Recursive fuzzy c-means clustering for recursive fuzzy identification of time-varying processes

In this paper we propose a new approach to on-line Takagi-Sugeno fuzzy model identification. It combines a recursive fuzzy c-means algorithm and recursive least squares. First the method is derived and than it is tested and compared on a benchmark problem of the Mackey-Glass time series with other established on-line identification methods. We showed that the developed algorithm gives a comparable degree of accuracy to other algorithms. The proposed algorithm can be used in a number of fields, including adaptive nonlinear control, model predictive control, fault detection, diagnostics and robotics. An example of identification based on a real data of the waste-water treatment process is also presented.     

Effect of plasma treatment on the release kinetics of a chemotherapy drug from biodegradable polyester films and polyester urethane films

Investigation was made into the effect of plasma treatment on the release kinetics of the drug Temozolomide (TMZ) from thin, biodegradable polyester films, comprising polylactic acid (PLA) and polyester urethane. The authors utilized two systems to achieve this, the first being diffuse coplanar surface barrier discharge, applying air as the gaseous medium, while the other involved capacitively coupled radio frequency discharge plasma under an argon atmosphere with hexamethyldisiloxane. Results showed that both forms of plasma treatment positively reduced the undesirable burst effect and benefited the release rate of TMZ. The hydrolytic degradability of the materials was slightly enhanced following hydrophilization, whereas the same diminished after hydrophobization had taken place. This was especially true for PLA due to modification of its wettability.     

Superhydrophobic Polyester/Cotton Fabrics Modified by Barrier Discharge Plasma and Organosilanes

In this paper, diffuse coplanar surface barrier discharge plasma at atmospheric pressure has been used for surface modification of polyester/cotton (PESc) fabric, which was subsequently modified by sol–gel process using suitable organofunctional silanes to enhance its hydrophobicity. Modified PESc fabric surfaces were conditioned during the gelling process to obtain the permanent hydrophobicity. The contact angle of water before washing of plasma and sol–gel pretreated PESc fabric was found to be 154° and 151° after standardized washings. It was also demonstrated that the process is applicable at the industrial scale.     

Commodification of accelerations for the Karp and Miller Construction

Karp and Miller’s algorithm is based on an exploration of the reachability tree of a Petri net where, the sequences of transitions with positive incidence are accelerated. The tree nodes of Karp and Miller are labeled with ω-markings representing (potentially infinite) coverability sets. This set of ω-markings allows us to decide several properties of the Petri net, such as whether a marking is coverable or whether the reachability set is finite. The edges of the Karp and Miller tree are labeled by transitions but the associated semantic is unclear which yields to a complex proof of the algorithm correctness. In this work we introduce three concepts: abstraction, acceleration and exploration sequence. In particular, we generalize the definition of transitions to ω-transitions in order to represent accelerations by such transitions. The notion of abstraction makes it possible to greatly simplify the proof of the correctness. On the other hand, for an additional cost in memory, which we theoretically evaluated, we propose an “accelerated” variant of the Karp and Miller algorithm with an expected gain in execution time. Based on a similar idea we have accelerated (and made complete) the minimal coverability graph construction, implemented it in a tool and performed numerous promising benchmarks issued from realistic case studies and from a random generator of Petri nets.

     

Are genetic algorithms useful for the parameter estimation of FM signals?

The estimation of polynomial-phase signals (PPSs) is a multiparameter problem, and the maximum likelihood (ML) optimization functions have numerous local optima, making the application of gradient techniques impossible. The common solution to this problem is based on the phase differentiation (PD) techniques that reduce the number of dimensions but, at the same time, reduce the accuracy and generate additional difficulties such as spurious components and error propagation. Here we show that genetic algorithms (GAs) can serve as a powerful alternative to the PD techniques. We investigate the limits of accuracy of the ML technique, and of some alternatives such as the high-order cubic phase function (HO-CPF) and high-order Wigner distribution (HO-WD). The ML approach combined with the proposed GA setup is limited up to the fifth-order PPS, which is not sufficient in many applications. However, the HO-CPF and HO-WD techniques coupled with the GA are able to accurately estimate phase parameters up to the tenth-order PPS. They significantly improve the accuracy with respect to the high-order ambiguity function (HAF) and product HAF (PHAF) and, for higher-order PPSs, they are much simpler and more efficient than the integrated generalized ambiguity function (IGAF).     

WSNs clustering based on semantic neighborhood relationships

We propose a semantic clustering model based on a fuzzy inference system to find out the semantic neighborhood relationships in wireless sensor networks in order to both reduce energy consumption and improve the data accuracy. As a case study we describe a structural health monitoring application which was used to illustrate and assess the proposed model. We conduct experiments in order to evaluate the proposal in two different scenarios of damage with different data aggregation methods. We also compared our proposal, using the same data set, with a deterministic clustering method and with the LEACH algorithm. The results indicate that our approach is an energy-efficient clustering method for WSNs, outperforming both the deterministic clustering and LEACH algorithms in about 70% and 47% of energy savings respectively. The energy saving comes from the fact that we have a more efficient in-network data aggregation process since by exploiting the semantic relation between sensor nodes we can potentially aggregate more similar data and consequently, decrease the data redundancy (thus minimizing transmissions). Nodes that are semantically unrelated can operate in low-duty cycle, further reducing the energy consumption. Moreover, our proposal has the potential to improve the data accuracy provided for the application where accuracy is a QoS requirement in typical WSN applications.     

Geometric computations by broadcasting automata

In this paper we introduce and apply a novel approach for self-organisation, partitioning and pattern formation on the non-oriented grid environment. The method is based on the generation of nodal patterns in the environment via sequences of discrete waves. The power of the primitives is illustrated by giving solutions to two geometric problems using the broadcast automata model arranged in an integer grid (a square lattice) formation. In this model automata cannot directly observe their neighbours?? state and can only communicate with neighbouring automata through the non-oriented broadcast of messages from a finite alphabet. In particular we show linear time algorithms for the problem of finding the centre of a digital disk starting from any point on the border of the disc and the problem of electing a set of automata that form the inscribed square of such a digital disk. Possible generalizations and applications of techniques based on nodal patterns and the construction of different discrete wave interference pictures are discussed in the conclusion.     

Data acquisition system for dark matter detectors

Progress in Ge detector technology has resulted in ultralow backgrounds of less than 0.3 counts keV^–1 kg^–1 d^–1 at energies between 5 and 12 keV, and less than 1.0 counts kev^–1 kg^–1 d^–1 for energies between 3 and 5 keV. Coupled with good energy resolution, 0.4 keV FWHM at 10 keV, this allows searches for DM particles with m 8 GeV/c².Electromagnetic interference and acoustical pick-up are the main sources of background in the best Ge detectors. These problems are even more important in cryogenic WIMP detectors under development. A PC-based on line pulse shape analysis system is presented which permits rejection of about 95% percent of the EMI/ acoustical background. The hardware uses a low cost, commercially available digital storage oscilloscope. The software consists of about 20,000 lines of code in Pascal and assembly language. We tested this system using a low radioactive background Ge-system on the Earth's surface. For low energy events (27 keV photons) this system permits improvement in the background from 0.1 cpm to 2 cpd.     

Enhancing design-for-test for active analog filters by using CLP(ℜ)

We describe a computer-aided approach to automatic fault isolation in active analog filters which enhances the design-for-test (DFT) methodology proposed by Soma (1990). His primary concern was in increased controllability and observability while the fault isolation procedure was sketched only in general terms. We operationalize and extend the DFT methodology by using CLP() to model analog circuits and by a model-based diagnosis approach to implement a diagnostic algorithm. CLP() is a logic programming language which combines symbolic and numeric computation. The diagnostic algorithm uses different DFT test modes and results of voltage measurements for different frequencies and computes a set of suspected components. Ranking of suspected components is based on a measure of (normalized) standard deviations from predicted mean values of component parameters. The diagnosis is performed incrementally, in each step reducing the set of potential candidates for the detected fault. Case studies show encouraging results in isolation of soft faults of a given low-pass biquad filter.