Abstract: In this study a clustering technique has been implemented which is K-Means like with hierarchical initial set (HKM). The goal of this study is to prove that clustering document sets do enhancement precision on information retrieval systems, since it was proved by Bellot & El-Beze on French language. A comparison is made between the traditional information retrieval system and the clustered one. Also the effect of increasing number of clusters on precision is studied. The indexing technique is Term Frequency * Inverse Document Frequency (TF * IDF). It has been found that the effect of Hierarchical K-Means Like clustering (HKM) with 3 clusters over 242 Arabic abstract documents from the Saudi Arabian National Computer Conference has significant results compared with traditional information retrieval system without clustering. Additionally it has been found that it is not necessary to increase the number of clusters to improve precision more.
Abstract: This paper proposes an innovative approach for the Connection Admission Control (CAC) problem. Starting from an abstract network modelling, the CAC problem is formulated in a technology independent fashion allowing the proposed concepts to be applied to any wireless and wired domain. The proposed CAC is decoupled from the other Resource Management procedures, but cooperates with them in order to guarantee the desired QoS requirements. Moreover, it is based on suitable performance measurements which, by using proper predictors, allow to forecast the domain dynamics in the next future. Finally, the proposed CAC control scheme is based on a feedback loop aiming at maximizing a suitable performance index accounting for the domain throughput, whilst respecting a set of constraints accounting for the QoS requirements.
Abstract: The morphological parameter of a thin film surface
can be characterized by power spectral density (PSD) functions
which provides a better description to the topography than the RMS
roughness and imparts several useful information of the surface
including fractal and superstructure contributions. Through the
present study Nanoparticle copper/carbon composite films were
prepared by co-deposition of RF-Sputtering and RF-PECVD method
from acetylene gas and copper target. Surface morphology of thin
films is characterized by using atomic force microscopy (AFM). The
Carbon content of our films was obtained by Rutherford Back
Scattering (RBS) and it varied from .4% to 78%. The power values of
power spectral density (PSD) for the AFM data were determined by
the fast Fourier transform (FFT) algorithms. We investigate the effect
of carbon on the roughness of thin films surface. Using such
information, roughness contributions of the surface have been
successfully extracted.