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We used various supervised machine learning and data mining techniques to generate a model for predicting risk of breast cancer in post menopausal women using genomic data, family history, and age. In this paper, we propose an approach to select nine best SNPs using various feature selection algorithms and evaluate binary classifiers performance. We have also designed an algorithm to incorporate domain knowledge into our machine learning model. Our observations revealed that the machine learning model generated using both the domain knowledge and the feature selection technique performed better compared to the naive approach of classification. It is also interesting to note that, in addition to selecting nine best SNPs, feature selection resulted in removing age from the set of features to be used for cancer risk assessment.

Managing and delivering virtualised cloud-based services in systems like the virtual computing lab (VCL) is an open challenge. Current research is focused on enhancing specific components like service discovery, composition and monitoring and there is no holistic view of what would constitute a lifecycle of virtualised services delivered on a cloud environment. We have developed a policy-based integrated framework for automating acquisition and consumption of cloud services. This framework divides the cloud service lifecycle into five phases: requirements, discovery, negotiation, composition, and consumption. We have also developed a cloud broker tool to automatically discover, negotiate and reserve images from the VCL platform. It was developed using web technologies and is built upon our service lifecycle framework. This paper describes our methodology and the tool as implemented on the VCL platform.

Lower bounds are proven on the parallel-time complexity of several basic functions on the most powerful concurrent-read concurrent-write PRAM with unlimited shared memory and unlimited power of individual processors (denoted by PRIORITY(∞)): It is proved that with a number of processors polynomial in n, Ω (log n) time is needed for addition, multiplication or bitwise OR of n numbers, when each number has n' bits. Hence even the bit complexity (i.e., the time complexity as a function of the total number of bits in the input) is logarithmic in this case. This improves a beautiful result of Meyer auf der Heide and Wigderson [22]. They proved a log n lower bound using Ramsey-type techniques. Using Ramsey theory, it is possible to get an upper bound on the number of bits in the inputs used. However, for the case of polynomially many processors, this upper bound is more than a polynomial in n. An Ω (log n) lower bound is given for PRIORITY(∞) with no(1) processors on a function with inputs from {0, 1}, namely for the function ƒ(x1, … , xn,) = Σ nl- 1 xlai where a is fixed and xi ε {0, 1}. Finally, by a new efficient simulation of PRIORITY(∞) by unbounded fan-in circuits, that with less than exponential number of processors, it is proven a PRIORITY(∞) cannot compute PARITY in constant time, and with nO(1) processors Ω(√log n) time is needed. The simulation technique is of independent interest since it can serve as a general tool to translate circuit lower bounds into PRAM lower bounds. Further, the lower bounds in (1) and (2) remain valid for probabilistic or nondeterministic concurrent-read concurrent-write PRAMS.

We develop efficient parallel algorithms for ther-dominating set and thep-center problems on trees. On a concurrent-read exclusive-write PRAM, our algorithm for ther-dominating set problem runs inO(lognlog logn) time withnprocessors. The algorithm for thep-center problem runs inO(log2nlog logn) time withnprocessors.

The transposition network Tn of order n! is the Cayley graph of the symmetric group Sn with generators the set of all transpositions in Sn. Finding the bisection width of the transposition network is an open question posed by F. T. Leighton. We resolve this question for n even, by showing that the bisection width of the transposition network Tn is equal to nn!/4. When n ≥ 2 is odd, we show that the bisection width of the transposition network Tn is (1 + o(1))nn!/4. In doing so, we determine the second smallest eigenvalue of the adjacency matrix of Tn. Further, given a Cayley graph of a finite group G, with m conjugacy classes and with a set of generators closed under taking conjugates and not containing the identity of G, we show how to construct an m × m integer matrix Q, from the conjugacy classes of G, such that the set of eigenvalues of Q is equal to the set of eigenvalues of the adjacency matrix A of the given Cayley graph. Hence, when the order of G is large compared to the number of its conjugacy classes, a faster method for computing the eigenvalues of A is provided. © 1997 John Wiley & Sons, Inc.

The contribution of this paper is in applying parameter replacement techniques to speech that is compressed by the Federal Standard 1016 CELP speech coder, protected by Reed–Solomon codes, and transmitted over a wireless channel. The parameter replacement results in significant improvement in speech quality without any increase in bit rate.