A wireless network consisting of a large number of small sensors with low-power transceivers can be an effective tool for gathering data in a variety of environments. The data collected by each sensor is communicated through the network to a single processing center that uses all reported data to determine characteristics of the environment or detect an event. The communication or message passing process must be designed to conserve the limited energy resources of the sensors. Clustering sensors into groups, so that sensors communicate information only to clusterheads and then the clusterheads communicate the aggregated information to the processing center, may save energy. In this paper, we propose a distributed, randomized clustering algorithm to organize the sensors in a wireless sensor network into clusters. We then extend this algorithm to generate a hierarchy of clusterheads and observe that the energy savings increase with the number of levels in the hierarchy. Results in stochastic geometry are used to derive solutions for the values of parameters of our algorithm that minimize the total energy spent in the network when all sensors report data through the clusterheads to the processing center.

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ments are usually obtained one slice at a time, where each slice is a 2D array of scalar values corresponding to meaIn computed tomography, magnetic resonance imaging and ultrasound imaging, reconstruction of the 3D object from the surements distributed over a plane passing through the 2D scalar-valued slices obtained by the imaging system is diffi-object. The set of planes generating the slices are usually cult because of the large spacings between the 2D slices. The parallel to each other and equispaced along some axis aliasing that results from this undersampling in the direction through the object.orthogonal to the slices leads to two problems, known as the Once these measurement slices have been obtained, the correspondence problem and the tiling problem. A third prob-goal is to enable a human to easily visualize, in 3D, this lem, known as the branching problem, arises because of the large collection of data. Many algorithms have been develstructure of the objects being imaged in these applications. oped for this purpose, but they can all be classified into Existing reconstruction algorithms typically address only one two categories [8]: volume rendering methods and surface or two of these problems. In this paper, we approach all three reconstruction methods.of these problems simultaneously. This is accomplished by imposing a set of three constraints on the reconstructed surface This paper concentrates on surface reconstruction methand then deriving precise correspondence and tiling rules from ods, all of which proceed by extracting the isosurfaces these constraints. The constraints ensure that the regions tiled corresponding to a specified image intensity. Each isosurby these rules obey physical constructs and have a natural face is represented as an assembly of simple surface primiappearance. Regions which cannot be tiled by these rules with-tives, such as triangles or other polygons. Once these surout breaking one or more constraints are tiled with their medial face primitives are calculated, they can be quickly rendered axis (edge Voronoi diagram). Our implementation of the above from different viewpoints using widely available graphics approach generates triangles of 3D isosurfaces from input hardware. This allows the user to quickly examine many which is either a set of contour data or a volume of image different viewing spaces. slices. Results obtained with synthetic and actual medical dataThis paper presents a surface-based algorithm which are presented. There are still specific cases in which our new achieves both faster rendering and lower likelihood of reapproach can generate distorted results, but these cases are much less likely to occur than those which cause distortions construction error than previous surface reconstruction alin other tiling approaches.

Academic theories of aggression can be dichotomized as expressive (in which aggression results from a failure of self control) or instrumental (in which aggression represents the exercise of control over others). We propose that the two sexes hold a parallel distinction in their social representations of aggression; women subscribe to an expressive model, men to an instrumental model. A 20‐item questionnaire was generated by systematic comparison of the two theories with respect to their differential predictions concerning perceived social value, proximate causes, relevant emotions and congnitions, form, aim, social facilitators, and reputational aspects of aggression. Factor analysis indicated a first factor of expressive‐instrumental aggression on which all items had significant loadings. A significant correlation (.46) was found between gender and questionnaire score confirming the hypothesis. The notion of gender‐specific social representations is discussed in terms of its ability to coherently interpret patterns of differences in aggression found in experimental and observational studies.

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