Linking early design decisions across multiple disciplines

The early stages of the building design process are when the most far reaching decisions are made regarding the configuration of the proposed project. This paper examines methods of providing decision support to building designers across multiple disciplines during the early stage of design. The level of detail supported is at the massing study stage where the basic envelope of the project is being defined. The block outlines on the building envelope are sliced into floors. Within a floor the only spatial divisions supported are the “user” space and the building core. The building core includes vertical transportation systems, emergency egress and vertical duct runs. The current focus of the project described in the paper is multi-storey mixed use office/residential buildings with car parking. This is a common type of building in redevelopment projects within and adjacent to the central business districts of major Australian cities. The key design parameters for system selection across the major systems in multi-storey building projects - architectural, structural, HVAC, vertical transportation, electrical distribution, fire protection, hydraulics and cost – are examined. These have been identified through literature research and discussions with building designers from various disciplines. This information is being encoded in decision support tools. The decision support tools communicate through a shared database to ensure that the relevant information is shared across all of the disciplines. An internal data model has been developed to support the very early design phase and the high level system descriptions required. A mapping to IFC 2x2 has also been defined to ensure that this early information is available at later stages of the design process.

Interoperable Standards Development : Final Report

Since 1995 the buildingSMART International Alliance for Interoperability (buildingSMART)has developed a robust standard called the Industry Foundation Classes (IFC). IFC is an object oriented data model with related file format that has facilitated the efficient exchange of data in the development of building information models (BIM). The Cooperative Research Centre for Construction Innovation has contributed to the international effort in the development of the IFC standard and specifically the reinforced concrete part of the latest IFC 2x3 release. Industry Foundation Classes have been endorsed by the International Standards Organisation as a Publicly Available Specification (PAS) under the ISO label ISO/PAS 16739. For more details, go to http://www.tc184- sc4.org/About_TC184-SC4/About_SC4_Standards/ The current IFC model covers the building itself to a useful level of detail. The next stage of development for the IFC standard is where the building meets the ground (terrain) and with civil and external works like pavements, retaining walls, bridges, tunnels etc. With the current focus in Australia on infrastructure projects over the next 20 years a logical extension to this standard was in the area of site and civil works. This proposal recognises that there is an existing body of work on the specification of road representation data. In particular, LandXML is recognised as also is TransXML in the broader context of transportation and CityGML in the common interfacing of city maps, buildings and roads. Examination of interfaces between IFC and these specifications is therefore within the scope of this project. That such interfaces can be developed has already been demonstrated in principle within the IFC for Geographic Information Systems (GIS) project. National road standards that are already in use should be carefully analysed and contacts established in order to gain from this knowledge. The Object Catalogue for the Road Transport Sector (OKSTRA) should be noted as an example. It is also noted that buildingSMART Norway has submitted a proposal

Writing the visible page : a multimodal approach to graphic devices in literary fiction

This practice-led project has two outcomes: a collection of short stories titled 'Corkscrew Section', and an exegesis. The short stories combine written narrative with visual elements such as images and typographic devices, while the exegesis analyses the function of these graphic devices within adult literary fiction. My creative writing explores a variety of genres and literary styles, but almost all of the stories are concerned with fusing verbal and visual modes of communication. The exegesis adopts the interpretive paradigm of multimodal stylistics, which aims to analyse graphic devices with the same level of detail as linguistic analysis. Within this framework, the exegesis compares and extends previous studies to develop a systematic method for analysing how the interactions between language, images and typography create meaning within multimodal literature.

Building adaptable agent-based models – application to the electricity distribution network

Agent-based modelling (ABM), like other modelling techniques, is used to answer specific questions from real world systems that could otherwise be expensive or impractical. Its recent gain in popularity can be attributed to some degree to its capacity to use information at a fine level of detail of the system, both geographically and temporally, and generate information at a higher level, where emerging patterns can be observed. This technique is data-intensive, as explicit data at a fine level of detail is used and it is computer-intensive as many interactions between agents, which can learn and have a goal, are required. With the growing availability of data and the increase in computer power, these concerns are however fading. Nonetheless, being able to update or extend the model as more information becomes available can become problematic, because of the tight coupling of the agents and their dependence on the data, especially when modelling very large systems. One large system to which ABM is currently applied is the electricity distribution where thousands of agents representing the network and the consumers’ behaviours are interacting with one another. A framework that aims at answering a range of questions regarding the potential evolution of the grid has been developed and is presented here. It uses agent-based modelling to represent the engineering infrastructure of the distribution network and has been built with flexibility and extensibility in mind. What distinguishes the method presented here from the usual ABMs is that this ABM has been developed in a compositional manner. This encompasses not only the software tool, which core is named MODAM (MODular Agent-based Model) but the model itself. Using such approach enables the model to be extended as more information becomes available or modified as the electricity system evolves, leading to an adaptable model. Two well-known modularity principles in the software engineering domain are information hiding and separation of concerns. These principles were used to develop the agent-based model on top of OSGi and Eclipse plugins which have good support for modularity. Information regarding the model entities was separated into a) assets which describe the entities’ physical characteristics, and b) agents which describe their behaviour according to their goal and previous learning experiences. This approach diverges from the traditional approach where both aspects are often conflated. It has many advantages in terms of reusability of one or the other aspect for different purposes as well as composability when building simulations. For example, the way an asset is used on a network can greatly vary while its physical characteristics are the same – this is the case for two identical battery systems which usage will vary depending on the purpose of their installation. While any battery can be described by its physical properties (e.g. capacity, lifetime, and depth of discharge), its behaviour will vary depending on who is using it and what their aim is. The model is populated using data describing both aspects (physical characteristics and behaviour) and can be updated as required depending on what simulation is to be run. For example, data can be used to describe the environment to which the agents respond to – e.g. weather for solar panels, or to describe the assets and their relation to one another – e.g. the network assets. Finally, when running a simulation, MODAM calls on its module manager that coordinates the different plugins, automates the creation of the assets and agents using factories, and schedules their execution which can be done sequentially or in parallel for faster execution. Building agent-based models in this way has proven fast when adding new complex behaviours, as well as new types of assets. Simulations have been run to understand the potential impact of changes on the network in terms of assets (e.g. installation of decentralised generators) or behaviours (e.g. response to different management aims). While this platform has been developed within the context of a project focussing on the electricity domain, the core of the software, MODAM, can be extended to other domains such as transport which is part of future work with the addition of electric vehicles.

Calibration functions for estimating soil moisture from GPR dielectric constant measurements

Ground-penetrating radar (GPR) is widely used for assessment of soil moisture variability in field soils. Because GPR does not measure soil water content directly, it is common practice to use calibration functions that describe its relationship with the soil dielectric properties and textural parameters. However, the large variety of models complicates the selection of the appropriate function. In this article an overview is presented of the different functions available, including volumetric models, empirical functions, effective medium theories, and frequency-specific functions. Using detailed information presented in summary tables, the choice for which calibration function to use can be guided by the soil variables available to the user, the frequency of the GPR equipment, and the desired level of detail of the output. This article can thus serve as a guide for GPR practitioners to obtain soil moisture values and to estimate soil dielectric properties.

Using Bayesian Mixture Models That Combine Expert Knowledge and GIS Data to Define Ecoregions

Conservation planning and management programs typically assume relatively homogeneous ecological landscapes. Such “ecoregions” serve multiple purposes: they support assessments of competing environmental values, reveal priorities for allocating scarce resources, and guide effective on-ground actions such as the acquisition of a protected area and habitat restoration. Ecoregions have evolved from a history of organism–environment interactions, and are delineated at the scale or level of detail required to support planning. Depending on the delineation method, scale, or purpose, they have been described as provinces, zones, systems, land units, classes, facets, domains, subregions, and ecological, biological, biogeographical, or environmental regions. In each case, they are essential to the development of conservation strategies and are embedded in government policies at multiple scales.

Dynamic agent composition for large-scale agent-based models

PURPOSE: This paper describes dynamic agent composition, used to support the development of flexible and extensible large-scale agent-based models (ABMs). This approach was motivated by a need to extend and modify, with ease, an ABM with an underlying networked structure as more information becomes available. Flexibility was also sought after so that simulations are set up with ease, without the need to program. METHODS: The dynamic agent composition approach consists in having agents, whose implementation has been broken into atomic units, come together at runtime to form the complex system representation on which simulations are run. These components capture information at a fine level of detail and provide a vast range of combinations and options for a modeller to create ABMs. RESULTS: A description of the dynamic agent composition is given in this paper, as well as details about its implementation within MODAM (MODular Agent-based Model), a software framework which is applied to the planning of the electricity distribution network. Illustrations of the implementation of the dynamic agent composition are consequently given for that domain throughout the paper. It is however expected that this approach will be beneficial to other problem domains, especially those with a networked structure, such as water or gas networks. CONCLUSIONS: Dynamic agent composition has many advantages over the way agent-based models are traditionally built for the users, the developers, as well as for agent-based modelling as a scientific approach. Developers can extend the model without the need to access or modify previously written code; they can develop groups of entities independently and add them to those already defined to extend the model. Users can mix-and-match already implemented components to form large-scales ABMs, allowing them to quickly setup simulations and easily compare scenarios without the need to program. The dynamic agent composition provides a natural simulation space over which ABMs of networked structures are represented, facilitating their implementation; and verification and validation of models is facilitated by quickly setting up alternative simulations.

Algorithms for colour image processing based on neurological models

373 p. : il., gráf., fot., tablas

MIRACLE Project Plan

Social scientists have used agent-based models (ABMs) to explore the interaction and feedbacks among social agents and their environments. The bottom-up structure of ABMs enables simulation and investigation of complex systems and their emergent behaviour with a high level of detail; however the stochastic nature and potential combinations of parameters of such models create large non-linear multidimensional “big data,” which are difficult to analyze using traditional statistical methods. Our proposed project seeks to address this challenge by developing algorithms and web-based analysis and visualization tools that provide automated means of discovering complex relationships among variables. The tools will enable modellers to easily manage, analyze, visualize, and compare their output data, and will provide stakeholders, policy makers and the general public with intuitive web interfaces to explore, interact with and provide feedback on otherwise difficult-to-understand models.

Computation and Pre-Parametric Design

My work is broadly concerned with the question "How can designs bessynthesized computationally?" The project deals primarily with mechanical devices and focuses on pre-parametric design: design at the level of detail of a blackboard sketch rather than at the level of detail of an engineering drawing. I explore the project ideas in the domain of single-input single-output dynamic systems, like pressure gauges, accelerometers, and pneumatic cylinders. The problem solution consists of two steps: 1) generate a schematic description of the device in terms of idealized functional elements, and then 2) from the schematic description generate a physical description.

A Neural Network Architecture for Autonomous Learning, Recognition, and Prediction in a Nonstationary World

In a constantly changing world, humans are adapted to alternate routinely between attending to familiar objects and testing hypotheses about novel ones. We can rapidly learn to recognize and narne novel objects without unselectively disrupting our memories of familiar ones. We can notice fine details that differentiate nearly identical objects and generalize across broad classes of dissimilar objects. This chapter describes a class of self-organizing neural network architectures--called ARTMAP-- that are capable of fast, yet stable, on-line recognition learning, hypothesis testing, and naming in response to an arbitrary stream of input patterns (Carpenter, Grossberg, Markuzon, Reynolds, and Rosen, 1992; Carpenter, Grossberg, and Reynolds, 1991). The intrinsic stability of ARTMAP allows the system to learn incrementally for an unlimited period of time. System stability properties can be traced to the structure of its learned memories, which encode clusters of attended features into its recognition categories, rather than slow averages of category inputs. The level of detail in the learned attentional focus is determined moment-by-moment, depending on predictive success: an error due to over-generalization automatically focuses attention on additional input details enough of which are learned in a new recognition category so that the predictive error will not be repeated. An ARTMAP system creates an evolving map between a variable number of learned categories that compress one feature space (e.g., visual features) to learned categories of another feature space (e.g., auditory features). Input vectors can be either binary or analog. Computational properties of the networks enable them to perform significantly better in benchmark studies than alternative machine learning, genetic algorithm, or neural network models. Some of the critical problems that challenge and constrain any such autonomous learning system will next be illustrated. Design principles that work together to solve these problems are then outlined. These principles are realized in the ARTMAP architecture, which is specified as an algorithm. Finally, ARTMAP dynamics are illustrated by means of a series of benchmark simulations.

Time Efficient Assessment and Feedback Methods for Large Computer-Aided-Design Cohorts

Timely and individualized feedback on coursework is desirable from a student perspective as it facilitates formative development and encourages reflective learning practice. Faculty however are faced with a significant and potentially time consuming challenge when teaching larger cohorts if they are to provide feedback which is timely, individualized and detailed. Additionally, for subjects which assess non-traditional submissions, such as Computer-Aided-Design (CAD), the methods for assessment and feedback tend not to be so well developed or optimized. Issues can also arise over the consistency of the feedback provided. Evaluations of Computer-Assisted feedback in other disciplines (Denton et al, 2008), (Croft et al, 2001) have shown students prefer this method of feedback to traditional “red pen” marking and also that such methods can be more time efficient for faculty.
Herein, approaches are described which make use of technology and additional software tools to speed up, simplify and automate assessment and the provision of feedback for large cohorts of first and second year engineering students studying modules where CAD files are submitted electronically. A range of automated methods are described and compared with more “manual” approaches. Specifically one method uses an application programming interface (API) to interrogate SolidWorks models and extract information into an Excel spreadsheet, which is then used to automatically send feedback emails. Another method describes the use of audio recordings made during model interrogation which reduces the amount of time while increasing the level of detail provided as feedback.
Limitations found with these methods and problems encountered are discussed along with a quantified assessment of time saving efficiencies made.

Multi-scale keypoints in V1 and face detection

End-stopped cells in cortical area V1, which combine out- puts of complex cells tuned to different orientations, serve to detect line and edge crossings (junctions) and points with a large curvature. In this paper we study the importance of the multi-scale keypoint representa- tion, i.e. retinotopic keypoint maps which are tuned to different spatial frequencies (scale or Level-of-Detail). We show that this representation provides important information for Focus-of-Attention (FoA) and object detection. In particular, we show that hierarchically-structured saliency maps for FoA can be obtained, and that combinations over scales in conjunction with spatial symmetries can lead to face detection through grouping operators that deal with keypoints at the eyes, nose and mouth, especially when non-classical receptive field inhibition is employed. Al- though a face detector can be based on feedforward and feedback loops within area V1, such an operator must be embedded into dorsal and ventral data streams to and from higher areas for obtaining translation-, rotation- and scale-invariant face (object) detection.

Modelos de simulação em MATSim aplicados à análise de sistemas de transporte

Dissertação para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização de Vias de Comunicação e Transportes

Intégration de la visualisation à multiples vues pour le développement du logiciel

Le développement du logiciel actuel doit faire face de plus en plus à la complexité de programmes gigantesques, élaborés et maintenus par de grandes équipes réparties dans divers lieux. Dans ses tâches régulières, chaque intervenant peut avoir à répondre à des questions variées en tirant des informations de sources diverses. Pour améliorer le rendement global du développement, nous proposons d'intégrer dans un IDE populaire (Eclipse) notre nouvel outil de visualisation (VERSO) qui calcule, organise, affiche et permet de naviguer dans les informations de façon cohérente, efficace et intuitive, afin de bénéficier du système visuel humain dans l'exploration de données variées. Nous proposons une structuration des informations selon trois axes : (1) le contexte (qualité, contrôle de version, bogues, etc.) détermine le type des informations ; (2) le niveau de granularité (ligne de code, méthode, classe, paquetage) dérive les informations au niveau de détails adéquat ; et (3) l'évolution extrait les informations de la version du logiciel désirée. Chaque vue du logiciel correspond à une coordonnée discrète selon ces trois axes, et nous portons une attention toute particulière à la cohérence en naviguant entre des vues adjacentes seulement, et ce, afin de diminuer la charge cognitive de recherches pour répondre aux questions des utilisateurs. Deux expériences valident l'intérêt de notre approche intégrée dans des tâches représentatives. Elles permettent de croire qu'un accès à diverses informations présentées de façon graphique et cohérente devrait grandement aider le développement du logiciel contemporain.