Weibull model selection for reliability modelling

A large number of models have been derived from the two-parameter Weibull distribution and are referred to as Weibull models. They exhibit a wide range of shapes for the density and hazard functions, which makes them suitable for modelling complex failure data sets. The WPP and IWPP plot allows one to determine in a systematic manner if one or more of these models are suitable for modelling a given data set. This paper deals with this topic.

Role of chemical cues from cotton in mediating host selection and oviposition behaviour in Helicoverpa armigera (Hubner) (Lepidoptera : Noctuidae)

We investigated the role of chemoreception in the host selection and oviposition behaviour of Helicoverpa armigera in the laboratory using five cotton genotypes and synthetic volatile terpenes. Female moths oviposited on substrates treated with methanol, ethanol, acetone and pentane extracts of leaves, squares and flowers of the cotton genotypes. Phytochemicals soluble in pentane were the most efficient in eliciting oviposition behaviour. In a two-way bioassay, pentane extracts of leaves or squares of a Multiple Host-plant Resistance genotype (MHR11), Deltapine commercial (DP90), and Smith Red Leaf (SRL) received significantly more eggs than solvent-treated controls. Extracts of squares of the native genotype Gossypium nelsonii did not receive more eggs. Females preferred DP90 and MHR11 to SRL and G. nelsonii. Female moths also laid more eggs on pentane extracts of MHR11 flowers than MHR11 leaves from preflowering, early flowering and peak-flowering plants. In a flight chamber, female moths used olfactory cues at short range to mediate oviposition and discrimination between host plants. Egg-laying, mated females were attracted at a distance (1.5 m) to volatile compounds released by whole plants and odours emanating from filter papers treated with synthetic volatile terpenes. Individually, the terpenes did not stimulate any significant oviposition response. However, there was a significant oviposition response to a mixture of equal volumes of the terpenes (trans-beta-caryophyllene, alpha-pinene, beta-pinene, myrcene, beta-bisabolol, and alpha-humulene). Conversely, antennectomised (moths with transected antennae), egg-laying, mated females did not stimulate any significant oviposition response. The significance of these findings in relation to H. armigera hostplant selection are discussed.

Minimum-order stable recursive filter design via the genetic algorithm approach

In this paper, the minimum-order stable recursive filter design problem is proposed and investigated. This problem is playing an important role in pipeline implementation sin signal processing. Here, the existence of a high-order stable recursive filter is proved theoretically, in which the upper bound for the highest order of stable filters is given. Then the minimum-order stable linear predictor is obtained via solving an optimization problem. In this paper, the popular genetic algorithm approach is adopted since it is a heuristic probabilistic optimization technique and has been widely used in engineering designs. Finally, an illustrative example is sued to show the effectiveness of the proposed algorithm.

Measuring macromolecular diffusion using heteronuclear multiple-quantum pulsed-field-gradient NMR

We have previously shown that H-1 pulsed-field-gradient (PFG) NMR spectroscopy provides a facile method for monitoring protein self-association and can be used, albeit with some caveats, to measure the apparent molecular mass of the diffusant [Dingley et al. (1995) J. Biomol. NMR, 6, 321-328]. In this paper we show that, for N-15-labelled proteins, selection of H-1-N-15 multiple-quantum (MQ) coherences in PFG diffusion experiments provides several advantages over monitoring H-1 single-quantum (SQ) magnetization. First, the use of a gradient-selected MQ filter provides a convenient means of suppressing resonances from both the solvent and unlabelled solutes. Second, H-1-N-15 zero-quantum coherence dephases more rapidly than H-1 SQ coherence under the influence of a PFG. This allows the diffusion coefficients of larger proteins to be measured more readily. Alternatively, the gradient length and/or the diffusion delay may be decreased, thereby reducing signal losses from relaxation. In order to extend the size of macromolecules to which these experiments can be applied, we have developed a new MQ PFG diffusion experiment in which the magnetization is stored as longitudinal two-spin order for most of the diffusion period, thus minimizing sensitivity losses due to transverse relaxation and J-coupling evolution.

The application of adaptive partitioned random search in feature selection problem

Feature selection is one of important and frequently used techniques in data preprocessing. It can improve the efficiency and the effectiveness of data mining by reducing the dimensions of feature space and removing the irrelevant and redundant information. Feature selection can be viewed as a global optimization problem of finding a minimum set of M relevant features that describes the dataset as well as the original N attributes. In this paper, we apply the adaptive partitioned random search strategy into our feature selection algorithm. Under this search strategy, the partition structure and evaluation function is proposed for feature selection problem. This algorithm ensures the global optimal solution in theory and avoids complete randomness in search direction. The good property of our algorithm is shown through the theoretical analysis.

International market selection: Developing a model from Australian case studies

This paper develops a theory that firms seek out new country markets on the basis of expected commercial returns. These expectations depend on judgements about the attractiveness of the market and the firm's competitive position in it, which in turn are influenced by informants. It is the number and strengths of these informants that will underlie the probability of a country being identified and assessed as a new market by any firm.

Host selection in phytophagous insects: a new explanation for learning in adults

Insect learning can change the preferences an egg laying female displays towards different host plant species. Current hypotheses propose that learning may be advantageous in adult host selection behaviour through improved recognition, accuracy or selectivity in foraging. In this paper, we present a hypothesis for when learning can be advantageous without such improvements in adult host foraging. Specifically, that learning can be an advantageous strategy for egg laying females when larvae must feed on more than one plant in order to complete development, if the fitness of larvae is reduced when they switch to a different host species. Here, larvae benefit from developing on the most abundant host species, which is the most likely choice of host for an adult insect which increases its preference for a host species through learning. The hypothesis is formalised with a mathematical model and we provide evidence from studies on the behavioural ecology, of a number of insect species which demonstrate that the assumptions of this hypothesis may frequently be fulfilled in nature. We discuss how multiple mechanisms may convey advantages in insect learning and that benefits to larval development, which have so far been overlooked, should be considered in explanations for the widespread occurrence of learning.

Materialized view selection under the maintenance time constraint

A data warehouse is a data repository which collects and maintains a large amount of data from multiple distributed, autonomous and possibly heterogeneous data sources. Often the data is stored in the form of materialized views in order to provide fast access to the integrated data. One of the most important decisions in designing a data warehouse is the selection of views for materialization. The objective is to select an appropriate set of views that minimizes the total query response time with the constraint that the total maintenance time for these materialized views is within a given bound. This view selection problem is totally different from the view selection problem under the disk space constraint. In this paper the view selection problem under the maintenance time constraint is investigated. Two efficient, heuristic algorithms for the problem are proposed. The key to devising the proposed algorithms is to define good heuristic functions and to reduce the problem to some well-solved optimization problems. As a result, an approximate solution of the known optimization problem will give a feasible solution of the original problem. (C) 2001 Elsevier Science B.V. All rights reserved.

Application of spatial analysis techniques to adjust for fertility trends and identify interplot competition in early stage sugarcane selection trials

Most sugarcane breeding programs in Australia use large unreplicated trials to evaluate clones in the early stages of selection. Commercial varieties that are replicated provide a method of local control of soil fertility. Although such methods may be useful in detecting broad trends in the field, variation often occurs on a much smaller scale. Methods such as spatial analysis adjust a plot for variability by using information from immediate neighbours. These techniques are routinely used to analyse cereal data in Australia and have resulted in increased accuracy and precision in the estimates of variety effects. In this paper, spatial analyses in which the variability is decomposed into local, natural, and extraneous components are applied to early selection trials in sugarcane. Interplot competition in cane yield and trend in sugar content were substantial in many of the trials and there were often large differences in the selections between the spatial and current method used by the Bureau of Sugar Experiment Stations. A joint modelling approach for tonnes sugar per hectare in response to fertility trends and interplot competition is recommended.

On continuous selection problems for multivalued mappings with the local intersection property in hyperconvex metric spaces

In the paper we present two continuous selection theorems in hyperconvex metric spaces and apply these to study xed point and coincidence point problems as well as variational inequality problems in hyperconvex metric spaces.

Adaptive stepsize based on control theory for stochastic differential equations

The numerical solution of stochastic differential equations (SDEs) has been focussed recently on the development of numerical methods with good stability and order properties. These numerical implementations have been made with fixed stepsize, but there are many situations when a fixed stepsize is not appropriate. In the numerical solution of ordinary differential equations, much work has been carried out on developing robust implementation techniques using variable stepsize. It has been necessary, in the deterministic case, to consider the best choice for an initial stepsize, as well as developing effective strategies for stepsize control-the same, of course, must be carried out in the stochastic case. In this paper, proportional integral (PI) control is applied to a variable stepsize implementation of an embedded pair of stochastic Runge-Kutta methods used to obtain numerical solutions of nonstiff SDEs. For stiff SDEs, the embedded pair of the balanced Milstein and balanced implicit method is implemented in variable stepsize mode using a predictive controller for the stepsize change. The extension of these stepsize controllers from a digital filter theory point of view via PI with derivative (PID) control will also be implemented. The implementations show the improvement in efficiency that can be attained when using these control theory approaches compared with the regular stepsize change strategy. (C) 2004 Elsevier B.V. All rights reserved.

Characterizing the physical and chemical properties of a vermicompost filter bed

Vermicompost filtration is a new on-site waste treatment system. Consequently, little is known about the filter medium properties. The aim of this preliminary study was to quantify physical and compositional properties of vermicompost filter beds that had been used to treat domestic solid organic waste and wastewater. This paper presents the trials performed on pilot-scale reactors filled with vermicompost from a full-scale vermicompost filtration system. Household solid organic waste and raw wastewater at the rate of 130 L/m(2)/d was applied to the reactor bed surface over a four-month period. It was found that fresh casts laid on the bed surface had a BOD of 1290 mg/g VS while casts buried to a depth of 10 cm had a BOD of 605 mg/g VS. Below this depth there was little further biodegradation of earthworm casts despite cast ages of up to five years. Solid material in the reactor accounted for only 7-10% of the reactor volume. The total voidage comprised of large free-draining pores, which accounted for 15-20% of the reactor volume and 60-70% micropores, able to hold up water against gravity. It was shown that water could flow through the medium micropores and macropores following a wastewater application. The wastewater flow characteristics were modeled by a two-region model based on the Richards Equation, an equation used to describe porous spatially heterogeneous materials.

Forecasting stock returns using model-selection criteria

This paper examines the economic significance of return predictability in Australian equities. In light of considerable model uncertainty, formal model-selection criteria are used to choose a specification for the predictive model. A portfolio-switching strategy is implemented according to model predictions. Relative to a buy-and-hold market investment, the returns to the portfolio-switching strategy are impressive under several model-selection criteria, even after accounting for transaction costs. However, as these findings are not robust across other model-selection criteria examined, it is difficult to conclude that the degree of return predictability is economically significant.

Manufacture of high pressure die-cast radio frequency filter bodies

The manufacture of a radio frequency filter box using high pressure die casting (HPDC) is compared to the traditional high speed machining route. This paper describes an industrial exercise that concluded HPDC to be an economical and appropriate method to produce larger volumes of thin-walled telecommunications components. Modifications to the component design were made to make the component suitable for the HPDC process. Development of the die design through simulation modelling is described. The wrought alloy was replaced by near-eutectic Al-Si die casting alloy that was found to give better temperature stability performance. Apart from the economic benefits, HPDC was found to give lower filter efficiency losses through better surface finish. The effects of HPDC process variables, such as intensification pressure and injection piston velocity, on component quality, particularly porosity levels, were investigated. The pressure was analysed in terms of HPDC machine set pressure and the pressure measured in the die cavity by pressure sensors. Porosity was found to decrease with increased pressure and slightly increase with higher casting velocities.