An MDA approach to knowledge engineering

This paper proposes an MDA approach to knowledge engineering, centered on the CommonKADS knowledge model. The latter corresponds to the CIM level of MDA whereas PRR, which represents production rules and rulesets, corresponds to the PIM level. The paper explores the mapping between CommonKADS knowledge models and production rules and rulesets based on PRR. Mapping CommonKADS knowledge models into PRR is very useful, due to the fact that the CIM level remains relatively unexplored, despite its key role in MDA. This motivates our choice to focus on the CIM and PIM levels. Furthermore, the mapping between PIM and PSM (i.e. the implementation of production rules in specific rule-based systems) constitutes less of an issue. To map CommonKADS knowledge models into PRR production rules and rulesets, we propose and illustrate a set of transformations. To ease these transformations, we start by grouping elements of the CommonKADS knowledge models into so-called “inference groups”. We propose and illustrate an algorithm that defines these inference groups automatically. The definition of transformations between models (CIM to PIM levels) requires a specific metamodel for CommonKADS as well as a dedicated metamodel for PRR. Unlike PRR, there is no published CommonKADS metamodel. This paper proposes a comprehensive CommonKADS knowledge metamodel. We describe and discuss an example, applying the whole approach.     

Towards identifying the roll motion parameters of a motorcycle simulator

This study aimed at identifying the roll motion parameters of a motorcycle simulator prototype. Experienced motorcyclists tuned the angular physical movement of the mock-up and that of the visual scene to achieve an optimal riding experience during curves. The participants exceeded the rolling angles that would be required in real-world riding, while avoiding leaning the mock-up beyond 10°. In addition, they were more influenced by the speed of the virtual motorcycle than by road curvature, especially in a wide field of view. Heterogeneity was found in the roll applied to the visual scene. The overall patterns suggest that at least when washout is not applied to remove the side forces that in real-world riding are compensated by a centrifugal force, greater roll of the visual at the expense of the mock-up is mandatory to avoid performance biases that might be enhanced due to fear of falling off the simulator. Future roll motion models must take into consideration factors such as riding postures, which might not only influence the forces operating on the rider-motorcycle system, but also how motorcyclists perceive the visual world.     

Strain differences in the isolation-induced effects on prepulse inhibition of the acoustic startle response and on locomotor activity.

The authors investigated the effects of isolation rearing on acoustic startle response, prepulse inhibition (PPI), its modification by apomorphine, and locomotor activity in 3 rat strains: Wistar (WS), Sprague-Dawley (SD), and Lister hooded (ListH). SD and ListH, but not WS, showed isolation-induced PPI deficits. In 2 consecutive PPI tests, only SD isolates showed significant PPI deficits. An isolation rearing effect in ListH was significant only in the 1st PPI test. Apomorphine dose-dependently (0.0–0.5 mg/kg) disrupted PPI, but sensitivity to the drug differed, with WS and SD rats being more sensitive to lower doses (0.01–0.05 mg/kg) than ListH rats (0.5 mg/kg). Isolates, irrespective of strain, did not differ from grouped rats in their response to the apomorphine challenge. Only WS and ListH isolates demonstrated significantly increased locomotor activity. Strain differences in the different parameters measured did not predict isolation-induced effects on PPI. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Stabilization of the inverted pendulum around its homoclinic orbit

The inverted pendulum has been used as a benchmark for motivating the study of nonlinear control techniques. We propose a simple controller for balancing the inverted pendulum and raise it to its upper equilibrium position while the cart displacement is brought to zero. The control strategy is based on an energy approach of the cart and pendulum system.     

Influences of haptic communication on a shared manual task

With the advent of new haptic feedback devices, researchers are giving serious consideration to the incorporation of haptic communication in collaborative virtual environments. For instance, haptic interactions based tools can be used for medical and related education whereby students can train in minimal invasive surgery using virtual reality before approaching human subjects. To design virtual environments that support haptic communication, a deeper understanding of humans′ haptic interactions is required. In this paper, human′s haptic collaboration is investigated. A collaborative virtual environment was designed to support performing a shared manual task. To evaluate this system, 60 medical students participated to an experimental study. Participants were asked to perform in dyads a needle insertion task after a training period. Results show that compared to conventional training methods, a visual-haptic training improves user′s collaborative performance. In addition, we found that haptic interaction influences the partners′ verbal communication when sharing haptic information. This indicates that the haptic communication training changes the nature of the users′ mental representations. Finally, we found that haptic interactions increased the sense of copresence in the virtual environment: haptic communication facilitates users′ collaboration in a shared manual task within a shared virtual environment. Design implications for including haptic communication in virtual environments are outlined.     

Visualization of Neural Network Predictions for Weather Forecasting

Recurrent neural networks are prime candidates for learning evolutions in multi‐dimensional time series data. The performance of such a network is judged by the loss function, which is aggregated into a scalar value that decreases during training. Observing only this number hides the variation that occurs within the typically large training and testing data sets. Understanding these variations is of highest importance to adjust network hyper‐parameters, such as the number of neurons, number of layers or to adjust the training set to include more representative examples. In this paper, we design a comprehensive and interactive system that allows users to study the output of recurrent neural networks on both the complete training data and testing data. We follow a coarse‐to‐fine strategy, providing overviews of annual, monthly and daily patterns in the time series and directly support a comparison of different hyper‐parameter settings. We applied our method to a recurrent convolutional neural network that was trained and tested on 25 years of climate data to forecast meteorological attributes, such as temperature, pressure and wind velocity. We further visualize the quality of the forecasting models, when applied to various locations on the Earth and we examine the combination of several forecasting models.     

Youth gambling behaviors: An examination of the role of resilience.

The study of resilient children has overturned many deficit-focused models concerning the ontogenesis of children raised in adversity. This study explored the relationship between risk and protective factors, resilience, and youth gambling behavior. More specifically, this study examined the relative contribution of various risk and protective domains in relation to problem gambling behavior and examined whether youth identified as resilient (high risk exposure- high internalized protection) were as likely as those identified as vulnerable (high risk exposure-low internalized protection) to engage in excessive gambling behavior. The sample consisted of 1,273 students ages 12 to 19. The findings demonstrated that risk and protective factors each provide a unique contribution to the prediction model of gambling problems. Resilient and vulnerable youth differed significantly in their self-reported gambling severity. As well, resilient youth were not statistically distinguishable from low-risk exposure groups in terms of their gambling severity. Findings are interpreted with respect to resilience and prevention research. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Cognitive control by brain-injured car drivers: an exploratory study

Cognitive control is a key tool for adaptation in dynamic situations. The aim of the study is to assess the relevance of a theoretical framework for cognitive control in dynamic situations, in order to understand brain-injured (BI) car drivers' cognitive impairment. The framework supports a cognitive control multimodality based on the crossing of two orthogonal dimensions: symbolic/subsymbolic; anticipative/reactive control. BI car drivers' behaviour was compared with that of a control group (CTRL) during driving simulator scenarios. Eye movement analysis, among other variables, revealed that BI car drivers made use of a more symbolic and reactive control than did CTRL drivers. CTRL drivers showed a more stable cognitive compromise than BI drivers. The latter became less symbolic and more reactive in the case of difficult scenarios. In addition, BI drivers focused on the main task of trajectory management, with fewer resources devoted to traffic interaction management. STATEMENT OF RELEVANCE: An explanation of differences between BI and CTRL drivers in terms of cognitive control requirements, attention and processing speed is put forward. From this, it is possible to derive some implications in terms of driver assistance (e.g. lane keeping or a warning assistance device) and rehabilitation.     

On Modeling Coordination via Asynchronous Communication and Enhanced Matching

The paper proposes a theoretical study of a coordination language embodying Linda's asynchronous communication primitive with a refined matching mechanism based on pairs composed of attribute names associated with their values. Computations in this language are described by means of an operational semantics, reporting the whole traces of executions. The non-compositionality of this intuitive operational semantics motivates the design of a compositional and fully abstract denotational semantics, which is then exploited for studying program equivalence in this setting.