Efficient reverse k-nearest neighbor estimation

The reverse k-nearest neighbor (RkNN) problem, i.e. finding all objects in a data set the k-nearest neighbors of which include a specified query object, has received increasing attention recently. Many industrial and scientific applications call for solutions of the RkNN problem in arbitrary metric spaces where the data objects are not Euclidean and only a metric distance function is given for specifying object similarity. Usually, these applications need a solution for the generalized problem where the value of k is not known in advance and may change from query to query. In addition, many applications require a fast approximate answer of RkNN-queries. For these scenarios, it is important to generate a fast answer with high recall. In this paper, we propose the first approach for efficient approximative RkNN search in arbitrary metric spaces where the value of k is specified at query time. Our approach uses the advantages of existing metric index structures but proposes to use an approximation of the nearest-neighbor-distances in order to prune the search space. We show that our method scales significantly better than existing non-approximative approaches while producing an approximation of the true query result with a high recall.     

The Effects of User-fee Policy on Attendance Rates among Kenyan Elementary Schoolchildren

What happens when a government cannot meet its obligation to provide universal primary education and enhance the quality of education for all of its citizens? The present study examines the interactions among stakeholders in the user-fee policy in primary education in Kenya. It seeks to show how this policy has affected attendance rates and drop-out rates among elementary schoolchildren. It reveals that, in addition to limiting access and contributing to attrition, user-fees significantly contribute to absenteeism. The study also exposes the dire situation of economically vulnerable citizens who do not have the resources which they need to ensure private education for their children. It concludes that together the government and household-level economic weaknesses have made it virtually impossible to attain the goal of education for all in Kenya.     

Development,direction, and damage limitation: Social learning in domestic fowl

This review highlights two areas of particular interest in the study of social learning in fowl. First, the role of social learning in the development of feeding and foraging behavior in young chicks and older birds is described. The role of the hen as a demonstrator and possible teacher is considered, and the subsequent social influence of brood mates and other companions on food avoidance and food preference learning is discussed. Second, the way in which work on domestic fowl has contributed to an understanding of the importance of directed social learning is examined. The well-characterized hierarchical social organization of small chicken flocks has been used to design studies which demonstrate that the probability of social transmission is strongly influenced by social relationships between birds. The practical implications of understanding the role of social learning in the spread of injurious behaviors in this economically important species are briefly considered.     

Extinction and retraining of simultaneous and successive flavor conditioning

In three experiments, rats received pairings of flavor conditioned stimuli with polycose unconditioned stimuli, in either a simultaneous or a sequential relation. Both temporal relations produced excellent conditioned increases in consumption of the flavors. Separate presentation of the flavors resulted in extinction in both cases. However, restoring the pairing of the flavor with polycose resulted in reconditioning only with the sequential, not with the simultaneous, relation.