Recruitment and training of board members for the 90's and beyond

An historical analysis of the management of the arts in Australia in the last fifty years demonstrates clearly the problems faced by arts organisations which have poorly selected and trained Boards of Directors. Traditionally Board members were selected because they represented the various facets and skills involved in business (marketing, law, accountancy, management, entrepreneurship) or they were arts practitioners or patrons, or they had some particular social standing. Arts organisations recruited Board members like a "mixed bag of lollies - one of these and one of those". No consideration was given to the vital qualities of enthusiasm, reliability, empathy, capacity for hard work, strong arts interest, effective communication skills and respect for organisational processes.

When Can Oral Health Education Begin? Relative effectiveness of three oral health education strategies starting pre-partum

Objective: To test the impact of oral health education provided to pregnant mothers on subsequent practices within the infant’s family. Research design: A quasi-experimental intervention trial comparing the effectiveness of ‘usual care’ to one, or both, of two oral health education resources: a ‘sample bag’ of information and oral health care products; and/or a nine-minute “Healthy Teeth for Life” video on postnatal oral health issues. Participants: Women attending the midwife clinic at approximately 30 weeks gestation were recruited (n=611) in a public hospital providing free maternity services. Results and Conclusions: Four months after the birth of their infant, relative to the usual care condition, each of the oral health education interventions had independent or combined positive impacts on mother’s knowledge of oral health practices. However young, single, health care card-holder or unemployed mothers were less likely to apply healthy behaviours or to improve knowledge of healthy choices, as a result of these interventions. The video intervention provided the strongest and most consistent positive impact on mothers’ general and infant oral health knowledge. While mothers indicated that the later stage of pregnancy was a good time to receive oral health education, many suggested that this should also be provided after birth at a time when teeth were a priority issue, such as when “baby teeth” start to erupt.

Summarisation of short-term and long-term videos using texture and colour

We present a novel approach to video summarisation that makes use of a Bag-of-visual-Textures (BoT) approach. Two systems are proposed, one based solely on the BoT approach and another which exploits both colour information and BoT features. On 50 short-term videos from the Open Video Project we show that our BoT and fusion systems both achieve state-of-the-art performance, obtaining an average F-measure of 0.83 and 0.86 respectively, a relative improvement of 9% and 13% when compared to the previous state-of-the-art. When applied to a new underwater surveillance dataset containing 33 long-term videos, the proposed system reduces the amount of footage by a factor of 27, with only minor degradation in the information content. This order of magnitude reduction in video data represents significant savings in terms of time and potential labour cost when manually reviewing such footage.

Automatic classification of human epithelial type 2 cell indirect immunofluorescence images using cell pyramid matching

This paper describes a novel system for automatic classification of images obtained from Anti-Nuclear Antibody (ANA) pathology tests on Human Epithelial type 2 (HEp-2) cells using the Indirect Immunofluorescence (IIF) protocol. The IIF protocol on HEp-2 cells has been the hallmark method to identify the presence of ANAs, due to its high sensitivity and the large range of antigens that can be detected. However, it suffers from numerous shortcomings, such as being subjective as well as time and labour intensive. Computer Aided Diagnostic (CAD) systems have been developed to address these problems, which automatically classify a HEp-2 cell image into one of its known patterns (eg. speckled, homogeneous). Most of the existing CAD systems use handpicked features to represent a HEp-2 cell image, which may only work in limited scenarios. We propose a novel automatic cell image classification method termed Cell Pyramid Matching (CPM), which is comprised of regional histograms of visual words coupled with the Multiple Kernel Learning framework. We present a study of several variations of generating histograms and show the efficacy of the system on two publicly available datasets: the ICPR HEp-2 cell classification contest dataset and the SNPHEp-2 dataset.

Towards automated content analysis of discussion transcripts: A cognitive presence case

In this paper, we present the results of an exploratory study that examined the problem of automating content analysis of student online discussion transcripts. We looked at the problem of coding discussion transcripts for the levels of cognitive presence, one of the three main constructs in the Community of Inquiry (CoI) model of distance education. Using Coh-Metrix and LIWC features, together with a set of custom features developed to capture discussion context, we developed a random forest classification system that achieved 70.3% classification accuracy and 0.63 Cohen's kappa, which is significantly higher than values reported in the previous studies. Besides improvement in classification accuracy, the developed system is also less sensitive to overfitting as it uses only 205 classification features, which is around 100 times less features than in similar systems based on bag-of-words features. We also provide an overview of the classification features most indicative of the different phases of cognitive presence that gives an additional insights into the nature of cognitive presence learning cycle. Overall, our results show great potential of the proposed approach, with an added benefit of providing further characterization of the cognitive presence coding scheme.

H.264 COMPRESSED VIDEO CLASSIFICATION USING HISTOGRAM OF ORIENTED MOTION VECTORS (HOMV)

In this paper, we have proposed a simple and effective approach to classify H.264 compressed videos, by capturing orientation information from the motion vectors. Our major contribution involves computing Histogram of Oriented Motion Vectors (HOMV) for overlapping hierarchical Space-Time cubes. The Space-Time cubes selected are partially overlapped. HOMV is found to be very effective to define the motion characteristics of these cubes. We then use Bag of Features (B OF) approach to define the video as histogram of HOMV keywords, obtained using k-means clustering. The video feature, thus computed, is found to be very effective in classifying videos. We demonstrate our results with experiments on two large publicly available video database.

A Cause and Effect Analysis of Motion Trajectories for Modeling Actions

An action is typically composed of different parts of the object moving in particular sequences. The presence of different motions (represented as a 1D histogram) has been used in the traditional bag-of-words (BoW) approach for recognizing actions. However the interactions among the motions also form a crucial part of an action. Different object-parts have varying degrees of interactions with the other parts during an action cycle. It is these interactions we want to quantify in order to bring in additional information about the actions. In this paper we propose a causality based approach for quantifying the interactions to aid action classification. Granger causality is used to compute the cause and effect relationships for pairs of motion trajectories of a video. A 2D histogram descriptor for the video is constructed using these pairwise measures. Our proposed method of obtaining pairwise measures for videos is also applicable for large datasets. We have conducted experiments on challenging action recognition databases such as HMDB51 and UCF50 and shown that our causality descriptor helps in encoding additional information regarding the actions and performs on par with the state-of-the art approaches. Due to the complementary nature, a further increase in performance can be observed by combining our approach with state-of-the-art approaches.

Evaluation and development of passion fruit (Passiflora alata Dryander) propagated by cutting and seet in conditions of commercial orchard

The present work was conducted in a fruit tree propagation area of the Plant Production Department of the Faculdade de Ciencias Agrarias e Veterinarias, Universidade Estadual Paulista (FCAV/UNESP) in Jaboticabal, SP, and also in a commercial orchard in Araguari, MG, with the objective to verify the potential of vegetative growth (stem diameter, height of plants and leaf number) of plants of passion fruit (Passiflora alata Dryander), gotten by cutting and seed, comparing the initial development of plants in the field. This experiment was carried out from January 2002 to February 2003. The experiment using seeds was conducted at a shadow house, and the one that used cuttings in an intermitent mist. The cuttings and seeds were collected from adult plants which came from Passifloraceae Active Germoplasm Bank (BAG) of the Plant Production Department of FCAC/UNESP. For the cuttings, it was used the intermediate part of the branches in stadium of vegetative growth. The seeds, in order to obtain the seedlings, had been sown in plastic trays. Cuttings and seedlings were transplanted to plastic bags with substrate in shadow house and with daily irrigation. They were acclimatized and planted on field, after 60 days. on field, the stem diameter, plant height and number of leaves were better for cuttings than for seedlings in Jaboticabal, SP. In Araguari, MG, stem diameter was larger in the seedlings, which plant heights and number of leaves were larger on cuttings.

Content Classification of Multimedia Documents using Partitions of Low-Level Features

Audio-visual documents obtained from German TV news are classified according to the IPTC topic categorization scheme. To this end usual text classification techniques are adapted to speech, video, and non-speech audio. For each of the three modalities word analogues are generated: sequences of syllables for speech, “video words” based on low level color features (color moments, color correlogram and color wavelet), and “audio words” based on low-level spectral features (spectral envelope and spectral flatness) for non-speech audio. Such audio and video words provide a means to represent the different modalities in a uniform way. The frequencies of the word analogues represent audio-visual documents: the standard bag-of-words approach. Support vector machines are used for supervised classification in a 1 vs. n setting. Classification based on speech outperforms all other single modalities. Combining speech with non-speech audio improves classification. Classification is further improved by supplementing speech and non-speech audio with video words. Optimal F-scores range between 62% and 94% corresponding to 50% - 84% above chance. The optimal combination of modalities depends on the category to be recognized. The construction of audio and video words from low-level features provide a good basis for the integration of speech, non-speech audio and video.

The metabolic implications of intracellular circulation

Two views currently dominate research into cell function and regulation. Model I assumes that cell behavior is quite similar to that expected for a watery bag of enzymes and ligands. Model II assumes that three-dimensional order and structure constrain and determine metabolite behavior. A major problem in cell metabolism is determining why essentially all metabolite concentrations are remarkably stable (are homeostatic) over large changes in pathway fluxes—for convenience, this is termed the [s] stability paradox. For muscle cells, ATP and O2 are the most perfectly homeostatic, even though O2 delivery and metabolic rate correlate in a 1:1 fashion. In total, more than 60 metabolites are known to be remarkably homeostatic in differing metabolic states. Several explanations of [s] stability are usually given by traditional model I studies—none of which apply to all enzymes in a pathway, and all of which require diffusion as the means for changing enzyme–substrate encounter rates. In contrast, recent developments in our understanding of intracellular myosin, kinesin, and dyenin motors running on actin and tubulin tracks or cables supply a mechanistic basis for regulated intracellular circulation systems with cytoplasmic streaming rates varying over an approximately 80-fold range (from 1 to >80 μm × sec−1). These new studies raise a model II hypothesis of intracellular perfusion or convection as a primary means for bringing enzymes and substrates together under variable metabolic conditions. In this view, change in intracellular perfusion rates cause change in enzyme–substrate encounter rates and thus change in pathway fluxes with no requirement for large simultaneous changes in substrate concentrations. The ease with which this hypothesis explains the [s] stability paradox is one of its most compelling features.

An effective approach to verbose queries using a limited dependencies language model

Intuitively, any `bag of words' approach in IR should benefit from taking term dependencies into account. Unfortunately, for years the results of exploiting such dependencies have been mixed or inconclusive. To improve the situation, this paper shows how the natural language properties of the target documents can be used to transform and enrich the term dependencies to more useful statistics. This is done in three steps. The term co-occurrence statistics of queries and documents are each represented by a Markov chain. The paper proves that such a chain is ergodic, and therefore its asymptotic behavior is unique, stationary, and independent of the initial state. Next, the stationary distribution is taken to model queries and documents, rather than their initial distri- butions. Finally, ranking is achieved following the customary language modeling paradigm. The main contribution of this paper is to argue why the asymptotic behavior of the document model is a better representation then just the document's initial distribution. A secondary contribution is to investigate the practical application of this representation in case the queries become increasingly verbose. In the experiments (based on Lemur's search engine substrate) the default query model was replaced by the stable distribution of the query. Just modeling the query this way already resulted in significant improvements over a standard language model baseline. The results were on a par or better than more sophisticated algorithms that use fine-tuned parameters or extensive training. Moreover, the more verbose the query, the more effective the approach seems to become.

Lighter than Tai

YEAR: 2008 ROLE: Performer FORMAT: Live Art Event at Tiananmen Square Beijing, China (3 hours) and Later on Summit of Mt. Tai Shan, Shandong Province, China (6 hrs + 3 hrs). WITH: Solo WHAT: In the Hall of Reverence on Tiananmen Square, Beijing Mao Zedong's body lies in state surrounded by flowers and draped with a Red Flag of Communist China. His casket with a glass top lies on a black stone from Mt. Tai, reflecting the quotation from Sima Qian (China's Han Dynasty historian) that "One's life can be weightier than Mt. Tai or lighter than a goose feather". This pair of performances were a quiet, personal reflection upon what such a once revolutionary expression might mean in today's very different time and place. The work was conceived during the Olympic Cultural Festival showing of Intimate Transactions (www.intimatetransactions.com) - during the tumultuous times leading up to China's proudly staged August 2008 Olympics. The rise and rise of China had long been generating major geopolitical, ecological and cross-cultural shifts throughout the region and beyond. In this dramatic epicentre of change and at a time of such great national pride, how might we each act in ways that are ecologically 'mighty' and yet simultaneously have an impact lighter than a goosefeather? This is both a question for China in its relations with the autonomous provinces and the environment as it is for all of us in our own 'local' affairs. However ecologically speaking all that is of local concern is of global concern and noone can therefore be exempt from the need to sustain that which we share in common and must all protect for the future. Performance 1: Tiananmen Square, Beijing: Dropping 100 goose feathers. Performance 2: The summit of Mt Tai, Shandong Province. Building a mountain from Goose Feathers. SHOWING HISTORY: 1: Anniversary of Protest Crackdown, Jun 8th 2008. 2: Dawn on Tai Shan's summit, 15th June, 2008 DETAILS: Performance 1: Begin an hour after dawn (5.45am) in Tiananmen Square Bring pre-prepared performance shirt, a bag of goose feathers tipped with red. Begin at the "Gate of Heavenly Peace" under the image of Chairman Mao. Circumnavigate the world's largest open and the most surveilled public space 5 times dropping feathers periodically. Meditate on Forces of Change. Finally enter Chairman Mao's mausoleum with the masses and move quietly past his preserved body. End the performance at the Gate of Heavenly Peace 3 hours later. Performance 2: Walk up Mt. Tai Shan in silence meditating on Forces of Change (6 hours). Stay overnight on the summit. Begin an hour before dawn (3.45am) in silence. Bring performance shirt, a sack of goose feathers and a simple wooden structure. On the sunrise viewing side of the mountain build a miniature, fragile 'mountain' in goose feathers and sticks on the edge of a sheer precipice. Watch the sun rise as the feathers blow away into the valley deep below (3 hours).

Wide-baseline keypoint detection and matching with wide-angle images for vision based localisation

This thesis addresses the problem of detecting and describing the same scene points in different wide-angle images taken by the same camera at different viewpoints. This is a core competency of many vision-based localisation tasks including visual odometry and visual place recognition. Wide-angle cameras have a large field of view that can exceed a full hemisphere, and the images they produce contain severe radial distortion. When compared to traditional narrow field of view perspective cameras, more accurate estimates of camera egomotion can be found using the images obtained with wide-angle cameras. The ability to accurately estimate camera egomotion is a fundamental primitive of visual odometry, and this is one of the reasons for the increased popularity in the use of wide-angle cameras for this task. Their large field of view also enables them to capture images of the same regions in a scene taken at very different viewpoints, and this makes them suited for visual place recognition. However, the ability to estimate the camera egomotion and recognise the same scene in two different images is dependent on the ability to reliably detect and describe the same scene points, or ‘keypoints’, in the images. Most algorithms used for this purpose are designed almost exclusively for perspective images. Applying algorithms designed for perspective images directly to wide-angle images is problematic as no account is made for the image distortion. The primary contribution of this thesis is the development of two novel keypoint detectors, and a method of keypoint description, designed for wide-angle images. Both reformulate the Scale- Invariant Feature Transform (SIFT) as an image processing operation on the sphere. As the image captured by any central projection wide-angle camera can be mapped to the sphere, applying these variants to an image on the sphere enables keypoints to be detected in a manner that is invariant to image distortion. Each of the variants is required to find the scale-space representation of an image on the sphere, and they differ in the approaches they used to do this. Extensive experiments using real and synthetically generated wide-angle images are used to validate the two new keypoint detectors and the method of keypoint description. The best of these two new keypoint detectors is applied to vision based localisation tasks including visual odometry and visual place recognition using outdoor wide-angle image sequences. As part of this work, the effect of keypoint coordinate selection on the accuracy of egomotion estimates using the Direct Linear Transform (DLT) is investigated, and a simple weighting scheme is proposed which attempts to account for the uncertainty of keypoint positions during detection. A word reliability metric is also developed for use within a visual ‘bag of words’ approach to place recognition.

Activity modelling in crowded environments : a soft decision approach

Probabilistic topic models have recently been used for activity analysis in video processing, due to their strong capacity to model both local activities and interactions in crowded scenes. In those applications, a video sequence is divided into a collection of uniform non-overlaping video clips, and the high dimensional continuous inputs are quantized into a bag of discrete visual words. The hard division of video clips, and hard assignment of visual words leads to problems when an activity is split over multiple clips, or the most appropriate visual word for quantization is unclear. In this paper, we propose a novel algorithm, which makes use of a soft histogram technique to compensate for the loss of information in the quantization process; and a soft cut technique in the temporal domain to overcome problems caused by separating an activity into two video clips. In the detection process, we also apply a soft decision strategy to detect unusual events.We show that the proposed soft decision approach outperforms its hard decision counterpart in both local and global activity modelling.