Photoelectric properties of undoped and lithium-doped Zn1−xMgxTe alloys

The room temperature photoelectric response of undoped and lithium-doped Zn_1–xMg_xTe (0 x 0.50) alloys has been measured in the wavelength range 0.50 3.0 m. The response curve for undoped samples is characterized by a single peak in the band edge region. The peak shifts with composition in accordance with the expected shift in the energy band gap. Lithium-doped samples show an additional peak centred at 1.04 eV for all compositions. This peak is attributed to photo-generated holes in the split-off band created as the result of electronic transitions to shallow acceptor impurities.     

Partitioned data objects in distributed databases

In many distributed databases locality of reference is crucial to achieve acceptable performance. However, the purpose of data distribution is to spread the data among several remote sites. One way to solve this contradiction is to use partitioned data techniques. Instead of accessing the entire data, a site works on a fraction that is made locally available, thereby increasing the site's autonomy. We present a theory of partitioned data that formalizes the concept and establishes the basis to develop a correctness criterion and a concurrency control protocol for partitioned databases. Set-serializability is proposed as a correctness criterion and we suggest an implementation that integrates partitioned and non-partitioned data. To complete this study, the policies required in a real implementation are also analyzed. Recommended by: Hector Garcia-Molina     

Dual Band PIFA MIMO Antenna Design with High Isolation for Mobile and Wireless Applications by Using the Genetics Algorithms and Non-uniform Overlapping Method

Wireless Personal Communications - Due to the development and growth of Internet platforms and web services as communication resources, the competition for the network and its limited resources is...     

Parallel best-first search algorithms for planning problems on multi-core processors

The Journal of Supercomputing - The multiplication of computing cores in modern processor units permits revisiting the design of classical algorithms to improve computational performance in complex...     

An industrial portrait background removal solution based on knowledge infusion

Background removal of an identity (ID) picture consists in separating the foreground (face, body, hair and clothes) from the background of the image. It is a necessary groundwork for all modern identity documents that also has many benefits for improving ID security. State of the art image processing techniques encountered several segmentation issues and offer only partial solutions. It is due to the presence of erratic components like hairs, poor contrast, luminosity variation, shadow, color overlap between clothes and background. In this paper, a knowledge infused approach is proposed that hybridizes smart image processing tasks and prior knowledge. The research is based on a divide and conquer strategy aiming at simulating the sequential attention of human when performing a manual segmentation. Knowledge is infused by considering the spatial relation between anatomic elements of the ID image (face feature, forehead, body and hair) as well as their “signal properties”. The process consists in first determining a convex hull around the person’s body including all the foreground while keeping very close to the contour between the background and the foreground. Then, a body map generated from biometric analysis associated to an automatic grab cut process is applied to reach a finer segmentation. Finally, a heuristic-based post-processing step consisting in correcting potential hair and fine boundary issues leads to the final segmentation. Experimental results show that the newly proposed architecture achieves better performances than tested current state-of-the-art methodologies including active contours, generalist popular deep learning techniques, and also two other ones considered as the smartest for portrait segmentation. This new technology has been adopted by an international company as its industrial ID foreground solution.

     

Vademecum‐based GFEM (V‐GFEM): optimal enrichment for transient problems

This paper proposes a generalized finite element method based on the use of parametric solutions as enrichment functions. These parametric solutions are precomputed off‐line and stored in memory in the form of a computational vademecum so that they can be used on‐line with negligible cost. This renders a more efficient computational method than traditional finite element methods at performing simulations of processes. One key issue of the proposed method is the efficient computation of the parametric enrichments. These are computed and efficiently stored in memory by employing proper generalized decompositions. Although the presented method can be broadly applied, it is particularly well suited in manufacturing processes involving localized physics that depend on many parameters, such as welding. After introducing the vademecum‐generalized finite element method formulation, we present some numerical examples related to the simulation of thermal models encountered in welding processes. Copyright © 2016 John Wiley & Sons, Ltd.