high-level DCell is constructed from many low-level DCells and DCells at the same level are fully connected with one another. DCell scales doubly exponentially as the node degree increases. DCell is fault tolerant since it does not have single point of failure and its distributed fault-tolerant routing

This paper is a comparative study of feature selection methods in statistical learning of text categorization. The focus is on aggressive dimensionality reduction. Five methods were evaluated, including term selection based on document frequency (DF), information gain (IG), mutual information (MI), a Ø 2 -test (CHI), and term strength (TS). We found IG and CHI most effective in our experiments. Using IG thresholding with a knearest neighbor classifier on the Reuters corpus, removal of up to 98% removal of unique terms actually yielded an improved classification accuracy (measured by average precision) . DF thresholding performed similarly. Indeed we found strong correlations between the DF, IG and CHI values of a term. This suggests that DF thresholding, the simplest method with the lowest cost in computation, can be reliably used instead of IG or CHI when the computation of these measures are too expensive. TS compares favorably with the other methods with up to 50% vocabulary redu...

This book presents a unified treatment of many different kinds of planning algorithms. The subject lies at the crossroads between robotics, control theory, artificial intelligence, algorithms, and computer graphics. The particular subjects covered include motion planning, discrete planning, planning under uncertainty, sensor-based planning, visibility, decision-theoretic planning, game theory, information spaces, reinforcement learning, nonlinear systems, trajectory planning, nonholonomic planning, and kinodynamic planning.

Strategies for hypothesis testing in scientific investigation and everyday reasoning have interested both psychologists and philosophers. A number of these scholars stress the importance of disconnrmation in reasoning and suggest that people are instead prone to a general deleterious "confirmation bias." In particular, it is suggested that people tend to test those cases that have the best chance of verifying current beliefs rather than those that have the best chance of falsifying them. We show, however; that many phenomena labeled "confirmation bias" are better understood in terms of a general positive test strategy. With this strategy, there is a tendency to test cases that are expected (or known) to have the property of interest rather than those expected (or known) to lack that property. This strategy is not equivalent to confirmation bias in the first sense; we show that the positive test strategy can be a very good heuristic for determining the truth or falsity of a hypothesis under realistic conditions. It can, however, lead to systematic errors or inefficiencies. The appropriateness of human hypothesis-testing strategies and prescriptions about optimal strategies must be understood in terms of the interaction between the strategy and the task at hand.

Abstract—DCell [7] has been proposed as a server centric network structure for data centers. DCell can support millions of servers with high network capacity and provide good fault tolerance by only using commodity mini-switches. In this paper, we show that DCell is only a special case of a more

and initiate reliable data transfer to the base station. During the deployment, the network recorded 229 earthquakes, eruptions, and other seismoacoustic events. The science requirements of reliable data collection, accurate event detection, and high timing precision drive sensor networks in new directions

Abstract—DCell [3] has been proposed as a server centric network structure for data centers. DCell can support millions of servers with high network capacity and provide good fault toler-ance by only using commodity mini-switches. However, the traffic in DCell is imbalanced in that links

Today’s data centers offer tremendous aggregate bandwidth to clusters of tens of thousands of machines. However, because of limited port densities in even the highest-end switches, data center topologies typically consist of multi-rooted trees with many equal-cost paths between any given pair of hosts. Existing IP multipathing protocols usually rely on per-flow static hashing and can cause substantial bandwidth losses due to longterm collisions. In this paper, we present Hedera, a scalable, dynamic flow scheduling system that adaptively schedules a multi-stage switching fabric to efficiently utilize aggregate network resources. We describe our implementation using commodity switches and unmodified hosts, and show that for a simulated 8,192 host data center, Hedera delivers bisection bandwidth that is 96 % of optimal and up to 113 % better than static load-balancing methods. 1

and performed gain-of-function experiments. RESULTS—We show that class IIa HDAC4,-5, and-9 have an unexpected restricted expression in the endocrine b- and d-cells of the pancreas. Analyses of the pancreas of class IIa HDAC

Ldb1 and Ldb2 are coregulators that mediate Lin11-Isl1-Mec3 (LIM)–homeodomain (HD) and LIM-only transcription factor– driven gene regulation. Although both Ldb1 and Ldb2 mRNA were produced in the developing and adult pancreas, immuno-histochemical analysis illustrated a broad Ldb1 protein expres-sion pattern during early pancreatogenesis, which subsequently became enriched in islet and ductal cells perinatally. The islet-enriched pattern of Ldb1 was similar to pan-endocrine cell– expressed Islet-1 (Isl1), which was demonstrated in this study to be the primary LIM-HD transcription factor in developing and adult islet cells. Endocrine cell–specific removal of Ldb1 during mouse development resulted in a severe reduction of hor-mone+ cell numbers (i.e., a, b, and d) and overt postnatal hyper-glycemia, reminiscent of the phenotype described for the Isl1 conditional mutant. In contrast, neither endocrine cell develop-