Micromechanical modelling of switching phenomena in polycrystalline piezoceramics: application of a polygonal finite element approach

A micromechanically motivated model is proposed to capture nonlinear effects and switching phenomena present in ferroelectric polycrystalline materials. The changing remnant state of the ferroelectric crystal is accounted for by means of so-called back fields—such as back stresses—to resist or assist further switching processes in the crystal depending on the local loading history. To model intergranular effects present in ferroelectric polycrystals, the computational model elaborated is embedded into a mixed polygonal finite element approach, whereby an individual ferroelectric grain is represented by one single irregular polygonal finite element. This computationally efficient coupled simulation framework is shown to reproduce the specific characteristics of the responses of ferroelectric polycrystals under complex electromechanical loading conditions in good agreement with experimental observations.     

Microstructural refinement and tensile properties enhancement of Mg-3Al alloy using charcoal additions

Significant grain refinement in Mg-3Al alloy is achieved with the addition of charcoal due to the formation of Al₄C₃ particles, which act as effective nuclei for magnesium grains. Addition of 0.5 wt% charcoal has lead to reduced grain size of Mg-3Al alloy from 500 to 80 μm and no substantial grain refinement is obtained on further addition of charcoal. The results further reveal that the prolonged holding of the melt after the addition of charcoal has not affected the grain refining efficiency of Al₄C₃. Steady increase in tensile properties observed with increasing amount of charcoal addition has been attributed to the grain refinement and the presence of fine Al₄C₃ particles. The strengthening mechanisms due to charcoal addition are discussed in terms of Hall-Petch relation and dispersion strengthening. The predicted values are in good agreement with experimental results.     

Production and properties of crude enterotoxin of Pseudomonas aeruginosa

Pseudomonas aeruginosa CTM-3 was found to be the most potentially enteroxigenic strain out of the 12 isolates recovered from milk, as a high fluid length ratio, i.e. F/L (1.1) in rabbit gut and a strong permeability response in rabbit skin (38.5 mm² necrotic zone) was obtained with this culture. No clear-cut relationship between the two tests was observed. Six of the ethidium bromide (300 μg/ml) cured variants of this culture completely lost their ability to produce enterotoxin indicating the possible involvement of a plasmid in enterotoxin synthesis. The crude enterotoxin from P. aeruginosa CTM-3 was completely inactivated in 15 s at 72°C. However, it was fairly stable at pH values in the range 4.5–7.5. Both pepsin and trypsin inactivated the enterotoxin activity at a concentration of 40 μg/ml. Organic acids, formalin and hydrogen peroxide had no significant effect on the enterotoxin activity. The need for further investigations with purified preparations is emphasized.     

A dynamic call admission scheme for VBR traffic in ATM networks

The role of call admission control (CAC) in high-speed networks is to maintain the network utilization at a high level, while ensuring that the quality of service (QoS) requirements of the individual calls are met. We use the term static CAC to describe schemes that always allocate the same bandwidth to a specific group of multiplexed calls, independent of the other traffic sharing the link. Dynamic CAC, on the other hand, denotes a scheme in which the bandwidth allocation to a group of calls sharing a queue is influenced by the traffic in other queues destined for the same outgoing link. We propose a generic dynamic call admission scheme for VBR and ABR traffic whose aim is to reduce the blocking rate for VBR calls at the expense of a higher blocking rate for ABR calls. Our scheme is generic because it builds up on a pre-existing static scheme, e.g., one based on a simple notion of effective bandwidth. Our simple approach results in a significant reduction of the blocking rate for VBR traffic (several orders of magnitude), if the bandwidth requirements of a single call are a reasonably small fraction of the link capacity. At the same time, the deterioration of service for ABR traffic can be contained. This revised version was published online in August 2006 with corrections to the Cover Date.     

Performance Analysis of WDM Optical Networks with Wavelength Usage Constraint

Due to power considerations, it is possible that not all wavelengths available in a fiber can be used at a given time. In this paper, an analytical model is proposed to evaluate the blocking performance of wavelength-routed optical networks with and without wavelength conversion where the usable wavelengths in a fiber is limited to a certain maximum number, referred to as wavelength usage constraint. The effect of the wavelength usage constraint is studied on ring and mesh-torus networks. It is shown that the analytical model closely approximates the simulation results. We also evaluate the performance of the first-fit wavelength assignment algorithm and compare its performance with the random wavelength assignment algorithm through simulation. It is observed that increasing the total number of wavelengths in a fiber is an attractive alternative to wavelength conversion when the number of usable wavelengths in a fiber is maintained the same.     

Run-to-run control of blood glucose concentrations for people with Type 1 diabetes mellitus

Run-to-run control has been applied to several traditional batch processes in the chemical industry. The 24-h cycle of eating meals, measuring blood glucose concentrations, and delivering the correct insulin bolus, with the goal of achieving the optimal blood glucose profile, can be viewed in the same spirit as traditional batch processes such as emulsion polymerization. In this paper, we aim to exploit the "repetitive" nature of the insulin therapy of people with Type 1 diabetes. A run-to-run algorithm is used on a virtual diabetic patient model to control blood glucose concentrations. The insulin input is parameterized into the timing and amount of the dose while the glucose output is parameterized into the maximum and minimum glucose concentrations. Robustness of the algorithm to variations in the meal amount, meal timing, and insulin sensitivity parameter is addressed. In general, the algorithm is able to converge when the meal timing is varied within +/- 40 min. If the meal size is underestimated by approximately 10 grams (g), the algorithm is able to converge within a reasonable time frame for breakfast, lunch, and dinner. If the meal size is overestimated by 20-25 g, the algorithm is able to converge. When random variations in the meal timing and the meal amount are introduced, the variation on the output variables, Gmax and Gmin, scales according to the amount of variation allowed. Along with this, the insulin sensitivity of the virtual patient model is varied. The algorithm is robust for differences in insulin sensitivity less than +/- 50% of the nominal value.     

Scheduling sensor activity for information coverage of discrete targets in sensor networks

In this paper, we study the problem of scheduling sensor activity to cover a set of targets with known locations such that all targets can be monitored all the time and the network can operate as long as possible. A solution to this scheduling problem is to partition all sensors into some sensor covers such that each cover can monitor all targets and the covers are activated sequentially. In this paper, we propose to provide information coverage instead of the conventional sensing disk coverage for target. The notion of information coverage is based on estimation theory to exploit the collaborative nature of geographically distributed sensors. Due to the use of information coverage, a target that is not within the sensing disk of any single sensor can still be considered to be monitored (information covered) by the cooperation of more than one sensor. This change of the problem settings complicates the solutions compared to that by using a disk coverage model. We first define the target information coverage (TIC) problem and prove its NP‐completeness. We then propose a heuristic to approximately solve our problem. Simulation results show that our heuristic is better than an existing algorithm and is close to the upper bound when only the sensing disk coverage model is used. Furthermore, simulation results also show that the network lifetime can be significantly improved by using the notion of information coverage compared with that by using the conventional definition of sensing disk coverage. Copyright © 2008 John Wiley & Sons, Ltd.     

An Adaptive Transmission Mode Selection Scheme for Cellular Underlaid D2D Communication

In this paper, we propose to use Artificial Bee Colony (ABC) optimization to solve the joint mode selection, channel assignment, and power allocation (JMSCPA) problem to maximize system throughput and spectral efficiency. JMSCPA is a problem where the allocation of channel and power depends on the mode selection. Such problems require two step solution and are called bi-level optimization problems. As bi-level optimization increases the complexity and computational time, we propose a modified version of single-level ABC algorithm aided with the adaptive transmission mode selection algorithm to allocate the cellular, reuse, and dedicated modes to the DUs along with channel and power allocation based on the network traffic load scenarios. A single variable, represented by the users (CUs and DUs) is used to allocate mode selection, and channel allocation to solve the JMSCPA problem, leading to a simpler solution with faster convergence, and significant reduction in the computational complexity which scales linearly with the number of users. Further, the proposed solution avoids premature stagnation of conventional ABC into local minima by incorporating a modification in its update procedure. The efficacy of the ABC-aided approach, as compared to the results reported in the literature, is validated by extensive numerical investigations under different simulation scenarios.

     

Adaptive source-channel subband video coding for wireless channels

This paper presents a general framework for combined source-channel coding within the context of subband coding. The unequal importance of subbands in reconstruction of the source is exploited by an appropriate allocation of source and channel coding rates for the coding and transmission of subbands over a noisy channel. For each subband, the source coding rate as well as the level of protection (quantified by the channel coding rate) are jointly chosen to minimize the total end-to-end mean-squared distortion suffered by the source. This allocation of source and channel coding rates is posed as a constrained optimization problem, and solved using a generalized bit allocation algorithm. The optimal choice of source and channel coding rates depends on the state of the physical channel. These results are extended to transmission over fading channels using a finite state model, where every state corresponds to an additive white Gaussian noise (AWGN) channel. A coding strategy is also developed that minimizes the average distortion when the channel state is unavailable at the transmitter. Experimental results are provided that demonstrate application of these combined source-channel coding strategies on video sequences     

Simple schemes for parallel acquisition of spreading sequences inDS/SS systems

Suboptimal parallel schemes for the acquisition of spreading sequences in chip-asynchronous spread-spectrum systems are considered. These acquisition schemes estimate the unknown delay of the received signal with respect to a locally generated spreading code. Two schemes are presented which are considerably easier to implement than the optimal estimator. An analytical expression is given for the error probability of the simpler of the two schemes, and it is shown that the average error probability of this scheme decreases exponentially with the signal-to-noise ratio. Numerical results show that the performance of both suboptimal estimators is comparable to that of the optimal estimator