Taxonomy and redescription of the Atherton Antechinus, Antechinus godmani (Thomas) (Marsupialia: Dasyuridae)

We provide a taxonomic redescription of the dasyurid marsupial Atherton Antechinus, Antechinus godmani (Thomas). A. godmani is only rarely encountered and limited to wet tropical rainforests of north-east Queensland, Australia, between the towns of Cardwell and Cairns (a distribution spanning 135 kilometres from north to south). The distinctive species occurs at altitudes of over 600 meters asl, in all major rainforest types, and can be found with both the northern subspecies of the Yellow-footed Antechinus, A. flavipes rubeculus Van Dyck and the Rusty Antechinus, A. adustus (Thomas). A. god-mani is clearly separated from all congeners on the basis of both morphometrics and genetics. A. godmani can be distin-guished from all extant congeners based on external morphology by a combination of large size, naked-looking tail and reddish fur on the face and head. A. godmani skulls are characteristically large, with a suite of long features: basicranium, palate, upper premolar tooth row, inter-palatal vacuity distance and dentary. Phylogenies generated from mt- and nDNA data position Antechinus godmani as monophyletic with respect to other members of the genus; A. godmani is strongly supported as the sister-group to a clade containing all other antechinus, but excluding the south-east Australian Dusky An-techinus, A. swainsonii (Waterhouse) and Swamp Antechinus, A. minimus (Geoffroy). Antechinus godmani are genetically very divergent compared to all congeners (mtDNA: range 12.9–16.3%).

Structured feature extraction using association rules

As of today, opinion mining has been widely used to iden- tify the strength and weakness of products (e.g., cameras) or services (e.g., services in medical clinics or hospitals) based upon people's feed- back such as user reviews. Feature extraction is a crucial step for opinion mining which has been used to collect useful information from user reviews. Most existing approaches only find individual features of a product without the structural relationships between the features which usually exists. In this paper, we propose an approach to extract features and feature relationship, represented as tree structure called a feature hi- erarchy, based on frequent patterns and associations between patterns derived from user reviews. The generated feature hierarchy profiles the product at multiple levels and provides more detailed information about the product. Our experiment results based on some popularly used review datasets show that the proposed feature extraction approach can identify more correct features than the baseline model. Even though the datasets used in the experiment are about cameras, our work can be ap- plied to generate features about a service such as the services in hospitals or clinics.

Integration of sentiment analysis into customer relational model : the importance of feature ontology and synonym

Online business or Electronic Commerce (EC) is getting popular among customers today, as a result large number of product reviews have been posted online by the customers. This information is very valuable not only for prospective customers to make decision on buying product but also for companies to gather information of customers’ satisfaction about their products. Opinion mining is used to capture customer reviews and separated this review into subjective expressions (sentiment word) and objective expressions (no sentiment word). This paper proposes a novel, multi-dimensional model for opinion mining, which integrates customers’ characteristics and their opinion about any products. The model captures subjective expression from product reviews and transfers to fact table before representing in multi-dimensions named as customers, products, time and location. Data warehouse techniques such as OLAP and Data Cubes were used to analyze opinionated sentences. A comprehensive way to calculate customers’ orientation on products’ features and attributes are presented in this paper.

Enhanced n-gram extraction using relevance feature discovery

Guaranteeing the quality of extracted features that describe relevant knowledge to users or topics is a challenge because of the large number of extracted features. Most popular existing term-based feature selection methods suffer from noisy feature extraction, which is irrelevant to the user needs (noisy). One popular method is to extract phrases or n-grams to describe the relevant knowledge. However, extracted n-grams and phrases usually contain a lot of noise. This paper proposes a method for reducing the noise in n-grams. The method first extracts more specific features (terms) to remove noisy features. The method then uses an extended random set to accurately weight n-grams based on their distribution in the documents and their terms distribution in n-grams. The proposed approach not only reduces the number of extracted n-grams but also improves the performance. The experimental results on Reuters Corpus Volume 1 (RCV1) data collection and TREC topics show that the proposed method significantly outperforms the state-of-art methods underpinned by Okapi BM25, tf*idf and Rocchio.

Australian animated feature films

Building on and bringing up to date the material presented in the first installment of Directory of World Cinema : Australia and New Zealand, this volume continues the exploration of the cinema produced in Australia and New Zealand since the beginning of the twentieth century. Among the additions to this volume are in-depth treatments of the locations that feature prominently in the countries' cinema. Essays by leading critics and film scholars consider the significance in films of the outback and the beach, which is evoked as a liminal space in Long Weekend and a symbol of death in Heaven's Burning, among other films. Other contributions turn the spotlight on previously unexplored genres and key filmmakers, including Jane Campion, Rolf de Heer, Charles Chauvel, and Gillian Armstrong.

Distribution and taxonomy of Enterococci from the Davis Station wastewater discharge, Antarctica

This project assessed the potential impact of untreated sewage release in a near-shore marine environment of Antarctica through the distribution and characterisation of the faecal indicator bacteria Enterococcus. Antibiotic resistance and genome sequencing analyses revealed that enterococci resistant to multiple antibiotics closely related to clinical pathogens were introduced to the pristine Antarctic environment by Australia's Davis station.

Taxonomy and control measures of SPAM and SPIM

In this age of electronic money transactions, the opportunities for electronic crime expanded at the same rate as ever expanding rise of on-line services. With world becoming a global village, crime over the internet transcends no boundaries, borders or jurisdictions. This paper critically examines the available literature on spam, and the control measures available to control spam. This study is followed by the literature overview related to mobility of devices and how the application of mobile technologies as communication medium has impacted the handling of spam. The conclusion of this literature review with proposed direction of study is summarized.

A taxonomy of computation offloading in mobile cloud computing

The ability of cloud computing to provide almost unlimited storage, backup and recovery, and quick deployment contributes to its widespread attention and implementation. Cloud computing has also become an attractive choice for mobile users as well. Due to limited features of mobile devices such as power scarcity and inability to cater computationintensive tasks, selected computation needs to be outsourced to the resourceful cloud servers. However, there are many challenges which need to be addressed in computation offloading for mobile cloud computing such as communication cost, connectivity maintenance and incurred latency. This paper presents taxonomy of the computation offloading approaches which aim to address the challenges. The taxonomy provides guidelines to identify research scopes in computation offloading for mobile cloud computing. We also outline directions and anticipated trends for future research.

Semantic context and visual feature effects in object naming : an fMRI study using arterial spin labeling

Previous behavioral studies reported a robust effect of increased naming latencies when objects to be named were blocked within semantic category, compared to items blocked between category. This semantic context effect has been attributed to various mechanisms including inhibition or excitation of lexico-semantic representations and incremental learning of associations between semantic features and names, and is hypothesized to increase demands on verbal self-monitoring during speech production. Objects within categories also share many visual structural features, introducing a potential confound when interpreting the level at which the context effect might occur. Consistent with previous findings, we report a significant increase in response latencies when naming categorically related objects within blocks, an effect associated with increased perfusion fMRI signal bilaterally in the hippocampus and in the left middle to posterior superior temporal cortex. No perfusion changes were observed in the middle section of the left middle temporal cortex, a region associated with retrieval of lexical-semantic information in previous object naming studies. Although a manipulation of visual feature similarity did not influence naming latencies, we observed perfusion increases in the perirhinal cortex for naming objects with similar visual features that interacted with the semantic context in which objects were named. These results provide support for the view that the semantic context effect in object naming occurs due to an incremental learning mechanism, and involves increased demands on verbal self-monitoring.

The SOLO Taxonomy as a means of shaping and assessing learning in higher education

This paper is a discussion of the use of the SOLO (Structure of Observed Learning Outcomes) Taxonomy (Biggs & Collis, 1982, 1989; Biggs, 1991, 1992a, 1992b; Boulton‐Lewis, 1992, 1994) as a means of developing and assessing higher order thinking in Higher Education. It includes a summary of the research into its use to date as an instrument to find out what students know and believe about their own learning, to assess entering knowledge in a discipline, to present examples of structural organization of knowledge in a discipline, to provide models of levels of desired learning outcomes, and in particular to assess learning outcomes. A proposal is made for further research.

A Study of feature extraction algorithms for optical flow tracking

Sparse optical flow algorithms, such as the Lucas-Kanade approach, provide more robustness to noise than dense optical flow algorithms and are the preferred approach in many scenarios. Sparse optical flow algorithms estimate the displacement for a selected number of pixels in the image. These pixels can be chosen randomly. However, pixels in regions with more variance between the neighbours will produce more reliable displacement estimates. The selected pixel locations should therefore be chosen wisely. In this study, the suitability of Harris corners, Shi-Tomasi's “Good features to track", SIFT and SURF interest point extractors, Canny edges, and random pixel selection for the purpose of frame-by-frame tracking using a pyramidical Lucas-Kanade algorithm is investigated. The evaluation considers the important factors of processing time, feature count, and feature trackability in indoor and outdoor scenarios using ground vehicles and unmanned aerial vehicles, and for the purpose of visual odometry estimation.

Taxonomy, ecology, and control of hypsipyla shoot borers of meliaceae

Hypsipyla grandella and Hypsipyla robusta are serious pests of species of the subfamily Swietenioideae of the family Meliaceae in virtually every moist tropical region of the world. An international workshop reviewed the ecology and control of Hypsipyla shoot borers of Meliaceae, identified promising control methods, and set priorities for future research. The conclusions of the workshop are presented with specific recommendations for research in aspects of the taxonomy, biology, and ecology of Hypsipyla, and pest management options that use host plant resistance and chemical, biological, and silvicultural control

Representation of facial expression categories in continuous arousal-valence space: Feature and correlation

Representation of facial expressions using continuous dimensions has shown to be inherently more expressive and psychologically meaningful than using categorized emotions, and thus has gained increasing attention over recent years. Many sub-problems have arisen in this new field that remain only partially understood. A comparison of the regression performance of different texture and geometric features and investigation of the correlations between continuous dimensional axes and basic categorized emotions are two of these. This paper presents empirical studies addressing these problems, and it reports results from an evaluation of different methods for detecting spontaneous facial expressions within the arousal-valence dimensional space (AV). The evaluation compares the performance of texture features (SIFT, Gabor, LBP) against geometric features (FAP-based distances), and the fusion of the two. It also compares the prediction of arousal and valence, obtained using the best fusion method, to the corresponding ground truths. Spatial distribution, shift, similarity, and correlation are considered for the six basic categorized emotions (i.e. anger, disgust, fear, happiness, sadness, surprise). Using the NVIE database, results show that the fusion of LBP and FAP features performs the best. The results from the NVIE and FEEDTUM databases reveal novel findings about the correlations of arousal and valence dimensions to each of six basic emotion categories.