Sparsity-aware multiple relay selection in large multi-hop decode-and-forward relay networks

In this paper, we propose and investigate two novel techniques to perform multiple relay selection in large multi-hop decode-and-forward relay networks. The two proposed techniques exploit sparse signal recovery theory to select multiple relays using the orthogonal matching pursuit algorithm and outperform state-of-the-art techniques in terms of outage probability and computation complexity. To reduce the amount of collected channel state information (CSI), we propose a limited-feedback scheme where only a limited number of relays feedback their CSI. Furthermore, a detailed performance-complexity tradeoff investigation is conducted for the different studied techniques and verified by Monte Carlo simulations.NPRP grant 6-070-2-024 from the Qatar National Research Fund (a member of Qatar Foundation)Scopu

A review of composite product data interoperability and product life-cycle management challenges in the composites industry

A review of composite product data interoperability and product life-cycle management challenges is presented, which addresses “Product Life-cycle Management”, developments in materials. The urgent need for this is illustrated by the life-cycle management issues faced in modern military aircraft, where in-service failure of composite parts is a problem, not just in terms of engineering understanding, but also in terms of the process for managing and maintaining the fleet. A demonstration of the use of ISO 10303-235 for a range of through-life composite product data is reported. The standardization of the digital representation of data can help businesses to automate data processing. With the development of new materials, the requirements for data information models for materials properties are evolving, and standardization drives transparency, improves the efficiency of data analysis, and enhances data accuracy. Current developments in Information Technology, such as big data analytics methodologies, have the potential to be highly transformative

Digitization and preservation of cultural heritage: The CEPROQHA approach

The humanity has always learned from the previous experiences for many reasons. The national heritage proves to be a great way to discover a nation's history. As a result, these priceless cultural items have a special attention. However, Since the wide adoption of new digital technologies, documenting, storing, and exhibiting cultural heritage assets became more affordable and reliable. These digital records are then used in several applications. Researchers saw the opportunity to use digital heritage recordings for long-term preservation. In this paper, we present the research progress in cultural heritage digital processing and preservation, highlighting the most impactful advances. Additionally, we present the CEPROQHA project which is based on a new approach aiming at achieving cost-effective acquisition and digital preservation for cultural heritage artifacts in Qatar. - 2017 IEEE.CEPROQHA3 is a cooperative research project between Qatar University and Brunel University, London, funded by the Qatar National Research Fund (QNRF) under the National Priorities Research Program(NPRP) 9th cycle. The project goal. ACKNOWLEDGEMENTS This publication was made possible by NPRP grant 9-181-1-036 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.Scopu

Secondary users selection and sparse narrow-band interference mitigation in cognitive radio networks

Spectrum scarcity is a critical problem that may reduce the effectiveness of wireless technologies and services. To address this problem, different spectrum management techniques have been proposed in the literature such as overlay cognitive radio (CR) where the unlicensed users can share the same spectrum with the licensed users. The main challenges in overlay CR networks are the identification and detection of the Primary User (PU) signals in a multi-source narrow-band interference (NBI) scenario. Therefore, in this paper, we investigate the performance of an orthogonal frequency division multiplexing (OFDM) overlay CR network with Secondary Users (SUs) and subcarriers selection schemes. Three approaches for SUs and subcarriers Selection named Direct, Distributed and Incremental selection techniques are proposed in this paper to increase the expected signal to interference and noise ratio based on full or partial knowledge of the channel state information (CSI). We also show that Distributed selection techniques provide all the SUs equal chances to be selected without affecting the selection diversity gain. General as well as simplified outage probability expressions are derived and extensive simulations are conducted to evaluate the performance of the proposed techniques and support the theoretical derivations. To accommodate more SUs, a new approach for asynchronous NBI estimation and mitigation in CR networks is investigated. Without any prior knowledge of the NBI characteristics and based on sparse signal recovery theory, the proposed approach allows the PU to exploit the sparsity of the SUs interference to recover it and approach the interference-free limit over practical ranges of NBI power levels.This publication was made possible by NPRP grant 6-070-2-024 from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors.Scopu

A Geometric Approach for Surface Intersections

rom any failure of the Newton method that a singularity case treatment is needed. 2. Tangential contacts In a case of a tangential contact, the convergence slows down when there is intersection and alternates around the solution when there is no intersection. Moreover, the result is inaccurate when there is intersection. The tangential contact detection fails because of the approximations of the curves and not because of a mathematical inaccuracy, and the detection by the Newton method may give wrong results (i.e. a point is found but its tangent to the curve is not parallel to a studied line, or a contact point is not detected). A typical numeric inaccuracy is about 10 012 , as a typical modelisation inaccuracy is about 10 04 , 10 05 . For the curve/curve intersection, we use the osculator circles. For each curve, we detect the parallel tangency point to a line which direction is ~ V =

Secondary users selection and sparse narrow-band interference mitigation in cognitive radio networks

International audienceSpectrum scarcity is a critical problem that may reduce the effectiveness of wireless technologies and services. To address this problem, different spectrum management techniques have been proposed in the literature such as overlay cognitive radio (CR) where the unlicensed users can share the same spectrum with the licensed users. The main challenges in overlay CR networks are the identification and detection of the Primary User (PU) signals in a multi-source narrow-band interference (NBI) scenario. Therefore, in this paper, we investigate the performance of an orthogonal frequency division multiplexing (OFDM) overlay CR network with Secondary Users (SUs) and subcarriers selection schemes. Three approaches for SUs and subcarriers Selection named Direct, Distributed and Incremental selection techniques are proposed in this paper to increase the expected signal to interference and noise ratio based on full or partial knowledge of the channel state information (CSI). We also show that Distributed selection techniques provide all the SUs equal chances to be selected without affecting the selection diversity gain. General as well as simplified outage probability expressions are derived and extensive simulations are conducted to evaluate the performance of the proposed techniques and support the theoretical derivations. To accommodate more SUs, a new approach for asynchronous NBI estimation and mitigation in CR networks is investigated. Without any prior knowledge of the NBI characteristics and based on sparse signal recovery theory, the proposed approach allows the PU to exploit the sparsity of the SUs interference to recover it and approach the interference-free limit over practical ranges of NBI power levels

A context-aware approach for long-term behavioural change detection and abnormality prediction in ambient assisted living

This research aims to describe pattern recognition models for detecting behavioural and health-related changes in a patient who is monitored continuously in an assisted living environment. The early anticipation of anomalies can improve the rate of disease prevention. Here we present different learning techniques for predicting abnormalities and behavioural trends in various user contexts. In this paper we described a Hidden Markov Model based approach for detecting abnormalities in daily activities, a process of identifying irregularity in routine behaviours from statistical histories and an exponential smoothing technique to predict future changes in various vital signs. The outcomes of these different models are then fused using a fuzzy rule-based model for making the final guess and sending an accurate context-aware alert to the health-care service providers. We demonstrated the proposed techniques by evaluating some case studies for different patient scenarios in ambient assisted living

Sparsity-aware narrowband interference mitigation and subcarriers selection in OFDM-based cognitive radio networks

In this paper, the performance of an orthogonal frequency division multiplexing overlay cognitive radio network with subcarrier selection schemes is investigated. We propose three subcarrier selection techniques that reduce the level of interference at the primary base station based on collected channel state information from the different network nodes. Approximated outage probability expressions are also derived and verified by simulations for the different studied techniques. In addition, we propose and investigate a new approach for asynchronous narrowband interference (NBI) estimation and mitigation in cognitive radio networks. The proposed approach does not require prior knowledge of the NBI characteristics and allows the primary user to exploit the sparsity of the secondary users interference to recover it based on sparse signal recovery theory and approach the interference-free limit over practical ranges of NBI power levels. 2016 IEEE.Scopu

Approximation of Pore Space with Ellipsoids: A Comparison of a Geometrical Method with a Statistical one

We work with tomographic images of pore space in soil. The images have large dimensions and so in order to speed-up biological simulations (as drainage or diffusion process in soil), we want to describe the pore space with a number of geometrical primitives significantly smaller than the number of voxels in pore space. In this paper, we use the curve skeleton of a volume to segment it into some regions. We describe the method to compute the curve skeleton and to segment it with a simple segment approximation. We approximate each obtained region with an ellipsoid. The set of final ellipsoids represents the geometry of pore space and will be used in future simulations. We compare this method which we call geometrical method with the one described in the paper [8], which we name statistical method (using k-means algorithm). ? 2018 IEEE.This publication was made possible by NPRP grant #9-390-1-088 from the Qatar National Research Fund. The findings achieved herein are solely the responsibility of the authors