17315153
Randomness and universal machines
The present work investigates several questions from a recent survey of Miller and Nies related to Chaitin's @W numbers and their dependence on the underlying universal machine. Furthermore, the notion @W"U[X][email protected]?"p":"U"("p")"@7"@?"X2^-^|^p^| is studied for various sets X and universal machines U. A universal machine U is constructed such that for all x, @W"U[{x}]=2^1^-^H^(^x^). For such a universal machine there exists a co-r.e. set X such that @W"U[X] is neither left-r.e. nor Martin-Lof random. Furthermore, one of the open problems of Miller and Nies is answered completely by showing that there is a sequence U"n of universal machines such that the truth-table degrees of the @W"U"""n form an antichain. Finally, it is shown that the members of hyperimmune-free Turing degree of a given @P"1^0-class are not low for @W unless this class contains a recursive set.
1961392
Degrees of Weakly Computable Reals
This paper studies the degrees of weakly computable reals. It is shown that certain types of limit-recursive reals are Turing incomparable to all weakly computable reals except the recursive and complete ones. Furthermore, it is shown that an r.e. Turing degree is array-recursive iff every real in it is weakly computable.
1638130
Bounding computably enumerable degrees in the Ershov hierarchy
Nanyang Technol Univ, Sch Math & Phys Sci, Div Math Sci, Singapore 639798, Singapore. Chinese Acad Sci, Inst Software, Beijing 100080, Peoples R China. Natl Univ Singapore, Dept Math, Singapore 119260, Singapore.
7723209
1-Generic splittings of computably enumerable degrees
Say a set G⊆ω is 1-generic if for any e∈ω, there is a string σ⊂G such that {e}σ(e)↓ or ∀τ⊇σ({e}τ(e)↑). It is known that 0′ can be split into two 1-generic degrees. In this paper, we generalize this and prove that any nonzero computably enumerable degree can be split into two 1-generic degrees. As a corollary, no two computably enumerable degrees bound the same class of 1-generic degrees.
35293254
Quasi-complements of the cappable degrees
Say that a nonzero c. e. degree b is a quasi-complement of a c. e. degree a if a ∩ b = 0 and a ∪ b is high. It is well-known (due to Shore) that each cappable degree has a high quasi-complement. However, by the existence of the almost deep degrees, there are nonzero cappable degrees having no low quasi-complements. In this paper, we prove that any nonzero cappable degree has a low2 quasi-complement. (© 2004 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)
18609322
On the Quotient Structure of Computably Enumerable Degrees Modulo the Noncuppable Ideal
We show that minimal pairs exist in the quotient structure of $\mathcal{R}$ modulo the ideal of noncuppable degrees.
9960122
Dynamic Zone-Balancing of Topology-Aware Peer-to-Peer Networks
Building a topology-aware peer-to-peer overlay network can bring many advantages, such as providing locality-aware connectivity and reducing routing path length. While its benefits on performance have been recognized, an uneven overlay zone distribution has emerged. Recent work has shown that topology-aware neighbor selection during construction can aggravate the unbalance of zone distribution while it reduces routing path length. The imbalance in zone sizes may lead to performance decrease and an unfair load distribution. 
 
In this paper, we present an even topology-aware peer-to-peer network based on De Bruijn Graph by developing a dynamic zone-balancing approach.
22669962
Generic universal switch blocks
A switch block M with W terminals on each side is said to be universal if every set of nets satisfying the dimension constraint (i.e., the number of nets on each side of M is at most W) is simultaneously routable through M (Y.W. Chang et al., 1996). We present an algorithm to construct N-sided universal switch blocks with W terminals on each side. Each of our universal switch blocks has (/sub 2//sup N/)W switches and switch-block flexibility N-1 (i.e., F/sub S/=N-1). We prove that no switch block with less than (/sub 2//sup N/)W switches can be universal. Further, the decomposition property of a universal switch block provides a key insight into its layout implementation with a smaller silicon area. We also compare our universal switch blocks with others of the topology associated with Xilinx XC4000-type FPGAs. Experimental results demonstrate that our universal switch blocks improve routability at the chip level.
1594579
GPSS Simulation Study of Quality Inspection System
6594297
Generic Universal Switch Blocks
A switch block M with W terminals on each side is said to be universal if every set of nets satisfying the dimension constraint (i.e., the number of nets on each side of M is at most W) is simultaneously routable through M. In this paper, we present an algorithm to construct N-sided universal switch blocks with W terminals on each side. Each of our universal switch blocks has (/sub 2//sup N/) W switches and switch-block flexibility N-1 (i.e., F/sub S/=N-1). We prove that no switch block with less than (/sub 2//sup N/)W switches can be universal. We also compare our universal switch blocks with others of the topology associated with Xilinx XC4000-type FPGAs. To explore the area performance of the universal switch blocks, we develop a detailed router for hierarchical FPGAs (HFPGAs) with 5-sided switch blocks. Experimental results demonstrate that our universal switch blocks improve routability at the chip level. Based on extensive experiments, we also provide key insights into the interactions between switch-block architectures and routing.
2439726
Concept boundary detection for speeding up SVMs
Support Vector Machines (SVMs) suffer from an O(n2) training cost, where n denotes the number of training instances. In this paper, we propose an algorithm to select boundary instances as training data to substantially reduce n. Our proposed algorithm is motivated by the result of (Burges, 1999) that, removing non-support vectors from the training set does not change SVM training results. Our algorithm eliminates instances that are likely to be non-support vectors. In the concept-independent preprocessing step of our algorithm, we prepare nearest-neighbor lists for training instances. In the concept-specific sampling step, we can then effectively select useful training data for each target concept. Empirical studies show our algorithm to be effective in reducing n, outperforming other competing downsampling algorithms without significantly compromising testing accuracy.