Can geocomputation save urban simulation? Throw some agents into the mixture, simmer and wait ...

There are indications that the current generation of simulation models in practical, operational uses has reached the limits of its usefulness under existing specifications. The relative stasis in operational urban modeling contrasts with simulation efforts in other disciplines, where techniques, theories, and ideas drawn from computation and complexity studies are revitalizing the ways in which we conceptualize, understand, and model real-world phenomena. Many of these concepts and methodologies are applicable to operational urban systems simulation. Indeed, in many cases, ideas from computation and complexity studies—often clustered under the collective term of geocomputation, as they apply to geography—are ideally suited to the simulation of urban dynamics. However, there exist several obstructions to their successful use in operational urban geographic simulation, particularly as regards the capacity of these methodologies to handle top-down dynamics in urban systems. This paper presents a framework for developing a hybrid model for urban geographic simulation and discusses some of the imposing barriers against innovation in this field. The framework infuses approaches derived from geocomputation and complexity with standard techniques that have been tried and tested in operational land-use and transport simulation. Macro-scale dynamics that operate from the topdown are handled by traditional land-use and transport models, while micro-scale dynamics that work from the bottom-up are delegated to agent-based models and cellular automata. The two methodologies are fused in a modular fashion using a system of feedback mechanisms. As a proof-of-concept exercise, a micro-model of residential location has been developed with a view to hybridization. The model mixes cellular automata and multi-agent approaches and is formulated so as to interface with meso-models at a higher scale

A Four-Way Comparison of Cardiac Function with Normobaric Normoxia, Normobaric Hypoxia, Hypobaric Hypoxia and Genuine High Altitude.

There has been considerable debate as to whether different modalities of simulated hypoxia induce similar cardiac responses.This was a prospective observational study of 14 healthy subjects aged 22-35 years. Echocardiography was performed at rest and at 15 and 120 minutes following two hours exercise under normobaric normoxia (NN) and under similar PiO2 following genuine high altitude (GHA) at 3,375m, normobaric hypoxia (NH) and hypobaric hypoxia (HH) to simulate the equivalent hypoxic stimulus to GHA.All 14 subjects completed the experiment at GHA, 11 at NN, 12 under NH, and 6 under HH. The four groups were similar in age, sex and baseline demographics. At baseline rest right ventricular (RV) systolic pressure (RVSP, p = 0.0002), pulmonary vascular resistance (p = 0.0002) and acute mountain sickness (AMS) scores were higher and the SpO2 lower (p<0.0001) among all three hypoxic groups (GHA, NH and HH) compared with NN. At both 15 minutes and 120 minutes post exercise, AMS scores, Cardiac output, septal S', lateral S', tricuspid S' and A' velocities and RVSP were higher and SpO2 lower with all forms of hypoxia compared with NN. On post-test analysis, among the three hypoxia groups, SpO2 was lower at baseline and 15 minutes post exercise with GHA (89.3±3.4% and 89.3±2.2%) and HH (89.0±3.1 and (89.8±5.0) compared with NH (92.9±1.7 and 93.6±2.5%). The RV Myocardial Performance (Tei) Index and RVSP were significantly higher with HH than NH at 15 and 120 minutes post exercise respectively and tricuspid A' was higher with GHA compared with NH at 15 minutes post exercise.GHA, NH and HH produce similar cardiac adaptations over short duration rest despite lower SpO2 levels with GHA and HH compared with NH. Notable differences emerge following exercise in SpO2, RVSP and RV cardiac function

Patents and Industrialisation. An Historical Overview of the British Case, 1624-1907

A Report to the Strategic Advisory Board on Intellectual Property Policy (SABIP), U

Useful downloads: Adobe Acrobat QuickTime Windows Media Player Real PlayerCellular Models of Urban Systems

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How Land-Use-Transportation Models work

This working paper serves as an introductory reference for those studying the application of landuse– transportation models to the simulation of urban systems. The paper is by no means comprehensive, but aims to provide the reader with a foundation in the basic principles underlying land-use–transportation models and to set those principles in the context of urban management and urban studies. The paper opens with taxonomy of urban simulation models and a treatment of descriptive and analytical models. This serves to situate land-use–transportation models in the context of a broader simulation environment. The paper then reviews land-use–transportation models according to their simulation techniques and individual components. Towards the second half of the paper, the discussion moves to a critical overview of urban simulation and deals with model weaknesses and strengths in a holistic fashion, before concluding with a discussion of some innovations in academic research that are likely to shape future models

A computational sandbox with human automata for exploring perceived egress safety in urban damage scenarios

In earthquakes and building collapse situations, volumes of people may need to move, suddenly, through spaces that have been destroyed and seem unfamiliar in configuration and appearance. Perception is significant in these cases, determining individual movement, collective egress, and phenomena in between. Alas, exploring how perception shapes critical egress is tricky because perception is both physical and cerebral in genesis and because critical scenarios are often hazardous. In this paper, we describe a computational sandbox for studying urban damage scenarios. The model is built as automata, specialized as human automata and rigid body automata, with interactivity provided by slipstreaming. Our sandbox supports parameterization of synthetic built settings and synthetic humans in fine detail for large interactive collections, allowing flexible analyses of damage scenarios and their determining processes, from micro-perspectives through to the macrocosm of the phenomena that might result. While we have much work to do to improve the model relative to real-world fidelity, our work thus far has produced some meaningful results, supporting practical questions of how urban design and parking scenarios shape egress, and pointing to potential phenomena of perceptual shadowing as a translation mechanism for processes at the built-human interface

NEW TOOLS FOR SIMULATING HOUSING CHOICES

There are indications that the current generation of models used to simulate the geography of housing choice has reached the limits of its usefulness under existing specifications. The relative stasis in residential choice modeling--and urban simulation in general--contrasts with simulation efforts in other disciplines, where techniques, theories, and ideas drawn from computation and complexity studies are revitalizing the ways in which we conceptualize, understand, and model real-world phenomena. Many of these concepts and methodologies are applicable to housing choice simulation. Indeed, in many cases, ideas from computation and complexity studies--often clustered under the collective term of geocomputation, as they apply to geography--are ideally suited to the simulation of residential location dynamics. However, there exist several obstructions to their successful use for these puropses, particularly as regards the capacity of these methodologies to handle top-down dynamics in urban systems. This paper presents a framework for developing a hybrid model for urban geographic simulation generally and discusses some of the imposing barriers against innovation in this field. The framework infuses approaches derived from geocomputation and complexity with standard techniques that have been tried and tested in operational land-use and transport simulation. As a proof-of-concept exercise, a micro-model of residential location has been developed with a view to hybridization. The model mixes cellular automata and multi-agent approaches and is formulated so as to interface with meso-models at a higher scale