Integration and segmentation in European investment services markets: assessing the implications for international real estate investment

This paper analyses developments in the growth and configuration of the institutional savings markets within the European Union. The paper discusses the changing socio-economic context in which investment services within the EU are being delivered. The is followed by an examination of drivers of market integration such as the growth and consolidation of the fund management industry, the demographic and fiscal pressures for reform of pensions markets and the process and effects of the deregulation of investment services markets. There is a review of outstanding sources of market segmentation. The projections for future growth in pensions are outlined and implications for real estate investment assessed. It is concluded that, although numerous imponderables render reliable quantitative projections problematic, growth and restructuring of the institutional savings market is likely to increase cross-border capital flows to real estate markets.

How could construction supply chain benefit from RFID/GPS integration: a knowledge management perspective

Construction materials and equipment are essential building blocks of every construction project and may account for 50-60 per cent of the total cost of construction. The rate of their utilization, on the other hand, is the element that most directly relates to a project progress. A growing concern in the industry that inadequate efficiency hinders its success could thus be accommodated by turning construction into a logistic process. Although mostly limited, recent attempts and studies show that Radio Frequency IDentification (RFID) applications have significant potentials in construction. However, the aim of this research is to show that the technology itself should not only be used for automation and tracking to overcome the supply chain complexity but also as a tool to generate, record and exchange process-related knowledge among the supply chain stakeholders. This would enable all involved parties to identify and understand consequences of any forthcoming difficulties and react accordingly before they cause major disruptions in the construction process. In order to achieve this aim the study focuses on a number of methods. First of all it develops a generic understanding of how RFID technology has been used in logistic processes in industrial supply chain management. Secondly, it investigates recent applications of RFID as an information and communication technology support facility in construction logistics for the management of construction supply chain. Based on these the study develops an improved concept of a construction logistics architecture that explicitly relies on integrating RFID with the Global Positioning System (GPS). The developed conceptual model architecture shows that categorisation provided through RFID and traceability as a result of RFID/GPS integration could be used as a tool to identify, record and share potential problems and thus vastly improve knowledge management processes within the entire supply chain. The findings thus clearly show a need for future research in this area.

Workflow data exchange semantics, object discovery & integration architecture for cross media production & distribution

There has been a clear lack of common data exchange semantics for inter-organisational workflow management systems where the research has mainly focused on technical issues rather than language constructs. This paper presents the neutral data exchanges semantics required for the workflow integration within the AXAEDIS framework and presents the mechanism for object discovery from the object repository where little or no knowledge about the object is available. The paper also presents workflow independent integration architecture with the AXAEDIS Framework.

Exact error estimates and optimal randomized algorithms for integration

Exact error estimates for evaluating multi-dimensional integrals are considered. An estimate is called exact if the rates of convergence for the low- and upper-bound estimate coincide. The algorithm with such an exact rate is called optimal. Such an algorithm has an unimprovable rate of convergence. The problem of existing exact estimates and optimal algorithms is discussed for some functional spaces that define the regularity of the integrand. Important for practical computations data classes are considered: classes of functions with bounded derivatives and Holder type conditions. The aim of the paper is to analyze the performance of two optimal classes of algorithms: deterministic and randomized for computing multidimensional integrals. It is also shown how the smoothness of the integrand can be exploited to construct better randomized algorithms.

Parallel Monte Carlo approach for integration of the rendering equation

This paper is addressed to the numerical solving of the rendering equation in realistic image creation. The rendering equation is integral equation describing the light propagation in a scene accordingly to a given illumination model. The used illumination model determines the kernel of the equation under consideration. Nowadays, widely used are the Monte Carlo methods for solving the rendering equation in order to create photorealistic images. In this work we consider the Monte Carlo solving of the rendering equation in the context of the parallel sampling scheme for hemisphere. Our aim is to apply this sampling scheme to stratified Monte Carlo integration method for parallel solving of the rendering equation. The domain for integration of the rendering equation is a hemisphere. We divide the hemispherical domain into a number of equal sub-domains of orthogonal spherical triangles. This domain partitioning allows to solve the rendering equation in parallel. It is known that the Neumann series represent the solution of the integral equation as a infinity sum of integrals. We approximate this sum with a desired truncation error (systematic error) receiving the fixed number of iteration. Then the rendering equation is solved iteratively using Monte Carlo approach. At each iteration we solve multi-dimensional integrals using uniform hemisphere partitioning scheme. An estimate of the rate of convergence is obtained using the stratified Monte Carlo method. This domain partitioning allows easy parallel realization and leads to convergence improvement of the Monte Carlo method. The high performance and Grid computing of the corresponding Monte Carlo scheme are discussed.