CONTEXTUALIZING LEARNING OBJECTS USING ONTOLOGIES

Educational research over the past three years has intensified such that the context of learning resources needs to be properly modeled. Many researchers have described and even mandated the use of ontologies in the research being conducted, yet the process of actually connecting one or more ontologies to a learning object has not been extensively discussed. This paper describes a practical model for associating multiple ontologies with learning objects while making full use of the IEEE LOM specification. The model categorizes these ontologies according to five major categories of context based on the most popular fields of study actively being pursued by the educational research community: Thematic context, Pedagogical context, Learner context, Organizational context, and Historical/Statistical context.     

New multiresolution modeling techniques in CAD

To apply wavelet transformation to CAD surface model composed of multiple surface patches, an algorithm called wavelet signal separation to preserve geometric constraints during wavelet transformation is proposed. The algorithm divides the B-spline control points into those associated and those unassociated with the geometric constraints. Through preserving the signal information associated with the constraint control points, the geometric constraints can be automatically preserved after wavelet transformation. This paper also briefly investigates two types of the detail feature propagation technique in wavelet-based multiresolution CAD system. One is detail feature motion. The other is detail feature repetition. Finally, a comprehensive example is presented to illustrate the effects of the combination of those techniques.     

Implicit, long-term spatial contextual memory.

Learning and memory of novel spatial configurations aids behaviors such as visual search through an implicit process called contextual cuing (M. M. Chun & Y. Jiang, 1998). The present study provides rigorous tests of the implicit nature of contextual cuing. Experiment 1 used a recognition test that closely matched the learning task, confirming that memory traces of predictive spatial context were not accessible to conscious retrieval. Experiment 2 gave explicit instructions to encode visual context during learning, but learning was not improved and conscious memory remained undetectable. Experiment 3 illustrates that memory traces for spatial context may persist for at least 1 week, suggesting a long-term component of contextual cuing. These experiments indicate that the learning and memory of spatial context in the contextual cuing task are indeed implicit. The results have implications for understanding the neural substrate of spatial contextual learning, which may depend on an intact medial temporal lobe system that includes the hippocampus (M. M. Chun & E. A. Phelps, 1999). (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Modeling Effects of Rhythmic Context on Perceived Duration: A Comparison of Interval and Entrainment Approaches to Short-Interval Timing.

Relative merits of interval and entrainment conceptions of the internal clock were assessed within a common theoretical framework by 4 time-judgment experiments. The timing of tone onsets marking the beginning and ending of standard and comparison time intervals relative to a context rhythm were manipulated: onsets were on time, early, or late relative to the implied rhythm, and 2 distinct accuracy patterns emerged. A quadratic ending profile indicated best performance when the standard ended on time and worst performance when it was early or late, whereas a flat beginning profile (Experiments 1-3) indicated uniform performance for the 3 expectancy conditions. Only in Experiment 4, in which deviations from expected onset times were large, did significant effects of beginning times appear in time-discrimination thresholds and points of subjective equality. Findings are discussed in the context of theoretical assumptions about clock resetting, the representation of time, and independence of successive time intervals. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Distributed Context Retrieval and Consistency Control in Pervasive Computing

The challenge of saturating all phases of pervasive service provision with context-aware functionality lies in coping with the complexity of maintaining, retrieving and distributing context information. To efficiently represent and query context information a sophisticated modelling scheme should exist. To distribute and synchronise context knowledge in various context repositories across a multitude of administrative domains, streamlined mechanisms are needed. This paper elaborates on an innovative context management framework that has been designed to cope with free-text and location based context retrieval and efficient context consistency control. The proposed framework has been incorporated in a multi-functional pervasive services platform, while most of the mechanisms it employs have been empirically evaluated.     

Error handling in a parallel LR substring parser

Parallel parsing is currently receiving attention but there is little discussion about the adaptation of sequential error handling techniques to these parallel algorithms. We describe a noncorrecting error handler implemented with a parallel LR substring parser. The parser used is a parallel version of Cormack's LR substring parser. The applicability of noncorrecting error handling for parallel parsing is discussed. The error information provided for a standard set of 118 erroneous Pascal programs is analysed. The programs are run on the sequential LR substring parser.     

Safe and intuitive manual guidance of a robot manipulator using adaptive admittance control towards robot agility

Key areas of robot agility include methods that increase capability and flexibility of industrial robots and facilitate robot re-tasking. Manual guidance can achieve robot agility effectively, provided that a safe and smooth interaction is guaranteed when the user exerts an external force on the end effector. We approach this by designing an adaptive admittance law that can adjust its parameters to modify the robot compliance in critical areas of the workspace, such as near and on configuration singularities, joint limits, and workspace limits, for a smooth and safe operation. Experimental validation was done with two tests: a constraint activation test and a 3D shape tracing task. In the first one, we validate the proper response to constraints and in the second one, we compare the proposed approach with different admittance parameter tuning strategies using a drawing task where the user is asked to guide the robot to trace a 3D profile with an accuracy or speed directive and evaluate performance considering path length error and execution time as metrics, and a questionnaire for user perception. Results show that appropriate response to individual and simultaneous activation of the aforementioned constraints for a safe and intuitive manual guidance interaction is achieved and that the proposed parameter tuning strategy has better performance in terms of accuracy, execution time, and subjective evaluation of users.     

gain bounds for systems with sector bounded and slope‐restricted nonlinearities

This paper proposes a new method for calculating a bound on the gain of a system comprising a linear time invariant part and a static nonlinear part, which is odd, bounded, zero at zero and has a restriction on its slope. The nonlinear part is also assumed to be sector bounded, with the sector bound being (possibly) different from that implied by the slope restriction. The computation of the gain bound is found by solving a set of linear matrix inequalities, which arise from an integral quadratic constraint formulation of a multiplier problem involving both Zames‐Falb and Popov multipliers. Examples illustrate the effectiveness of the results, and comparisons are made against the state‐of‐the‐art. Copyright © 2011 John Wiley & Sons, Ltd.     

Routing with multiple quality-of-services constraints: An approximation perspective

Finding a path that satisfies multiple Quality-of-Service (QoS) constraints is vital to the deployment of current emerged services. However, existing algorithms are not very efficient and effective at finding such a path. Moreover, few works focus on three or more QoS constraints. In this paper, we present an enhanced version of fully polynomial time approximation scheme (EFPTAS) for multiconstrainted path optimal (MCOP) problem. Specifically, we make four major contributions. We first allow the proposed algorithm to construct an auxiliary graph, through which the QoS parameters on each of the finding path can be guaranteed not to exceed the given constraints. Then we adopt a concept, called nonlinear definition of path constraints in EFPTAS for reducing both time and space complexity. Also, we enable EFPTAS to run iteratively to facilitate a progressive refinement of the finding result. In addition to these, we identify some “deployment” issues for proposed algorithm, the essential steps that how and when the EFPTAS takes place are presented. By analyzing the proposed algorithm theoretically, we find that the presented EFPTAS can find a (1+ε)-approximation path in the network with time complexity O(|E||V|/ε) (where |E| is the number of edges and |V| is the number of nodes), which outperforms the previous best-known algorithm for MCOP. We conduct an extensive comparison between the algorithm presented in this paper and previous best-known study experimentally, our results indicate that EFPTAS can find a path with low complexity and preferable quality.