744 resultados para 380305 Knowledge Representation and Machine Learning
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A diagnostic method based on Bayesian Networks (probabilistic graphical models) is presented. Unlike conventional diagnostic approaches, in this method instead of focusing on system residuals at one or a few operating points, diagnosis is done by analyzing system behavior patterns over a window of operation. It is shown how this approach can loosen the dependency of diagnostic methods on precise system modeling while maintaining the desired characteristics of fault detection and diagnosis (FDD) tools (fault isolation, robustness, adaptability, and scalability) at a satisfactory level. As an example, the method is applied to fault diagnosis in HVAC systems, an area with considerable modeling and sensor network constraints.
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The purpose of this article is to describe a project with one Torres Strait Islander Community. It provides some insights into parents’ funds of knowledge that are mathematical in nature, such as sorting shells and giving fish. The idea of funds of knowledge is based on the premise that people are competent and have knowledge that has been historically and culturally accumulated into a body of knowledge and skills essential for their functioning and well-being. This knowledge is then practised throughout their lives and passed onto the next generation of children. Through adopting a community research approach, funds of knowledge that can be used to validate the community’s identities as knowledgeable people, can also be used as foundations for future learnings for teachers, parents and children in the early years of school. They can be the bridge that joins a community’s funds of knowledge with schools validating that knowledge.
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In this conceptual article, we extend earlier work on Open Innovation and Absorptive Capacity. We suggest that the literature on Absorptive Capacity does not place sufficient emphasis on distributed knowledge and learning or on the application of innovative knowledge. To accomplish physical transformations, organisations need specific Innovative Capacities that extend beyond knowledge management. Accessive Capacity is the ability to collect, sort and analyse knowledge from both internal and external sources. Adaptive Capacity is needed to ensure that new pieces of equipment are suitable for the organisation's own purposes even though they may have been originally developed for other uses. Integrative Capacity makes it possible for a new or modified piece of equipment to be fitted into an existing production process with a minimum of inessential and expensive adjustment elsewhere in the process. These Innovative Capacities are controlled and coordinated by Innovative Management Capacity, a higher-order dynamic capability.
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The aim of this paper is to contribute to our understanding of the link between HR practices, learning orientation and types of innovation in knowledge-intensive firms (KIFs). To this end, we first compiled a comprehensive overview of the existing literature on HR practices aimed at supporting innovation. On the basis of this literature, we then collected and analyzed data from a qualitative study of 19 Danish KIFs recognized for their innovation performance, focusing on links between the HR practices they use to support exploratory and exploitive learning behaviors to enhance incremental and/or radical innovation. The findings from this study demonstrate that KIFs utilize a range of HR practices that enable different learning orientations, based on the type of innovation compatible with their organizational goals.
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This paper explores the design of virtual and physical learning spaces developed for students of drama and theatre studies. What can we learn from the traditional drama workshop that will inform the design of drama and theatre spaces created in technology-mediated learning environments? The authors examine four examples of spaces created for online, distance and on-campus students and discuss the relationship between the choice of technology, the learning and teaching methods, and the outcomes for student engagement. Combining insights from two previous action research projects, the discussion focuses on the physical space used for contemporary drama workshops, supplemented by Web 2.0 technologies; a modular online theatre studies course; the blogging space of students creating a group devised play; and the open and immersive world of Second Life, where students explore 3D simulations of historical theatre sites. The authors argue that the drama workshop can be used as inspiration for the design of successful online classrooms. This is achieved by focusing on students’ contributions to the learning as individuals and group members, the aesthetics and mise-en-scene of the learning space, and the role of mobile and networked technologies. Students in this environment increase their capacity to become co-creators of knowledge and to achieve creative outcomes. The drama workshop space in its physical and virtual forms is seen as a model for classrooms in other disciplines, where dynamic, creative and collaborative spaces are required.
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The communal nature of knowledge production predicts the importance of creating learning organisations where knowledge arises out of processes that are personal, social, situated and active. It follows that workplaces must provide both formal and informal learning opportunities for interaction with ideas and among individuals. This grounded theory for developing contemporary learning organisations harvests insights from the knowledge management, systems sciences, and educational learning literatures. The resultant hybrid theoretical framework informs practical application, as reported in a case study that harnesses the accelerated information exchange possibilities enabled through web 2.0 social networking and peer production technologies. Through complementary organisational processes, 'meaning making' is negotiated in formal face-to-face meetings supplemented by informal 'boundary spanning' dialogue. The organisational capacity building potential of this participatory and inclusive approach is illustrated through the example of the Dr. Martin Luther King, Jr. Library in San Jose, California, USA. As an outcome of the strategic planning process at this joint city-university library, communication, decision-making, and planning structures, processes, and systems were re-invented. An enterprise- level redesign is presented, which fosters contextualising information interactions for knowledge sharing and community building. Knowledge management within this context envisions organisations as communities where knowledge, identity, and learning are situated. This framework acknowledges the social context of learning - i.e., that knowledge is acquired and understood through action, interaction, and sharing with others. It follows that social networks provide peer-to-peer enculturation through intentional exchange of tacit information made explicit. This, in turn, enables a dynamic process experienced as a continuous spiral that perpetually elevates collective understanding and enables knowledge creation.
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As researchers interested in the pursuit of high quality/high equity literacy learning outcomes, we focus on the learning experiences of five early years French students, with a special regard for those who are already considered as being at-risk of educational failure. We narrow the empirical focus to a single lesson on a mechanical concept of print, that is matching lower and upper case alphabet letters. In doing so, we examine a deeply philosophical question: Which pedagogical practices dis/enable what sorts of early years students as literacy learners? We extend Cazden’s (2006) notion of ‘weaving’ knowledge across dimensions of knowing to describe how the case study teacher ‘weaves’ visible and invisible pedagogies over the four movements of a lesson. The findings reveal different pedagogical framings (Bernstein, 1996) have potentially different cognitive and social effects that constitute different kinds of literacy knowledge and oppressive subject positions for at-risk students (Young, 1990).
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While past knowledge-based approaches to service innovation have emphasized the role of integration of knowledge in the provisioning of solutions, these approaches fail to address complexities involved with knowledge integration in project-oriented context, specifically, how the firm’s capability to acquire new knowledge from clients and past project episodes influence the development of new service solutions. Adopting a dynamic capability framework and building on knowledge-based approaches to innovation, this paper presents a conceptual model that captures the interplay of learning capabilities and the knowledge integration capability in the service innovation-based competitive strategy. Implications to theory and directions for future research are discussed.
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Background Cancer monitoring and prevention relies on the critical aspect of timely notification of cancer cases. However, the abstraction and classification of cancer from the free-text of pathology reports and other relevant documents, such as death certificates, exist as complex and time-consuming activities. Aims In this paper, approaches for the automatic detection of notifiable cancer cases as the cause of death from free-text death certificates supplied to Cancer Registries are investigated. Method A number of machine learning classifiers were studied. Features were extracted using natural language techniques and the Medtex toolkit. The numerous features encompassed stemmed words, bi-grams, and concepts from the SNOMED CT medical terminology. The baseline consisted of a keyword spotter using keywords extracted from the long description of ICD-10 cancer related codes. Results Death certificates with notifiable cancer listed as the cause of death can be effectively identified with the methods studied in this paper. A Support Vector Machine (SVM) classifier achieved best performance with an overall F-measure of 0.9866 when evaluated on a set of 5,000 free-text death certificates using the token stem feature set. The SNOMED CT concept plus token stem feature set reached the lowest variance (0.0032) and false negative rate (0.0297) while achieving an F-measure of 0.9864. The SVM classifier accounts for the first 18 of the top 40 evaluated runs, and entails the most robust classifier with a variance of 0.001141, half the variance of the other classifiers. Conclusion The selection of features significantly produced the most influences on the performance of the classifiers, although the type of classifier employed also affects performance. In contrast, the feature weighting schema created a negligible effect on performance. Specifically, it is found that stemmed tokens with or without SNOMED CT concepts create the most effective feature when combined with an SVM classifier.
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This paper investigates the teaching and learning of fractions to Indigenous adult learners in a Civil Construction Certificate Course. More specifically it explores why the use of materials is critical to building knowledge and understanding. This focus is important for two reasons. First, it allows for considerations of a trainer’s approach for teaching fractions and, second it provides insights into how adult learners can be supported with representing their practical experiences of fractions to make generalisation thus building on their knowledge and learning experiences. The paper draws on teaching episodes from an Australian Research Council funded Linkage project that investigates how mathematics is taught and learned in Certificate Courses, here, Certificate 11 in Civil Construction. Action research and decolonising methods (Smith, 1999) were used to conduct the research. Video excerpts which feature one trainer and three students are analysed and described. Findings from the data indicate that adult learners need to be supported with materials to assist with building their capacity to know and apply understandings of fractions in a range of contexts, besides construction. Without materials and where fractions are taught via pen and paper tasks, students are less likely to retain and apply fraction ideas to their Certificate Course. Further they are less likely to understand decimals because of limited understanding of fractions.
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In this study, a machine learning technique called anomaly detection is employed for wind turbine bearing fault detection. Basically, the anomaly detection algorithm is used to recognize the presence of unusual and potentially faulty data in a dataset, which contains two phases: a training phase and a testing phase. Two bearing datasets were used to validate the proposed technique, fault-seeded bearing from a test rig located at Case Western Reserve University to validate the accuracy of the anomaly detection method, and a test to failure data of bearings from the NSF I/UCR Center for Intelligent Maintenance Systems (IMS). The latter data set was used to compare anomaly detection with SVM, a previously well-known applied method, in rapidly finding the incipient faults.
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Recent advances in computer vision and machine learning suggest that a wide range of problems can be addressed more appropriately by considering non-Euclidean geometry. In this paper we explore sparse dictionary learning over the space of linear subspaces, which form Riemannian structures known as Grassmann manifolds. To this end, we propose to embed Grassmann manifolds into the space of symmetric matrices by an isometric mapping, which enables us to devise a closed-form solution for updating a Grassmann dictionary, atom by atom. Furthermore, to handle non-linearity in data, we propose a kernelised version of the dictionary learning algorithm. Experiments on several classification tasks (face recognition, action recognition, dynamic texture classification) show that the proposed approach achieves considerable improvements in discrimination accuracy, in comparison to state-of-the-art methods such as kernelised Affine Hull Method and graph-embedding Grassmann discriminant analysis.
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This paper is a discussion of the use of the SOLO (Structure of Observed Learning Outcomes) Taxonomy (Biggs & Collis, 1982, 1989; Biggs, 1991, 1992a, 1992b; Boulton‐Lewis, 1992, 1994) as a means of developing and assessing higher order thinking in Higher Education. It includes a summary of the research into its use to date as an instrument to find out what students know and believe about their own learning, to assess entering knowledge in a discipline, to present examples of structural organization of knowledge in a discipline, to provide models of levels of desired learning outcomes, and in particular to assess learning outcomes. A proposal is made for further research.
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While past knowledge-based approaches to service innovation have emphasized the role of knowledge integration in the delivery of customer-focused solutions, these approaches do not adequately address the complexities inherent in knowledge acquisition and integration in project-oriented firms. Adopting a dynamic capability framework and building on knowledge-based approaches to innovation, the current study examines how the interplay of learning capabilities and knowledge integration capability impacts service innovation and sustained competitive advantage. This two-stage multi-sample study finds that entrepreneurial project-oriented service firms in their quest for competitive advantage through greater innovation invest in knowledge acquisition and integration capabilities. Implications for theory and practice are discussed and directions for future research provided.