Designing for parallel fuzzy computing

As the number of fuzzy logic applications increases, demand for faster architectures will grow. Our design for a VLSI fuzzy processor uses fuzzy inference techniques that optimize processing time. Preprocessing that reduces the number of rules to be processed, parallel computation of active rule degrees of activation, and scalability are major features of this architecture. The journal issue contains a concise summary of this article. The complete article is linked to Micro's home page on the World Wide Web (http://www.computer.org/pubs/micro/micro.htm)     

An evolutionary management scheme in high-performance packet switches

This paper deals with a novel buffer management scheme based on the combination of evolutionary computing and fuzzy logic for shared-memory packet switches. The philosophy behind it is adaptation of the threshold for each logical output queue to the real traffic conditions by means of a system of fuzzy inferences. The optimal fuzzy system is achieved using a systematic methodology based on Genetic Algorithms for membership-function selecting and tuning. This methodology approach allows the fuzzy system parameters to be automatically derived when the switch parameters vary, offering a high degree of scalability to the fuzzy control system. Its performance is close to that of the push-out mechanism, which can be considered ideal from a performance viewpoint, and at any rate much better than that of threshold schemes based on conventional logic. In addition, the fuzzy threshold scheme is simple to implement, unlike the push-out mechanism which is not practically feasible in high-speed switches due to the amount of time required for computation, and above all inexpensive when implemented using current standard technology.     

Hybrid photocatalytic membranes embedding decatungstate for heterogeneous photooxygenation

The incorporation of decatungstate in polymeric membranes provides new heterogeneous photocatalysts for the oxidation of organic substrates under oxygen atmosphere at 25 °C. Photocatalytic membranes have been prepared yielding polymeric films with a high thermal, chemical and mechanical stability (PVDF, PDMS, Hyflon). Surface spectroscopy techniques including transmittance and reflectance UV-Vis and FT-IR have been used to assess the photocatalyst integrity within the polymeric support. Catalyst screening has been performed under both homogeneous and heterogeneous photooxygenation conditions. The photocatalyst activity has been evaluated in terms of the substrate conversion, turnover numbers, and recycling experiments. A membrane induced selectivity behavior has been evidenced by comparison with homogeneous oxidations.     

In Vitro Characterization of Human CD24hiCD38hi Regulatory B Cells Shows CD9 Is Not a Stable Breg Cell Marker

Regulatory B (Breg) cells are endowed with immune suppressive functions. Various human and murine Breg subtypes have been reported. While interleukin (IL)-10 intracellular staining remains the most reliable way to identify Breg cells, this technique hinders further essential functional studies. Recent findings suggest that CD9 is an effective surface marker of murine IL-10 competent Breg cells. However, the stability of CD9 and its relevance as a unique marker for human Breg cells, which have been widely characterized as CD24^hiCD38^hi, have not been investigated. Here, we demonstrate that CD9 expression is sensitive to in vitro B cell stimulations. CD9 expression could either be re-expressed or downregulated in purified CD9-negative B cells and CD9-positive B cells, respectively. We found no significant differences in the Breg differentiation capacity of the CD9-negative and CD9-positive B cells. Furthermore, CD9-positive B cells co-express CD40 and CD86, suggesting their nature as B cell activation or co-stimulatory molecules, rather than regulatory ones. Therefore, we report the relatively unstable CD9 as a distinct surface molecule, indicating the need for further research for a more reliable marker to purify human Breg cells.     

Time series clustering and classification by the autoregressive metric

The statistical properties of the autoregressive (AR) distance between ARIMA processes are investigated. In particular, the asymptotic distribution of the squared AR distance and an approximation which is computationally efficient are derived. Moreover, the problem of time series clustering and classification is discussed and the performance of the AR distance is illustrated by means of some empirical applications.     

Optimal sampling for the estimation of dispersion parameters in soil columns using an Iterative Genetic Algorithm

In groundwater modelling, an appropriate soil characterization is strongly recommended to evaluate both the fate and transport of solutes and the performance of groundwater remediation criterion, though parameter estimation techniques are often blocked by several inherent difficulties (i.e. ill-posedness and insufficient quantity and quality of observation data). In this paper, an iterative decision model is built and tested in order to locate the position of a fixed number of sample points in a soil column experiment to obtain optimal parameter estimation (OPE), minimizing the parametric uncertainty and the overall cost of the experimental campaign. Starting from an initial guess of chosen points (given by a fraction of the total disposable ones), an Iterative Genetic Algorithm (IGA) is capable of finding the best points able to minimize a first-order approximation of the parameter covariance matrix. The parameter estimates are updated under a Bayesian scheme, using exclusively the observations collected after the earlier run of minimization, and the iterative process stops when the imposed convergence criterion based on the parameter values is reached. An important contribution of this work is the development of an effective direct search algorithm (IGA) for solving the sampling network optimization problem at a laboratory scale.     

Performance evaluation of efficient multi-objective evolutionary algorithms for design space exploration of embedded computer systems

Multi-objective evolutionary algorithms (MOEAs) have received increasing interest in industry because they have proved to be powerful optimizers. Despite the great success achieved, however, MOEAs have also encountered many challenges in real-world applications. One of the main difficulties in applying MOEAs is the large number of fitness evaluations (objective calculations) that are often needed before an acceptable solution can be found. There are, in fact, several industrial situations in which fitness evaluations are computationally expensive and the time available is very short. In these applications efficient strategies to approximate the fitness function have to be adopted, looking for a trade-off between optimization performance and efficiency. This is the case in designing a complex embedded system, where it is necessary to define an optimal architecture in relation to certain performance indexes while respecting strict time-to-market constraints. This activity, known as design space exploration (DSE), is still a great challenge for the EDA (electronic design automation) community. One of the most important bottlenecks in the overall design flow of an embedded system is due to simulation. Simulation occurs at every phase of the design flow and is used to evaluate a system which is a candidate for implementation. In this paper we focus on system level design, proposing an extensive comparison of the state-of-the-art of MOEA approaches with an approach based on fuzzy approximation to speed up the evaluation of a candidate system configuration. The comparison is performed in a real case study: optimization of the performance and power dissipation of embedded architectures based on a Very Long Instruction Word (VLIW) microprocessor in a mobile multimedia application domain. The results of the comparison demonstrate that the fuzzy approach outperforms in terms of both performance and efficiency the state of the art in MOEA strategies applied to DSE of a parameterized embedded system.     

An efficient fuzzy system for traffic management in high-speed packet-switched networks

 In this paper we present a novel buffer management scheme based on fuzzy logic. We deal with the problem of managing traffic flows with different priorities within the same buffer. The aim is to guarantee the QoS of high-priority traffic, and at the same time exploit unused buffer resources to accommodate best-effort traffic in order to maximize the total throughput. The scheme we propose can be applied both to ATM and IP networks. The performance evaluation of the fuzzy priority control scheme shows that it outperforms any static threshold mechanism and, as far as the total throughput is concerned, it is very close to that of the push out mechanism considered in literature as an ideal mechanism. Finally, we address some implementation issues of the control system and propose the design of a new cost-effective VLSI fuzzy processor.     

A high-voltage cardiac stimulator for field shocks of a whole heart in a bath

Defibrillators are a critical tool for treating heart disease; however, the mechanisms by which they halt fibrillation are still not fully understood and are the subject of ongoing research. Clinical defibrillators do not provide the precise control of shock timing, duration, and voltage or other features needed for detailed scientific inquiry, and there are few, if any, commercially available units designed for research applications. For this reason, we have developed a high-voltage, programmable, capacitive-discharge stimulator optimized to deliver defibrillation shocks with precise timing and voltage control to an isolated animal heart, either in air or in a bath. This stimulator is capable of delivering voltages of up to 500 V and energies of nearly 100 J with timing accuracy of a few microseconds and with rise and fall times of 5 micros or less and is controlled only by two external timing pulses and a control computer that sets the stimulation parameters via a LABVIEW interface. Most importantly, the stimulator has circuits to protect the high-voltage circuitry and the operator from programming and input-output errors. This device has been tested and used successfully in field shock experiments on rabbit hearts as well as other protocols requiring high voltage.