Quantitative Approaches to Comparing Communication Patterns on Twitter

To date, available literature mainly discusses Twitter activity patterns in the context of individual case studies, while comparative research on a large number of communicative events, their dynamics and patterns is missing. By conducting a comparative study of more than forty different cases (covering topics such as elections, natural disasters, corporate crises, and televised events) we identify a number of distinct types of discussion which can be observed on Twitter. Drawing on a range of communicative metrics, we show that thematic and contextual factors influence the usage of different communicative tools available to Twitter users, such as original tweets, @replies, retweets, and URLs. Based on this first analysis of the overall metrics of Twitter discussions, we also demonstrate stable patterns in the use of Twitter in the context of major topics and events.

Computational analysis of laminated glass panels under blast loads: A comparison of two dimensional and three dimensional modelling approaches

This paper illustrates the use of finite element (FE) technique to investigate the behaviour of laminated glass (LG) panels under blast loads. Two and three dimensional (2D and 3D) modelling approaches available in LS-DYNA FE code to model LG panels are presented. Results from the FE analysis for mid-span deflection and principal stresses compared well with those from large deflection plate theory. The FE models are further validated using the results from a free field blast test on a LG panel. It is evident that both 2D and 3D LG models predict the experimental results with reasonable accuracy. The 3D LG models give slightly more accurate results but require considerably more computational time compared to the 2D LG models.

Middle schooling and scientific literacy : bringing the students to science

This study is about young adolescents' engagement in learning science. The middle years of schooling are critical in the development of students' interest and engagement with learning. Successful school experiences enhance dispositions towards a career related to those experiences. Poor experiences lead to negative attitudes and rejection of certain career pathways. At a time when students are becoming more aware, more independent and focused on peer relationships and social status, the high school environment in some circumstances offers more a content-centred curriculum that is less personally relevant to their lives than the social melee surrounding them. Science education can further exacerbate the situation by presenting abstract concepts that have limited contextual relevance and a seemingly difficult vocabulary that further alienates adolescents from the curriculum. In an attempt to reverse a perceived growing disinterest by students to science (Goodrum, Druhan & Abbs, 2011), a study was initiated based on a student-centred unit designed to enhance and sustain adolescent engagement in science. The premise of the study was that adolescent students are more responsive toward learning if they are given an appropriate learning environment that helps connect their learning with life beyond the school. The purpose of this study was to examine the experiences of young adolescents with the aim of transforming school learning in science into meaningful experiences that connected with their lives. Two areas were specifically canvassed and subsumed within the study to strengthen the design base. One area that of the middle schooling ideology, offered specific pedagogical approaches and a philosophical framework that could provide opportunities for reform. The other area, the construct of scientific literacy (OECD, 2007) as defined by Holbrook and Rannikmae, (2009) appeared to provide a sense of purpose for students to aim toward and value for becoming active citizens. The study reported here is a self-reflection of a teacher/researcher exploring practice and challenging existing approaches to the teaching of science in the middle years of schooling. The case study approach (Yin, 2003) was adopted to guide the design of the study. Over a 6-month period, the researcher, an experienced secondary-science teacher, designed, implemented and documented a range of student-centred pedagogical practices with a Year-7 secondary science class. Data for this case study included video recordings, journals, interviews and surveys of students. Both quantitative and qualitative data sources were employed in a partially mixed methods research approach (Leech & Onwuegbuzie, 2009) dominated by qualitative data with the concurrent collection of quantitative data to corroborate interpretations as a means of analysing and developing a model of the dynamic learning environment. The findings from the case study identified five propositions that became the basis for a model of a student-centred learning environment that was able to sustain student participation and thus engagement in science. The study suggested that adolescent student engagement can be promoted and sustained by providing a classroom climate that encourages and strengthens social interaction. Engagement in science can be enhanced by presenting developmentally appropriate challenges that require rigorous exploration of contextually relevant learning environments; supporting students to develop connections with a curriculum that aligns with their own experiences. By setting an environment empathetic to adolescent needs and understandings, students were able to actively explore phenomena collaboratively through developmentally appropriate experiences. A significant outcome of this study was the transformative experiences of an insider, the teacher as researcher, whose reflections provide an authentic model for reforming pedagogy. The model and theory presented became an adjunct to my repertoire for science teaching in the middle years of schooling. The study was rewarding in that it helped address a void in my understanding of middle years of schooling by prompting me to re-think the notion of adolescence in the context of the science classroom. This study is timely given the report "The Status and Quality of Year 11 and 12 Science in Australian Schools" (Goodrum, Druhan & Abbs, 2011) and national curricular changes that are being proposed for science (ACARA, 2009).

Food in an Australian primary school curriculum : a critical sociological study

Food is a multidimensional construct. It has social, cultural, economic, psychological, emotional, biological, and political dimensions. It is both a material object and a catalyst for a range of social and cultural action. Richly implicated in the social and cultural milieu, food is a central marker of culture and society. Yet little is known about the messages and knowledges in the school curriculum about food. Popular debates around food in schools are largely connected with biomedical issues of obesity, exercise and nutrition. This is a study of the sociological dimensions of food-related messages, practices and knowledge formations in the primary school curriculum. It uses an exploratory, qualitative case study methodology to identify and examine the food activities of a Year 5 class in a Queensland school. Data was gathered over a twoyear period using observation, documentation and interviews methods. Food was found to be an integral part of the primary school's activity. It had economic, symbolic, pedagogic, and instrumental value. Messages about food were found in the official, enacted and hidden curricular which were framed by a food governance framework of legislation, procedures and norms. In the school studied, food knowledge was commodified as a part of a political economy that centred on an 'eat more' message. Certain foods were privileged over others while myths about energy, fruit, fruit juice and sugar shaped student dispositions, values, norms and action. There was little engagement with the cognitive and behavioural dimensions of food and nutrition. The thesis concludes with recommendations for a whole scale reconsideration of food in schools as curricular content and knowledge.

Building an augmented map for road risk assessment

Recent road safety statistics show that the decades-long fatalities decreasing trend is stopping and stagnating. Statistics further show that crashes are mostly driven by human error, compared to other factors such as environmental conditions and mechanical defects. Within human error, the dominant error source is perceptive errors, which represent about 50% of the total. The next two sources are interpretation and evaluation, which accounts together with perception for more than 75% of human error related crashes. Those statistics show that allowing drivers to perceive and understand their environment better, or supplement them when they are clearly at fault, is a solution to a good assessment of road risk, and, as a consequence, further decreasing fatalities. To answer this problem, currently deployed driving assistance systems combine more and more information from diverse sources (sensors) to enhance the driver's perception of their environment. However, because of inherent limitations in range and field of view, these systems' perception of their environment remains largely limited to a small interest zone around a single vehicle. Such limitations can be overcomed by increasing the interest zone through a cooperative process. Cooperative Systems (CS), a specific subset of Intelligent Transportation Systems (ITS), aim at compensating for local systems' limitations by associating embedded information technology and intervehicular communication technology (IVC). With CS, information sources are not limited to a single vehicle anymore. From this distribution arises the concept of extended or augmented perception. Augmented perception allows extending an actor's perceptive horizon beyond its "natural" limits not only by fusing information from multiple in-vehicle sensors but also information obtained from remote sensors. The end result of an augmented perception and data fusion chain is known as an augmented map. It is a repository where any relevant information about objects in the environment, and the environment itself, can be stored in a layered architecture. This thesis aims at demonstrating that augmented perception has better performance than noncooperative approaches, and that it can be used to successfully identify road risk. We found it was necessary to evaluate the performance of augmented perception, in order to obtain a better knowledge on their limitations. Indeed, while many promising results have already been obtained, the feasibility of building an augmented map from exchanged local perception information and, then, using this information beneficially for road users, has not been thoroughly assessed yet. The limitations of augmented perception, and underlying technologies, have not be thoroughly assessed yet. Most notably, many questions remain unanswered as to the IVC performance and their ability to deliver appropriate quality of service to support life-saving critical systems. This is especially true as the road environment is a complex, highly variable setting where many sources of imperfections and errors exist, not only limited to IVC. We provide at first a discussion on these limitations and a performance model built to incorporate them, created from empirical data collected on test tracks. Our results are more pessimistic than existing literature, suggesting IVC limitations have been underestimated. Then, we develop a new CS-applications simulation architecture. This architecture is used to obtain new results on the safety benefits of a cooperative safety application (EEBL), and then to support further study on augmented perception. At first, we confirm earlier results in terms of crashes numbers decrease, but raise doubts on benefits in terms of crashes' severity. In the next step, we implement an augmented perception architecture tasked with creating an augmented map. Our approach is aimed at providing a generalist architecture that can use many different types of sensors to create the map, and which is not limited to any specific application. The data association problem is tackled with an MHT approach based on the Belief Theory. Then, augmented and single-vehicle perceptions are compared in a reference driving scenario for risk assessment,taking into account the IVC limitations obtained earlier; we show their impact on the augmented map's performance. Our results show that augmented perception performs better than non-cooperative approaches, allowing to almost tripling the advance warning time before a crash. IVC limitations appear to have no significant effect on the previous performance, although this might be valid only for our specific scenario. Eventually, we propose a new approach using augmented perception to identify road risk through a surrogate: near-miss events. A CS-based approach is designed and validated to detect near-miss events, and then compared to a non-cooperative approach based on vehicles equiped with local sensors only. The cooperative approach shows a significant improvement in the number of events that can be detected, especially at the higher rates of system's deployment.

Knowledge governance in project-based organizations : theoretical and empirical approaches

This paper conceptualizes knowledge governance (KG) in project-based organizations (PBOs) and its methodological approaches for empirical investigation. Three key contributions towards a multi-faceted view of KG and an understanding of KG in PBOs are advanced. These contributions include a definition of KG in PBOs, a conceptual framework to investigate KG and a methodological framework for empirical inquiry into KG in PBO settings. Our definition highlights the contingent nature of KG processes in relation to their organizational context. The conceptual framework addresses macro- and micro-level elements of KG and their interaction. The methodological framework proposes five different research approaches, structured by differentiation and integration of various ontological and epistemological stances. Together these contributions provide a novel platform for understanding KG in PBOs and developing new insights into the design and execution of research on KG within PBOs.

Personalized ontology learning for enhancing text mining effectiveness

Over the last decade, the majority of existing search techniques is either keyword- based or category-based, resulting in unsatisfactory effectiveness. Meanwhile, studies have illustrated that more than 80% of users preferred personalized search results. As a result, many studies paid a great deal of efforts (referred to as col- laborative filtering) investigating on personalized notions for enhancing retrieval performance. One of the fundamental yet most challenging steps is to capture precise user information needs. Most Web users are inexperienced or lack the capability to express their needs properly, whereas the existent retrieval systems are highly sensitive to vocabulary. Researchers have increasingly proposed the utilization of ontology-based tech- niques to improve current mining approaches. The related techniques are not only able to refine search intentions among specific generic domains, but also to access new knowledge by tracking semantic relations. In recent years, some researchers have attempted to build ontological user profiles according to discovered user background knowledge. The knowledge is considered to be both global and lo- cal analyses, which aim to produce tailored ontologies by a group of concepts. However, a key problem here that has not been addressed is: how to accurately match diverse local information to universal global knowledge. This research conducts a theoretical study on the use of personalized ontolo- gies to enhance text mining performance. The objective is to understand user information needs by a \bag-of-concepts" rather than \words". The concepts are gathered from a general world knowledge base named the Library of Congress Subject Headings. To return desirable search results, a novel ontology-based mining approach is introduced to discover accurate search intentions and learn personalized ontologies as user profiles. The approach can not only pinpoint users' individual intentions in a rough hierarchical structure, but can also in- terpret their needs by a set of acknowledged concepts. Along with global and local analyses, another solid concept matching approach is carried out to address about the mismatch between local information and world knowledge. Relevance features produced by the Relevance Feature Discovery model, are determined as representatives of local information. These features have been proven as the best alternative for user queries to avoid ambiguity and consistently outperform the features extracted by other filtering models. The two attempt-to-proposed ap- proaches are both evaluated by a scientific evaluation with the standard Reuters Corpus Volume 1 testing set. A comprehensive comparison is made with a num- ber of the state-of-the art baseline models, including TF-IDF, Rocchio, Okapi BM25, the deploying Pattern Taxonomy Model, and an ontology-based model. The gathered results indicate that the top precision can be improved remarkably with the proposed ontology mining approach, where the matching approach is successful and achieves significant improvements in most information filtering measurements. This research contributes to the fields of ontological filtering, user profiling, and knowledge representation. The related outputs are critical when systems are expected to return proper mining results and provide personalized services. The scientific findings have the potential to facilitate the design of advanced preference mining models, where impact on people's daily lives.

A fuzzy TOPSIS based multi criteria performance measurement model for lean supply chain

Increasing global competition, rapid technological changes, advances in manufacturing and information technology and discerning customers are forcing supply chains to adopt improvement practices that enable them to deliver high quality products at a lower cost and in a shorter period of time. A lean initiative is one of the most effective approaches toward achieving this goal. In the lean improvement process, it is critical to measure current and desired performance level in order to clearly evaluate the lean implementation efforts. Many attempts have tried to measure supply chain performance incorporating both quantitative and qualitative measures but failed to provide an effective method of measuring improvements in performances for dynamic lean supply chain situations. Therefore, the necessity of appropriate measurement of lean supply chain performance has become imperative. There are many lean tools available for supply chains; however, effectiveness of a lean tool depends on the type of the product and supply chain. One tool may be highly effective for a supply chain involved in high volume products but may not be effective for low volume products. There is currently no systematic methodology available for selecting appropriate lean strategies based on the type of supply chain and market strategy This thesis develops an effective method to measure the performance of supply chain consisting of both quantitative and qualitative metrics and investigates the effects of product types and lean tool selection on the supply chain performance Supply chain performance matrices and the effects of various lean tools over performance metrics mentioned in the SCOR framework have been investigated. A lean supply chain model based on the SCOR metric framework is then developed where non- lean and lean as well as quantitative and qualitative metrics are incorporated in appropriate metrics. The values of appropriate metrics are converted into triangular fuzzy numbers using similarity rules and heuristic methods. Data have been collected from an apparel manufacturing company for multiple supply chain products and then a fuzzy based method is applied to measure the performance improvements in supply chains. Using the fuzzy TOPSIS method, which chooses an optimum alternative to maximise similarities with positive ideal solutions and to minimise similarities with negative ideal solutions, the performances of lean and non- lean supply chain situations for three different apparel products have been evaluated. To address the research questions related to effective performance evaluation method and the effects of lean tools over different types of supply chains; a conceptual framework and two hypotheses are investigated. Empirical results show that implementation of lean tools have significant effects over performance improvements in terms of time, quality and flexibility. Fuzzy TOPSIS based method developed is able to integrate multiple supply chain matrices onto a single performance measure while lean supply chain model incorporates qualitative and quantitative metrics. It can therefore effectively measure the improvements for supply chain after implementing lean tools. It is demonstrated that product types involved in the supply chain and ability to select right lean tools have significant effect on lean supply chain performance. Future study can conduct multiple case studies in different contexts.

Critical factors for sustainable reconstruction of post natural disasters

While scientists are still debating the level of climate change impact to new weather patterns, there have been some devastating natural disasters worldwide in the last decade. From cyclones to earthquakes and from Tsunamis to landslides, these disasters occur with formidable forces and crushing effects. As one of the most important arrangements to erase the negative influence of natural disasters and help with the recovery and redevelopment of the hit area, reconstruction is of utmost importance in light of sustainable objectives. However, current reconstruction practice confronts quite a lot of criticisms for focusing on providing short-term necessities. How to conduct the post disaster reconstruction in a long-term perspective and achieve sustainable development is thereby a highlight for industry practice and research. This paper introduced an on-going research project which is aimed at establishing an operational framework for improving sustainability performance of post disaster reconstruction by identifying critical sustainable factors and exploring their internal relationships. The research reported in this paper is part of the project. After a comprehensive literature review, 17 potential critical sustainability factors for post disaster reconstruction were identified. Preliminary examination and discussion of the factors was conducted.

End-of-life care in the critical care setting : nurses' practices and factors affecting these practices

Background: Critical care units are designed and resourced to save lives, yet the provision of end-of-life care is a significant component of nursing work in these settings. Limited research has investigated the actual practices of critical care nurses in the provision of end-of-life care, or the factors influencing these practices. To improve the care that patients at the end of life and their families receive, and to support nurses in the provision of this care, further research is needed. The purpose of this study was to identify critical care nurses' end-of-life care practices, the factors influencing the provision of end-of-life care and the factors associated with specific end-of-life care practices. Methods: A three-phase exploratory sequential mixed-methods design was utilised. Phase one used a qualitative approach involving interviews with a convenience sample of five intensive care nurses to identify their end-of-life care experiences and practices. In phase two, an online survey instrument was developed, based on a review of the literature and the findings of phase one. The survey instrument was reviewed by six content experts and pilot tested with a convenience sample of 28 critical care nurses (response rate 45%) enrolled in a postgraduate critical care nursing subject. The refined survey instrument was used in phase three of this study to conduct a national survey of critical care nurses. Descriptive analyses, exploratory factor analysis and univariate general linear modelling was undertaken on completed survey responses from 392 critical care nurses (response rate 25%). Results: Six end-of-life care practice areas were identified in this study: information sharing, environmental modification, emotional support, patient and family-centred decision making, symptom management and spiritual support. The items most frequently identified as always undertaken by critical care nurses in the provision of end-of-life care were from the information sharing and environmental modification practice areas. Items least frequently identified as always undertaken included items from the emotional support practice area. Eight factors influencing the provision of end-of-life care were identified: palliative values, patient and family preferences, knowledge, preparedness, organisational culture, resources, care planning, and emotional support for nurses. Strong agreement was noted with items reflecting values consistent with a palliative approach and inclusion of patient and family preferences. Variation was noted in agreement for items regarding opportunities for knowledge acquisition in the workplace and formal education, yet most respondents agreed that they felt adequately prepared. A context of nurse-led practice was identified, with variation in access to resources noted. Collegial support networks were identified as a source of emotional support for critical care nurses. Critical care nurses reporting values consistent with a palliative approach and/or those who scored higher on support for patient and family preferences were more likely to be engaged in end-of-life care practice areas identified in this study. Nurses who reported higher levels of preparedness and access to opportunities for knowledge acquisition were more likely to report engaging in interpersonal practices that supported patient and family centred decision making and emotional support of patients and their families. A negative relationship was identified between the explanatory variables of emotional support for nurses and death anxiety, and the patient and family centred decision making practice area. Contextual factors had a limited influence as explanatory variables of specific end-of-life care practice areas. Gender was identified as a significant explanatory variable in the emotional and spiritual support practice areas, with male gender associated with lower summated scores on these practice scales. Conclusions: Critical care nurses engage in practices to share control with and support inclusion of families experiencing death and dying. The most frequently identified end-of-life care practices were those that are easily implemented, practical strategies aimed at supporting the patient at the end of life and the patient's family. These practices arguably require less emotional engagement by the nurse. Critical care nurses' responses reflected values consistent with a palliative approach and a strong commitment to the inclusion of families in end-of-life care, and these factors were associated with engagement in all end-of-life care practice areas. Perceived preparedness or confidence with the provision of end-of-life care was associated with engagement in interpersonal caring practices. Critical care nurses autonomously engage in the provision of end-of-life care within the constraints of an environment designed for curative care and rely on their colleagues for emotional support. Critical care nurses must be adequately prepared and supported to provide comprehensive care in all areas of end-of-life care practice. The findings of this study raise important implications, and informed recommendations for practice, education and further research.

How Can Models of Motor Control Be Useful for Understanding Low Back Pain?

Introduction. The purpose of this chapter is to address the question raised in the chapter title. Specifically, how can models of motor control help us understand low back pain (LBP)? There are several classes of models that have been used in the past for studying spinal loading, stability, and risk of injury (see Reeves and Cholewicki (2003) for a review of past modeling approaches), but for the purpose of this chapter we will focus primarily on models used to assess motor control and its effect on spine behavior. This chapter consists of 4 sections. The first section discusses why a shift in modeling approaches is needed to study motor control issues. We will argue that the current approach for studying the spine system is limited and not well-suited for assessing motor control issues related to spine function and dysfunction. The second section will explore how models can be used to gain insight into how the central nervous system (CNS) controls the spine. This segues segue nicely into the next section that will address how models of motor control can be used in the diagnosis and treatment of LBP. Finally, the last section will deal with the issue of model verification and validity. This issue is important since modelling accuracy is critical for obtaining useful insight into the behavior of the system being studied. This chapter is not intended to be a critical review of the literature, but instead intended to capture some of the discussion raised during the 2009 Spinal Control Symposium, with some elaboration on certain issues. Readers interested in more details are referred to the cited publications.

Analysis and prediction of the critical current density across [001]-tilt YBa2Cu3O7- grain boundaries of arbitrary misorientation angles

A qualitative analysis of the expected dilatation strain field in the vicinity of an array of grain-boundary (GB) dislocations is presented. The analysis provides a basis for the prediction of the critical current densities (jc) across low-angle YBa2Cu3O7- (YBCO) GBs as a function of their energy. The introduction of the GB energy allows the extension of the analysis to high-angle GBs using established models which predict the GB energy as a function of misorientation angle. The results are compared to published data for jc across [001]-tilt YBCO GBs for the full range of misorientations, showing a good fit. Since the GB energy is directly related to the GB structure, the analysis may allow a generalization of the scaling behavior of jc with the GB energy. © 1995 The American Physical Society.

Critical factors for project efficiency in a defence environment

Defence projects are typically undertaken within a multi-project-management environment where a common agenda of project managers is to achieve higher project efficiency. This study adopted a multi-facet qualitative approach to investigate factors contributing to or impeding project efficiency in the Defence sector. Semi-structured interviews were undertaken to identify additional factors to those compiled from the literature survey. This was followed by a three-round Delphi study to examine the perceived critical factors of project efficiency. The results showed that project efficiency in the Defence sector went beyond its traditional internally focused scope to one that is externally focused. As a result, efforts are needed on not only those factors related to individual projects but also those factors related to project inter-dependencies and external customers. The management of these factors will help to enhance the efficiency of a project within the Defence sector.

A new method for quantifying the contribution of different critical agents on railway bridge deterioration

Railway Bridges deteriorate over time due to different critical factors including, flood, wind, earthquake, collision, and environment factors, such as corrosion, wear, termite attack, etc. In current practice, the contributions of the critical factors, towards the deterioration of railway bridges, which show their criticalities, are not appropriately taken into account. In this paper, a new method for quantifying the criticality of these factors will be introduced. The available knowledge as well as risk analyses conducted in different Australian standards and developed for bridge-design will be adopted. The analytic hierarchy process (AHP) is utilized for prioritising the factors. The method is used for synthetic rating of railway bridges developed by the authors of this paper. Enhancing the reliability of predicting the vulnerability of railway bridges to the critical factors, will be the significant achievement of this research.

Artscience in practice : exploring the critical and creative potentials of transdisciplinary art and science practice using a methodological and conceptual framework of creative becoming

In response to a growing interest in art and science interactions and transdisciplinary research strategies, this research project examines the critical and conceptual affordances of ArtScience practice and outlines a new experiential methodology for practice-lead research using a framework of creative becoming. In doing so, the study contributes to the field of ArtScience and transdisciplinary practice, by providing new strategies for creative development and critical enquiry across art and science.