VQ tree search system based on bit level systolic arrays

A bit-level systolic array system for performing a binary tree vector quantization (VQ) codebook search is described. This is based on a highly regular VLSI building block circuit. The system in question exhibits a very high data rate suitable for a range of real-time applications. A technique is described which reduces the storage requirements of such a system by 50%, with a corresponding decrease in hardware complexity.

A bit-level systolic architecture for implementing a VQ tree search

A bit-level systolic array system for performing a binary tree Vector Quantization codebook search is described. This consists of a linear chain of regular VLSI building blocks and exhibits data rates suitable for a wide range of real-time applications. A technique is described which reduces the computation required at each node in the binary tree to that of a single inner product operation. This method applies to all the common distortion measures (including the Euclidean distance, the Weighted Euclidean distance and the Itakura-Saito distortion measure) and significantly reduces the hardware required to implement the tree search system. © 1990 Kluwer Academic Publishers.

Tea tree oil (5%) body wash versus standard care (Johnson's Baby Softwash) to prevent colonization with methicillin-resistant Staphylococcus aureus in critically ill adults::a randomized controlled trial

OBJECTIVES: To determine whether the daily use of 5% tea tree oil (TTO) body wash (Novabac 5% Skin Wash) compared with standard care [Johnson's Baby Softwash (JBS)] had a lower incidence of methicillin-resistant Staphylococcus aureus (MRSA) colonization.

PATIENTS: The study setting was two intensive care units (ICUs; mixed medical, surgical and trauma) in Northern Ireland between October 2007 and July 2009. The study population comprised 391 patients who were randomized to JBS or TTO body wash.

METHODS: This was a Phase 2/3, prospective, open-label, randomized, controlled trial. Trial registration: ISRCTN65190967. The primary outcome was new MRSA colonization during ICU stay. Secondary outcomes included the incidence of MRSA bacteraemia and maximum increase in sequential organ failure assessment score.

RESULTS: A total of 445 patients were randomized to the study. After randomization, 54 patients were withdrawn; 30 because of a positive MRSA screen at study entry, 11 due to lack of consent, 11 were inappropriately randomized and 2 had adverse reactions. Thirty-nine (10%) patients developed new MRSA colonization (JBS n?=?22, 11.2%; TTO body wash n?=?17, 8.7%). The difference in percentage colonized (2.5%, 95% CI -?8.95 to 3.94; P?=?0.50) was not significant. The mean maximum increase in sequential organ failure assessment score was not significant (JBS 1.44, SD 1.92; TTO body wash 1.28, SD 1.79; P?=?0.85) and no study patients developed MRSA bacteraemia.

CONCLUSIONS: Compared with JBS, TTO body wash cannot be recommended as an effective means of reducing MRSA colonization.

The forgiving tree: a self-healing distributed data structure

We consider the problem of self-healing in peer-to-peer networks that are under repeated attack by an omniscient adversary. We assume that the following process continues for up to n rounds where n is the total number of nodes initially in the network: the adversary deletesan arbitrary node from the network, then the network responds by quickly adding a small number of new edges.

We present a distributed data structure that ensures two key properties. First, the diameter of the network is never more than O(log Delta) times its original diameter, where Delta is the maximum degree of the network initially. We note that for many peer-to-peer systems, Delta is polylogarithmic, so the diameter increase would be a O(loglog n) multiplicative factor. Second, the degree of any node never increases by more than 3 over its original degree. Our data structure is fully distributed, has O(1) latency per round and requires each node to send and receive O(1) messages per round. The data structure requires an initial setup phase that has latency equal to the diameter of the original network, and requires, with high probability, each node v to send O(log n) messages along every edge incident to v. Our approach is orthogonal and complementary to traditional topology-based approaches to defending against attack.

Shape and Rotation Modeling and Thermophysical Analysis of Near-Earth Asteroid (1917) Cuyo

We are conducting an ESO Large Program that includes optical photometry, thermal-IR observations, and optical-NIR spectroscopy of selected NEAs. Among the principal goals of the program are shape and spin-state modeling, and searching for YORP-induced changes in rotation periods. One of our targets is asteroid (1917) Cuyo, a near-Earth asteroid from the Amor group. We carried out an extensive observing campaign on Cuyo between April 2010 and April 2013, operating primarily at the ESO 3.6m NTT for optical photometry, and the 8.2m VLT at Paranal for thermal-IR imaging. Further optical observations were acquired at the ESO 2.2m telescope, the Palomar 200" Hale telescope (California), JPL’s Table Mountain Observatory (California) and the Faulkes Telescope South (Australia). We obtained optical imaging data for rotational lightcurves throughout this period, as the asteroid passed through a wide range of observational geometries, conducive to producing a good shape model and spin state solution. The preliminary shape and spin state model indicates a nearly spherical shape and a rotation pole at ecliptic longitude λ = 53° ± 20° and latitude β = -37° ± 10° (1-sigma error bars are approximate). The sidereal rotation period was measured to be 2.6899522 ± (3 × 10^-7) hours. Linkage with earlier lightcurve data shows possible evidence of a small change in rotation rate during the period 1989-2013. We applied the NEATM thermal model (Harris A., Icarus 131, 291, 1998) to our VLT thermal-IR measurements (8-19.6 μm), obtained in September and December 2011. The derived effective diameter ranges from 3.4 to 4.2 km, and the geometric albedo is 0.16 (+0.07, -0.04). Using the shape model and thermal fluxes we will perform a detailed thermophysical analysis using the new Advanced Thermophysical Model (Rozitis, B. & Green, S.F., MNRAS 415, 2042, 2011; Rozitis, B. & Green, S.F., MNRAS 423, 367, 2012). This work was performed in part at the Jet Propulsion Laboratory under a contract with NASA.

The Geography of Revolution: The case of Longford, 1917-1921

Why were some areas of the Ireland more active than others during the War of Independence, and why did the areas of most activity change over the course of the war between 1919 and 1921? In the context of the Irish midlands, County Longford stands out as one of the most violent counties surrounded by areas where there was much less activity by the IRA. Even within the county there was a significant difference in the strength of republican activity between north and south Longford. This article will examine the factors that were responsible for the strength of the IRA campaign in this midland enclave, including socio-economic conditions, administrative decisions and failures, and the contemporary political context.
Much of the evidence upon which the paper is based comes from applications made by Longford Volunteers for military service pensions, granted to veterans of the campaign by the Irish government after 1924. Many of these documents are soon to be released by the Irish government. The paper will also include a discussion of these sources and the way in which they can be used by historians to advance our understanding of Ireland’s revolutionary decade.

Extended Tree Augmented Naive Classifier

This work proposes an extended version of the well-known tree-augmented naive Bayes (TAN) classifier where the structure learning step is performed without requiring features to be connected to the class. Based on a modification of Edmonds’ algorithm, our structure learning procedure explores a superset of the structures that are considered by TAN, yet achieves global optimality of the learning score function in a very efficient way (quadratic in the number of features, the same complexity as learning TANs). A range of experiments show that we obtain models with better accuracy than TAN and comparable to the accuracy of the state-of-the-art classifier averaged one-dependence estimator.

A tree augmented classifier based on Extreme Imprecise Dirichlet Model

We present TANC, a TAN classifier (tree-augmented naive) based on imprecise probabilities. TANC models prior near-ignorance via the Extreme Imprecise Dirichlet Model (EDM). A first contribution of this paper is the experimental comparison between EDM and the global Imprecise Dirichlet Model using the naive credal classifier (NCC), with the aim of showing that EDM is a sensible approximation of the global IDM. TANC is able to deal with missing data in a conservative manner by considering all possible completions (without assuming them to be missing-at-random), but avoiding an exponential increase of the computational time. By experiments on real data sets, we show that TANC is more reliable than the Bayesian TAN and that it provides better performance compared to previous TANs based on imprecise probabilities. Yet, TANC is sometimes outperformed by NCC because the learned TAN structures are too complex; this calls for novel algorithms for learning the TAN structures, better suited for an imprecise probability classifier.