Towards universal and statistical-driven heuristics for automatic classification of sports video events

Researchers worldwide have been actively seeking for the most robust and powerful solutions to detect and classify key events (or highlights) in various sports domains. Most approaches have employed manual heuristics that model the typical pattern of audio-visual features within particular sport events To avoid manual observation and knowledge, machine-learning can be used as an alternative approach. To bridge the gaps between these two alternatives, an attempt is made to integrate statistics into heuristic models during highlight detection in our investigation. The models can be designed with a modest amount of domain-knowledge, making them less subjective and more robust for different sports. We have also successfully used a universal scope of detection and a standard set of features that can be applied for different sports that include soccer, basketball and Australian football. An experiment on a large dataset of sport videos, with a total of around 15 hours, has demonstrated the effectiveness and robustness of our
aIlgorithms.

Classification of main meal patterns - a latent class approach

Relatively little examination of the meals that are prepared in households has been conducted, despite their well-defined properties and widespread community interest in their preparation. The purpose of the present study was to identify the patterns of main meal preparation among Australian adult household meal preparers aged 44 years and younger and 45 years and over, and the relationships between these patterns and likely socio-demographic and psychological predictors. An online cross-sectional survey was conducted by Meat and Livestock Australia among a representative sample of people aged 18–65 years in Australia in 2011. A total of 1076 usable questionnaires were obtained, which included categorical information about the main meal dishes that participants had prepared during the previous 6 months along with demographic information, the presence or absence of children at home, confidence in seasonal food knowledge and personal values. Latent class analysis was applied and four types of usage patterns of thirty-three popular dishes were identified for both age groups, namely, high variety, moderate variety, high protein but low beef and low variety. The meal patterns were associated differentially with the covariates between the age groups. For example, younger women were more likely to prepare a high or moderate variety of meals than younger men, while younger people who had higher levels of education were more likely to prepare high-protein but low-beef meals. Moreover, young respondents with higher BMI were less likely to prepare meals with high protein but low beef content. Among the older age group, married people were more likely to prepare a high or moderate variety of meals than people without partners. Older people who held strong universalist values were more likely to prepare a wide variety of meals with high protein but low beef content. For both age groups, people who had children living at home and those with better seasonal food knowledge were more likely to prepare a high variety of dishes. The identification of classes of meal users would enable health communication to be tailored to improve meal patterns. Moreover, the concept of meals may be useful for health promotion, because people may find it easier to change their consumption of meals rather than individual foods.

Objective classification of fabric pilling based on the two-dimensional discrete wavelet transform

A number of methods for automated objective ratings of fabric pilling based on image analysis are described in the literature. The periodic structure of fabrics makes them suitable candidates for frequency domain analysis. We propose a new method of frequency domain analysis based on the two-dimensional discrete wavelet transform to objectively measure pilling intensity in sample images. We present a preliminary evaluation of the proposed method based on analysis of two series of standard pilling evaluation test images. The initial results suggest that the proposed method is feasible, and that the ability of the method to discriminate between levels of pilling intensity depends on the wavelet analysis scale being closely matched to the fabric interyarn pitch. We also present a heuristic method for optimal selection of an analysis wavelet and associated analysis scale.

Role of knowledge and ability in student nurses` clinical decision-making

Little is known about the acquisition of decision-making skills in nursing students as a function of experience and academic ability. Knowing how experience and academic skills interact may help inform clinical education programs and formulate ways of assessing students' progress. The aims of the present study were to develop a problem-solving task capable of measuring clinical decision-making skills in novice nurses at different levels of domain-specific knowledge; and to establish the relative impact on decision-making of domain-specific knowledge and general ability as determinants of the acquisition of decision-making skills. Three types of clinical problems of increasing complexity were developed. Sixty second-year and third-year student nurses with high and low academic scores were studied in terms of their ability to generate hypotheses for a hypothetical case, recognize disconfirming information and the need to access additional information, and diagnostic accuracy. The results showed that general academic ability and knowledge function partly independently in the acquisition of expertise in nursing. Academic ability affects decision-making in low complexity tasks, but as case complexity increases, domain-specific knowledge and experience determines decision-making skills. There are important differences in the way novices with different levels of knowledge and ability make clinical decisions and these can be studied by systematically increasing the complexity of the decision task. These results have implications for the way in which clinical education is structured and evaluated.

A new algorithm for the Petrov classification of the Weyl tensor

A new algorithm for the Petrov classification of the Weyl tensor is introduced. It is similar to the Letniowski-McLenaghan algorithm [1] when someof the ¥'s are zero, but offers a completely new approach when all of the ¥'s are nonzero. In all cases, new code in Maple has been implemented.

A new algorithm for the Segre classification of the trace-free Ricci tensor

A new algorithm, based on the introduction of new spinor quantities, for the Segre classification of the trace-free Ricci tensor is presented. It is capable of automatically distinguishing between the two Segre types [1,1(11)] and [(1,1)11] where all other known algorithms fail to do so.

The classification of lands managed for conservation : existing and proposed frameworks, with particular reference to Australia

Comprehensive classification systems to accurately account for lands managed for biodiversity conservation, are an essential component of conservation planning and policy. The current international classification systems for lands managed for nature conservation are reviewed, with a particular emphasis on Australia. The need for a broader, all-encompassing, categorisation of lands managed for conservation is presented and a proposed broader categorisation system is developed—the Conservation Lands Classification. This classification system has the advantage of incorporating data on both tenure and protection mechanisms and has been applied in this paper using conservation lands in three Australian jurisdictions as examples. It is envisaged that this method of classification has the potential to significantly improve the ability to measure current and future trends in nature conservation across all land types at a variety of scales and hence is put forward in order to stimulate discussion on this important topic.

Hydrology or floristics? Mapping and classification of wetlands in Victoria, Australia, and implications for conservation planning

A national approach to the conservation of biodiversity in Australia’s freshwater ecosystems is a high priority. This requires a consistent and comprehensive system for the classification, inventory, and assessment of wetland ecosystems. This paper, using the State of Victoria as a case study, compares two classification systems that are commonly utilized to delineate and map wetlands—one based on hydrology (Victorian Wetland Database [VWD]) and one based on indigenous vegetation types and other natural features (Ecological Vegetation Classes [EVC]). We evaluated the extent of EVC mapping of wetlands relative to the VWD classification system using a number of datasets within a geographical information system. There were significant differences in the coverage of extant EVCs across bioregions, different-sized wetlands, and VWD wetland types. Resultant depletion levels were markedly different when examined using the two systems, with depletion levels, and therefore perceived conservation status, of EVCs being significantly higher. Although there is little doubt that many wetland ecosystems in Victoria are in fact threatened, the extent of this threat cannot accurately be determined by relying on the EVC mapping as it currently stands. The study highlighted the significant impact wetland classification methods have in determining the conservation status of freshwater ecosystems.

Toward a receiver-based theory of knowledge sharing

Managers and researchers alike have sought new ways to address the challenges of sharing dispersed knowledge in modern business environments. Careful consideration by sharers of receivers' knowledge needs and behaviours may improve the effectiveness of knowledge sharing. This research examines how sharers react to their perceptions of receivers' knowledge needs and behaviours when making choices relating to sharing knowledge. The focus of this article is to propose and empirically explore a theoretical framework for a study of the role of the receiver in knowledge sharing--receiver-based theory. Data collected from two case studies highlight a key role played by perceived receiver knowledge needs and behaviours in shaping sharer choices when explicit knowledge is shared. A set of receiver influences on knowledge sharing is provided that highlights key receiver and sharer issues. The paper concludes that companies should develop better ways to connect potential sharers with receivers' real knowledge needs. Further, the findings suggest that sharing on a need-to-know basis hinders change in organisational power structures, and prevents the integration of isolated pockets of knowledge that may yield new value.

The role and theoretical evolution of knowledge translation and exchange in public health

Background There is an increased emphasis in public health research on effective models and strategies to support knowledge translation (KT), the exchange, synthesis and ethically sound application of research findings within a complex set of interactions among researchers and knowledge users. In other words, KT can be seen as an acceleration of the knowledge cycle—an acceleration of the natural transformation of knowledge into use (Canadian Institutes of Health Services Research. Knowledge Translation Strategy, 2004). The most recent conceptualizations consider the complexities of public health decision-making. The role of practitioners and communities is increasingly considered.

Methods We identify, describe and discuss the theoretical underpinnings of KT and recommend a way forward to build the evidence for more effective practice.

Results Theoretical perspectives increasingly influence research on KT in public health. A range of innovative work is being conducted to explore methods for KT using practical tools, often with the support of government.

Conclusions KT describes a crucial and to date under-developed element of the research process. There is an important gap in theoretically informed empirical studies of effectiveness of proposed approaches in public health, health promotion and preventive medicine, and thus much of the debate remains abstract. There is clearly an urgent policy need to establish the effectiveness of KT models in a range of contexts. This must include both the consideration of development and the utilization of knowledge.

Developing and testing a model of knowledge utilisation through marketing research

Little research has examined the return on marketing research, be that financial or knowledge acquisition. Furthermore, there has been insufficient research into the factors affecting the conduct of marketing research. This paper investigates and reports on a conceptual model proposed by Yaman (2000), which explores knowledge acquisition, dissemination, and utilisation through marketing research. The study specifically explores and attempts to replicate the model’s conceptual structure. The data were collected electronically via emails and an HTML web-form questionnaire, with a sample of 182 being obtained. Using structural equation modelling, the results obtained indicated an adequate fit for a modified Yaman model to the data from this particular sample.

Classification of self-consumable highlights for soccer video summaries

An effective scheme for soccer summarization is significant to improve the usage of this massively growing video data. The paper presents an extension to our recent work which proposed a framework to integrate highlights into play-breaks to construct more complete soccer summaries. The current focus is to demonstrate the benefits of detecting some specific audio-visual features during play-break sequences in order to classify highlights contained within them. The main purpose is to generate summaries which are self-consumable individually. To support this framework, the algorithms for shot classification and detection of near-goal and slow-motion replay scenes is described. The results of our experiment using 5 soccer videos (20 minutes each) show the performance and reliability of our framework.