Notes in regard to some textile plants of Brazil, at the International exhibition in Philadelphia in 1876,

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Innovation implementation effectiveness : a multiorganizational test of Klein Conn and Sorra���s model.

In an empirical test and extension of Klein Conn and Sorra���s model of innovation implementation effectiveness, we apply structural equation modelling to identify the generalizability of their data-modified model in comparison with their theorised model. We examined the implementation of various types of innovations in a sample of 135 organizations. We found that the data supported the original model rather than the data-modified model, such that implementation climate mediated polices and practices and implementation effectiveness, while implementation effectiveness partially mediated the relationship between implementation climate and innovation effectiveness. Furthermore, we extend their model to suggest that non-financial resources availability plays a critical role in implementation policies and practices.

Virtual reality or virtually real : blended teaching and learning in a Master's level research methods class

This paper examines the enabling effect of using blended learning and synchronous internet mediated communication technologies to improve learning and develop a Sense of Community (SOC) in a group of post-graduate students consisting of a mix of on-campus and off-campus students. Both quantitative and qualitative data collected over a number of years supports the assertion that the blended learning environment enhanced both teaching and learning. The development of a SOC was pivotal to the success of the blended approach when working with geographically isolated groups within a single learning environment.

Identifying critical success factors of ERP Systems at the higher education sector

In response to a range of contextual drivers, the worldwide adoption of ERP Systems in Higher Education Institutions (HEIs) has increased substantially over the past decade. Though the difficulties and high failure rate in implementing ERP systems at university environments have been cited in the literature, research on critical success factors (CSFs) for ERP implementations in this context is rare and fragmented. This paper is part of a larger research effort that aims to contribute to understanding the phenomenon of ERP implementations and evaluations in HEIs in the Australasian region; it identifies, previously reported, critical success factors (CSFs) in relation to ERP system implementations and discusses the importance of these factors.

Validating the IS-Impact Model At Queensland University Of Technology (QUT): Part A

The overall research aims to develop a standardised instrument to measure the impacts resulting from contemporary Information Systems (IS). The research adopts the IS-Impact measurement model, introduced by Gable et al, (2008), as its theoretical foundation, and applies the extension strategy described by Berthon et al. (2002); extending both theory and the context, where the new context is the Human Resource (HR) system. The research will be conducted in two phases, the exploratory phase and the specification phase. The purpose of this paper is to present the findings of the exploratory phase. 134 respondents from a major Australian University were involved in this phase. The findings have supported most of the existing IS-Impact model���s credibility. However, some textual data may suggest new measures for the IS-Impact model, while the low response rate or the averting of some may suggest the elimination of some measures from the model.

Romancing the Dane : reviving (and revising) Ophelia in contemporary YA fiction

Shakespeare���s Ophelia has been circulated in recent times as a figure of the adolescent woman at risk. Mary Pipher���s best-selling and influential Reviving Ophelia (1994) argued that the ���story of Ophelia [���] shows the destructive forces that affect young women��� (20). Without undermining Pipher���s project, this paper reads two contemporary YA romance novels���Lisa Fiedler���s Dating Hamlet (2002) and Lisa Klein���s Ophelia (2006)���in order to demonstrate that not only can Ophelia be appropriated as a figure of empowerment for young women today, but that such appropriations are, seemingly ironically, most powerfully rendered within the genre of romance; a genre long-maligned by feminists as recuperative of patriarchy.--------- These two novels stage interventions both into narratives of female adolescence as a time of being ���at risk��� or ���under threat���, and also into narratives of canonical literary patriarchy. Rather than a suicidal Ophelia, subject to the whims of men, these authors imagine Ophelias who take charge of their own destiny; who dictate their own romance and agency; who refuse to be subject to or subjected by, those scripts of cultural authority and heteronormative romance so often perceived as antithetical to female agency. In doing so, they force us to revise our own notions of the romance genre and the functions of canonical literary tradition in contemporary YA culture.

Extending Alexander���s ecological dominance-social competition (EDSC) evolutional model

Alexander���s Ecological Dominance and Social Competition (EDSC) model currently provides the most comprehensive overview of human traits in the development of a theory of human evolution and sociality (Alexander, 1990; Finn, Geary & Ward, 2005; Irons, 2005). His model provides a basis for explaining the evolution of human socio-cognitive abilities. Our paper examines the extension of Alexander���s model to incorporate the human trait of information behavior in synergy with ecological dominance and social competition as a human socio-cognitive competence. This paper discusses the various interdisciplinary perspectives exploring how evolution has shaped information behavior and why information behavior is emerging as an important human socio-cognitive competence. This paper outlines these issues, including the extension of Spink and Currier���s (2006a,b) evolution of information behavior model towards a more integrated understanding of how information behaviors have evolved (Spink & Cole, 2006).

A stochastic model for natural feature representation

This paper presents a robust stochastic model for the incorporation of natural features within data fusion algorithms. The representation combines Isomap, a non-linear manifold learning algorithm, with Expectation Maximization, a statistical learning scheme. The representation is computed offline and results in a non-linear, non-Gaussian likelihood model relating visual observations such as color and texture to the underlying visual states. The likelihood model can be used online to instantiate likelihoods corresponding to observed visual features in real-time. The likelihoods are expressed as a Gaussian Mixture Model so as to permit convenient integration within existing nonlinear filtering algorithms. The resulting compactness of the representation is especially suitable to decentralized sensor networks. Real visual data consisting of natural imagery acquired from an Unmanned Aerial Vehicle is used to demonstrate the versatility of the feature representation.

Learning articulated motion structures with Bayesian Networks

This paper presents a general methodology for learning articulated motions that, despite having non-linear correlations, are cyclical and have a defined pattern of behavior Using conventional algorithms to extract features from images, a Bayesian classifier is applied to cluster and classify features of the moving object. Clusters are then associated in different frames and structure learning algorithms for Bayesian networks are used to recover the structure of the motion. This framework is applied to the human gait analysis and tracking but applications include any coordinated movement such as multi-robots behavior analysis.

Rich probabilistic representations for bearing only decentralised data fusion

The aim of this paper is to demonstrate the validity of using Gaussian mixture models (GMM) for representing probabilistic distributions in a decentralised data fusion (DDF) framework. GMMs are a powerful and compact stochastic representation allowing efficient communication of feature properties in large scale decentralised sensor networks. It will be shown that GMMs provide a basis for analytical solutions to the update and prediction operations for general Bayesian filtering. Furthermore, a variant on the Covariance Intersect algorithm for Gaussian mixtures will be presented ensuring a conservative update for the fusion of correlated information between two nodes in the network. In addition, purely visual sensory data will be used to show that decentralised data fusion and tracking of non-Gaussian states observed by multiple autonomous vehicles is feasible.

Applying incremental EM to Bayesian classifiers in the learning of hyperspectral remote sensing data

In this paper, we apply the incremental EM method to Bayesian Network Classifiers to learn and interpret hyperspectral sensor data in robotic planetary missions. Hyperspectral image spectroscopy is an emerging technique for geological investigations from airborne or orbital sensors. Many spacecraft carry spectroscopic equipment as wavelengths outside the visible light in the electromagnetic spectrum give much greater information about an object. The algorithm used is an extension to the standard Expectation Maximisation (EM). The incremental method allows us to learn and interpret the data as they become available. Two Bayesian network classifiers were tested: the Naive Bayes, and the Tree-Augmented-Naive Bayes structures. Our preliminary experiments show that incremental learning with unlabelled data can improve the accuracy of the classifier.

Capstones : transitions and professional identity

The literature identifies transition as a key objective for capstone experiences. Capstones should take account of the particular needs of final year students by assisting them to transition from their student to their professional identity. The authors are currently completing an Australian Learning and Teaching Council (ALTC) funded project, ���Curriculum Renewal in Legal Education: articulating final year curriculum design principles and a final year program���, which seeks to achieve curriculum renewal for legal education in the Australian context through the articulation of a set of curriculum design principles for the final year and the design of a transferable model for an effective final year program. The project has investigated the contemporary role of capstones in assisting transition out by reviewing the relevant literature and considering feedback from a project reference group, a final year student focus group and a recent graduate���s focus group. Analysis of this extensive research- and evidence-base suggests that capstone experiences should support transition through: ��� Assisting students to develop a sense of professional identity; ��� Consolidating students��� lifelong learning skills; ��� Providing opportunities for consolidation of career development and planning processes; ��� Enabling students to enhance professional skills and competencies; and ��� Preparing students as ethical citizens and leaders. This paper will examine the role of capstones in assisting students to transition to their professional identity and will propose learning and teaching approaches and assessment of learning methods that support transition out.