Dynamic evolution of the genetic search region through fuzzy coding

A technique for automatic exploration of the genetic search region through fuzzy coding (Sharma and Irwin, 2003) has been proposed. Fuzzy coding (FC) provides the value of a variable on the basis of the optimum number of selected fuzzy sets and their effectiveness in terms of degree-of-membership. It is an indirect encoding method and has been shown to perform better than other conventional binary, Gray and floating-point encoding methods. However, the static range of the membership functions is a major problem in fuzzy coding, resulting in longer times to arrive at an optimum solution in large or complicated search spaces. This paper proposes a new algorithm, called fuzzy coding with a dynamic range (FCDR), which dynamically allocates the range of the variables to evolve an effective search region, thereby achieving faster convergence. Results are presented for two benchmark optimisation problems, and also for a case study involving neural identification of a highly non-linear pH neutralisation process from experimental data. It is shown that dynamic exploration of the genetic search region is effective for parameter optimisation in problems where the search space is complicated.

Short distance phase shifts revisited: tracking clock-shifted homing pigeons (Rock Dove Columba livia) close to the loft

Clock-shifted homing pigeons (Rock Dove Columba livia) were tracked from familiar release sites using a direction recorder. At relatively short distances from the home loft (

Distance limits to intermediate- and high-velocity clouds

We present optical spectra of 403 stars and quasi-stellar objects in order to obtain distance limits towards intermediate- and high-velocity clouds (IHVCs), including new Fibre-fed Extended Range Optical Spectrograph (FEROS) observations plus archival ELODIE, FEROS, High Resolution Echelle Spectrometer (HIRES) and Ultraviolet and Visual Echelle Spectrograph (UVES) data. The non-detection of Ca II K interstellar (IS) absorption at a velocity of −130 to −60 km s−1 towards HDE 248894 (d ∼ 3 kpc) and HDE 256725 (d ∼ 8 kpc) in data at signal-to-noise ratio (S/N) > 450 provides a new firm lower distance limit of 8 kpc for the anti-centre shell HVC. Similarly, the non-detection of Ca II K IS absorption towards HD 86248 at S/N ∼ 500 places a lower distance limit of 7.6 kpc for Complex EP, unsurprising since this feature is probably related to the Magellanic System. The lack of detection of Na I D at S/N = 35 towards Mrk 595 puts an improved upper limit for the Na I column density of log (NNaD <) 10.95 cm−2 towards this part of the Cohen Stream where Ca II was detected by Wakker et al. Absorption at ∼ −40 km s−1 is detected in Na I D towards the Galactic star PG 0039+049 at S/N = 75, placing a firm upper distance limit of 1 kpc for the intermediate-velocity cloud south (IVS), where a tentative detection had previously been obtained by Centurion et al. Ca ´ II K and Na I D absorption is detected at −53 km s−1 towards HD 93521, which confirms the upper distance limit of 2.4 kpc for part of the IV arch complex obtained using the International Ultraviolet Explorer (IUE) data by Danly. Towards HD 216411 in Complex H a non-detection in Na D towards gas with log(NH I) = 20.69 cm−2 puts a lower distance limit of 6.6 kpc towards this HVC complex. Additionally, Na I D absorption is detected at −43.7 km s−1 in the star HD 218915 at a distance of 5.0 kpc in gas in the same region of the sky as Complex H. Finally, the Na I/Ca II and Ca II/H I ratios of the current sample are found to lie in the range observed for previous studies of IHVCs.

Analysis of pharmacists attitudes toward a distance learning initiative on health screening

A questionnaire was developed to investigate pharmacists' attitudes to distance learning (DL) as a vehicle for continuing education (CE). It was included in each of a two part DL course on Health Screening. Part One was mailed to all community pharmacists in England (16,400) and returns were received from 1487. The questionnaire in Part Two was returned by 436 pharmacists. Attitude statements were scored using a five-point Likert scale. The mean response to all attitude statements was positive. Participants were significantly more satisfied than non-participants with DL in general and the DL course studied (P less than or equal to 0.05). Over 80 percent of respondents completing the course found DL to be enjoyable and more suitable than other CE methods. More females and less males than expected (based on registration statistics) requested (P less than or equal to 0.001) and completed the course (P less than or equal to 0.001). Pharmacists of all ages participated, although those recently qualified showed greater interest.

Telephone survey evaluation of the educational impact of a distance learning course

The educational impact of a distance learning (DL) course entitled ''Health Screening for Health Promotion, was investigated using a telephone questionnaire survey. An introduction to the DL course was distributed to all community pharmacists in England (16,400); the main body of the course, on which pharmacists were examined, was distributed free of charge to all pharmacists who requested it (1,485). Pharmacists participating in the survey (868) were organized by random selection into groups and stratified according to age, sex and postcode. A matched control group was randomly drawn from those pharmacists who had not participated in the course. The DL course improved pharmacists' knowledge about health screening/health promotion issues (e.g., mean score of 66 percent achieved by a group who had completed the course; 51 percent achieved by the control group; P<0.001). Factors influencing score achieved included sex and year of registration. Males performed better than females (P<0.008) while performance decreased with number of years on the register (P<0.001).

The chemical composition towards the galactic anti-centre .2. Differential abundance analyses and distance determinations

In a previous paper we have published observational data for 6 early B-type stars having, galactocentric distances of between 10 and 18 kpc. Using LTE line-blanketed model at mosphere techniques we derived their atmospheric parameters, finding that all our targets had similar effective temperatures and surface gravities. In the following study we additionally include two stars which have been presented previously (Rolleston et al. 1993) and found also to have compatible atmospheric parameters to the original programme stars. The homogeneity of this sample allows quantitative line-by-line differential abundance analyses to be carried out which should reliably detect variations in the chemical compositions of the stellar photospheres. We present differential abundances for eight stars, in either young open clusters or the field, with respect to an arbitrarily chosen standard which shows a normal abundance pattern. Our method of calculating distances from the derived atmospheric parameters means that the relative distance scale should be accurate.

Improved structure optimization for fuzzy-neural networks

Fuzzy-neural-network-based inference systems are well-known universal approximators which can produce linguistically interpretable results. Unfortunately, their dimensionality can be extremely high due to an excessive number of inputs and rules, which raises the need for overall structure optimization. In the literature, various input selection methods are available, but they are applied separately from rule selection, often without considering the fuzzy structure. This paper proposes an integrated framework to optimize the number of inputs and the number of rules simultaneously. First, a method is developed to select the most significant rules, along with a refinement stage to remove unnecessary correlations. An improved information criterion is then proposed to find an appropriate number of inputs and rules to include in the model, leading to a balanced tradeoff between interpretability and accuracy. Simulation results confirm the efficacy of the proposed method.

A New Gradient Descent Approach for Local Learning of Fuzzy Neural Models

The majority of reported learning methods for Takagi-Sugeno-Kang fuzzy neural models to date mainly focus on the improvement of their accuracy. However, one of the key design requirements in building an interpretable fuzzy model is that each obtained rule consequent must match well with the system local behaviour when all the rules are aggregated to produce the overall system output. This is one of the distinctive characteristics from black-box models such as neural networks. Therefore, how to find a desirable set of fuzzy partitions and, hence, to identify the corresponding consequent models which can be directly explained in terms of system behaviour presents a critical step in fuzzy neural modelling. In this paper, a new learning approach considering both nonlinear parameters in the rule premises and linear parameters in the rule consequents is proposed. Unlike the conventional two-stage optimization procedure widely practised in the field where the two sets of parameters are optimized separately, the consequent parameters are transformed into a dependent set on the premise parameters, thereby enabling the introduction of a new integrated gradient descent learning approach. A new Jacobian matrix is thus proposed and efficiently computed to achieve a more accurate approximation of the cost function by using the second-order Levenberg-Marquardt optimization method. Several other interpretability issues about the fuzzy neural model are also discussed and integrated into this new learning approach. Numerical examples are presented to illustrate the resultant structure of the fuzzy neural models and the effectiveness of the proposed new algorithm, and compared with the results from some well-known methods.