Researching employment relations : a self-reflexive analysis of a multi-method, school-based project

Drawing on primary data and adjunct material, this article adopts a critical self-reflexive approach to a three-year, Australian Research Council-funded projectthat explored themes around 'employment citizenship'for high school students in Queensland. The article addresses three overlapping areas that reflect some of the central dilemmas and challenges arising through the project- consent in the context of research ethics, questionnaire administration in schools, and focus group research practice. It contributes to the broader methodological literature addressing research with young people by canvassing pragmatic suggestions for future school-based research, and research addressing adolescent employment.

Multi-step ahead direct prediction for the machine condition prognosis using regression trees and neuro-fuzzy systems

This paper presents an approach to predict the operating conditions of machine based on classification and regression trees (CART) and adaptive neuro-fuzzy inference system (ANFIS) in association with direct prediction strategy for multi-step ahead prediction of time series techniques. In this study, the number of available observations and the number of predicted steps are initially determined by using false nearest neighbor method and auto mutual information technique, respectively. These values are subsequently utilized as inputs for prediction models to forecast the future values of the machines’ operating conditions. The performance of the proposed approach is then evaluated by using real trending data of low methane compressor. A comparative study of the predicted results obtained from CART and ANFIS models is also carried out to appraise the prediction capability of these models. The results show that the ANFIS prediction model can track the change in machine conditions and has the potential for using as a tool to machine fault prognosis.

Identification of circulating tumour cells in early stage breast cancer patients using multi marker immunobead RT-PCR

Introduction The ability to screen blood of early stage operable breast cancer patients for circulating tumour cells is of potential importance for identifying patients at risk of developing distant relapse. We present the results of a study of the efficacy of the immunobead RT-PCR method in identifying patients with circulating tumour cells. Results Immunomagnetic enrichment of circulating tumour cells followed by RT-PCR (immunobead RT-PCR) with a panel of five epithelial specific markers (ELF3, EPHB4, EGFR, MGB1 and TACSTD1) was used to screen for circulating tumour cells in the peripheral blood of 56 breast cancer patients. Twenty patients were positive for two or more RT-PCR markers, including seven patients who were node negative by conventional techniques. Significant increases in the frequency of marker positivity was seen in lymph node positive patients, in patients with high grade tumours and in patients with lymphovascular invasion. A strong trend towards improved disease free survival was seen for marker negative patients although it did not reach significance (p = 0.08). Conclusion Multi-marker immunobead RT-PCR analysis of peripheral blood is a robust assay that is capable of detecting circulating tumour cells in early stage breast cancer patients.

Multi-modal summarization of key events and top players in sports tournament videos

To detect and annotate the key events of live sports videos, we need to tackle the semantic gaps of audio-visual information. Previous work has successfully extracted semantic from the time-stamped web match reports, which are synchronized with the video contents. However, web and social media articles with no time-stamps have not been fully leveraged, despite they are increasingly used to complement the coverage of major sporting tournaments. This paper aims to address this limitation using a novel multimodal summarization framework that is based on sentiment analysis and players' popularity. It uses audiovisual contents, web articles, blogs, and commentators' speech to automatically annotate and visualize the key events and key players in a sports tournament coverage. The experimental results demonstrate that the automatically generated video summaries are aligned with the events identified from the official website match reports.

The impact of rhetoric and reality on community anticipation of risk in the development of multi-purpose services (MPS) : A grounded theory study

better health service.Conclusion:This research provides an insight into the perceptions of the rhetoric and reality of community member involvement in the process of developing multi-purpose services. It revealed a grounded theory in which fear and trust were intrinsic to a process of changing from a traditional hospital service to the acceptance of a new model of health care provided at a multi-purpose service.

Consumers’ intentions to adopt 3G in regional cities in China : a comparative study

Rapid mobile technological evolution and the large economic stake in commercial development of mobile technological innovation make it necessary to understand consumers' motivations towards the latest advanced and updated technologies and services. 3G (the third generation of mobile communication technology) recently started its commercial development in the world‘s largest mobile communication market, China, after being delayed for a few years. Although China fell behind in commercially developing 3G, it is difficult to ignore studying this area, given the size of the market and promising future developments. This market deserves focused research attention, especially in terms of consumer behaviour towards the adoption of mobile technological innovation. Thus, the program of research in this thesis was designed to investigate how Chinese consumers respond to the use of this newly launched mobile technological innovation, with a focus on what factors affect their 3G adoption intentions. It aimed to yield important insights into Chinese consumers‘ innovation adoption behaviours and to contribute to marketing and innovation adoption research. Furthermore, it has been documented that Chinese consumers vary widely between regions in dialect, lifestyle, culture, purchasing power and consumption attitudes. Based on economic development and local culture, China can be divided geographically into distinctive regional consumer markets. Consequently, the results of consumer behaviour research in one region may not necessarily be extrapolated to other regions. In order to better understand Chinese consumers, the disparities between regions should not be overlooked. Therefore, another objective of this program of research was to examine regional variances in consumers' innovation adoption, specifically to identify the similarities and differences in factors influencing 3G adoption, contributing to intra-cultural studies. An extensive literature review identified two gaps: current China-based innovation adoption research studies are limited in providing adequate prediction and explanation of Chinese consumers' intentions to adopt 3G; and there was limited knowledge about the differences between regional Chinese consumers in innovation adoption. Two research questions therefore were developed to address these gaps: 1) What factors influence Chinese consumers' intentions to adopt 3G? 2) How do Chinese consumers differ between regional markets in the relative influence of the factors in determining their intentions to adopt 3G? In accordance with postpositivist research philosophy, two studies were designed to answer the research questions, using mixed methods. To meet the research objectives, the two studies were both conducted in three regional cities, namely Beijing, Shanghai and Wuhan, centred in the three regions of North China, East China and Central China respectively, with sufficient cultural and economical regional variances. Study One was an exploratory study with qualitative research methods. It involved 45 in-depth interviews in the three research cities to gain rich insights into the research context from natural settings. Eight important concepts related to 3G adoption were generated from analysis of the interview data, namely utilitarian expectation, hedonic expectation, status gains, status loss avoidance, normative influence, external influence, cost and quality concern. The concepts of social loss avoidance and quality concern were two unique findings, whereas the other concepts were similar to the findings in Western innovation adoption studies. Moreover, variances in 3G adoption between three groups of regional consumers were also identified, focusing on the perceptions of two concepts, namely status gains and normative influence. The conceptual research model was then developed incorporating the eight concepts plus the dependent variable of adoption intention. The hypothesized relationships between the nine constructs and hypotheses about the differences between regional consumers in 3G adoption were informed by the findings of Study One and the literature reviewed. Study Two was a quantitative study involving a web-based survey and statistical analysis procedure. The web-based survey attracted 800 residents from the three research cities, 270 from Beijing, 265 from Shanghai and 265 from Wuhan. They comprised three research samples for this study and consequently three sets of data were obtained. The data was analysed by Structural Equation Modelling together with Multi-group Analysis. The analysis confirmed that the concepts generated in Study One were influential factors affecting Chinese consumers' 3G adoption intention, with the exception of the concept external influence. Differences were found between the samples in the three research cities in the effect of hedonic expectation, status gains, status loss avoidance and normative influence on 3G adoption intention. The two Studies undertaken in this thesis contributed a better understanding of Chinese consumers' intentions to adopt advanced mobile technological innovation, namely 3G, in three regional markets. This knowledge contributes to innovation adoption and intra-cultural research, as well as consumer behaviour theory. It is also able to inform international and domestic telecommunication companies to develop and deliver more effective marketing strategies across Chinese regional markets. Limitations in the research were identified in terms of the sampling techniques used and the design of the two Studies. Future research was suggested in other Chinese regional markets and into consumer adoption of other types of mobile technological innovations.

Raman microscopy study of tyrolite : a multi-anion arsenate mineral

The Raman spectrum of tyrolite, CaCu5(AsO4)2(CO3)(OH) 4.6H2O, from Brixlegg, Tyrol, Austria, is reported. Comparison with copper hydroxy-arsenate and basic carbonates was used to achieve assignments of the observed bands. The AsO43- group is characterized by two υ4 modes around 433 and 480 cm-1 plus a broad band around 840 cm-1 as the υ overlapping with the υ. The υ3 mode is observed as a single band around 355 cm -1. The CO32- υ1 mode is observed around 1035 and 1088 cm-1, although this assignment is difficult because of the in-plane OH bending vibrations at similar frequencies. Two υ4 modes are assigned to the 717 and 755 cm-1 bands. The υ3 mode is present as three bands at 1431, 1463, and 1498 cm-1. A large split caused by bridging carbonates may explain the band at 1370 cm -1. The H2O bending region shows two bands at 1635 and 1667 cm-1 together with stretching modes around 3204 and 3303 cm-1, the first associated with adsorbed H2O, while the second indicates more strongly bonded H2O. Three bands around 3534, 3438, and 3379 cm -1 are assigned to OH stretching modes of the OH groups in the crystal structure. The 202, 262, 301, 524, and 534 cm-1 bands are assigned to Cu-OH bending and stretching modes, whereas the bands around 179, 202, and 217 cm-1 are ascribed to O-(Ca, Cu)-O(H) with the O(H) at much greater distance from the cation. The bands around 503, 570, and 598 cm-1 are ascribed to the Cu-O stretching modes.

Selection of solar energy for green building using superiority and inferiority multi-criteria ranking (SIR) method

Green energy is one of the key factors, driving down electricity bill and zero carbon emission generating electricity to green building. However, the climate change and environmental policies are accelerating people to use renewable energy instead of coal-fired (convention type) energy for green building that energy is not environmental friendly. Therefore, solar energy is one of the clean energy solving environmental impact and paying less in electricity fee. The method of solar energy is collecting sun from solar array and saves in battery from which provides necessary electricity to whole house with zero carbon emission. However, in the market a lot of solar arrays suppliers, the aims of this paper attempted to use superiority and inferiority multi-criteria ranking (SIR) method with 13 constraints establishing I-flows and S-flows matrices to evaluate four alternatives solar energies and determining which alternative is the best, providing power to sustainable building. Furthermore, SIR is well-known structured approach of multi-criteria decision support tools and gradually used in construction and building. The outcome of this paper significantly gives an indication to user selecting solar energy.

Exponentiated gradient algorithms for conditional random fields and max-margin Markov Networks

Log-linear and maximum-margin models are two commonly-used methods in supervised machine learning, and are frequently used in structured prediction problems. Efficient learning of parameters in these models is therefore an important problem, and becomes a key factor when learning from very large data sets. This paper describes exponentiated gradient (EG) algorithms for training such models, where EG updates are applied to the convex dual of either the log-linear or max-margin objective function; the dual in both the log-linear and max-margin cases corresponds to minimizing a convex function with simplex constraints. We study both batch and online variants of the algorithm, and provide rates of convergence for both cases. In the max-margin case, O(1/ε) EG updates are required to reach a given accuracy ε in the dual; in contrast, for log-linear models only O(log(1/ε)) updates are required. For both the max-margin and log-linear cases, our bounds suggest that the online EG algorithm requires a factor of n less computation to reach a desired accuracy than the batch EG algorithm, where n is the number of training examples. Our experiments confirm that the online algorithms are much faster than the batch algorithms in practice. We describe how the EG updates factor in a convenient way for structured prediction problems, allowing the algorithms to be efficiently applied to problems such as sequence learning or natural language parsing. We perform extensive evaluation of the algorithms, comparing them to L-BFGS and stochastic gradient descent for log-linear models, and to SVM-Struct for max-margin models. The algorithms are applied to a multi-class problem as well as to a more complex large-scale parsing task. In all these settings, the EG algorithms presented here outperform the other methods.