A hierarchical system of learning automata that can learn die globally optimal path

Systems of learning automata have been studied by various researchers to evolve useful strategies for decision making under uncertainity. Considered in this paper are a class of hierarchical systems of learning automata where the system gets responses from its environment at each level of the hierarchy. A classification of such sequential learning tasks based on the complexity of the learning problem is presented. It is shown that none of the existing algorithms can perform in the most general type of hierarchical problem. An algorithm for learning the globally optimal path in this general setting is presented, and its convergence is established. This algorithm needs information transfer from the lower levels to the higher levels. Using the methodology of estimator algorithms, this model can be generalized to accommodate other kinds of hierarchical learning tasks.

Effect of phosphine dose on sorption in wheat

BACKGROUND: In spite of the extensive use of phosphine fumigation around the world to control insects in stored grain, and the knowledge that grain sorbs phosphine, the effect of concentration on sorption has not been quantified. A laboratory study was undertaken, therefore, to investigate the effect of phosphine dose on sorption in wheat. Wheat was added to glass flasks to achieve filling ratios of 0.25-0.95, and the flasks were sealed and injected with phosphine at 0.1-1.5 mg L-1 based on flask volume. Phosphine concentration was monitored for 8 days at 25°C and 55% RH. RESULTS: When sorption occurred, phosphine concentration declined with time and was approximately first order, i.e. the data fitted an exponential decay equation. Percentage sorption per day was directly proportional to filling ratio, and was negatively correlated with dose for any given filling ratio. Based on the results, a tenfold increase in dose would result in a halving of the sorption constant and the percentage daily loss. Wheat was less sorptive if it was fumigated for a second time. CONCLUSIONS: The results have implications for the use of phosphine for control of insects in stored wheat. This study shows that dose is a factor that must be considered when trying to understand the impact of sorption on phosphine concentration, and that there appears to be a limit to the capacity of wheat to sorb phosphine.

A near Optimal Cane Rail Scheduler under Limited and Unlimited Capacity Constraints

Australia is the world’s third largest exporter of raw sugar after Brazil and Thailand, with around $2.0 billion in export earnings. Transport systems play a vital role in the raw sugar production process by transporting the sugarcane crop between farms and mills. In 2013, 87 per cent of sugarcane was transported to mills by cane railway. The total cost of sugarcane transport operations is very high. Over 35% of the total cost of sugarcane production in Australia is incurred in cane transport. A cane railway network mainly involves single track sections and multiple track sections used as passing loops or sidings. The cane railway system performs two main tasks: delivering empty bins from the mill to the sidings for filling by harvesters; and collecting the full bins of cane from the sidings and transporting them to the mill. A typical locomotive run involves an empty train (locomotive and empty bins) departing from the mill, traversing some track sections and delivering bins at specified sidings. The locomotive then, returns to the mill, traversing the same track sections in reverse order, collecting full bins along the way. In practice, a single track section can be occupied by only one train at a time, while more than one train can use a passing loop (parallel sections) at a time. The sugarcane transport system is a complex system that includes a large number of variables and elements. These elements work together to achieve the main system objectives of satisfying both mill and harvester requirements and improving the efficiency of the system in terms of low overall costs. These costs include delay, congestion, operating and maintenance costs. An effective cane rail scheduler will assist the traffic officers at the mill to keep a continuous supply of empty bins to harvesters and full bins to the mill with a minimum cost. This paper addresses the cane rail scheduling problem under rail siding capacity constraints where limited and unlimited siding capacities were investigated with different numbers of trains and different train speeds. The total operating time as a function of the number of trains, train shifts and a limited number of cane bins have been calculated for the different siding capacity constraints. A mathematical programming approach has been used to develop a new scheduler for the cane rail transport system under limited and unlimited constraints. The new scheduler aims to reduce the total costs associated with the cane rail transport system that are a function of the number of bins and total operating costs. The proposed metaheuristic techniques have been used to find near optimal solutions of the cane rail scheduling problem and provide different possible solutions to avoid being stuck in local optima. A numerical investigation and sensitivity analysis study is presented to demonstrate that high quality solutions for large scale cane rail scheduling problems are obtainable in a reasonable time. Keywords: Cane railway, mathematical programming, capacity, metaheuristics

Deriving optimal competition in infrastructure procurement

Typically only a limited number of consortiums are able to competitively bid for Public Private Partnership (PPP) projects. Consequently, this may lead to oligopoly pricing constraints and ineffective competition, thus engendering ex ante market failure. In addressing this issue, this paper aims to determine the optimal number of bidders required to ensure a healthy level of competition is available to procure major infrastructure projects. The theories of Structure-Conduct-Performance (SCP) paradigm; Game Theory and Auction Theory and Transaction Cost Economics are reviewed and discussed and used to produce an optimal level of competition for major infrastructure procurement, that prevents market failure ex ante (lack of competition) and market failure ex post (due to asymmetric lock-in).

A high-density consensus map of barley linking DArT markers to SSR, RFLP and STS loci and agricultural traits

Background: Molecular marker technologies are undergoing a transition from largely serial assays measuring DNA fragment sizes to hybridization-based technologies with high multiplexing levels. Diversity Arrays Technology (DArT) is a hybridization-based technology that is increasingly being adopted by barley researchers. There is a need to integrate the information generated by DArT with previous data produced with gel-based marker technologies. The goal of this study was to build a high-density consensus linkage map from the combined datasets of ten populations, most of which were simultaneously typed with DArT and Simple Sequence Repeat (SSR), Restriction Enzyme Fragment Polymorphism (RFLP) and/or Sequence Tagged Site (STS) markers. Results: The consensus map, built using a combination of JoinMap 3.0 software and several purpose-built perl scripts, comprised 2,935 loci (2,085 DArT, 850 other loci) and spanned 1,161 cM. It contained a total of 1,629 'bins' (unique loci), with an average inter-bin distance of 0.7 ± 1.0 cM (median = 0.3 cM). More than 98% of the map could be covered with a single DArT assay. The arrangement of loci was very similar to, and almost as optimal as, the arrangement of loci in component maps built for individual populations. The locus order of a synthetic map derived from merging the component maps without considering the segregation data was only slightly inferior. The distribution of loci along chromosomes indicated centromeric suppression of recombination in all chromosomes except 5H. DArT markers appeared to have a moderate tendency toward hypomethylated, gene-rich regions in distal chromosome areas. On the average, 14 ± 9 DArT loci were identified within 5 cM on either side of SSR, RFLP or STS loci previously identified as linked to agricultural traits. Conclusion: Our barley consensus map provides a framework for transferring genetic information between different marker systems and for deploying DArT markers in molecular breeding schemes. The study also highlights the need for improved software for building consensus maps from high-density segregation data of multiple populations.

Optimal management of agricultural systems

To remain competitive, many agricultural systems are now being run along business lines. Systems methodologies are being incorporated, and here evolutionary computation is a valuable tool for identifying more profitable or sustainable solutions. However, agricultural models typically pose some of the more challenging problems for optimisation. This chapter outlines these problems, and then presents a series of three case studies demonstrating how they can be overcome in practice. Firstly, increasingly complex models of Australian livestock enterprises show that evolutionary computation is the only viable optimisation method for these large and difficult problems. On-going research is taking a notably efficient and robust variant, differential evolution, out into real-world systems. Next, models of cropping systems in Australia demonstrate the challenge of dealing with competing objectives, namely maximising farm profit whilst minimising resource degradation. Pareto methods are used to illustrate this trade-off, and these results have proved to be most useful for farm managers in this industry. Finally, land-use planning in the Netherlands demonstrates the size and spatial complexity of real-world problems. Here, GIS-based optimisation techniques are integrated with Pareto methods, producing better solutions which were acceptable to the competing organizations. These three studies all show that evolutionary computation remains the only feasible method for the optimisation of large, complex agricultural problems. An extra benefit is that the resultant population of candidate solutions illustrates trade-offs, and this leads to more informed discussions and better education of the industry decision-makers.

Flux balance analysis of biological systems: applications and challenges

Systems level modelling and simulations of biological processes are proving to be invaluable in obtaining a quantitative and dynamic perspective of various aspects of cellular function. In particular, constraint-based analyses of metabolic networks have gained considerable popularity for simulating cellular metabolism, of which flux balance analysis (FBA), is most widely used. Unlike mechanistic simulations that depend on accurate kinetic data, which are scarcely available, FBA is based on the principle of conservation of mass in a network, which utilizes the stoichiometric matrix and a biologically relevant objective function to identify optimal reaction flux distributions. FBA has been used to analyse genome-scale reconstructions of several organisms; it has also been used to analyse the effect of perturbations, such as gene deletions or drug inhibitions in silico. This article reviews the usefulness of FBA as a tool for gaining biological insights, advances in methodology enabling integration of regulatory information and thermodynamic constraints, and finally addresses the challenges that lie ahead. Various use scenarios and biological insights obtained from FBA, and applications in fields such metabolic engineering and drug target identification, are also discussed. Genome-scale constraint-based models have an immense potential for building and testing hypotheses, as well as to guide experimentation.

Optimal Parameter Trajectory Estimation in Parameterized SDEs: An Algorithmic Procedure

We consider the problem of estimating the optimal parameter trajectory over a finite time interval in a parameterized stochastic differential equation (SDE), and propose a simulation-based algorithm for this purpose. Towards this end, we consider a discretization of the SDE over finite time instants and reformulate the problem as one of finding an optimal parameter at each of these instants. A stochastic approximation algorithm based on the smoothed functional technique is adapted to this setting for finding the optimal parameter trajectory. A proof of convergence of the algorithm is presented and results of numerical experiments over two different settings are shown. The algorithm is seen to exhibit good performance. We also present extensions of our framework to the case of finding optimal parameterized feedback policies for controlled SDE and present numerical results in this scenario as well.

Bi-criteria single machine scheduling problem with a learning effect: Aneja-Nair method to obtain the set of optimal sequences

In this paper, we consider the bi-criteria single machine scheduling problem of n jobs with a learning effect. The two objectives considered are the total completion time (TC) and total absolute differences in completion times (TADC). The objective is to find a sequence that performs well with respect to both the objectives: the total completion time and the total absolute differences in completion times. In an earlier study, a method of solving bi-criteria transportation problem is presented. In this paper, we use the methodology of solvin bi-criteria transportation problem, to our bi-criteria single machine scheduling problem with a learning effect, and obtain the set of optimal sequences,. Numerical examples are presented for illustrating the applicability and ease of understanding.

Comment: Eigenvalue sensitivity method for optimal stabilisation of linear systems

In a letter RauA proposed a new method for designing statefeedback controllers using eigenvalue sensitivity matrices. However, there appears to be a conceptual mistake in the procedure, or else it is unduly restricted in its applicability. In particular the equation — BR~lBTK = A/.I, in which K is a positive-definite symmetric matrix.

D-MG Tradeoff and Optimal Codes for a Class of AF and DF Cooperative Communication Protocols

Cooperative relay communication in a fading channel environment under the orthogonal amplify-and-forward (OAF), nonorthogonal and orthogonal selection decode-and-forward (NSDF and OSDF) protocols is considered here. The diversity-multiplexing gain tradeoff (DMT) of the three protocols is determined and DMT-optimal distributed space-time (ST) code constructions are provided. The codes constructed are sphere decodable and in some instances incur minimum possible delay. Included in our results is the perhaps surprising finding that the orthogonal and the nonorthogonal amplify-and-forward (NAF) protocols have identical DMT when the time durations of the broadcast and cooperative phases are optimally chosen to suit the respective protocol. Moreover our code construction for the OAF protocol incurs less delay. Two variants of the NSDF protocol are considered: fixed-NSDF and variable-NSDF protocol. In the variable-NSDF protocol, the fraction of time occupied by the broadcast phase is allowed to vary with multiplexing gain. The variable-NSDF protocol is shown to improve on the DMT of the best previously known static protocol when the number of relays is greater than two. Also included is a DMT optimal code construction for the NAF protocol.

Development and testing of an evaluation procedure for commercial manure additive products.

Manure additive products can be used to reduce odour emissions (OE) from livestock farms. The standardised evaluation of these manure additive products under specific farm conditions is important. In this study, the efficacy of a manure additive (WonderTreat(TM), CKLS, Inc., Hong-Kong) was assessed under Australian conditions utilising a combination of laboratory and field-scale evaluation techniques. As a first step, the efficacy of the manure additive was assessed in a laboratory-scale trial using a series of uniformly managed digesters and standard odour, liquor ammonia and hydrogen sulphide concentration measurement procedures. This showed that the addition of WonderTreat(TM) at the 'low dose rate' (LDR) (102.6 g m-2) used during the trial significantly, but only marginally (30%; P = 0.02) reduced the OE rate (mean 13.9 OU m-2 s-1) of anaerobic pig liquor relative to an untreated control (UC) (19.9 OU m-2 s-1). However, the 'high dose rate' (HDR) (205.3 g m-2) also assessed during the trial preformed similarly (19.7 OU m-2 s-1) to the UC. No statistically significant difference in the concentrations of a range of measured water quality variables at the 5% level was observed between the treatments or controls digesters. As a second step, a field-scale assessment of the manure additive was undertaken at a commercial piggery. Two piggery manure lagoons (each with approximately 2500 m2 surface area) were included in the study; one was treated with WonderTreat(TM) while the other was used as control. The efficacy of the treatment was assessed using olfactometric evaluation of odour samples collected from the surface of the pond using a dynamic wind tunnel and ancillary equipment. No statistically significant reduction in OE rate could be demonstrated (P = 0.35), partially due to the limited number of samples taken during the assessment. However, there was a numerical reduction in the average OE rate of the treatment pond (29 OU m-2 s-1 at 1 m s-1) compared to the control lagoon (38 OU m-2 s-1 at 1 m s-1).

Learning Optimal Discriminant Functions through a Cooperative Game of Automata

The problem of learning correct decision rules to minimize the probability of misclassification is a long-standing problem of supervised learning in pattern recognition. The problem of learning such optimal discriminant functions is considered for the class of problems where the statistical properties of the pattern classes are completely unknown. The problem is posed as a game with common payoff played by a team of mutually cooperating learning automata. This essentially results in a probabilistic search through the space of classifiers. The approach is inherently capable of learning discriminant functions that are nonlinear in their parameters also. A learning algorithm is presented for the team and convergence is established. It is proved that the team can obtain the optimal classifier to an arbitrary approximation. Simulation results with a few examples are presented where the team learns the optimal classifier.

Optimal eradication: when to stop looking for an invasive plant

The notion of being sure that you have completely eradicated an invasive species is fanciful because of imperfect detection and persistent seed banks. Eradication is commonly declared either on an ad hoc basis, on notions of seed bank longevity, or on setting arbitrary thresholds of 1% or 5% confidence that the species is not present. Rather than declaring eradication at some arbitrary level of confidence, we take an economic approach in which we stop looking when the expected costs outweigh the expected benefits. We develop theory that determines the number of years of absent surveys required to minimize the net expected cost. Given detection of a species is imperfect, the optimal stopping time is a trade-off between the cost of continued surveying and the cost of escape and damage if eradication is declared too soon. A simple rule of thumb compares well to the exact optimal solution using stochastic dynamic programming. Application of the approach to the eradication programme of Helenium amarum reveals that the actual stopping time was a precautionary one given the ranges for each parameter.

Käsityöläisyyden kuva kultasepän ammatissa : Käsityöläisyys Suomen Kultaseppien Liiton lehdessä 1990-luvun lopussa

The aim of this study is to survey the meaning of craftmanship in goldsmith occupation. The image of craftmanship is built theoretically as well as researcher's own practical experience. The study describes a dialogue between self-employed goldsmith s everyday work and trade union's opinion. Suomen Kultaseppien Liitto (The Goldsmith Assosiation of Finland) was chosen forthe trade union, because it is the biggest, the oldest and the most influential on the occupational area. The research data are volumes 1995 - 1998 of occupational membership journal of Suomen Kultaseppien Liitto. The data analyzed with Adapted Content Analysis and Grounded Theory. The professional occupation of goldsmiths, the role of craftmanship and the future of the occupation are discussed. Additionally, the relationship between the Suomen Kultaseppien Liitto and occupational culture and profession of goldsmiths was studied. Craft and craftmanship is most often discussed in articles related to tradition and education.Craftmanship is understood very idealistically, with little meaning in practical life. St. Eligius and the skill and art of goldsmiths in St Petersburg are raised to symbols of craftmanship. The occupational image is broken and a clear conflict between education and occupation is visible. Education produces artist-craftsmen, while handicraft workers are required in industry, and retailers or specially trained store assistant in business. Computer-aided design and manufacture render handicraft workmanship unnecessary. In a pessimistic view, the future possibilities of the goldsmith occupational profession are dim, because the artist-craftsmen are bound to lose to fast-paced machines. On the other hand, people involved in goldsmith education see the future light, designer-goldsmiths developing the occupational to new dimensions. Suomen Kultaseppien Liitto represents goldsmiths in public. The union, however is governed by non-artisan goldsmiths. The union stresses business attitudes and enterpreneurship, and has succeeded in protecting the privileges of retailers and industry. Goldsmiths profession is seen in the research data as a combination of precious-metal industry, jewellery and watch stores, anda goldsmith shop is considered a specialized giftstore. The goldsmiths occupation is not a profession, and the Suomen Kultaseppien Liitto is not a trade union for artist and craftmen. Accordingly, part of the representative authority of the union could be transferred from the Association to Taidekäsityöläiset Taiko ry, a member of organization of Ornamo. Results of this study show the importance of defining the images of the goldsmith occupational profession and the trade union. The results could be applied to goldsmith education to examine what would be the optimal education and training for present employment opportunities. The important background theories has been the theories of Habermas and Lévi-Strauss.