Dynamic Geospatial Spectrum Modelling: Taxonomy, Options and Consequences

Much of the research in Dynamic Spectrum Access (DSA) has focused on opportunistic access in the temporal domain. While this has been quite useful in establishing the technical feasibility of DSA systems, it has missed large sections of the overall DSA problem space. In this paper, we argue that the spatio-temporal operating context of specific environments matters to the selection of the appropriate technology for learning context information. We identify twelve potential operating environments and compare four context awareness approaches (on-board sensing, databases, sensor networks, and cooperative sharing) for these environments. Since our point of view is overall system cost and efficiency, this analysis has utility for those regulators whose objectives are reducing system costs and enhancing system efficiency. We conclude that regulators should pay attention to the operating environment of DSA systems when determining which approaches to context learning to encourage

Evolving information systems: meeting the ever-changing environment

To meet the demands of organizations and their ever-changing environment, information systems are required which are able to evolve to the same extent as organizations do. Such a system has to support changes in all time-and application-dependent aspects. In this paper, requirements and a conceptual framework for evolving information systems are presented. This framework includes an architecture for such systems and a revision of the traditional notion of update. Based on this evolutionary notion of update (recording, correction and forgetting) a state transition-oriented model on three levels of abstraction (event level, recording level, correction level) is introduced. Examples are provided to illustrate the conceptual framework for evolving information systems

Root Cause Analysis in Business Processes

Conceptual modeling is an important tool for understanding and revealing weaknesses of business processes. Yet, the current practice in reengineering projects often considers simply the as-is control flow and uses the respective model barely as a reference for brain-storming about improvement opportunities. This approach heavily relies on the intuition of the participants and misses a clear description of steps to identify root causes of problems. In contrast to that, this paper introduces a systematic methodology to detect and document the quality dimension of a business process. It builds on the definition of softgoals for each process activity, of correlations between softgoals, and metrics to measure the occurrence of quality issues. In this regard our contribution is a foundation of root-cause analysis in business process modeling, and a conceptual integration of goal-based and activity-based approaches to capturing processes

Parallel processing and expert systems

Whether it be monitoring the thermal subsystem of Space Station Freedom, or controlling the navigation of the autonomous rover on Mars, NASA missions in the 90's cannot enjoy an increased level of autonomy without the efficient use of expert systems. Merely increasing the computational speed of uniprocessors may not be able to guarantee that real time demands are met for large expert systems. Speed-up via parallel processing must be pursued alongside the optimization of sequential implementations. Prototypes of parallel expert systems have been built at universities and industrial labs in the U.S. and Japan. The state-of-the-art research in progress related to parallel execution of expert systems was surveyed. The survey is divided into three major sections: (1) multiprocessors for parallel expert systems; (2) parallel languages for symbolic computations; and (3) measurements of parallelism of expert system. Results to date indicate that the parallelism achieved for these systems is small. In order to obtain greater speed-ups, data parallelism and application parallelism must be exploited

Supporting software maintenance with non-functional information

The paper highlights the role of non functional information (about efficiency, reliability and other software attributes) of software components in software maintenance, focusing in the component programming framework. Non functional information is encapsulated in modules bound to both definitions and implementations of software components and it is written as expressions in a classical programming language. It is shown with an example how this notation supports software maintenance, with the help of an algorithm which is able to select the best implementation of a software component in its context of use, meaning byPeer ReviewedPostprint (published version

Using Ontologies for the Design of Data Warehouses

Obtaining an implementation of a data warehouse is a complex task that forces designers to acquire wide knowledge of the domain, thus requiring a high level of expertise and becoming it a prone-to-fail task. Based on our experience, we have detected a set of situations we have faced up with in real-world projects in which we believe that the use of ontologies will improve several aspects of the design of data warehouses. The aim of this article is to describe several shortcomings of current data warehouse design approaches and discuss the benefit of using ontologies to overcome them. This work is a starting point for discussing the convenience of using ontologies in data warehouse design.Comment: 15 pages, 2 figure

UVMag: Space UV and visible spectropolarimetry

UVMag is a project of a space mission equipped with a high-resolution spectropolarimeter working in the UV and visible range. This M-size mission will be proposed to ESA at its M4 call. The main goal of UVMag is to measure the magnetic fields, winds and environment of all types of stars to reach a better understanding of stellar formation and evolution and of the impact of stellar environment on the surrounding planets. The groundbreaking combination of UV and visible spectropolarimetric observations will allow the scientists to study the stellar surface and its environment simultaneously. The instrumental challenge for this mission is to design a high-resolution space spectropolarimeter measuring the full-Stokes vector of the observed star in a huge spectral domain from 117 nm to 870 nm. This spectral range is the main difficulty because of the dispersion of the optical elements and of birefringence issues in the FUV. As the instrument will be launched into space, the polarimetric module has to be robust and therefore use if possible only static elements. This article presents the different design possibilities for the polarimeter at this point of the project.Comment: 9 pages, 4 figures, SPIE Conference Astronomical Telescopes + Instrumentation Montreal June 201