Bilgisayar Mühendisliği Bölümü Koleksiyonu

Permanent URI for this collectionhttps://gcris.khas.edu.tr/handle/20.500.12469/45

Browse

Browsing Bilgisayar Mühendisliği Bölümü Koleksiyonu by Scopus Q "Q4"

Filter results by typing the first few letters
Now showing 1 - 3 of 3
  • Thumbnail Image
    Article
    Citation Count: 1
    A Bayesian approach to developing a strategic early warning system for the French milk market
    (Halmstad University, 2017) Bisson, Christophe; Gürpınar, Furkan
    A new approach is provided in our paper for creating a strategic early warning system allowing the estimation of the future state of the milk market as scenarios. This is in line with the recent call from the EU commission for tools that help to better address such a highly volatile market. We applied different multivariate time series regression and Bayesian networks on a pre-determined map of relations between macro-economic indicators. The evaluation of our findings with root mean square error (RMSE) performance score enhances the robustness of the prediction model constructed. Our model could be used by competitive intelligence teams to obtain sharper scenarios, leading companies and public organisations to better anticipate market changes and make more robust decisions.
  • Thumbnail Image
    Article
    Citation Count: 10
    Competitive intelligence and information technology adoption of SMEs in Turkey: Diagnosing current performance and identifying barriers
    (Halmstad University, 2013) Wright, Sheila; Bisson, Christophe; Duffy, Alistair P.
    The need for SMEs to behave in a more concise and coherent competitive fashion is well recognised. This study reports on an empirical study of SMEs in Turkey. Their responses were applied to a behavioural and information technology adoption framework which enabled the identification of areas where changes would be required for these firms to begin operating at a higher level of competence. The findings revealed significant scope for improvements on all strands of the diagnostic framework: attitude gathering location technology support IT systems support and finally use of intelligence-based output by decision-makers. Through free form responses it was also possible to identify barrier to higher level adoption and performance inhibiters which were subsequently categorised and assessed for significance.
  • Thumbnail Image
    Conference Object
    Citation Count: 0
    Rapidly Varying Sparse Channel Tracking with Hybrid Kalman-OMP Algorithm
    (Springer, 2019) Şenol, Habib; Erküçük, Serhat; Erküçük, Serhat; Cirpan, Hakan Ali
    It is expected from future communication standards that channel estimation algorithms should be able to operate over very fast varying frequency selective channel models. Therefore in this study autoregressive (AR) modeled fast varying channel has been considered and tracked with Kalman filter over one orthogonal frequency division multiplexing (OFDM) symbol. Channel sparsity is exploited which decreases the complexity requirements of the Kalman algorithm. Since Kalman filter is not directly applicable to sparse channels orthogonal matching pursuit (OMP) algorithm is modified for AR modeled sparse signal estimation. Also by using windows sparsity detection errors have been decreased. The simulation results showed that sparse fast varying channel can be tracked with the proposed hybrid Kalman-OMP algorithm and windowing method offers improved MSE results.