A multi-scale template method for shape detection with bio-medical applications

In this paper we present a novel methodology based on non-parametric deformable prototype templates for reconstructing the outline of a shape from a degraded image. Our method is versatile and fast and has the potential to provide an automatic procedure for classifying pathologies. We test our approach on synthetic and real data from a variety of medical and biological applications. In these studies it is important to reconstruct accurately the shape of the object under investigation from very noisy data. Here we assume that we have some prior knowledge about the object outline represented by a prototype shape. Our procedure deforms this shape by means of non-affine transformations and the contour is reconstructed by minimizing a newly developed objective function that depends on the transformation parameters. We introduce an iterative template deformation procedure in which the scale of the deformation decreases as the algorithm proceeds. We compare our results with those from a Gaussian Mixture Model segmentation and two state-of-the-art Level Set methods. This comparison shows that the proposed procedure performs consistently well on both real and simulated data. As a by-product we develop a new filter that recovers the connectivity of a shape.

An investigation of the option space in conceptual building design for advanced building simulation

This article describes research conducted to gather empirical evidence on size, character and content of the option space in building design projects. This option space is the key starting point for the work of any climate engineer using building performance simulation who is supporting the design process. The underlying goal is to strengthen the role of advanced computing in building design, especially in the early conceptual stage, through a better integration of building performance simulation tools augmented with uncertainty analysis and sensitivity analysis. Better integration will need to assist design rather than automate design, allowing a spontaneous, creative and flexible process that acknowledges the expertise of the design team members. This research investigates and contrasts emergent option spaces and their inherent uncertainties in an artificial setting (student design studios) and in real-life scenarios (commercial design project case studies). The findings provide empirical evidence of the high variability of the option space that can be subjected to uncertainty analysis and sensitivity analysis.     

Finding Your True IT Transformation

If you want to transform your business and cause a dramatic improvement for the enterprise, you'll need to start by truly transforming your IT life cycle. It's easy to believe that IT is truly reinventing itself by hiring new people, installing new tools, or preaching a new methodology. However, providing transformational leadership starts with the leadership itself along with the development of the three core competencies of strategy, solutions, and implementation. Your job in IT leadership is to develop all three competencies in your organization by cultivating the necessary skills and techniques, and then to cause each of them to happen continuously and concurrently. When these changes become the organization's new habits, you're on the path to true transformation.     

The Green language type system

A programming language that considers basic values and classes as objects brings more opportunities of code reuse and it is easier to use than a language that does not support this feature. However, popular statically typed object-oriented languages do not consider classes as first-class objects because this concept is difficult to integrate with static type checking. They also do not consider basic values as objects for sake of efficiency. This article presents the Green language type system which supports classes as classless objects and offers a mechanism to treat basic values as objects. The result is a reasonably simple type system which is statically typed and easy to implement. It simplifies several other language mechanisms and prevents any infinite regression of metaclasses.     

Making a Clean Sweep of Cultural Heritage

Digitization brings about new ways of analyzing data from cultural heritage areas. Automatic error detection, as input to semiautomatic error correction, is one type of analysis that can be found high on the priority list of cultural heritage data managers and researchers. We describe a general approach to cleaning cultural heritage databases. We present four case studies on databases from different cultural heritage institutions, and describe an information system in which we embed our error detector in a larger framework, enabling researchers to access, check, and correct their data more easily than before.     

Detail-preserving fluid control

We propose a new fluid control technique that uses scale-dependent force control to preserve small-scale fluid detail. Control particles define local force fields and can be generated automatically from either a physical simulation or a sequence of target shapes. We use a multi-scale decomposition of the velocity field and apply control forces only to the coarse-scale components of the flow. Small-scale detail is thus preserved in a natural way avoiding the artificial viscosity often introduced by force-based control methods. We demonstrate the effectiveness of our method for both Lagrangian and Eulerian fluid simulation environments.     

Architectures for Fast Transcoding of H.264/AVC to Quality-Scalable SVC Streams

The scalable extension of H.264/AVC (SVC) was recently standardized, and offers scalability at a minor penalty in rate-distortion efficiency when compared to single-layer H.264/AVC coding. In SVC, a scaled version of the original video sequence can easily be extracted by dropping layers from the stream. However, most of the video content nowadays is still produced in a single-layer format. While decoding and reencoding is a possible solution to introduce scalability in the existing bitstreams, this is an approach which requires a tremendous amount of time and effort. In this paper, we show that transcoding can be used to intelligently derive scalable bitstreams from existing single-layer streams. We focus on SNR scalability, and introduce techniques that are able to create multiple quality layers in the bitstreams. We also discuss bitstream rewriting from SVC to H.264/AVC, and examine how our newly proposed architectures can benefit from the changes that were introduced for bitstream rewriting. Architectures with different rate distribution flexibility and computational complexity are discussed. Rate-distortion performance of transcoding is shown to be comparable to that of reencoding at a fraction of the time needed for the latter.     

An algebra of hybrid systems

Hybrid systems are heterogeneous systems characterised by the interaction of discrete and continuous dynamics. We present a trajectory-based algebraic model for describing hybrid systems; the trajectories used are closely related to streams. The algebra is based on left quantales and left semirings and provides a new application for these algebraic structures. We show that hybrid automata, which are probably the standard tool for describing hybrid systems, can conveniently be embedded into our algebra. Moreover we point out some important advantages of the algebraic approach. In particular, we show how to handle Zeno effects, which are excluded by most other authors. The development of the theory is illustrated by a running example and a larger case study.     

Designing an extensible architecture for Personalized Ambient Information

Ambient displays provide us with information in the background of our awareness. However, as each user has individual wishes and needs of how, which and when information is presented, the acceptance of ambient displays is low.In this paper we introduce an extensible architecture for personalized ambient information.We employ a notification system to extend the capability of a fixture to display more than one variable. Multiple variables can be updated by multiple information providers. Thereby, our architecture covers a broader spectrum of notifications from alarms to ambient information.We evaluate our concept within a dual-task experiment in comparison to preset notifications. The results show a level of self-interruption which is significantly lower than using preset notifications. Therefore our approach outperforms preset notifications and moves ambient displays closer to secondary displays in human–computer interaction.