180 research outputs found

    Embodied Discourses of Literacy in the Lives of Two Preservice Teachers

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    This study examines the emerging teacher literacy identities of Ian and A.J., two preservice teachers in a graduate teacher education program in the United States. Using a poststructural feminisms theoretical framework, the study illustrates the embodiment of literacy pedagogy discourses in relation to the literacy courses’ discourse of comprehensive literacy and the literacy biographical discourses of Ian and A.J. The results of this study indicate the need to deconstruct how the discourse of comprehensive literacy limits how we, as literacy teacher educators, position, hear and respond to our preservice teachers and suggests the need for differentiation in our teacher education literacy courses

    Why educators need to implement physical activity into special education

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    In this paper, the problem of practice covers the topic of implementing physical education into special education through the benefits of exercise, adaptive physical education, and the resources and materials needed to do so. There are many benefits to exercise for all children and it is important to allow any student to participate in such activities. Students who have physical and intellectual disabilities are capable of many things and should be encouraged to participate in numerous activities alongside those in general education. Students with disabilities should not be discriminated against or not given the same opportunities as someone who does not have a disability. Each student is unique in their own way and it is our job as educators to push them toward their individual goals and success through many subjects including P.E.. In order for students in special education to have a beneficial physical education experience schools must provide the proper resources and materials for students to participate along with students in general education. Each educator should take into consideration that all students are different and will need different modifications. It is important to participate in trainings and resources for students to fully understand the benefits of physical education and for educators to provide the best quality education

    On How Network Architecture Determines the Dominant Patterns of Spontaneous Neural Activity

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    In the absence of sensory stimulation, neocortical circuits display complex patterns of neural activity. These patterns are thought to reflect relevant properties of the network, including anatomical features like its modularity. It is also assumed that the synaptic connections of the network constrain the repertoire of emergent, spontaneous patterns. Although the link between network architecture and network activity has been extensively investigated in the last few years from different perspectives, our understanding of the relationship between the network connectivity and the structure of its spontaneous activity is still incomplete. Using a general mathematical model of neural dynamics we have studied the link between spontaneous activity and the underlying network architecture. In particular, here we show mathematically how the synaptic connections between neurons determine the repertoire of spatial patterns displayed in the spontaneous activity. To test our theoretical result, we have also used the model to simulate spontaneous activity of a neural network, whose architecture is inspired by the patchy organization of horizontal connections between cortical columns in the neocortex of primates and other mammals. The dominant spatial patterns of the spontaneous activity, calculated as its principal components, coincide remarkably well with those patterns predicted from the network connectivity using our theory. The equivalence between the concept of dominant pattern and the concept of attractor of the network dynamics is also demonstrated. This in turn suggests new ways of investigating encoding and storage capabilities of neural networks

    iButton Enrolment and Verification Requirements for the Pressure Sequence Smartcard Biometric

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    With the growing number of smartcard applications there comes an increasing need to restrict access to the card itself. In previous work we proposed the pressure sequence biometric, within which a biometric sensor is integrated onto the card in a low-cost and mechanically compliant manner. Using an off-card verifier we demonstrated reasonable discrimination between users. In this paper we consider a number of on-card verification schemes, the best of which offers an equal error rate of 2.3%. On-card computational time requirements were found to be 3.1 seconds for enrolment and 0.12 seconds for verification. Incorporating our implementation into an existing applet used 684 bytes of program space. Whilst data memory requirements are estimated to be 1400 and 300 bytes for enrolment and verification, respectively. These time and size requirements demonstrate our biometric as a practical proposition for the protection of smart cards. Experiments were performed with the iButton's Java Card platform

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    The success of fMRI places constraints on the nature of the neural code. The fact that researchers can infer similarities between neural representations, despite fMRI's limitations, implies that certain neural coding schemes are more likely than others. For fMRI to succeed given its low temporal and spatial resolution, the neural code must be smooth at the voxel and functional level such that similar stimuli engender similar internal representations. Through proof and simulation, we determine which coding schemes are plausible given both fMRI's successes and its limitations in measuring neural activity. Deep neural network approaches, which have been forwarded as computational accounts of the ventral stream, are consistent with the success of fMRI, though functional smoothness breaks down in the later network layers. These results have implications for the nature of the neural code and ventral stream, as well as what can be successfully investigated with fMRI

    Creative Thinking and Modelling for the Decision Support in Water Management

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    This paper reviews the state of art in knowledge and preferences elicitation techniques. The purpose of the study was to evaluate various cognitive mapping techniques in order to conclude with the identification of the optimal technique for the NetSyMod methodology. Network Analysis Creative System Modelling (NetSyMod) methodology has been designed for the improvement of decision support systems (DSS) with respect to the environmental problems. In the paper the difference is made between experts and stakeholders knowledge and preference elicitation methods. The suggested technique is very similar to the Nominal Group Techniques (NGT) with the external representation of the analysed problem by means of the Hodgson Hexagons. The evolving methodology is undergoing tests within several EU-funded projects such as: ITAES, IISIM, NostrumDSS

    Application of Neural Nets to Ultrasound Tissue Characterization

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    Automatic learning in chaotic neural networks

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