HVOF sprayed WC–Co coatings: Microstructure,mechanical properties and friction moment prediction

This study aims at gaining a better understanding of the microstructural features that control the mechanical and the tribological performances of WC–12 wt.% Co coatings under High Velocity Oxygen Fuel (HVOF) spraying conditions. This paper looks at the influences of the HVOF process parameters for WC–12Co material on the microstructural and the tribological behaviours of the coatings. The correlation between the coating microstructure and the wear behaviour is investigated by observing and analysing the microstructure and by studying the friction moment using enhanced statistical tool based on neural computations. According to the experimental and the numerical results, it has been shown that the spray parameters affect the phase composition, hardness and porosity of HVOF sprayed WC–12Co coatings and the correlations with HVOF process parameters are fully predictable in the steady-state regime.     

Direct adaptive fuzzy control of a class of MIMO non-affine nonlinear systems

An adaptive fuzzy control approach is proposed for a class of multiple-input–multiple-output (MIMO) nonlinear systems with completely unknown non-affine functions. The global implicit function theorem is first used to prove the existence of an unknown ideal implicit controller that can achieve the control objectives. Within this scheme, fuzzy systems are employed the approximate the unknown ideal implicit controller, and robustifying control terms are used to compensate the approximation errors and external disturbances. The adjustable parameters of the used fuzzy systems are deduced from the stability analysis of the closed-loop system in the sense of Lyapunov. To show the efficiency of the proposed controllers, two simulation examples are presented.     

Cooperative Association/Re-association Approaches to Optimize Energy Consumption for Real-Time IEEE 802.15.4/ZigBee Wireless Sensor Networks

The major challenge of real-time Wireless Sensor Networks stills the optimization of both constraints: energy consumption, to get long network lifetime and the communication delay, to meet real-time requirements. In the context of IEEE 802.15.4/ZigBee networks, the association procedure has a direct effect on building paths optimizing those constraints. In this paper, we are interested on the definition of an ideal approach of load balancing to fairly distribute energy consumption among nodes in IEEE 802.15.4/ZigBee WSNs. This approach leads to conserve energy of each node in order to extend the network lifetime. To be closer to this ideal, we propose new dynamic association/re-association approaches allowing path alternation relative to association criteria and their threshold parameters. The implementation of those approaches in NS2 simulator highlights the efficiency of cooperative and dynamic association criteria particularly the one based on the sum of the inverses of remaining energy. Indeed, this approach gives better results with regard to energy distribution according to ideal approach which leads to a longer lifetime. It also performs lower latency for real time communication.     

Effect of Silicone Carbide on the Elastic Properties of Starch‐Based Composites: A Three‐Phase Model

The effect of a rigid filler on the elastic properties of starch‐based composites is investigated. Thermomolding of the targeted composite is conducted using a starch matrix with varying silicone carbide content. Mechanical testing reveals that the composite's Young modulus cannot be rationalized using two‐phase analytical models. The effect of a weak interphase region is highlighted using a finite‐element model that assumes the generation of virtual microstructures. Numerical results are discussed by describing the influence of the structural and interphase parameters on the composite's elastic modulus. Identification of optimal interphase parameters quantitatively demonstrates the weak adhesion between intrinsic phases for all studied filler fractions.

     

Quantized based image watermarking in an independent domain

This paper presents a performance study for two well known quantized based watermarking schemes Scalar Costa Scheme (SCS), and Trellis Coded Quantization scheme (TCQ) in an independent domain. For our study, the independent domain is obtained by the combination of the cited schemes with Independent Component Analysis (ICA). The Independent Component Analysis is used while inserting and extracting the message. Thus a performance compromise improvement of the original SCS and TCQ schemes in terms of robustness, capacity, and security is shown. Then the obtained schemes performances are compared to the Spread Transform (ST) based scheme well known for its proven good robustness properties. Our results show that, using watermarking with side information in independent domain permits to improve the global SCS and TCQ schemes performances. For example, in the case of SCS, by studying the Bit Error Rate (BER) in function of the watermark to noise ratio (WNR), the robustness has been improved by 20 dB (1 decade) when WNR is equal to 0 dB. Moreover, the capacity study shows for the same WNR=0 dB, the amount of information to be transmitted without error for a given noise level of the proposed SCS combined with ICA scheme (SCS-ICA) is much higher than that of the existing schemes. Finally, the study of the probability density functions (PDF) of the original and marked signals has shown that the Cachin-security level of the TCQ in an independent domain scheme (TCQ-ICA) is the best one compared to the other known schemes.     

Improving the time resolution and signal noise ratio of ultrasonic testing of welds by the wavelet packet

In ultrasonic testing of welds, detection of small flaws is often difficult by the superimposed noise due to the grain structure of the material. The scattering of ultrasonic waves from grain boundaries can interfere and introduce disturbance in the received signal that can sometimes mask indications due to a small but potentially dangerous defect. However, to enhance the flaw characterization, methods based on ‘thresholding’ have given good results only when the signal to noise ratio is high, and since bandwidth of the reflected signal as well as its principal frequency is subject to wide variation, it is impossible to create an appropriate band pass filter. So linear filtering does not provide good results, because both, the structure noise and flaw signal concentrate energy in the same frequency band. Non-linear filtering can be used to reduce or suppress the noise from ultrasonic signals. One way out is to use the time frequency transforms, the method is based on the wavelet packet decomposition. The Debauchee function of order 8 [Daubauchee I. Orthogonal bases of capacity wavelets. Commun Pure Appl Math 1998;41] has been chosen as the analyzing function, and each measured ultrasonic signal is analyzed by a filter bank through only three levels of decomposition. This work demonstrates that the following analysis is very efficient with respect to signal recovery from noisy data. The experimental results have shown that the proposed method has excellent performances on SNR enhancements.     

Self-organizing technique for improving coverage in connected mobile objects networks

Despite the multiple benefits offered today by connected mobile objects networks (CMONs), some constraints continue to limit their development and to degrade their applications and services’ performance. Given their limited energy, some or many objects may stop functioning which leads to the deterioration of network functionalities such as monitoring, detection and transfer of data. It is in this context that our work is situated, namely the improvement of applications performance and the quality of service (QoS) within CMONs, by exploiting some communication environment parameters and geometry techniques. We propose a new technique called self-organization area coverage (SOAC) for CMONs which aims to ensure maximum coverage in the network while optimizing the exploited resources. SOAC has been evaluated and compared not only to the network without improvement but to two other solutions proposed in the literature. The obtained results show a clear improvement in terms of network coverage and several QoS parameters.     

Structural robustness and service reachability in urban settings

The concept of city or urban resilience has emerged as one of the key challenges for the next decades. As a consequence, institutions like the United Nations or Rockefeller Foundation have embraced initiatives that increase or improve it. These efforts translate into funded programs both for action “on the ground” and to develop quantification of resilience, under the for of an index. Ironically, on the academic side there is no clear consensus regarding how resilience should be quantified, or what it exactly refers to in the urban context. Here we attempt to link both extremes providing an example of how to exploit large, publicly available, worldwide urban datasets, to produce objective insight into one of the possible dimensions of urban resilience. We do so via well-established methods in complexity science, such as percolation theory—which has a long tradition at providing valuable information on the vulnerability in complex systems. Our findings uncover large differences among studied cities, both regarding their infrastructural fragility and the imbalances in the distribution of critical services.     

Partial syndrome-based system-level fault diagnosis using game theory

This paper introduces a novel diagnosis approach, using game theory, to solve the comparison-based system-level fault identification problem in distributed and parallel systems based on the asymmetric comparison model. Under this diagnosis model tasks are assigned to pairs of nodes and the results of executing these tasks are compared. Using the agreements and disagreements among the nodes’ outputs, i.e. the input syndrome, the fault diagnosis algorithm identifies the fault status of the system’s nodes, under the assumption that at most t of these nodes can permanently fail simultaneously. Since the introduction of the comparison model, significant progress has been made in both theory and practice associated with the original model and its offshoots. Nevertheless, the problem of efficiently identifying the set of faulty nodes when not all the comparison outcomes are available to the fault identification algorithm prior to initiating the diagnosis phase, i.e. partial syndromes, remains an outstanding research issue. In this paper, we first show how game theory can be adapted to solve the fault diagnosis problem by maximising the payoffs of all players (nodes). We then demonstrate, using results from a thorough simulation, the effectiveness of this approach in solving the fault identification problem using partial syndromes from randomly generated diagnosable systems of different sizes and under various fault scenarios. We have considered large diagnosable systems, and we have experimented extreme faulty situations by simulating all possible fault sets even those that are less likely to occur in practice. Over all the extensive simulations we have conducted, the new game-theory-based diagnosis algorithm performed very well and provided good diagnosis results, in terms of correctness, latency, and scalability, making it a viable addition or alternative to existing diagnosis algorithms.