918 resultados para Technology-based document


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It has been argued that different bundles or configurations of human resource practices can improve innovation performance, but there is little empirically-based research that provides details of the practices utilised by different types of innovative firms. This study aimed to identify how different types of firms vary their HR practices to build organisation-specific innovation capabilities. The paper presents findings from a qualitative study of 26 innovative Danish firms categorised as technology-based, knowledge-intensive, or hybrid in their industry orientation. The findings highlight that knowledge-intensive firms have notably different profiles of HRM practices to technology-based firms, suggesting that firms utilise different practices to build innovation capacity depending on the core capabilities required for success in their respective industries. This paper contributes by demonstrating how HR practices differ across types of firms rather than relying on a universal perspective or one best way to design and implement HR practices.

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Knowledge Integration (KI) is one of the major aspects driving innovation within an organisation. In this paper, we attempt to develop a better understanding of responses to the challenges of knowledge integration within the innovation process in technology-based firms. Using four technology-based Australian firms, we investigated how knowledge integration may be managed within the context of innovation in technology firms. Previous research highlights the role of four KI tasks that affect the innovation capability within technology-oriented firms, namely team building capability, capturing tacit knowledge, role of Knowledge Management (KM) systems and technological systemic integration. Our findings indicate that in addition to these four tasks, a strategic approach to integrating knowledge for innovation, as well as leadership and management, are essential to achieving effective KI across multiple levels of engagement. Our findings also offer practical insights into how knowledge can be integrated within innovation process, with specific implications for managers.

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Traditional text classification technology based on machine learning and data mining techniques has made a big progress. However, it is still a big problem on how to draw an exact decision boundary between relevant and irrelevant objects in binary classification due to much uncertainty produced in the process of the traditional algorithms. The proposed model CTTC (Centroid Training for Text Classification) aims to build an uncertainty boundary to absorb as many indeterminate objects as possible so as to elevate the certainty of the relevant and irrelevant groups through the centroid clustering and training process. The clustering starts from the two training subsets labelled as relevant or irrelevant respectively to create two principal centroid vectors by which all the training samples are further separated into three groups: POS, NEG and BND, with all the indeterminate objects absorbed into the uncertain decision boundary BND. Two pairs of centroid vectors are proposed to be trained and optimized through the subsequent iterative multi-learning process, all of which are proposed to collaboratively help predict the polarities of the incoming objects thereafter. For the assessment of the proposed model, F1 and Accuracy have been chosen as the key evaluation measures. We stress the F1 measure because it can display the overall performance improvement of the final classifier better than Accuracy. A large number of experiments have been completed using the proposed model on the Reuters Corpus Volume 1 (RCV1) which is important standard dataset in the field. The experiment results show that the proposed model has significantly improved the binary text classification performance in both F1 and Accuracy compared with three other influential baseline models.

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This chapter extends the phenomenographical research method by arguing the merits of engineering the outcome space from these investigations to effectively communicate the outcomes to an audience in technology-based discipline areas. Variations discovered from the phenomenographical study are blended with pre and post tests and a frequency distribution. Outcomes are then represented in a visual statistical manner to suit the specific target audience. This chapter provides useful insights that will be of interest to researchers wishing to present findings from qualitative research methods, and particularly the outcomes of phenomenographic investigations, to an audience in technology-based discipline areas.

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Current Australian policies and curricular frameworks demand that teachers and students use technology creatively and meaningfully in classrooms to develop students into 21C technological citizens. English teachers and students also have to learn new metalanguage around visual grammar since multimodal tasks often combine creative with critical General Capabilities (GC) with that of the of ICTs and literacy in the Australian Curriculum: English (AC:E). Both teachers and learners come to these tasks with varying degrees of techno-literacy, skills and access to technologies. This paper reports on case-study research following a technology based collaborative professional development (PD) program between a university Lecturer facilitator and English Teachers in a secondary Catholic school. The study found that the possibilities for creative and critical engagement are rich, but there are real grounded constraints such as lack of time, impeding teachers’ ability to master and teach new technologies in classrooms. Furthermore, pedagogical approaches are affected by technical skill levels and school infrastructure concerns which can militate against effective use of ICTs in school settings. The research project was funded by the Brisbane Catholic Education Office and focused on how teachers can be supported in these endeavours in educational contexts as they prepare students of English to be creative global citizens who use technology creatively.

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This study describes the post-school circumstances and service needs of older teenagers and adults with high-functioning Autism Spectrum Disorder, living in Queensland, Australia. The respondents were 95 parents. Results indicated that the majority of the young people lived in the family home and were unemployed. Of those who worked, 56% had unskilled jobs. They were estimated to spend a significant proportion of their time engaged in solitary, technology-based activities, and comparatively little time in employment or socialising. Parents rated employment support as the greatest service priority for their sons and daughters, followed by specialised support to assist with completing post-school education and training, assistance to support the transition from high school to adulthood, and social skills training.

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The ever expanding availability of technology-based mental health services and resources has opened up new areas of psychological practice and research. There are many reasons to embrace this technology movement, whether specialising in providing e-mental health services, conducting research on e-mental health or using technology to assist you in your work in other fields of psychology. e-mental health services not only offer more treatment choices for clients but they provide health professionals with an array of free and comprehensive resources that can help streamline their face-to-face work. This growth in ePsychology (the application of e-mental health by psychologists) also opens up an exciting range of research and teaching possibilities. In this article we cover what ePsychology can offer the early career psychologist.

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Dr Michael Whelan from Autism Queensland talks about a mentoring program supporting young people to develop creative industries skills… Following the extreme social stresses of high school, a lot of young people on the autism spectrum retreat to their bedrooms and computers to hibernate for extended periods of time. Online gaming communities and digital media hubs often provide a more accessible forum for young adults on the autism spectrum to establish and maintain social connections. A recent study suggests that school leavers on the autism spectrum in Queensland spend an average of 9.5 hours per day (68 hours per week) engaged in solitary technology-based activities. While this astonishing figure has its foundations in the sobering fact that most of these young people have limited social networks and experience significant anxiety and depression, it also serves to illustrate the extraordinary skill sets that these extended hours of technological engagement can facilitate.

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This paper reports on a study to evaluate technology-based processes for assessment moderation. The aim was to evaluate standard features found in an institutional Learning Management System, and their compatibility with the values and practices of a large teaching team. The process used an online discussion board forum for tutors, the paring of more experienced tutors with those new to the process, and further meetings conducted in both face-to-face and web conferencing environments. Online rubrics were used for assessing student work and the provision of feedback. A focus group conducted after marking was concluded and the analysis of the discussion board forum demonstrated a strong community of practice with a shared understanding of assessment requirements.

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Since the emergence of service marketing, the focus of service research has evolved. Currently the focus of research is shifting towards value co-created by the customer. Consequently, value creation is increasingly less fixed to a specific time or location controlled by the service provider. However, present service management models, although acknowledging customer participation and accessibility, have not considered the role of the empowered customer who may perform the service at various locations and time frames. The present study expands this scope and provides a framework for exploring customer perceived value from a temporal and spatial perspective. The framework is used to understand and analyse customer perceived value and to explore customer value profiles. It is proposed that customer perceived value can be conceptualised as a function of technical, functional, temporal and spatial value dimensions. These dimensions are suggested to have value-increasing and value-decreasing facets. This conceptualisation is empirically explored in an online banking context and it is shown that time and location are more important value dimensions relative to the technical and functional dimensions. The findings demonstrate that time and location are important not only in terms of having the possibility to choose when and where the service is performed. Customers also value an efficient and optimised use of time and a private and customised service location. The study demonstrates that time and location are not external elements that form the service context, but service value dimensions, in addition to the technical and functional dimensions. This thesis contributes to existing service management research through its framework for understanding temporal and spatial dimensions of perceived value. Practical implications of the study are that time and location need to be considered as service design elements in order to differentiate the service from other services and create additional value for customers. Also, because of increased customer control and the importance of time and location, it is increasingly relevant for service providers to provide a facilitating arena for customers to create value, rather than trying to control the value creation process. Kristina Heinonen is associated with CERS, the Center for Relationship Marketing and Service Management at the Swedish School of Economics and Business Administration

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Candida albicans is a commensal opportunistic pathogen, which can cause superficial infections as well as systemic infections in immuocompromised hosts. Among nosocomial fungal infections, infections by C. albicans are associated with highest mortality rates even though incidence of infections by other related species is on the rise world over. Since C. albicans and other Candida species differ in their susceptibility to antifungal drug treatment, it is crucial to accurately identify the species for effective drug treatment. Most diagnostic tests that differentiate between C. albicans and other Candida species are time consuming, as they necessarily involve laboratory culturing. Others, which employ highly sensitive PCR based technologies often, yield false positives which is equally dangerous since that leads to unnecessary antifungal treatment. This is the first report of phage display technology based identification of short peptide sequences that can distinguish C. albicans from other closely related species. The peptides also show high degree of specificity towards its different morphological forms. Using fluorescence microscopy, we show that the peptides bind on the surface of these cells and obtained clones that could even specifically bind to only specific regions of cells indicating restricted distribution of the epitopes. What was peculiar and interesting was that the epitopes were carbohydrate in nature. This gives insight into the complexity of the carbohydrate composition of fungal cell walls. In an ELISA format these peptides allow specific detection of relatively small numbers of C. albicans cells. Hence, if used in combination, such a test could help accurate diagnosis and allow physicians to initiate appropriate drug therapy on time.

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We propose a set of metrics that evaluate the uniformity, sharpness, continuity, noise, stroke width variance,pulse width ratio, transient pixels density, entropy and variance of components to quantify the quality of a document image. The measures are intended to be used in any optical character recognition (OCR) engine to a priori estimate the expected performance of the OCR. The suggested measures have been evaluated on many document images, which have different scripts. The quality of a document image is manually annotated by users to create a ground truth. The idea is to correlate the values of the measures with the user annotated data. If the measure calculated matches the annotated description,then the metric is accepted; else it is rejected. In the set of metrics proposed, some of them are accepted and the rest are rejected. We have defined metrics that are easily estimatable. The metrics proposed in this paper are based on the feedback of homely grown OCR engines for Indic (Tamil and Kannada) languages. The metrics are independent of the scripts, and depend only on the quality and age of the paper and the printing. Experiments and results for each proposed metric are discussed. Actual recognition of the printed text is not performed to evaluate the proposed metrics. Sometimes, a document image containing broken characters results in good document image as per the evaluated metrics, which is part of the unsolved challenges. The proposed measures work on gray scale document images and fail to provide reliable information on binarized document image.