Spatial data mining is the process of discovering, motivating and previously unknown, but potentially helpful patterns from large spatial datasets. Extracting interesting and useful patterns from spatial datasets is more tricky than extracting the parallel patterns from established numeric and definite data due to the complexity of spatial data types, spatial relationships, and spatial autocorr...

Background: The genetic variants identified by three large genome-wide association studies (GWAS) of educational attainment and the largest intelligence GWAS were used to test a polygenic selection model. Methods: Average frequencies of alleles with positive effect (polygenic scores or PS) were compared across populations (N=26) using data from 1000 Genomes. Factor analysis was used to extract ...

We present an algorithm to compute the set of perfect public equilibrium payoffs as the discount factor tends to one for stochastic games with observable states and public (but not necessarily perfect) monitoring when the limiting set of (long-run players’) equilibrium payoffs is independent of the state. This is the case, for instance, if the Markov chain induced by any Markov strategy profile...

This note studies the relationship between a player’s (stage game) minmax payoff and the (lowest) individually rational payoff in repeated games with imperfect monitoring. We characterize the signal structures under which these two payoffs coincide for any payoff matrix. Under an identifiability assumption, we further show that, if the monitoring structure of an infinitely repeated game ‘nearly...

Meaningful use of the autocorrelation in jet noise analysis is examined. The effect of peak frequency on the autocorrelation function width is removed through a temporal scaling prior to making comparisons between measurements or drawing conclusions about source characteristics. In addition, a Hilbert transform-based autocorrelation envelope helps to define consistent characteristic time scales...

In this paper we analyze the application of the Ant Colony Optimization to the Minimum Weight Vertex Covering Problem. We use the software system that we developed and implemented different standard ACO algorithms to this problem: Ant Colony System, the use of Elitism, Rank based approach and the MinMax system. We have made a comparative assessment of the effectiveness of these algorithms to th...

In this paper we consider the problem of computing an optimum set of watchmen routes in a histogram. A watchman, in the terminology of art galleries, is a mobile guard and in this version we want to minimize the length of the longest route in the solution. We give an O(n 2 log n) time algorithm to compute the MinMax optimum set of m watchmen in a histogram polygon and we extend the algorithm to...

Score normalization and results merging are important components of many IR applications. Recently MinMax—an unsupervised linear score normalization method—was shown to perform quite well across various distributed retrieval testbeds, although based on strong assumptions. The CORI results merging method relaxes these assumptions to some extent and significantly improves the performance of MinMa...

The relationship between conditions in the local environment and individual-level behavior is of general interest to many fields of research. Unfortunately, researchers often encounter situations where individuals’ locations are reported at the region-level, and modeling individual-level outcomes as a function of region-level data introduces the potential for biased estimates. We show analytica...

This paper investigates single-family residential development for housing market equilibria using microeconomic theory and disaggregate spatial data. Mixed logit models and notions of price competition are used to simulate household location choices for three different household segments, assuming job sites of household members are known. Consistent with bid-rent theory, housing market equilibr...