129,160 research outputs found

    Web-based information systems development and dynamic organisational change: the need for emergent development tools

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    This paper considers contextual issues relating to the problem of developing web-based information systems in and for emergent organisations. It postulates that the methods available suffer because of sudden and unexpected changing characteristics within the organisation. The Theory of Deferred Action is used as the basis for the development of an emergent development tool. Many tools for managing change in a continuously changing organisation are susceptible to inadequacy. The insights proposed are believed to assist designers in developing functional and relevant approaches within dynamic organisational contexts

    Active Authentication using an Autoencoder regularized CNN-based One-Class Classifier

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    Active authentication refers to the process in which users are unobtrusively monitored and authenticated continuously throughout their interactions with mobile devices. Generally, an active authentication problem is modelled as a one class classification problem due to the unavailability of data from the impostor users. Normally, the enrolled user is considered as the target class (genuine) and the unauthorized users are considered as unknown classes (impostor). We propose a convolutional neural network (CNN) based approach for one class classification in which a zero centered Gaussian noise and an autoencoder are used to model the pseudo-negative class and to regularize the network to learn meaningful feature representations for one class data, respectively. The overall network is trained using a combination of the cross-entropy and the reconstruction error losses. A key feature of the proposed approach is that any pre-trained CNN can be used as the base network for one class classification. Effectiveness of the proposed framework is demonstrated using three publically available face-based active authentication datasets and it is shown that the proposed method achieves superior performance compared to the traditional one class classification methods. The source code is available at: github.com/otkupjnoz/oc-acnn.Comment: Accepted and to appear at AFGR 201

    Forward-backward asymmetry in top quark production from light colored scalars in SO(10) model

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    The forward-backward asymmetry in top pair production at Tevatron has been reconfirmed by the CDF collaboration with 5.3 fb^{-1} of accumulated data. These measurements also report that the asymmetry is the largest in regions of high invariant mass M_{t\bar{t}} and rapidity difference |\Delta Y|. We consider light colored sextet scalars appearing in a particular non-supersymmetric \10 grand unification model within the \bar{126} scalar representation. These scalar states have masses in the range of 300 \text{GeV}-2 \text{TeV} consistent with the requirements of gauge coupling unification and bounds on the proton lifetime. The cross section and the total asymmetry can be simultaneously explained with the contributions of these scalars within 1σ\sigma. We find that the simultaneous fitting of the cross section, the total asymmetry and the asymmetries in different rapidity and M_{t\bar{t}} bins gives only a marginal improvement over the SM contribution. We also study various production mechanisms of these colored sextet scalars at the LHC.Comment: 22 pages, 11 Figures, References added, Section III and V modified. Version accepted for publication in JHE
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