3,737 research outputs found

    The increasing importance of serviced offices as a competing land use in global cities

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    Once considered a relatively low key land use in central business districts, the number of serviced offices has increased dramatically in recent years. The factors driving the demand for serviced offices have changed, and the suppliers of this service have reacted quickly to meet these needs. This trend has been assisted by the expansion of a select number of multi-national companies that specialise in the provision of serviced offices, available in a flexible range of office types and costs.This paper considers the reasons behind the rapid growth in the serviced office market, and examines the role of both the user and the provider. Attention is focused on the global marketplace and how these changes have been transformed into the Australian central business districts. The information will be of benefit to property analysts, developers and investors, especially when seeking an alternative use of existing traditional office accommodation.<br /

    The Effects of Service-Learning Participation on Pre-Internship Educators’ Teachers’ Sense of Efficacy

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    This study aimed to determine if pre-internship teacher education students’ participation in service-learning activities in K-12 classrooms would significantly affect their teachers’ sense of efficacy (TSE). A secondary focus sought to determine if one type of service-learning activity (e.g., whole-class instruction) would affect teacher efficacy more than another (e.g., small-group tutoring). Findings revealed that pre-internship service-learners in both types of service-learning activities increased significantly in their TSE. However, neither type of service-learning activity was superior to the other as measured by the minimally accepted .05 level. The discussion focuses on factors shared between the two service-learning designs that might mediate a positive mastery experience.L’objectif de cette étude était de déterminer si la participation par des étudiants en pédagogie à des activités de bénévolat dans des classes de la maternelle à la 12e année augmenterait de façon significative leur sentiment d’être efficaces comme enseignants. Un deuxième objectif consistait à déterminer si un type d’activité de bénévolat (par ex. l’enseignement à toute la classe) affecterait l’efficacité d’un enseignant plus qu’une autre (par ex. le tutorat à de petits groupes). Les résultats indiquent que les deux types d’activité ont accru de façon significative le sentiment d’efficacité comme enseignants chez les étudiants bénévoles. Toutefois, les paramètres selon le seuil minimal de 0,05 ont révélé qu’aucune activité n’était supérieure à l’autre. La discussion porte sur des facteurs communs aux deux activités de bénévolat et qui pourraient entrainer une expérience d’apprentissage fructueuse

    Services provided by community pharmacies in Queensland

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    Bridging the Great Divide Between Theoretical and Empirical Management Research

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    Management research places a great premium on theory development. Despite this emphasis, concerns have been expressed regarding the extent to which management theories are tested in empirical research. This article reviews evidence concerning the connections between theoretical and empirical management research and reports an investigation that examines the correspondence between the propositions presented in 20 highly cited theoretical articles and the hypotheses stated in 361 empirical articles that cite the theories. Results indicate that the vast majority of theoretical propositions are not translated into empirical hypotheses, indicating a great divide between theoretical and empirical management research. Implications of these results are discussed, and potential solutions are offered

    Study of similarity metrics for matching network-based personalised human activity recognition.

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    Personalised Human Activity Recognition (HAR) models trained using data from the target user (subject-dependent) have been shown to be superior to non personalised models that are trained on data from a general population (subject-independent). However, from a practical perspective, collecting sufficient training data from end users to create subject-dependent models is not feasible. We have previously introduced an approach based on Matching networks which has proved effective for training personalised HAR models while requiring very little data from the end user. Matching networks perform nearest-neighbour classification by reusing the class label of the most similar instances in a provided support set, which makes them very relevant to case-based reasoning. A key advantage of matching networks is that they use metric learning to produce feature embeddings or representations that maximise classification accuracy, given a chosen similarity metric. However, to the best of our knowledge, no study has been provided into the performance of different similarity metrics for matching networks. In this paper, we present a study of five different similarity metrics: Euclidean, Manhattan, Dot Product, Cosine and Jaccard, for personalised HAR. Our evaluation shows that substantial differences in performance are achieved using different metrics, with Cosine and Jaccard producing the best performance

    Personalised human activity recognition using matching networks.

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    Human Activity Recognition (HAR) is typically modelled as a classification task where sensor data associated with activity labels are used to train a classifier to recognise future occurrences of these activities. An important consideration when training HAR models is whether to use training data from a general population (subject-independent), or personalised training data from the target user (subject-dependent). Previous evaluations have shown personalised training to be more accurate because of the ability of resulting models to better capture individual users' activity patterns. From a practical perspective however, collecting sufficient training data from end users may not be feasible. This has made using subject-independent training far more common in real-world HAR systems. In this paper, we introduce a novel approach to personalised HAR using a neural network architecture called a matching network. Matching networks perform nearest-neighbour classification by reusing the class label of the most similar instances in a provided support set, which makes them very relevant to case-based reasoning. A key advantage of matching networks is that they use metric learning to produce feature embeddings or representations that maximise classification accuracy, given a chosen similarity metric. Evaluations show our approach to substantially out perform general subject-independent models by at least 6% macro-averaged F1 score

    Development and validation of the Beliefs and Behaviour Questionnaire (BBQ)

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    Objective: To develop and validate a questionnaire to screen for potential nonadherence in patients with chronic ailments. Methods: Themes from qualitative interviews with chronic obstructive pulmonary disease patients were used in developing content of the questionnaire. The questionnaire was distributed to 525 ambulatory patients with chronic lung diseases. Principal components analysis was performed to identify the subscales in the questionnaire. Internal consistency, validity and stability of the subscales were also evaluated. Results: The 30-item Beliefs and Behaviour Questionnaire (BBQ) measures beliefs, experiences and adherent behaviour on five-point Likert-type scales. Two hundred and eighty patients (53.3%) with a mean age of 71.1 years responded to the questionnaire. The 'beliefs' section had a two-factor solution-'confidence' and 'concerns' with internal consistencies of 0.82 and 0.45, respectively. The two domains identified from the section 'experiences'-satisfaction' and 'disappointment' had internal consistencies of 0.85 and 0.52, respectively. The 'behaviour' section, separately entitled the Tool for Adherence Behaviour Screening (TABS), had a two-factor solution-'adherence' and 'nonadherence', with internal consistencies of 0.80 and 0.59, respectively. All the domains demonstrated comparable reliabilities across two different patient populations. Their temporal stabilities ranged between 0.62 and 0.94. Conclusion: The validity, reliability and utility of the BBQ and the TABS, a sub-scale of the BBQ that screens both intentional and unintentional nonadherence to pharmacological and non-pharmacological disease management, have been established. Practice implications: The BBQ and the TABS have potential applications in screening adherence beliefs, experiences and behaviour in both clinical practice and research
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