Complex flow simulations in natural aquifer

Natural aquifers are complex media and contain heterogeneous structures. This paper introduces a new algorithm to simulate flow fluid in such complex media. A parallel version of the method is released, and two well-known sparse linear solvers, based, respectively, on a multifrontal Cholesky factorization and an iterative structured multigrid method, are tested. The mixed finite element (MFE) method is used to discretize Darcy’s equation. The efficiency of the algorithm proposed is shown in different numerical examples.     

Output feedback control of a class of stochastic hybrid systems

This paper deals with static output feedback control of a class of reconfigurable systems with Markovian Parameters and state-dependent noise. The main contribution is to formulate conditions for multi-performance design related to this class of stochastic hybrid systems. The specifications and objectives under consideration include stochastic stability, and performances. Another problem related to a more general class of stochastic hybrid systems, known as Markovian Jump Linear Systems (MJLS), is also addressed. This problem concerns the mode-independent output feedback control of MJLS. The obtained results are illustrated on a numerical example.     

Arrays of high aspect ratio magnetic microstructures for large trapping throughput in lab-on-chip systems

Here we report a novel technology to obtain arrays of highly efficient magnetic micro-traps that relies on simple fabrication process. Developed micro-traps consist in chains of iron particles diluted in polydimethylsiloxane (PDMS). We analyzed the microstructure of the composite membrane by X-ray tomography. It revealed the predominance of aligned chain-like agglomerates. Largest traps, with diameter ranging from 4 to 11 µm, are found to be the most efficient. The trap arrays were characterized by a density of 1300 magnetic micro-traps/mm², an average nearest neighbor distance of 21 µm. Implemented in a microfluidic channel operating at a relatively high flow rate of 0.97 µL/s—a flow velocity of 8.3 mm/s—we measured a trapping efficiency of more than 99.7%, with a throughput of up to 7100 trapped beads/min. These performances are competitive with other approaches like hydrodynamic trapping. The strengths of this technology are its simple fabrication and easy handling.     

Probabilistic Verification Scenarios with Reduced Authentication Delay for Handoff Clients in Mesh Networks

Wireless Personal Communications - In this paper, we have proposed a secure handoff procedure by generating and assessing the tickets for each mesh client which are divided among various zones of...     

Effects of imperfect channel sensing and estimation on the performance of cognitive radio systems

In realistic scenarios of cognitive radio (CR) systems, imperfect channel sensing may occur due to false alarms and miss detections. Channel estimation between the secondary user transmitter and another secondary user receiver is another challenge in CR systems, especially for frequency‐selective fading channels. In this context, this paper presents a study of the effects of imperfect channel sensing and channel estimation on the performance of CR systems. In particular, different methods of channel estimation are analyzed under channel sensing imperfections. Initially, a CR system model with channel sensing errors is described. Then, the expectation maximization (EM) algorithm is implemented in order to learn the channel fading coefficients. By exploiting the pilot symbols and the detected symbols at the secondary user receiver, we can estimate the channel coefficients. We further compare the proposed EM estimation algorithm with different estimation algorithms such as the least squares (LS) and linear minimum mean square error (LMMSE). The expressions of channel estimates and mean squared errors (MSE) are determined, and their dependencies on channel sensing uncertainty are investigated. Finally, to reduce the complexity of EM algorithm, a sub‐optimal algorithm is also proposed. The obtained results show that the proposed sub‐optimal algorithm provides a comparable bit error rate (BER) performance with that of the optimal one yet with less computational complexity.     

Deterministically Isolating a Perfect Matching in Bipartite Planar Graphs

We present a deterministic Logspace procedure, which, given a bipartite planar graph on n vertices, assigns O(log n) bits long weights to its edges so that the minimum weight perfect matching in the graph becomes unique. The Isolation Lemma as described in Mulmuley et al. (Combinatorica 7(1):105–131, 1987) achieves the same for general graphs using randomness, whereas we can do it deterministically when restricted to bipartite planar graphs. As a consequence, we reduce both decision and construction versions of the perfect matching problem in bipartite planar graphs to testing whether a matrix is singular, under the promise that its determinant is 0 or 1, thus obtaining a highly parallel SPL\mathsf{SPL} algorithm for both decision and construction versions of the bipartite perfect matching problem. This improves the earlier known bounds of non-uniform SPL\mathsf{SPL} by Allender et al. (J. Comput. Syst. Sci. 59(2):164–181, 1999) and NC\mathsf{NC} ² by Miller and Naor (SIAM J. Comput. 24:1002–1017, 1995), and by Mahajan and Varadarajan (Proceedings of the Thirty-Second Annual ACM Symposium on Theory of Computing (STOC), pp. 351–357, 2000). It also rekindles the hope of obtaining a deterministic parallel algorithm for constructing a perfect matching in non-bipartite planar graphs, which has been open for a long time. Further we try to find the lower bound on the number of bits needed for deterministically isolating a perfect matching. We show that our particular method for isolation will require Ω(log n) bits. Our techniques are elementary.     

An adaptive model for sequential labeling systems

There are many levels in the task of information extraction. Level 1 deals with named entities such as PERSON, ORG, DATE, etc. Level 2 concerns the role played by the named entities wrt a specific event. For instance, in a management change event, a PERSON might be either the new coming person to the company or the leaving one. Building learning models for event extraction without considering the different levels is completely misleading. In this paper, the reasons for considering these levels are explained, and an adaptive model for event extraction is proposed. It could be applied on any sequence labeleling system, e.g., CRF-based classifier, RNN, LSTM, etc. The experimental results show that the adaptive model outperforms the direct model in terms of efficiency and gives comparable results compared to GLA2E, an expert’s pattern based event extractor.

     

On computing the stabilizing solution of a class of discrete‐time periodic Riccati equations

This paper addresses the problem of solving a class of periodic discrete‐time Riccati equation with an indefinite sign of its quadratic term. Such an equation is closely related to the so‐called full‐information H _∞ control of discrete‐time periodic systems. A globally convergent iterative algorithm with a local quadratic convergence rate is proposed for this purpose. An application to the problem of H _∞ filtering of discrete‐time periodic systems is also developed and illustrated via a numerical example. Copyright © 2013 John Wiley & Sons, Ltd.     

Self‐oscillating mixer using six port power divider

A self‐oscillating mixer (SOM) that uses a six port microstrip power divider is presented in this article. The oscillation and mixing functions are executed using a pair of identical GaAs field effect transistors. The power division and combination of the RF and local oscillator (LO) signals involved in the operation are implemented using the six port network. The RF input port of the proposed SOM is totally isolated from the operation of the LO which is a desirable feature in many applications. The proposed structure can work as a stand‐alone oscillator with a frequency of 4.71 GHz and a power level of 16.1 dBm. When fed with a RF signal, the proposed structure becomes a fully functional SOM exhibiting a conversion gain of 5.2 dBm. The simulation and measurement results of the proposed SOM are presented to validate the design concept. © 2014 Wiley Periodicals, Inc. Int J RF and Microwave CAE 25:269–276, 2015.     

Enhanced DHT-based P2P Architecture for Effective Resource Discovery and Management

Recently, Peer-to-Peer (P2P) has become a popular paradigm for building distributed systems, aiming to provide resource localization and sharing in large-scale networks. However, advanced searching for resources remains an open issue. The flooding technique used by some P2P systems is expensive in bandwidth usage, and shows a serious lack in scalability. Also, more efficient systems based on distributed hash tables (DHT) lack in query expressiveness and flexibility. This paper addresses this issue by discussing existing solutions, and proposing a novel approach to support advanced multi-keyword queries in the context of P2P systems. It extends the existing, and widely established DHT-based localization frameworks. This new approach provides an effective resource localization framework; it can substantially reduce bandwidth consumption and improve load balancing over the network. Moreover, various kinds of applications can be deployed on top of this generic framework. As a relevant use case, this paper describes a novel service discovery and management application.