Perspectives in Human Sexuality

This book is an overview of key debates, research findings and theories in the area of sex and sexuality. Controversial issues are discussed in an informative and fair, balanced manner. With its sociological orientation, Perspectives in Human Sexuality employs a range of empirical and theoretical resources, including those which utilise scientific, medical, historical and ethical knowledge in order to elucidate the critical issues affecting contemporary life. This is the first textbook written especially for undergraduate students to offer a detailed and comprehensive introduction to sex and sexuality from an Australian and New Zealand perspective. This work examines issues such as sex and age, sex work and gay, lesbian and queer sex. Leading Australian and New Zealand authors in the field of sex and sexuality have contributed to the book. The book deals with sexuality from an Australasian perspective, addressing the specific concerns and interests of an Australasian audience, providing it with a unique standing in the current market.

Analysing children’s persuasive texts : the use of hedging and intensification

Research Quality This is a dialogue between two Australian literacy scholars about two persuasive writing techniques that posed difficulty for the students in our research. This dialogue flows from the analysis of Year 6 writing samples from an ARC Linkage Project, URLearning (2009-2013) - the focus of the symposium. We use vivid examples of writing from students’ handwritten persuasive texts on topics that were chosen by teachers. The persuasive structure in the texts followed the Toulmin (2003) model: a thesis statement, three arguments with evidence, and a conclusion. The findings show that to realise the effective power of rhetorical persuasion, students need an expanded lexicon that does not rely on intensifiers, and which employs a greater range of advanced hedging techniques to use to their advantage. National & International Importance The study is potentially of national and international relevance, given that argumentation or persuasion is a key life skill in many professional, personal, and discourses. It is also a requirement in the International English Language Testing Systems (IELTS) tests, which are a critical gateway for tertiary studies in many English-speaking countries (Coffin, 2004). Timeliness The research is timely given the Australian Curriculum English, in which persuasive texts figure prominently from Preparatory to Year 10 (ACARA, 2014). The recommendations are also timely in the context of educational policies in other parts of the world. For example, in the United States, the Common Core Standards: English Language Arts, mandates the teaching of persuasive texts (Council of Chief State School Officers & National Governors Association, 2013) Implications for practice/policy The findings of the study have specific practical implications for teachers, who can address the persuasive writing techniques of hedging and intensification with which children need targeted support and explicit instruction. The presentation is positioned at the nexus of teacher practice to better address the national priorities of the Australian Curriculum: English (ACARA, 2014), while having implications for applied linguistics research by identifying common problems in students' persuasive writing.

Maternal employment, work experiences, and financial well-being of Australian mothers who care for young children with special health care needs

The employment and work experiences of mothers who care for young children with special health care needs is the focus of this study. It addresses a gap in the research literature, by providing an understanding of how mothers’ caring role may affect employment conditions, family life, and financial well-being. Quantitative data are drawn from Growing Up in Australia: The Longitudinal Study of Australian Children. The current study employs a matched case–control methodology to compare the experiences of a group of 292 mothers whose children (aged 4-5 years) with long-term special health care needs with those mothers whose children were typically developing. There were few differences between the two groups with regard to job characteristics and job quality. There were significant differences between the two groups with regard to work–family balance. Fewer mothers with children with special health care needs reported work having a positive effect on family functioning.

A novel ambiguity acceptance test threshold determination method with controllable failure rate

Ambiguity validation as an important procedure of integer ambiguity resolution is to test the correctness of the fixed integer ambiguity of phase measurements before being used for positioning computation. Most existing investigations on ambiguity validation focus on test statistic. How to determine the threshold more reasonably is less understood, although it is one of the most important topics in ambiguity validation. Currently, there are two threshold determination methods in the ambiguity validation procedure: the empirical approach and the fixed failure rate (FF-) approach. The empirical approach is simple but lacks of theoretical basis. The fixed failure rate approach has a rigorous probability theory basis, but it employs a more complicated procedure. This paper focuses on how to determine the threshold easily and reasonably. Both FF-ratio test and FF-difference test are investigated in this research and the extensive simulation results show that the FF-difference test can achieve comparable or even better performance than the well-known FF-ratio test. Another benefit of adopting the FF-difference test is that its threshold can be expressed as a function of integer least-squares (ILS) success rate with specified failure rate tolerance. Thus, a new threshold determination method named threshold function for the FF-difference test is proposed. The threshold function method preserves the fixed failure rate characteristic and is also easy-to-apply. The performance of the threshold function is validated with simulated data. The validation results show that with the threshold function method, the impact of the modelling error on the failure rate is less than 0.08%. Overall, the threshold function for the FF-difference test is a very promising threshold validation method and it makes the FF-approach applicable for the real-time GNSS positioning applications.

Structural damage detection method using frequency response functions

Structural damage detection using measured dynamic data for pattern recognition is a promising approach. These pattern recognition techniques utilize artificial neural networks and genetic algorithm to match pattern features. In this study, an artificial neural network–based damage detection method using frequency response functions is presented, which can effectively detect nonlinear damages for a given level of excitation. The main objective of this article is to present a feasible method for structural vibration–based health monitoring, which reduces the dimension of the initial frequency response function data and transforms it into new damage indices and employs artificial neural network method for detecting different levels of nonlinearity using recognized damage patterns from the proposed algorithm. Experimental data of the three-story bookshelf structure at Los Alamos National Laboratory are used to validate the proposed method. Results showed that the levels of nonlinear damages can be identified precisely by the developed artificial neural networks. Moreover, it is identified that artificial neural networks trained with summation frequency response functions give higher precise damage detection results compared to the accuracy of artificial neural networks trained with individual frequency response functions. The proposed method is therefore a promising tool for structural assessment in a real structure because it shows reliable results with experimental data for nonlinear damage detection which renders the frequency response function–based method convenient for structural health monitoring.

Bridging the gap: Exploring the barriers to using economic evidence in healthcare decision making and strategies for improving uptake

Evidence from economic evaluations is often not used to inform healthcare policy despite being well regarded by policy makers and physicians. This article employs the accessibility and acceptability framework to review the barriers to using evidence from economic evaluation in healthcare policy and the strategies used to overcome these barriers. Economic evaluations are often inaccessible to policymakers due to the absence of relevant economic evaluations, the time and cost required to conduct and interpret economic evaluations, and lack of expertise to evaluate quality and interpret results. Consistently reported factors that limit the translation of findings from economic evaluations into healthcare policy include poor quality of research informing economic evaluations, assumptions used in economic modelling, conflicts of interest, difficulties in transferring resources between sectors, negative attitudes to healthcare rationing, and the absence of equity considerations. Strategies to overcome these barriers have been suggested in the literature, including training, structured abstract databases, rapid evaluation, reporting checklists for journals, and considering factors other than cost effectiveness in economic evaluations, such as equity or budget impact. The factors that prevent or encourage decision makers to use evidence from economic evaluations have been identified, but the relative importance of these factors to decision makers is uncertain.

Teaching young queers a lesson: How police teach lessons about non-heteronormativity in public spaces

This paper analyses qualitative data with LGBT young people to think about police-LGBT youth interactions, and the outcomes of these interactions, as pedagogical moments for LGBT young people, police, and public onlookers. Although the data in this paper could be interpreted in line with dominant ways of thinking about LGBT young people and police, as criminalization for instance, the data suggested something more complex. This paper employs a theoretical framework informed by poststructural theories, queer theories, and pedagogical theories, to theorise LGBT youth-police interactions as instruction about managing police relationships in public spaces. The analysis shows how LGBT young people are learning from police encounters about the need to avoid ‘looking queer’ to minimise police harm.

Addressing barriers to help-seeking behaviour through M-mental health services : a social marketing perspective

Although seeking help for mental ill-health is beneficial, the majority of persons afflicted do not access available help services. Young adults (16-24 years old) in particular have the highest prevalence of mental health problems and the lowest rate of help-seeking behaviour. Key barriers to help-seeking for young adults, including cost, privacy concerns, inconvenience, access to health professionals and interpersonal interaction, appear to derive from the face-to-face method of service delivery traditionally used to distribute mental health services. Social marketing employs the principle of value exchange, whereby consumers will choose a behaviour in exchange for receiving valued benefits and/or a reduction in key barriers, to achieve behavioural goals for social good. The appropriation of mobile digital technology to deliver self-help mental health services may reduce the current barriers to help seeking, however, extant literature offers no empirical support for this proposition. Our research addresses this gap by examining the perceptions of young adults regarding M-mental health services. Depth interviews were undertaken with 15 young adults (18-24 years old), who had self-reported mild-moderate stress, anxiety or depression. The data were thematically analysed with the assistance of Nvivo. The findings reveal M-mental health services reduce the barriers to accessing face-to-face help services to a large extent. However, they also present their own barriers to help-seeking that must be considered by social marketers, including negligible cost expectations and service efficacy concerns. Overall, this study highlights the potential of M-mental health services to encourage early intervention and help-seeking behaviour as part of a social marketing strategy to address mental illness in young adults.

DS-VBF : dual sink vector-based routing protocol for underwater wireless sensor network

Underwater wireless sensor networks (UWSNs) have become the seat of researchers' attention recently due to their proficiency to explore underwater areas and design different applications for marine discovery and oceanic surveillance. One of the main objectives of each deployed underwater network is discovering the optimized path over sensor nodes to transmit the monitored data to onshore station. The process of transmitting data consumes energy of each node, while energy is limited in UWSNs. So energy efficiency is a challenge in underwater wireless sensor network. Dual sinks vector based forwarding (DS-VBF) takes both residual energy and location information into consideration as priority factors to discover an optimized routing path to save energy in underwater networks. The modified routing protocol employs dual sinks on the water surface which improves network lifetime. According to deployment of dual sinks, packet delivery ratio and the average end to end delay are enhanced. Based on our simulation results in comparison with VBF, average end to end delay reduced more than 80%, remaining energy increased 10%, and the increment of packet reception ratio was about 70%.

Learning the learning rate for prediction with expert advice

Most standard algorithms for prediction with expert advice depend on a parameter called the learning rate. This learning rate needs to be large enough to fit the data well, but small enough to prevent overfitting. For the exponential weights algorithm, a sequence of prior work has established theoretical guarantees for higher and higher data-dependent tunings of the learning rate, which allow for increasingly aggressive learning. But in practice such theoretical tunings often still perform worse (as measured by their regret) than ad hoc tuning with an even higher learning rate. To close the gap between theory and practice we introduce an approach to learn the learning rate. Up to a factor that is at most (poly)logarithmic in the number of experts and the inverse of the learning rate, our method performs as well as if we would know the empirically best learning rate from a large range that includes both conservative small values and values that are much higher than those for which formal guarantees were previously available. Our method employs a grid of learning rates, yet runs in linear time regardless of the size of the grid.

A Novel High Order Space-Time Spectral Method for the Time Fractional Fokker--Planck Equation

The fractional Fokker-Planck equation is an important physical model for simulating anomalous diffusions with external forces. Because of the non-local property of the fractional derivative an interesting problem is to explore high accuracy numerical methods for fractional differential equations. In this paper, a space-time spectral method is presented for the numerical solution of the time fractional Fokker-Planck initial-boundary value problem. The proposed method employs the Jacobi polynomials for the temporal discretization and Fourier-like basis functions for the spatial discretization. Due to the diagonalizable trait of the Fourier-like basis functions, this leads to a reduced representation of the inner product in the Galerkin analysis. We prove that the time fractional Fokker-Planck equation attains the same approximation order as the time fractional diffusion equation developed in [23] by using the present method. That indicates an exponential decay may be achieved if the exact solution is sufficiently smooth. Finally, some numerical results are given to demonstrate the high order accuracy and efficiency of the new numerical scheme. The results show that the errors of the numerical solutions obtained by the space-time spectral method decay exponentially.

Experiencing information use for early career academics’ learning: A knowledge ecosystem model

Purpose This study explores the informed learning experiences of early career academics while building their networks for professional and personal development. The notion that information and learning are inextricably linked via the concept of ‘informed learning’ is used as a conceptual framework to gain a clearer picture of what informs early career academics while they learn and how they experience using that which informs their learning within this complex practice: to build, maintain and utilise their developmental networks. Methodology This research employs a qualitative framework using a constructivist grounded theory approach (Charmaz, 2006). Through semi-structured interviews with a sample of fourteen early career academics from across two Australian universities, data were generated to investigate the research questions. The study used the methods of constant comparison to create codes and categories towards theme development. Further examination considered the relationship between thematic categories to construct an original theoretical model. Findings The model presented is a ‘knowledge ecosystem’, which represents the core informed learning experience. The model consists of informal learning interactions such as relating to information to create knowledge and engaging in mutually supportive relationships with a variety of knowledge resources found in people who assist in early career development. Originality/Value Findings from this study present an alternative interpretation of informed learning that is focused on processes manifesting as human interactions with informing entities revolving around the contexts of reciprocal human relationships.

Mini-Orb : A personal indoor climate preference feedback interface

The control of environmental factors in open-office environments, such as lighting and temperature is becoming increasingly automated. This development means that office inhabitants are losing the ability to manually adjust environmental conditions according to their needs. In this paper we describe the design, use and evaluation of MiniOrb, a system that employs ambient and tangible interaction mechanisms to allow inhabitants of office environments to maintain awareness of environmental factors, report on their own subjectively perceived office comfort levels and see how these compare to group average preferences. The system is complemented by a mobile application, which enables users to see and set the same sensor values and preferences, but using a screen-based interface. We give an account of the system’s design and outline the results of an in-situ trial and user study. Our results show that devices that combine ambient and tangible interaction approaches are well suited to the task of recording indoor climate preferences and afford a rich set of possible interactions that can complement those enabled by more conventional screen-based interfaces.

BPMN Miner: Automated Discovery of BPMN Process Models with Hierarchical Structure

Existing techniques for automated discovery of process models from event logs gen- erally produce flat process models. Thus, they fail to exploit the notion of subprocess as well as error handling and repetition constructs provided by contemporary process modeling notations, such as the Business Process Model and Notation (BPMN). This paper presents a technique for automated discovery of hierarchical BPMN models con- taining interrupting and non-interrupting boundary events and activity markers. The technique employs functional and inclusion dependency discovery techniques in order to elicit a process-subprocess hierarchy from the event log. Given this hierarchy and the projected logs associated to each node in the hierarchy, parent process and subprocess models are then discovered using existing techniques for flat process model discovery. Finally, the resulting models and logs are heuristically analyzed in order to identify boundary events and markers. By employing approximate dependency discovery tech- niques, it is possible to filter out noise in the event log arising for example from data entry errors or missing events. A validation with one synthetic and two real-life logs shows that process models derived by the proposed technique are more accurate and less complex than those derived with flat process discovery techniques. Meanwhile, a validation on a family of synthetically generated logs shows that the technique is resilient to varying levels of noise.

Reliable fault diagnosis for incipient low-speed bearings using fault feature analysis based on a binary bat algorithm

In this paper, we propose a highly reliable fault diagnosis scheme for incipient low-speed rolling element bearing failures. The scheme consists of fault feature calculation, discriminative fault feature analysis, and fault classification. The proposed approach first computes wavelet-based fault features, including the respective relative wavelet packet node energy and entropy, by applying a wavelet packet transform to an incoming acoustic emission signal. The most discriminative fault features are then filtered from the originally produced feature vector by using discriminative fault feature analysis based on a binary bat algorithm (BBA). Finally, the proposed approach employs one-against-all multiclass support vector machines to identify multiple low-speed rolling element bearing defects. This study compares the proposed BBA-based dimensionality reduction scheme with four other dimensionality reduction methodologies in terms of classification performance. Experimental results show that the proposed methodology is superior to other dimensionality reduction approaches, yielding an average classification accuracy of 94.9%, 95.8%, and 98.4% under bearing rotational speeds at 20 revolutions-per-minute (RPM), 80 RPM, and 140 RPM, respectively.