An agent-based approach to modelling driver route choice behaviour under the influence of real-time information

This paper presents an agent-based approach to modelling individual driver behaviour under the influence of real-time traffic information. The driver behaviour models developed in this study are based on a behavioural survey of drivers which was conducted on a congested commuting corridor in Brisbane, Australia. Commuters' responses to travel information were analysed and a number of discrete choice models were developed to determine the factors influencing drivers' behaviour and their propensity to change route and adjust travel patterns. Based on the results obtained from the behavioural survey, the agent behaviour parameters which define driver characteristics, knowledge and preferences were identified and their values determined. A case study implementing a simple agent-based route choice decision model within a microscopic traffic simulation tool is also presented. Driver-vehicle units (DVUs) were modelled as autonomous software components that can each be assigned a set of goals to achieve and a database of knowledge comprising certain beliefs, intentions and preferences concerning the driving task. Each DVU provided route choice decision-making capabilities, based on perception of its environment, that were similar to the described intentions of the driver it represented. The case study clearly demonstrated the feasibility of the approach and the potential to develop more complex driver behavioural dynamics based on the belief-desire-intention agent architecture. (C) 2002 Elsevier Science Ltd. All rights reserved.

Computational tools for the study of allergens

Allergy is a major cause of morbidity worldwide. The number of characterized allergens and related information is increasing rapidly creating demands for advanced information storage, retrieval and analysis. Bioinformatics provides useful tools for analysing allergens and these are complementary to traditional laboratory techniques for the study of allergens. Specific applications include structural analysis of allergens, identification of B- and T-cell epitopes, assessment of allergenicity and cross-reactivity, and genome analysis. In this paper, the most important bioinformatic tools and methods with relevance to the study of allergy have been reviewed.

A model of seller holdout

We model a buyer who wishes to combine objects owned by two separate sellers in order to realize higher value. Sellers are able to avoid entering into negotiations with the buyer, so that the order in which they negotiate is endogenous. Holdout occurs if at least one of the sellers is not present in the first round of negotiations. We demonstrate that complementarity of the buyer's technology is a necessary condition for equilibrium holdout. Moreover, a rise in complementarity leads to an increased likelihood of holdout, and an increased efficiency loss. Applications include patents, the land assembly problem, and mergers.

Multiresolution spatial databases: Making web-based spatial applications faster

Spatial data has now been used extensively in the Web environment, providing online customized maps and supporting map-based applications. The full potential of Web-based spatial applications, however, has yet to be achieved due to performance issues related to the large sizes and high complexity of spatial data. In this paper, we introduce a multiresolution approach to spatial data management and query processing such that the database server can choose spatial data at the right resolution level for different Web applications. One highly desirable property of the proposed approach is that the server-side processing cost and network traffic can be reduced when the level of resolution required by applications are low. Another advantage is that our approach pushes complex multiresolution structures and algorithms into the spatial database engine. That is, the developer of spatial Web applications needs not to be concerned with such complexity. This paper explains the basic idea, technical feasibility and applications of multiresolution spatial databases.

The Adequacy of the Enterprise Resources Planning (ERP) Systems for the Creation of intangible Managerial Accounting Information: an exploratory study

The general objective of this work was to study the contribution of the ERP for the quality of the managerial accounting information, through the perception of managers of large sized Brazilian companies. The initial principle was that, presently, we live in an enterprise reality characterized by global and competitive worldwide scenery where the information about the enterprise performance and the evaluation of the intangible assets are necessary conditions for the survival, of the companies. The research of the exploratory type is based on a sample of 37 managers of large sized-Brazilian companies. The analysis of the data treated by means of the qualitative method showed that the great majority of the companies of the sample (86%) possess an ERP implanted. It also showed that this system is used in combination with other applicative software. The managers, in its majority, were also satisfied with the information generated in relation to the dimensions Time and Content. However, with regard to the qualitative nature of the information, the ERP made some analysis possible when the Balanced Scorecard was adopted, but information able to provide an estimate of the investments carried through in the intangible assets was not obtained. These results Suggest that in these companies ERP systems are not adequate to support strategic decisions.

Variable Demand and Profitability in Service Companies: a case study in the information technology sector

Managing a variable demand scenario is particularly challenging on services organizations because services companies usually have a major part of fixed costs. The article studies how a services organization manages its demand variability and its relation with the organization`s profitability. Moreover, the study searched for alternatives used to reduce the demand variability`s impact on the profitability of the company. The research was based on a case study with a Brazilian services provider on information technology business. The study suggests that alternatives like using outsourced employees to cover demand peaks may bring benefits only on short term, reducing the profitability of the company on long term: Some options are revealed, like the internationalization of employees and the investment on developing its own workforce.

A comparative study of similarity measures for manufacturing cell formation

We introduced a spectral clustering algorithm based on the bipartite graph model for the Manufacturing Cell Formation problem in [Oliveira S, Ribeiro JFF, Seok SC. A spectral clustering algorithm for manufacturing cell formation. Computers and Industrial Engineering. 2007 [submitted for publication]]. It constructs two similarity matrices; one for parts and one for machines. The algorithm executes a spectral clustering algorithm on each separately to find families of parts and cells of machines. The similarity measure in the approach utilized limited information between parts and between machines. This paper reviews several well-known similarity measures which have been used for Group Technology. Computational clustering results are compared by various performance measures. (C) 2008 The Society of Manufacturing Engineers. Published by Elsevier Ltd. All rights reserved.

Identification of "pathologs" (disease-related genes) from the RIKEN mouse cDNA dataset using human curation plus FACTS, a new biological information extraction system

Background: A major goal in the post-genomic era is to identify and characterise disease susceptibility genes and to apply this knowledge to disease prevention and treatment. Rodents and humans have remarkably similar genomes and share closely related biochemical, physiological and pathological pathways. In this work we utilised the latest information on the mouse transcriptome as revealed by the RIKEN FANTOM2 project to identify novel human disease-related candidate genes. We define a new term patholog to mean a homolog of a human disease-related gene encoding a product ( transcript, anti-sense or protein) potentially relevant to disease. Rather than just focus on Mendelian inheritance, we applied the analysis to all potential pathologs regardless of their inheritance pattern. Results: Bioinformatic analysis and human curation of 60,770 RIKEN full-length mouse cDNA clones produced 2,578 sequences that showed similarity ( 70 - 85% identity) to known human-disease genes. Using a newly developed biological information extraction and annotation tool ( FACTS) in parallel with human expert analysis of 17,051 MEDLINE scientific abstracts we identified 182 novel potential pathologs. Of these, 36 were identified by computational tools only, 49 by human expert analysis only and 97 by both methods. These pathologs were related to neoplastic ( 53%), hereditary ( 24%), immunological ( 5%), cardio-vascular (4%), or other (14%), disorders. Conclusions: Large scale genome projects continue to produce a vast amount of data with potential application to the study of human disease. For this potential to be realised we need intelligent strategies for data categorisation and the ability to link sequence data with relevant literature. This paper demonstrates the power of combining human expert annotation with FACTS, a newly developed bioinformatics tool, to identify novel pathologs from within large-scale mouse transcript datasets.

On S-asymptotically omega-periodic functions on Banach spaces and applications

This paper is devoted to the study of the class of continuous and bounded functions f : [0, infinity] -> X for which exists omega > 0 such that lim(t ->infinity) (f (t + omega) - f (t)) = 0 (in the sequel called S-asymptotically omega-periodic functions). We discuss qualitative properties and establish some relationships between this type of functions and the class of asymptotically omega-periodic functions. We also study the existence of S-asymptotically omega-periodic mild solutions of the first-order abstract Cauchy problem in Banach spaces. (C) 2008 Elsevier Inc. All rights reserved.

Pt-RuO(2) electrodes prepared by thermal decomposition of polymeric precursors as catalysts for direct methanol fuel cell applications

The electrocatalytic activity of Pt and RuO(2) mixed electrodes of different compositions towards methanol oxidation was investigated. The catalysts were prepared by thermal decomposition of polymeric precursors and characterized by energy dispersive X-ray, scanning electronic microscopy, X-ray diffraction and cyclic voltammetry. This preparation method allowed obtaining uniform films with controlled stoichiometry and high surface area. Cyclic voltammetry experiments in the presence of methanol showed that mixed electrodes decreased the potential peak of methanol oxidation by approximately 100 mV (RHE) when compared to the electrode containing only Pt. In addition, voltammetric experiments indicated that the Pt(0.6)Ru(0.4)O(y) electrode led to higher oxidation current densities at lower potentials. Chronoamperometry experiments confirmed the contribution of RuO(2) to the catalytic activity as well as the better performance of the Pt(0.6)Ru(0.4)O(y) electrode composition. Formic acid and CO(2) were identified as being the reaction products formed in the electrolysis performed at 400 and 600 mV. The relative formation of CO(2) was favored in the electrolysis performed at 400 mV (RHE) with the Pt(0.6)Ru(0.4)O(y) electrode. The presence of RuO(2) in Pt-Ru-based electrodes is important for improving the catalytic activity towards methanol electrooxidation. Moreover, the thermal decomposition of polymeric precursors seems to be a promising route for the production of catalysts applicable to DMFC. (C) 2009 International Association for Hydrogen Energy. Published by Elsevier Ltd. All rights reserved.

Bayesian analysis of the error correction model

This paper presents a method for estimating the posterior probability density of the cointegrating rank of a multivariate error correction model. A second contribution is the careful elicitation of the prior for the cointegrating vectors derived from a prior on the cointegrating space. This prior obtains naturally from treating the cointegrating space as the parameter of interest in inference and overcomes problems previously encountered in Bayesian cointegration analysis. Using this new prior and Laplace approximation, an estimator for the posterior probability of the rank is given. The approach performs well compared with information criteria in Monte Carlo experiments. (C) 2003 Elsevier B.V. All rights reserved.