Executive redirection to agile IT methods: A proposed pilot effort to radically improve time to value. A credible way to move DoD forward from its traditional and failing IT ways (One-page memorandum, )

Unpublished, but freely shared

Event Processing in the Global Information Grid GIG): Orders of Magnitude Advantage in Information Supply Chains through Context-sensitive Smart Push VIRT

(2nd Event Processing Symposium, Oracle, Redwood Shores, CA

Valuing Persistent ISR Resources

AFCEA-GMU C4I Center Symposium, Challenges in C4I, George Mason University, Fairfax, VA., May 25This paper describes how to optimize PISR resources to maximize VIRT

Webteaching: sequencing of subject matter in relation to prior knowledge of pupils

Two experiments are discussed in which the sequencing procedure of webteaching is compared with a linear sequence for the presentation of text material.\ud \ud In the first experiment variations in the level of prior knowledge of pupils were studied for their influence on the sequencing mode of text presentation. Prior knowledge greatly reduced the effect of the size of sequencing procedures.\ud \ud In the second experiment pupils with a low level of prior knowledge studied a text, following either a websequence or a linear sequence. Webteaching was superior to linear teaching on a number of dependent variables. It is concluded that webteaching is an effective sequencing procedure in those cases where substantial new learning is required

Dealing with mobility: Understanding access anytime, anywhere

The rapid and accelerating move towards the adoption and use of mobile technologies has increasingly provided people and organisations with the ability to work away from the office and on the move. The new ways of working afforded by these technologies are often characterised in terms of access to information and people ‘anytime, anywhere’. This paper presents a study of mobile workers that highlights different facets of access to remote people and information, and different facets of anytime, anywhere. Four key factors in mobile work are identified from the study: the role of planning, working in ‘dead time’, accessing remote technological and informational resources, and monitoring the activities of remote colleagues. By reflecting on these issues, we can better understand the role of technology and artefact use in mobile work and identify the opportunities for the development of appropriate technological solutions to support mobile workers

Semantic Correctness in Adaptive Process Management Systems

Abstract. Adaptivity in Process Management Systems (PMS) is key to their successful applicability in pratice. Approaches have already been de-veloped to ensure the system correctness after arbitrary process changes at the syntactical level. However, still errors may be caused at the se-mantical level. Therefore, the integration of application knowledge will flag a milestone in the development of process management technology. In this paper, we introduce a framework for defining semantic constraints over processes in such a way that they can express real-world applica-tion knowledge. On the other hand, these constraints are still manageable concerning the effort for maintenance and semantic process verification. This can be used, for example, to detect semantic conflicts when ap-plying process changes (e.g., drug incompatibilities). In order to enable the PMS to deal with such semantic conflicts we also introduce a notion of semantic correctness and discuss how to (efficiently) verify semantic correctness in the context of process changes

Semantic Enrichment for Building Information Modeling: Procedure for Compiling Inference Rules and Operators for Complex Geometry

Semantic enrichment of building models adds meaningful domain-specific or application-specific information to a digital building model. It is applicable to solving interoperability problems and to compilation of models from point cloud data. The SeeBIM (Semantic Enrichment Engine for BIM) prototype software encapsulates domain expert knowledge in computer readable rules for inference of object types, identity and aggregation of systems. However, it is limited to axis-aligned bounding box geometry and the adequacy of its rule-sets cannot be guaranteed. This paper solves these drawbacks by (1) devising a new procedure for compiling inference rule sets that are known a priori to be adequate for complete and thorough classification of model objects, and (2) enhancing the operators to compute complex geometry and enable precise topological rule processing. The procedure for compiling adequate rule sets is illustrated using a synthetic concrete highway bridge model. A real-world highway bridge model, with 333 components of 13 different types and compiled from a laser scanned point cloud, is used to validate the approach and test the enhanced SeeBIM system. All of the elements are classified correctly, demonstrating the efficacy of the approach to semantic enrichment

Machine Learning in Automated Text Categorization

The automated categorization (or classification) of texts into predefined categories has witnessed a booming interest in the last ten years, due to the increased availability of documents in digital form and the ensuing need to organize them. In the research community the dominant approach to this problem is based on machine learning techniques: a general inductive process automatically builds a classifier by learning, from a set of preclassified documents, the characteristics of the categories. The advantages of this approach over the knowledge engineering approach (consisting in the manual definition of a classifier by domain experts) are a very good effectiveness, considerable savings in terms of expert manpower, and straightforward portability to different domains. This survey discusses the main approaches to text categorization that fall within the machine learning paradigm. We will discuss in detail issues pertaining to three different problems, namely document representation, classifier construction, and classifier evaluation.Comment: Accepted for publication on ACM Computing Survey