A New PSO-based Algorithm for Two-Dimensional Non-Guillotine Non-Oriented Cutting Stock Problem

In this paper, a new algorithm is proposed for the two-dimensional non-guillotine non-oriented cutting stock problem. The considered problem consists of cutting small rectangular pieces of predetermined sizes from large but finite rectangular plates. The objective is to generate cutting patterns that minimize the unused area and fulfill customer orders. The proposed algorithm is a combination of a new particle swarm optimization approach with a heuristic criterion inspired from the literature. The algorithm is tested on twenty-two instances divided into two sets. Corresponding results show the algorithm efficiency in optimizing the trim loss that is comprised between 2.6% and 7.8% for all considered instances.     

Advanced classification approach for neuronal phoneme recognition system based on efficient constructive training algorithm

This paper introduces a neural network optimization procedure allowing the generation of multilayer perceptron (MLP) network topologies with few connections, low complexity and high classification performance for phoneme’s recognition. An efficient constructive algorithm with incremental training using a new proposed Frame by Frame Neural Networks (FFNN) classification approach for automatic phoneme recognition is thus proposed. It is based on a novel recruiting hidden neuron’s procedure for a single hidden-layer. After an initializing phase started with initial small number of hidden neurons, this algorithm allows the Neural Networks (NNs) to adjust automatically its parameters during the training phase. The modular FFNN classification method is then constructed and tested to recognize 5 broad phonetic classes extracted from the TIMIT database. In order to take into account the speech variability related to the coarticulation effect, a Context Window of Three Successive Frame’s (CWTSF) analysis is applied. Although, an important reduction of the computational training time is observed, this technique penalized the overall Phone Recognition Rate (PRR) and increased the complexity of the recognition system. To alleviate these limitations, two feature dimensionality reduction techniques respectively based on Principal Component Analysis (PCA) and Self Organizing Maps (SOM) are investigated. It is observed an important improvement in the performance of the recognition system when the PCA technique is applied. Optimal neuronal phone recognition architecture is finally derived according to the following criteria: best PRR, minimum computational training time and complexity of the BPNN architecture.     

Budget-bounded model-checking pushdown systems

We address the verification problem for concurrent programs modeled as multi-pushdown systems (MPDS). In general, MPDS are Turing powerful and hence come along with undecidability of all basic decision problems. Because of this, several subclasses of MPDS have been proposed and studied in the literature (Atig et al. in LNCS, Springer, Berlin, 2005; La Torre et al. in LICS, IEEE, 2007; Lange and Lei in Inf Didact 8, 2009; Qadeer and Rehof in TACAS, LNCS, Springer, Berlin, 2005). In this paper, we propose the class of bounded-budget MPDS, which are restricted in the sense that each stack can perform an unbounded number of context switches only if its depth is below a given bound, and a bounded number of context switches otherwise. We show that the reachability problem for this subclass is Pspace-complete and that LTL-model-checking is Exptime-complete. Furthermore, we propose a code-to-code translation that inputs a concurrent program \(P\) and produces a sequential program \(P'\) such that running \(P\) under the budget-bounded restriction yields the same set of reachable states as running \(P'\) . Moreover, detecting (fair) non-terminating executions in \(P\) can be reduced to LTL-Model-Checking of \(P'\) . By leveraging standard sequential analysis tools, we have implemented a prototype tool and applied it on a set of benchmarks, showing the feasibility of our translation.     

Free poset algebras and combinatorics of cones

In Free poset Boolean algebra F(P ), uniqueness of normal form of non-zero elements is proved and the notion of support of a non-zero element is, therefore, well defined. An Inclusion–Exclusion-like formula is given by defining, for each non-zero element x, using support of x ∈F(P ) in a very natural way.      

Experimental Investigation of Passive Fault Tolerant Control for Induction Machine Using Sliding Mode Approach

This paper presents a passive fault tolerant control approach dedicated to stator inter‐turn short‐circuit fault of an induction machine. This control is based on sliding mode strategy and is implemented for validation on real‐time data acquisition and control platform. The proposed work highlights the integral sliding mode controller benefits during healthy and faulty operations. It can make the induction machine outputs to track their desired reference signals in finite‐time and allows to obtain a better dynamic response performances even in presence of fault. Moreover to avoid the use of a flux sensor, a second order sliding mode observer is used to estimate the rotor flux. Since the used observer converges in finite time, the closed‐loop stability of the proposed system (controller+observer) is proved using the Lyapunov stability theorem. Experimental results are conducted for squirrel cage induction machine to highlight the efficiency and applicability of the proposed fault tolerant control.     

FPGA implementation of a HW/SW platform for multimedia embedded systems

This paper presents a HW/SW platform for embedded video system. It has been designed around an embedded RISC processor and FPGA technologies and provides video input and output interfaces. The configurable platform has been used to implement a real time video processing and vision systems. The Altera’s Nios II development board was chosen to realise this real time video platform which uses μClinux as embedded Linux Operating System. Experimental results using H.263 video encoder show that this platform provides enough resources and speed to implement even complex multimedia embedded systems in real time.     

Study of RF N LDMOS critical electrical parameter drifts after a thermal and electrical ageing in pulsed RF

An innovative reliability test bench dedicated to RF power devices is currently implemented. This bench allows to apply both electric and thermal stress for lifetime test under radar pulsed RF conditions. This paper presents the first investigation findings of critical electrical parameter degradations after thermal and electrical ageing. It shows that the tracking of a set of parameters (drain–source current, on-state resistance, threshold voltage, feedback capacitance and transconductance) can give insight into the hot carrier injection phenomenon for a RF n⁻ channel lateral DMOS (N⁻ LDMOS) working under pulsed conditions.     

Swarm intelligence‐based radio resource management for V2V‐based D2D communication

Internet of Things is a promising paradigm that provides the future network of interconnected devices. Device‐to‐Device (D2D) communication, which is considered as an enabler for vehicle‐to‐everything applications, has become an emerging technology to optimize network performance. In this paper, we study the Radio Resource Management (RRM) issue for D2D‐based Vehicle‐to‐Vehicle communication. The RRM key role is to assure the proficient exploitation of available resources while serving users according to their quality of service parameters. An Ant Colony Optimization (ACO)‐based Resource Allocation (ACORA) scheme is proposed in this paper. Swarm intelligence algorithm ACO is adopted to reduce the computational complexity while realizing satisfactory performance. Simulation results show promising performance of our proposed ACORA scheme.     

A generalized switching CFAR processor based on test cell statistics

In this paper, a new constant false alarm rate (CFAR) thresholding algorithm which is a generalisation of the switching CFAR (S-CFAR) that takes into account the statistics of the sample in the test cell for reference sample selection is proposed. It employs a composite approach based on the switching CFAR and the order statistic CFAR (OS-CFAR). A mathematical analysis in a homogeneous environment is provided for this detector. The results obtained show that the detection performance of the generalised S-CFAR (GS-CFAR) is improved both in homogenous background and non-homogenous environment caused by interfering targets and clutter edge.     

PEAL: Power Efficient and Adaptive Latency Hierarchical Routing Protocol for Cluster-Based WSN

In wireless sensor networks, one of the most important constraints is the low power consumption requirement. For that reason, several hierarchical or cluster-based routing methods have been proposed to provide an efficient way to save energy during communication. However, their main challenge is to have efficient mechanisms to achieve the trade-off between increasing the network lifetime and accomplishing acceptable transmission latency. In this paper, we propose a novel protocol for cluster-based wireless sensor networks called PEAL (Power Efficient and Adaptive Latency). Our simulation results show that PEAL can extend the network lifetime about 47% compared to the classic protocol LEACH (Low-Energy Adaptive Clustering Hierarchy) and introduces an acceptable transmission latency compared to the energy conservation gain.