Implementing a New Data Model for Simulating Processes

The paper describes the development of a new methodological approach for simulating geographic processes through the development of a data model that represents a process. This methodology complements existing approaches to dynamic modelling, which focus on the states of the system at each time step, by storing and representing the processes that are implicit in the model. The data model, called nen, focuses existing modelling approaches on representing and storing process information, which provides advantages for querying and analyzing processes. The flux simulation framework was created utilizing the nen data model to represent processes. This simulator includes basic classes for developing a domain specific simulation and a set of query tools for inquiring after the results of a simulation. The methodology is prototyped with a watershed runoff simulation

Integrated urban evolutionary modeling

Cellular automata models have proved rather popular as frameworks for simulating the physical growth of cities. Yet their brief history has been marked by a lack of application to real policy contexts, notwithstanding their obvious relevance to topical problems such as urban sprawl. Traditional urban models which emphasize transportation and demography continue to prevail despite their limitations in simulating realistic urban dynamics. To make progress, it is necessary to link CA models to these more traditional forms, focusing on the explicit simulation of the socio-economic attributes of land use activities as well as spatial interaction. There are several ways of tackling this but all are based on integration using various forms of strong and loose coupling which enable generically different models to be connected. Such integration covers many different features of urban simulation from data and software integration to internet operation, from interposing demand with the supply of urban land to enabling growth, location, and distributive mechanisms within such models to be reconciled. Here we will focus on developin

Simulating intertwined design processes that have similar structures: A case study of a small company that creates made-to-order fashion products

The authors use simulation to analyse the resource-driven dependencies between concurrent processes used to create customised products in a company. Such processes are uncertain and unique according to the design changes required. However, they have similar structures. For simulation, a level of abstraction is chosen such that all possible processes are represented by the same activity network. Differences between processes are determined by the customisations that they implement. The approach is illustrated through application to a small business that creates customised fashion products. We suggest that similar techniques could be applied to study intertwined design processes in more complex domains.The case study was carried out as part of Considerate Design for Personalised Fashion funded by the EPSRC/AHRC Design in the 21st century programme. The context of a multi-project environment was analysed as part of the EU Framework 7 CONVERGE project CP-FP 228746-2.Post-prin

Learning novel sound patterns

The acquisition of vocabulary represents a key phenomenon in language acquisition, yet it is still poorly understood. Gathercole and colleagues have recently provided a rigorous test of vocabulary knowledge (the nonword repetition test, Gathercole, Willis, Baddeley, & Emslie, 1994) and have adapted the phonological loop part of the working memory model (Baddeley & Hitch, 1974) to explain the nonword repetition findings (e.g. Gathercole & Baddeley, 1989). However, there are two major failings in their explanation: there is no description of how words are learned, and no definition of how the phonological loop interacts with long-term memory. We present an EPAM based computational model which overcomes these problems by combining the phonological loop approach with the EPAM/chunking approach (Feigenbaum & Simon, 1984). Trained on naturalistic phonemically coded speech (from mother’s utterances to 2-3 year old children), the model provides a good match to the nonword repetition data from 2-3 year old children. The model is also able to show the effect on nonword repetition when the model is trained using different sets of input. Implementing the phonological loop within EPAM represents a parsimonious approach to learning novel sound patterns and provides a more precise definition of how vocabulary acquisition may occur

Decision support system for accessing costs and risks of connected and autonomous vehicles as mobility service in urban contexts

A predicted increase of connected autonomous vehicles (CAVs) in our roads paved the way for new opportunities and challenges towards the promotion of sustainable mobility. However, the impacts of CAVs on the road environment and its implications are widely dependent on technological choices and public policy [1,2]. Therefore, this research (PhD Workplan) intends to assess whether CAVs could be effective mobility solutions for improving social, economic and environmental efficiency [4]. This question will be addressed by developing a decision support tool driven by comprehensive data analysis and modelling processes. The outputs achieved will integrate a tool that will support transport system’s planning and the implementation of urban strategies to introduce CAVs [3,5]. Thus, the research’s main focus encompasses the development of a model-driven decision support system (DSS) that allows assessing the costs and risks of implementing CAVs in urban context [3,4]. Three specific research objectives are assumed: I) Predicting impacts of CAVs operation in urban contexts, by analyzing cost-efficiency, transportation demand and mobility patterns considering market penetration scenarios of CAVs in Portugal; II) Conceiving a hybrid transport planning tool to assess possible restrictions to CAVs on different types of links through field data testing and simulating scenarios using a microscopic traffic model. Data will support the development of a macroscopic model for a full network assessment performance; III) Developing a multidimensional decision tool directed to a wide range of stakeholders, both from public or private sectors, to compute the benefits, costs, constraints and risks of implementing CAVs on urban mobility systems. Preliminary results from different urban arterials indicate that CAVs can have negative or negligible impacts in some urban contexts. However, if the impact on the traffic flow’s energy performance is considered into the internal car following algorithm, global energy savings of up to 12% can be achieved.publishe

Augmenting Biogas Process Modeling by Resolving Intracellular Metabolic Activity

The process of anaerobic digestion in which waste biomass is transformed to methane by complex microbial communities has been modeled for more than 16 years by parametric gray box approaches that simplify process biology and do not resolve intracellular microbial activity. Information on such activity, however, has become available in unprecedented detail by recent experimental advances in metatranscriptomics and metaproteomics. The inclusion of such data could lead to more powerful process models of anaerobic digestion that more faithfully represent the activity of microbial communities. We augmented the Anaerobic Digestion Model No. 1 (ADM1) as the standard kinetic model of anaerobic digestion by coupling it to Flux-Balance-Analysis (FBA) models of methanogenic species. Steady-state results of coupled models are comparable to standard ADM1 simulations if the energy demand for non-growth associated maintenance (NGAM) is chosen adequately. When changing a constant feed of maize silage from continuous to pulsed feeding, the final average methane production remains very similar for both standard and coupled models, while both the initial response of the methanogenic population at the onset of pulsed feeding as well as its dynamics between pulses deviates considerably. In contrast to ADM1, the coupled models deliver predictions of up to 1,000s of intracellular metabolic fluxes per species, describing intracellular metabolic pathway activity in much higher detail. Furthermore, yield coefficients which need to be specified in ADM1 are no longer required as they are implicitly encoded in the topology of the species’ metabolic network. We show the feasibility of augmenting ADM1, an ordinary differential equation-based model for simulating biogas production, by FBA models implementing individual steps of anaerobic digestion. While cellular maintenance is introduced as a new parameter, the total number of parameters is reduced as yield coefficients no longer need to be specified. The coupled models provide detailed predictions on intracellular activity of microbial species which are compatible with experimental data on enzyme synthesis activity or abundance as obtained by metatranscriptomics or metaproteomics. By providing predictions of intracellular fluxes of individual community members, the presented approach advances the simulation of microbial community driven processes and provides a direct link to validation by state-of-the-art experimental techniques