Query Evaluation in Deductive Databases

It is desirable to answer queries posed to deductive databases by computing fixpoints because such computations are directly amenable to set-oriented fact processing. However, the classical fixpoint procedures based on bottom-up processing — the naive and semi-naive methods — are rather primitive and often inefficient. In this article, we rely on bottom-up meta-interpretation for formalizing a new fixpoint procedure that performs a different kind of reasoning: We specify a top-down query answering method, which we call the Backward Fixpoint Procedure. Then, we reconsider query evaluation methods for recursive databases. First, we show that the methods based on rewriting on the one hand, and the methods based on resolution on the other hand, implement the Backward Fixpoint Procedure. Second, we interpret the rewritings of the Alexander and Magic Set methods as specializations of the Backward Fixpoint Procedure. Finally, we argue that such a rewriting is also needed in a database context for implementing efficiently the resolution-based methods. Thus, the methods based on rewriting and the methods based on resolution implement the same top-down evaluation of the original database rules by means of auxiliary rules processed bottom-up

Upside-down Deduction

Over the recent years, several proposals were made to enhance database systems with automated reasoning. In this article we analyze two such enhancements based on meta-interpretation. We consider on the one hand the theorem prover Satchmo, on the other hand the Alexander and Magic Set methods. Although they achieve different goals and are based on distinct reasoning paradigms, Satchmo and the Alexander or Magic Set methods can be similarly described by upside-down meta-interpreters, i.e., meta-interpreters implementing one reasoning principle in terms of the other. Upside-down meta-interpretation gives rise to simple and efficient implementations, but has not been investigated in the past. This article is devoted to studying this technique. We show that it permits one to inherit a search strategy from an inference engine, instead of implementing it, and to combine bottom-up and top-down reasoning. These properties yield an explanation for the efficiency of Satchmo and a justification for the unconventional approach to top-down reasoning of the Alexander and Magic Set methods

Context-based task ontologies for clinical guidelines

Evidence-based medicine relies on the execution of clinical practice guidelines and protocols. A great deal of of effort has been invested in the development of various tools which automate the representation and execution of the recommendations contained within such guidelines and protocols by creating Computer Interpretable Guideline Models (CIGMs). Context-based task ontologies (CTOs), based on standard terminology systems like UMLS, form one of the core components of such a model. We have created DAML+OIL-based CTOs for the tasks mentioned in the WHO guideline for hypertension management, drawing comparisons also with other related guidelines. The advantages of CTOs include: contextualization of ontologies, providing ontologies tailored to specific aspects of the phenomena of interest, dividing the complexity involved in creating ontologies into different levels, providing a methodology by means of which the task recommendations contained within guidelines can be integrated into the clinical practices of a health care set-up

Promoting active learning in Universiti Teknologi Malaysia: A bottom-up, top-down approach

Being a leading technological higher education institute in the country, Universiti Teknologi Malaysia (UTM) is aggressively encouraging teaching staff to enhance teaching and learning to produce graduates who are relevant in today’s highly competitive world. To achieve this goal, grassroots awareness and training campaign, followed by encouragements are rigorously made. Active learning techniques, especially the Cooperative Learning (CL) and Problem Based Learning (PBL) are currently being promoted across all disciplines as well as levels of studies. This effort which was initiated by a group of enthusiastic teaching staff received a welcome endorsement from the highest level of university administrative key personnel. A special task force called CL-PBL Support Group was then set up to facilitate the promotion of CL and PBL practices across the board. At implementation level, faculty-based core groups were set up and trained to acquire and apply the necessary knowledge and teaching skills pertaining to these active learning approaches. This paper describes strategies and efforts to convince and encourage the implementation of active learning techniques among teaching staff and administrators, especially those in the engineering and engineering-related faculties. Training and support provided to academic staff are also discussed. Finally, factors that influence the success of university-wide implementation will be included

Modeling laser wakefield accelerators in a Lorentz boosted frame

Modeling of laser-plasma wakefield accelerators in an optimal frame of reference \cite{VayPRL07} is shown to produce orders of magnitude speed-up of calculations from first principles. Obtaining these speedups requires mitigation of a high-frequency instability that otherwise limits effectiveness in addition to solutions for handling data input and output in a relativistically boosted frame of reference. The observed high-frequency instability is mitigated using methods including an electromagnetic solver with tunable coefficients, its extension to accomodate Perfectly Matched Layers and Friedman's damping algorithms, as well as an efficient large bandwidth digital filter. It is shown that choosing the frame of the wake as the frame of reference allows for higher levels of filtering and damping than is possible in other frames for the same accuracy. Detailed testing also revealed serendipitously the existence of a singular time step at which the instability level is minimized, independently of numerical dispersion, thus indicating that the observed instability may not be due primarily to Numerical Cerenkov as has been conjectured. The techniques developed for Cerenkov mitigation prove nonetheless to be very efficient at controlling the instability. Using these techniques, agreement at the percentage level is demonstrated between simulations using different frames of reference, with speedups reaching two orders of magnitude for a 0.1 GeV class stages. The method then allows direct and efficient full-scale modeling of deeply depleted laser-plasma stages of 10 GeV-1 TeV for the first time, verifying the scaling of plasma accelerators to very high energies. Over 4, 5 and 6 orders of magnitude speedup is achieved for the modeling of 10 GeV, 100 GeV and 1 TeV class stages, respectively

Cooperative learning in process dynamics & control course for undergraduate chemical engineering students

titute in the country, Universiti Teknologi Malaysia (UTM) is aggressively encouraging teaching staff to enhance teaching and learning to produce graduates who are relevant in today’s highly competitive world. To achieve this goal, grassroots awareness and training campaign, followed by encouragements are rigorously made. Active learning techniques, especially the Cooperative Learning (CL) and Problem Based Learning (PBL) are currently being promoted across all disciplines as well as levels of studies. This effort which was initiated by a group of enthusiastic teaching staff received a welcome endorsement from the highest level of university administrative key personnel. A special task force called CL-PBL Support Group was then set up to facilitate the promotion of CL and PBL practices across the board. At implementation level, faculty-based core groups were set up and trained to acquire and apply the necessary knowledge and teaching skills pertaining to these active learning approaches. This paper describes strategies and efforts to convince and encourage the implementation of active learning techniques among teaching staff and administrators, especially those in the engineering and engineering-related faculties. Training and support provided to academic staff are also discussed. Finally, factors that influence the success of university-wide implementation will be included