Robust network monitoring in the presence of non-cooperative traffic queries

We present the design of a predictive load shedding scheme for a network monitoring platform that supports multiple and competing traffic queries. The proposed scheme can anticipate overload situations and minimize their impact on the accuracy of the traffic queries. The main novelty of our approach is that it considers queries as black boxes, with arbitrary (and highly variable) input traffic and processing cost. Our system only requires a high-level specification of the accuracy requirements of each query to guide the load shedding procedure and assures a fair allocation of computing resources to queries in a non-cooperative environment. We present an implementation of our load shedding scheme in an existing network monitoring system and evaluate it with a diverse set of traffic queries. Our results show that, with the load shedding mechanism in place, the monitoring system can preserve the accuracy of the queries within predefined error bounds even during extreme overload conditions.     

The role of long-term-memory and short-term-memory links in the Simon effect.

In Experiment 1, children performed a Simon task after a spatially compatible or incompatible task. Results showed a Simon effect after the spatially compatible task and a reversed Simon effect after the spatially incompatible task. In Experiments 2–5, an identical procedure was adopted with adult participants, who performed the Simon task immediately after, a day after, or a week after the spatial compatibility task. Experiment 6 established a baseline for the Simon effect. Results showed a Simon effect after the spatially compatible task and no Simon effect or a reversed Simon effect after the spatially incompatible task. A modified version of the computational model of M. Zorzi and C. Umiltà (1995) was used to compare possible accounts of the findings. The best account exploits 2 types of short-term-memory links between stimulus and response and their interaction with long-term-memory links. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Christopher Strachey—Understanding Programming Languages

Higher-Order and Symbolic Computation -     

FA2BOUG—A FORTRAN 90 code to compute Bouguer gravity anomalies from gridded free-air anomalies: Application to the Atlantic-Mediterranean transition zone

In this paper we present a computer program written in FORTRAN 90 specifically designed to determine the Bouguer anomaly from publicly available global gridded free-air anomaly and elevation database sets. FA2BOUG computes the complete Bouguer correction (i.e. Bullard A, B and C corrections) for both land and sea points in several spatial domains according to the distance between the topography and the calculation point. In each zone a different algorithm is used. In a distant zone we consider the harmonic spherical expansion of the potential of each right rectangular prism representing an elevation grid point. In an intermediate zone we compute the gravitational attraction produced by each prism using the analytic formula. Finally, an inner zone contribution is divided into two parts: a flat-topped prism with a height equal to the elevation of the calculation point, and four quadrants of a conic prism sloping continuously from each square of the inner zone to the calculation point. The program has been applied to the Atlantic-Mediterranean transition zone to obtain a complete Bouguer anomaly map of the area, integrating available onshore Bouguer anomaly with satellite-derived free-air anomaly data. Positive Bouguer anomalies are found in the Atlantic oceanic domain (240–300 mGal), central and eastern Alboran Basin (40–160 mGal) and SW Iberian Peninsula (>40 mGal). Major negative Bouguer anomalies are located beneath the west Alboran Basin (<?40 mGal), the Rif, the Rharb Basin and the Atlas Mountains (<?120 mGal). An isostatic residual anomaly map of the study area has been computed and compared with the crustal and lithospheric structure inferred from previous work.     

The feasibility of a mixed reality surgical training environment

The Sheffield knee arthroscopy training system (SKATS) was originally a visual-based virtual environment without haptic feedback, but has been further developed as a mixed reality-training environment through the use of tactile augmentation (or passive haptics). The design of the new system is outlined and then tested. In the first experiment described, the effect of tactile augmentation on performance is considered by comparing novice performance using the original and mixed reality system. In the second experiment the mixed reality system is assessed in terms of construct validity by comparing the performance of users with differing levels of surgical expertise. The results are discussed in terms of the validity of a mixed reality environment for training knee arthroscopy.     

Analogue OTA multiplier without input voltage swing restrictions, and temperature-compensated

An analogue multiplier with operational transconductance amplifiers (OTAs) is presented. It overcomes the typical problems of previous OTA multipliers: limited input voltage swings and temperature dependence. It uses a minimum number of resistive components, and only two of them are critical in their performance. A simple temperature compensation scheme for the OTA multiplier is introduced.     

Monoclonal antibody for the demonstration by ELISA of antibodies to protein p24 of enzootic bovine leukosis virus in individual and pooled blood serum and milk samples

A sensitive and specific ELISA for the demonstration of antibodies to the protein p24 of enzootic bovine leukosis virus (EBVL) using a 'capture' monoclonal antibody to this protein (MAb p24) was developed. The method is sensitive enough to detect the international reference serum E4/10 in pooled blood serum samples collected from up to 50 cows, or, if a 10-fold concentrate of milk whey is tested, in samples of bulk milk collected from up to 400 cows. The application of MAb p24 has considerably increased not only the sensitivity, but also the specificity of ELISA. Moreover it is possible to differentiate reliably between positive and 'false positive' reagents by testing a suspicious sample in a pair of wells of which one is coated with MAb p24 alone and the other with the complex MAb p24 + EBLV antigen and the subsequent calculation of 'specific absorbance'. This method, showing the highest sensitivity of detection of antibodies to EBLV p24 described so far, can become an effective tool on the sanitation of infected herds as well as in checks of the EBL-free status. A diagnostic kit suitable for commercial manufacture has been devised.     

Effects of cathodic electrodeposition parameters of cerium oxide film on the corrosion resistance of the 2024 Al alloy

Cerium oxide thin films obtained by cathodic electrodeposition on 2024 aluminium alloy have been studied. The coatings, obtained with electrochemical deposition, offer an effective corrosion protection and require a lower deposition time when compared to chemical conversion coatings. The coatings were obtained at room temperature by deposition from CeCl₃/H₂O₂ aqueous solutions and the influence of several parameters (CeCl₃ concentration, H₂O₂ concentration, deposition time, current intensity) on the corrosion resistance was studied. The composition, morphology and microstructure of the films have been characterized by SEM, XPS and AFM. The corrosion resistance was investigated through potentiodynamic tests in 3% NaCl solution.     

A Machine Learning Approach to POS Tagging

We have applied the inductive learning of statistical decision trees and relaxation labeling to the Natural Language Processing (NLP) task of morphosyntactic disambiguation (Part Of Speech Tagging). The learning process is supervised and obtains a language model oriented to resolve POS ambiguities, consisting of a set of statistical decision trees expressing distribution of tags and words in some relevant contexts. The acquired decision trees have been directly used in a tagger that is both relatively simple and fast, and which has been tested and evaluated on the Wall Street Journal (WSJ) corpus with competitive accuracy. However, better results can be obtained by translating the trees into rules to feed a flexible relaxation labeling based tagger. In this direction we describe a tagger which is able to use information of any kind (n-grams, automatically acquired constraints, linguistically motivated manually written constraints, etc.), and in particular to incorporate the machine-learned decision trees. Simultaneously, we address the problem of tagging when only limited training material is available, which is crucial in any process of constructing, from scratch, an annotated corpus. We show that high levels of accuracy can be achieved with our system in this situation, and report some results obtained when using it to develop a 5.5 million words Spanish corpus from scratch.