Analytical analysis of applying packet fragmentation mechanism on IEEE 802.11b DCF network in non ideal channel with infinite load conditions

The analytical modeling and performance analysis of the 802.11 network in all its various extensions (802.11b, 802.11a, 802.11g, 802.11e, 802.11n, etc.) have already been widely explored over the past years. However, the packet fragmentation mechanism (PFM), which is proposed by the IEEE work group to reduce the impact of bit error rate (BER) on the packet error rate (PER), has not been considered in the analytical models proposed in the literature. Yet, the PFM constitutes a key parameter to achieve the best performances of 802.11 networks. In this paper, we extend the Bianchi’s Markov chain model with the PFM and the PER. Then, we analyze the performance improvement level achieved with the PFM in an IEEE 802.11 network under the impact of BER and packet length. The proposed analysis has been applied on the basic access method of 802.11b network in saturated traffic conditions. So, we have analyzed the throughput and the mean response time of the 802.11 network. The obtained theoretical results are validated by simulation.     

Determination of the combustion properties of natural gases by pseudo-constituents

This paper presents a methodology for a rapid determination of important natural gas combustion properties (lower heating value, Wobbe index and the stoichiometric air-fuel ratio) using easily detectable physical properties. It is possible to determine natural gas composition by measuring two physical properties and using specific ternary diagrams (CH₄-C₂H₆-C₃H₈ and CH₄-C₂H₆-N₂). The first part of the work deals with the selection of two physical properties from a group comprising thermal conductivity, refraction index, and speed of sound. Then, in the second part, a sensor using the best couple of physical property is used to determine the ternary pseudo-constituents of the gas mixture. The model and the sensor are applied to specific situations such as the online determination of LHV. The error on the combustion properties of natural gas is less than 1% over the gases considered in the present study and over about 20 typical gases supplied over Europe. The effect of small errors in the measurement of physical properties has also been highlighted.     

Performances comparison of pulse-pair and 2-step prediction algorithms for the doppler spectrum estimation

In this work we use real data provided by terminal pulse Doppler radar (WSR-88D) echoes to estimate the windshear hazards disastrous for the aircraft takeoffs and landings. Briefly two different methods are used to estimate the received Doppler moments. The second central moment which is the variance of the wind speed is called width or shear. A first method is in the time domain and also called pulse-pair, while the second is in the frequency domain. The main aim of this study is a performances comparison of results provided by the two mentioned methods and assumes that the power spectrums of the received signals are approached with the Gaussian shape.     

Molecularly‐Engineered, 4D‐Printed Liquid Crystal Elastomer Actuators

Three‐dimensional structures that undergo reversible shape changes in response to mild stimuli enable a wide range of smart devices, such as soft robots or implantable medical devices. Herein, a dual thiol‐ene reaction scheme is used to synthesize a class of liquid crystal (LC) elastomers that can be 3D printed into complex shapes and subsequently undergo controlled shape change. Through controlling the phase transition temperature of polymerizable LC inks, morphing 3D structures with tunable actuation temperature (28 ± 2 to 105 ± 1 °C) are fabricated. Finally, multiple LC inks are 3D printed into single structures to allow for the production of untethered, thermo‐responsive structures that sequentially and reversibly undergo multiple shape changes.     

Profit-oriented partial disassembly line design: dealing with hazardous parts and task processing times uncertainty

This paper addresses the problem of profit-oriented disassembly line design and balancing considering partial disassembly, presence of hazardous parts and uncertainty of task processing times. Few papers have studied the stochastic disassembly line balancing problem and existing approaches have focused on heuristic and metaheuristic methods. Most existing work has concentrated on complete disassembly where task times are assumed to be normal random variables and where AND/OR graphs are not considered. The objective of this paper is the design of a serial line that obtains the maximum revenue and then balances the workload under uncertainty. The processing time of a disassembly task is assumed to be a random variable with any known probability distribution. An AND/OR graph is used to model the precedence relationships among tasks. Stochastic programming models and exact-based solution approaches combining the L-shaped algorithm and Monte Carlo sampling techniques are proposed. The relevance and applicability of the proposed models and solution methods are shown by solving efficiently a set of disassembly problem instances from the literature.     

Learning-based symbolic assume-guarantee reasoning for Markov decision process by using interval Markov process

Many real-life critical systems are described with large models and exhibit both probabilistic and non-deterministic behaviour. Verification of such systems requires techniques to avoid the state space explosion problem. Symbolic model checking and compositional verification such as assume-guarantee reasoning are two promising techniques to overcome this barrier. In this paper, we propose a probabilistic symbolic compositional verification approach (PSCV) to verify probabilistic systems where each component is a Markov decision process (MDP). PSCV starts by encoding implicitly the system components using compact data structures. To establish the symbolic compositional verification process, we propose a sound and complete symbolic assume-guarantee reasoning rule. To attain completeness of the symbolic assume-guarantee reasoning rule, we propose to model assumptions using interval MDP. In addition, we give a symbolic MTBDD-learning algorithm to generate automatically the symbolic assumptions. Moreover, we propose to use causality to generate small counterexamples in order to refine the conjecture assumptions. Experimental results suggest promising outlooks for our probabilistic symbolic compositional approach.     

Modeling and performance evaluation of the IEEE 802.15.4e LLDN mechanism designed for industrial applications in WSNs

The IEEE 802.15.4 standard has been introduced for low latency and low energy consumption in wireless sensor networks. To better support the requirements of industrial applications, where the use of this standard is limited, the low latency deterministic network (LLDN) mechanism of the IEEE 802.15.4e amendment has been proposed. In this paper, we develop a three dimensional Markov chain model for the IEEE 802.15.4e LLDN mechanism. Then, we estimate the stationary probability distribution of this chain in order to derive theoretical expressions of some performance metrics, as the reliability, energy consumption, throughput, delay and jitter. After that, we conduct a comparative study between the IEEE 802.15.4e LLDN and the IEEE 802.15.4 slotted carrier sense multiple access with collision avoidance (CSMA/CA). Numerical results show that the deterministic behavior of the LLDN mechanism significantly reduces the collision probability providing best performances in terms of reliability, energy consumption, throughput and delay compared to the IEEE 802.15.4 slotted CSMA/CA. Finally, the accuracy of our theoretical analysis is validated by Monte Carlo simulations.     

Nonlinear analysis and reliability of metallic truss structures

The present study goes into the search for the safety domain of civil engineering structures. The objective is to show how a reliability-evaluation brought by a mechanical sizing can be obtained. For that purpose, it is necessary to have a mechanical model and a reliability model representing correctly the behavior of this type of structure.It is a question on one hand, to propose a formulation for the nonlinear calculation (mechanical nonlinearity) of the spatial structures in trusses, and on the other hand, to propose or to adapt a formulation and a modeling of the reliability. The principle of Hasofer-Lind can be applied, in first approach, for the reliability index estimation, scenarios and the probability of failure.The made check concerned metallic in truss structures. Finally, some structures are calculated using the method adapted by Hasofer-Lind to validate the probability approach of the reliability analysis.