Sketching space

In this paper, we present a sketch modelling system which we call Stilton. The program resembles a desktop VRML browser, allowing a user to navigate a three-dimensional model in a perspective projection, or panoramic photographs, which the program maps onto the scene as a `floor' and `walls'. We place an imaginary two-dimensional drawing plane in front of the user, and any geometric information that user sketches onto this plane may be reconstructed to form solid objects through an optimization process. We show how the system can be used to reconstruct geometry from panoramic images, or to add new objects to an existing model. While panoramic imaging can greatly assist with some aspects of site familiarization and qualitative assessment of a site, without the addition of some foreground geometry they offer only limited utility in a design context. Therefore, we suggest that the system may be of use in `just-in-time' CAD recovery of complex environments, such as shop floors, or construction sites, by recovering objects through sketched overlays, where other methods such as automatic line-retrieval may be impossible. The result of using the system in this manner is the `sketching of space' - sketching out a volume around the user - and once the geometry has been recovered, the designer is free to quickly sketch design ideas into the newly constructed context, or analyze the space around them. Although end-user trials have not, as yet, been undertaken we believe that this implementation may afford a user-interface that is both accessible and robust, and that the rapid growth of pen-computing devices will further stimulate activity in this area

3D freeform surfaces from planar sketches using neural networks

A novel intelligent approach into 3D freeform surface reconstruction from planar sketches is proposed. A multilayer perceptron (MLP) neural network is employed to induce 3D freeform surfaces from planar freehand curves. Planar curves were used to represent the boundaries of a freeform surface patch. The curves were varied iteratively and sampled to produce training data to train and test the neural network. The obtained results demonstrate that the network successfully learned the inverse-projection map and correctly inferred the respective surfaces from fresh curves

Stream Reasoning in Temporal Datalog

In recent years, there has been an increasing interest in extending traditional stream processing engines with logical, rule-based, reasoning capabilities. This poses significant theoretical and practical challenges since rules can derive new information and propagate it both towards past and future time points; as a result, streamed query answers can depend on data that has not yet been received, as well as on data that arrived far in the past. Stream reasoning algorithms, however, must be able to stream out query answers as soon as possible, and can only keep a limited number of previous input facts in memory. In this paper, we propose novel reasoning problems to deal with these challenges, and study their computational properties on Datalog extended with a temporal sort and the successor function (a core rule-based language for stream reasoning applications)

Automatic creation of boundary-representation models from single line drawings

This thesis presents methods for the automatic creation of boundary-representation models of polyhedral objects from single line drawings depicting the objects. This topic is important in that automated interpretation of freehand sketches would remove a bottleneck in current engineering design methods. The thesis does not consider conversion of freehand sketches to line drawings or methods which require manual intervention or multiple drawings. The thesis contains a number of novel contributions to the art of machine interpretation of line drawings. Line labelling has been extended by cataloguing the possible tetrahedral junctions and by development of heuristics aimed at selecting a preferred labelling from many possible. The ”bundling” method of grouping probably-parallel lines, and the use of feature detection to detect and classify hole loops, are both believed to be original. The junction-line-pair formalisation which translates the problem of depth estimation into a system of linear equations is new. Treating topological reconstruction as a tree-search is not only a new approach but tackles a problem which has not been fully investigated in previous work

A Modelling and Simulation Tool for DNA Strand Displacement Systems

DNA is the hereditary material in almost all organisms, and the sequence of its monomers efficiently conveys essential biological information. Although DNA is well known for its biological functions, the unique material properties of DNA also motivate scientists to design and manufacture DNA complexes for technological purposes. This research field is termed DNA nanotechnology, and it aims to construct arbitrary biomolecular structures using DNA molecules as building blocks. DNA nanotechnology initially focused on programmable static structures, but it has further inspired the designs of engineering systems with dynamic properties such as logic circuits and catalytic systems. This dynamic variant of DNA nanotechnology is enabled by the DNA strand displacement (DSD) mechanism. The design of a DSD system involves discreetly designed initial species that can execute expected sequential reactions. However, such task is hard to be accomplished by hand as the complete reaction network of a large-scaled DSD system can be intractable. In this thesis, we study the problem of modelling DSD systems, i.e., enumerating combinatorially the full space of molecular complexes reachable from the initial species and transferring the resulting chemical reaction network to a simulation engine. We present a rule-based modelling pipeline RuleDSD for generating and simulating reaction networks of DSD systems. RuleDSD is implemented as a software package DSDPy, a tool that automatically generates a complete reaction network for a described DSD system and integrates with the PySB framework for further simulations using the BioNetGen engine. The reaction networks produced by DSDPy show that it is suitable for modelling various DSD systems from existing literature

Administrative burdens in the European food industry : with special attention to the dairy sector

This report investigates the relationship between administrative burdens and competitiveness in the European dairy industry. A firm perspective is used. The relationship between administrative burdens and competitiveness has been broken down into four aspects: innovation, deployment of food safety and quality systems, food labelling and supply chain transparenc