A Faceted Classification Scheme for Computer-Mediated Discourse

This article describes a classification scheme for computer-mediated discourse that classifies samples in terms of clusters of features, or “facets”. The goal of the scheme is to synthesize and articulate aspects of technical and social context that influence discourse usage in CMC environments. The classification scheme is motivated, presented in detail with support from existing literature, and illustrated through a comparison of two types of weblog (blog) data. In concluding, the advantages and limitations of the scheme are weighed.

Explaining the Long-Term Trend in Violent Crime: A Heuristic Scheme and Some Methodological Considerations

There has been a discontinuous but fairly persistent long-term decline in homicide rates in core European countries since about 1500. Since the 1950s, however, we observe an upward trend in violent crime not only in Europe but in almost all of the economically advanced nations that combine democratic political structures with free-market economies. The paper presents an explanatory scheme designed to account for both, the long decline and its apparent reversal. The theoretical model draws heavily upon ideas taken from the sociological work of Emile Durkheim and Norbert Elias—with some modifications and extensions. It seeks to integrate sociological and historical perspectives and to give due weight to both, structural and developmental forces. A key hypothesis is that the pacifying effects of the erosion of traditional collectivism can only be maintained to the extent by which “cooperative individualism” dominates over against the forces of “disintegrative individualism.” Some suggestions are made concerning the selection of appropriate indicators and the handling of methodological problems related to causal attribution.

Collision Detection: Broad Phase Adaptation from Multi-Core to Multi-GPU Architecture

We present in this paper several contributions on the collision detection optimization centered on hardware performance. We focus on the broad phase which is the first step of the collision detection process and propose three new ways of parallelization of the well-known Sweep and Prune algorithm. We first developed a multi-core model takes into account the number of available cores. Multi-core architecture enables us to distribute geometric computations with use of multi-threading. Critical writing section and threads idling have been minimized by introducing new data structures for each thread. Programming with directives, like OpenMP, appears to be a good compromise for code portability. We then proposed a new GPU-based algorithm also based on the "Sweep and Prune" that has been adapted to multi-GPU architectures. Our technique is based on a spatial subdivision method used to distribute computations among GPUs. Results show that significant speed-up can be obtained by passing from 1 to 4 GPUs in a large-scale environment.