB), Australia, based on their physiographic characteristics (e.g. slope, rainfall, lithology). The most likely classification found nine classes of catchments. Members of each class were aggregated geographically within the MDB. Rainfall and slope were the two most important variables that defined classes. The second-most likely classification was very similar to the first, but had one fewer class. Increasing the nominal uncertainty of continuous data resulted in a most likely classification with five classes, which were again aggregated geographically. Membership probabilities suggested that a small number of cases could be members of either of two classes. Such cases were located on the edges of groups of catchments that belonged to one class, with a group belonging to the second-most likely class adjacent. A comparison of the Bayesian approach to a distance-based deterministic method showed that the Bayesian mixture model produced solutions that were more spatially cohesive and intuitively appealing. The probabilistic presentation of results from the Bayesian classification allows richer interpretation, including decisions on how to treat cases that are intermediate between two or more classes, and whether to consider more than one classification. The explicit consideration and presentation of uncertainty makes this approach useful for ecological investigations, where both data and expectations are often highly uncertain.

Species-specific characteristics and individual variation of the bark call produced by male Australian fur seals (Arctocephalus pusillus doriferus)

Australian fur seals Arctocephalus pusillus doriferus are colonial breeding animals forming dense social groups during the breeding season. During this time, males establish and defend territories through physical conflicts, stereotyped posturing and vocalisations. While vocalisations are suggested to play an important role in male recognition systems, it has received little attention. Recordings of nine adult male Australian fur seals were made during the 2000 and 2001 breeding seasons at Kanowna Island (39° 10’S, 146° 18' E), Bass Strait, Australia. The in-air bark vocalisations of territory-holding males were used to characterise the Bark Call and to determine whether males produce individually distinct calls, which could be used as a basis for vocal recognition. Seventeen frequency and temporal variables were measured from a total of 162 barks from nine individual males. The Bark Series was more reliably classified (83%) to the correct caller compared to the Bark Unit. This was assigned with less certainty (68%), although the classification was still relatively high. Findings from this study indicate that there is sufficient stereotypy within individual calls, and sufficient variation between them, to enable vocal recognition in male Australian fur seals.

A public sector scale for codes of ethics classification

This article examines the results of a study conducted of the top 100 public sector units in Sweden. These units comprise 40 entities of government, 40 municipalities, and 20 county councils. The aim of the study was to examine and describe the codes of ethics in these Swedish public sector units. This research reports on the responses of 27 public sector units that possessed a code of ethics. The principal contribution of this work is a customized PUB SEC-scale to measure and evaluate the content of codes of ethics artefacts in public sector units. The PUB SEC-scale differs to a large extent from the current private sector-scales (PRlSEC-scales) in literature, due to the specific characteristics of the public sector.

Object classification under ignorance using CaRBS : the case of the European barn swallow

This article investigates the potential of a novel technique for object classification, called Classification and Ranking Belief Simplex (CaRBS), which is based on the Dempster-Shafer theory of evidence. As such, the classification of objects and the evidence from their characteristics have a level of ignorance associated with them. Its potential is exposited in the application of the classification of European barn swallows according to their gender. The classification of biological data in the presence of ignorance about such data sets is a common problem in biology. Comparisons of the results from CaRBS with those from multivariate discriminant analysis and neural networks are made. Also shown throughout the investigation is the interpretability of the results with the utilisation of the simplex plot method of representing data

Multilabel classification by BCH code and random forests

This paper uses error correcting codes for multilabel classification. BCH code and random forests learner are used to form the proposed method. Thus, the advantage of the error-correcting properties of BCH is merged with the good performance of the random forests learner to enhance the multilabel classification results. Three experiments are conducted on three common benchmark datasets. The results are compared against those of several exiting approaches. The proposed method does well against its counterparts for the three datasets of varying characteristics.

A multi-filter enhanced genetic ensemble system for gene selection and sample classification of microarray data

Background: Feature selection techniques are critical to the analysis of high dimensional datasets. This is especially true in gene selection from microarray data which are commonly with extremely high feature-to-sample ratio. In addition to the essential objectives such as to reduce data noise, to reduce data redundancy, to improve sample classification accuracy, and to improve model generalization property, feature selection also helps biologists to focus on the selected genes to further validate their biological hypotheses.
Results: In this paper we describe an improved hybrid system for gene selection. It is based on a recently proposed genetic ensemble (GE) system. To enhance the generalization property of the selected genes or gene subsets and to overcome the overfitting problem of the GE system, we devised a mapping strategy to fuse the goodness information of each gene provided by multiple filtering algorithms. This information is then used for initialization and mutation operation of the genetic ensemble system.
Conclusion: We used four benchmark microarray datasets (including both binary-class and multi-class classification problems) for concept proving and model evaluation. The experimental results indicate that the proposed multi-filter enhanced genetic ensemble (MF-GE) system is able to improve sample classification accuracy, generate more compact gene subset, and converge to the selection results more quickly. The MF-GE system is very flexible as various combinations of multiple filters and classifiers can be incorporated based on the data characteristics and the user preferences.

Internet traffic classification using machine learning : a token-based approach

Due to the increasing unreliability of traditional port-based methods, Internet traffic classification has attracted a lot of research efforts in recent years. Quite a lot of previous papers have focused on using statistical characteristics as discriminators and applying machine learning techniques to classify the traffic flows. In this paper, we propose a novel machine learning based approach where the features are extracted from packet payload instead of flow statistics. Specifically, every flow is represented by a feature vector, in which each item indicates the occurrence of a particular token, i.e.; a common substring, in the payload. We have applied various machine learning algorithms to evaluate the idea and used different feature selection schemes to identify the critical tokens. Experimental result based on a real-world traffic data set shows that the approach can achieve high accuracy with low overhead.

Temporal PDMs for gait classification

Gait classification is a developing research area, particularly with regards to biometrics. It aims to use the distinctive spatial and temporal characteristics of human motion to classify differing activities. As a biometric, this extends to recognising different people by the heterogeneous aspects of their gait. This research aims to use a modified deformable model, the temporal PDM, to distinguish the movements of a walking and miming person. The movement of 2D points on the moving form is used to provide input into the model and classify the type of gait present.

Interobserver reliability of radial head fracture classification : two-dimensional compared with three-dimensional CT

Background: The Broberg and Morrey modification of the Mason classification of radial head fractures has substantial interobserver variation. This study used a large web-based collaborative of experienced orthopaedic surgeons to test the hypothesis that three-dimensional reconstructions of computed tomography (CT) scans improve the interobserver reliability of the classification of radial head fractures according to the Broberg and Morrey modification of the Mason classification.

Methods: Eighty-five orthopaedic surgeons evaluated twelve radial head fractures. They were randomly assigned to review either radiographs and two-dimensional CT scans or radiographs and three-dimensional CT images to determine the fracture classification, fracture characteristics, and treatment recommendations. The kappa multirater measure (κ) was calculated to estimate agreement between observers.

Results: Three-dimensional CT had moderate agreement and two-dimensional CT had fair agreement among observers for the Broberg and Morrey modification of the Mason classification, a difference that was significant. Observers assessed seven fracture characteristics, including fracture line, comminution, articular surface involvement, articular step or gap of ≥2 mm, central impaction, recognition of more than three fracture fragments, and fracture fragments too small to repair. There was a significant difference in kappa values between three-dimensional CT and two-dimensional CT for fracture fragments too small to repair, recognition of three fracture fragments, and central impaction. The difference between the other four fracture characteristics was not significant. Among treatment recommendations, there was fair agreement for both three-dimensional CT and two-dimensional CT.

Conclusions: Although three-dimensional CT led to some small but significant decreases in interobserver variation, there is still considerable disagreement regarding classification and characterization of radial head fractures. Three-dimensional CT may be insufficient to optimize interobserver agreement.

Interobserver reliability of coronoid fracture classification : two-dimensional versus three-dimensional computed tomography

Purpose : This study tests the hypothesis that 3-dimensional computed tomography (CT) reconstructions improve interobserver agreement on classification and treatment of coronoid fractures compared with 2-dimensional CT.

Methods : A total of 29 orthopedic surgeons evaluated 10 coronoid fractures on 2 occasions (first with radiographs and 2-dimensional CT and then with radiographs and 3-dimensional CT), separated by a minimum of 2 weeks. Surgeons classified fractures according to the classifications of Regan and Morrey and of O'Driscoll et al., identified specific characteristics, recommended the most appropriate treatment approach, and made treatment recommendations. The kappa multirater measure (κ) was calculated to estimate agreement between observers.

Results : Regardless of the imaging modality used, there was fair to moderate agreement for most of the observations. Three-dimensional CT improved interobserver agreement in Regan and Morrey's classsication (κ3-dimensional = 0.51 vs κ2-dimensional = 0.40; p < .001) and O'Driscoll et al.'s classifications (κ3-dimensional = 0.48 vs κ2-dimensional = 0.42; p = .009). There were trends toward better reliability for 3-dimensional reconstruction in recognition of coronoid tip fractures (κ3-dimensional = 0.19, κ2-dimensional = 0.03; p = .268), comminution (κ3-dimensional = 0.41 vs κ2-dimensional = 0.29; p = .133), and impacted fragments (κ3-dimensional = 0.39 vs κ2-dimensional = 0.27; p = .094), and in surgeons' opinions on the need for something other than screws or plate for surgical fixation (κ3-dimensional = 0.31 vs κ2-dimensional = 0.15; p = .138). Interobserver agreement on treatment approach was better with 2-dimensional CT (κ3-dimensional = 0.27, κ2-dimensional = 0.32; p = .015).

Conclusions : Three-dimensional CT reconstructions improve interobserver agreement with respect to fracture classification compared with 2-dimensional CT.