A Label space reduction algorithm for P2MP LSPs using asymmetric tunnels

The aim of traffic engineering is to optimise network resource utilization. Although several works on minimizing network resource utilization have been published, few works have focused on LSR label space. This paper proposes an algorithm that uses MPLS label stack features in order to reduce the number of labels used in LSPs forwarding. Some tunnelling methods and their MPLS implementation drawbacks are also discussed. The algorithm described sets up the NHLFE tables in each LSR, creating asymmetric tunnels when possible. Experimental results show that the algorithm achieves a large reduction factor in the label space. The work presented here applies for both types of connections: P2MP and P2P

SLAM using an Imaging Sonar for Partially Structured Underwater Environments

In this paper we describe a system for underwater navigation with AUVs in partially structured environments, such as dams, ports or marine platforms. An imaging sonar is used to obtain information about the location of planar structures present in such environments. This information is incorporated into a feature-based SLAM algorithm in a two step process: (I) the full 360deg sonar scan is undistorted (to compensate for vehicle motion), thresholded and segmented to determine which measurements correspond to planar environment features and which should be ignored; and (2) SLAM proceeds once the data association is obtained: both the vehicle motion and the measurements whose correct association has been previously determined are incorporated in the SLAM algorithm. This two step delayed SLAM process allows to robustly determine the feature and vehicle locations in the presence of large amounts of spurious or unrelated measurements that might correspond to boats, rocks, etc. Preliminary experiments show the viability of the proposed approach

Underwater SLAM in a marina environment

This paper describes a navigation system for autonomous underwater vehicles (AUVs) in partially structured environments, such as dams, harbors, marinas or marine platforms. A mechanical scanning imaging sonar is used to obtain information about the location of planar structures present in such environments. A modified version of the Hough transform has been developed to extract line features, together with their uncertainty, from the continuous sonar dataflow. The information obtained is incorporated into a feature-based SLAM algorithm running an Extended Kalman Filter (EKF). Simultaneously, the AUV's position estimate is provided to the feature extraction algorithm to correct the distortions that the vehicle motion produces in the acoustic images. Experiments carried out in a marina located in the Costa Brava (Spain) with the Ictineu AUV show the viability of the proposed approach

Use of Hy's law and a new composite algorithm to predict acute liver failure in patients with drug-induced liver injury.

BACKGROUND & AIMS Hy's Law, which states that hepatocellular drug-induced liver injury (DILI) with jaundice indicates a serious reaction, is used widely to determine risk for acute liver failure (ALF). We aimed to optimize the definition of Hy's Law and to develop a model for predicting ALF in patients with DILI. METHODS We collected data from 771 patients with DILI (805 episodes) from the Spanish DILI registry, from April 1994 through August 2012. We analyzed data collected at DILI recognition and at the time of peak levels of alanine aminotransferase (ALT) and total bilirubin (TBL). RESULTS Of the 771 patients with DILI, 32 developed ALF. Hepatocellular injury, female sex, high levels of TBL, and a high ratio of aspartate aminotransferase (AST):ALT were independent risk factors for ALF. We compared 3 ways to use Hy's Law to predict which patients would develop ALF; all included TBL greater than 2-fold the upper limit of normal (×ULN) and either ALT level greater than 3 × ULN, a ratio (R) value (ALT × ULN/alkaline phosphatase × ULN) of 5 or greater, or a new ratio (nR) value (ALT or AST, whichever produced the highest ×ULN/ alkaline phosphatase × ULN value) of 5 or greater. At recognition of DILI, the R- and nR-based models identified patients who developed ALF with 67% and 63% specificity, respectively, whereas use of only ALT level identified them with 44% specificity. However, the level of ALT and the nR model each identified patients who developed ALF with 90% sensitivity, whereas the R criteria identified them with 83% sensitivity. An equal number of patients who did and did not develop ALF had alkaline phosphatase levels greater than 2 × ULN. An algorithm based on AST level greater than 17.3 × ULN, TBL greater than 6.6 × ULN, and AST:ALT greater than 1.5 identified patients who developed ALF with 82% specificity and 80% sensitivity. CONCLUSIONS When applied at DILI recognition, the nR criteria for Hy's Law provides the best balance of sensitivity and specificity whereas our new composite algorithm provides additional specificity in predicting the ultimate development of ALF.

Rank estimation of trajectory matrix in motion segmentation

A novel technique for estimating the rank of the trajectory matrix in the local subspace affinity (LSA) motion segmentation framework is presented. This new rank estimation is based on the relationship between the estimated rank of the trajectory matrix and the affinity matrix built with LSA. The result is an enhanced model selection technique for trajectory matrix rank estimation by which it is possible to automate LSA, without requiring any a priori knowledge, and to improve the final segmentation

Fast calculation of the CAC convolution algorithm using the multinomial distribution function

The authors focus on one of the methods for connection acceptance control (CAC) in an ATM network: the convolution approach. With the aim of reducing the cost in terms of calculation and storage requirements, they propose the use of the multinomial distribution function. This permits direct computation of the associated probabilities of the instantaneous bandwidth requirements. This in turn makes possible a simple deconvolution process. Moreover, under certain conditions additional improvements may be achieved

Enhanced Model Selection for motion segmentation

In this paper a novel rank estimation technique for trajectories motion segmentation within the Local Subspace Affinity (LSA) framework is presented. This technique, called Enhanced Model Selection (EMS), is based on the relationship between the estimated rank of the trajectory matrix and the affinity matrix built by LSA. The results on synthetic and real data show that without any a priori knowledge, EMS automatically provides an accurate and robust rank estimation, improving the accuracy of the final motion segmentation

A simulation-based algorithm for solving the resource-assignment problem in satellite telecommunication networks

This paper proposes an heuristic for the scheduling of capacity requests and the periodic assignment of radio resources in geostationary (GEO) satellite networks with star topology, using the Demand Assigned Multiple Access (DAMA) protocol in the link layer, and Multi-Frequency Time Division Multiple Access (MF-TDMA) and Adaptive Coding and Modulation (ACM) in the physical layer.

Recanalization and Collaterals Predict Outcome in Proximal MCA Occlusion, but neither Penumbra nor Core of Stroke

Data on new predictors of outcome include penumbra core or collaterals.Objective: To test the predictive value of recanalization, collaterals, penumbra and core of ischemia for functional outcome in a large group of patients with MCA occlusion. Method: Consecutive events included prospectively in the Acute Stroke Registry and Analysis of Lausanne from April 2002 to April 2009 with an acute stroke due to proximal MCA occlusion (M1) were considered for analysis. Acute CTA were reviewed to grade the collaterals (dichotomized in poor __50% or good _50% compared to the normal side) and localization of M1 occlusion (proximal or mid-distal). Acute CTP were reviewed and reconstructed to determine penumbra, core and stroke index (penumbra/penumbra_core) of brain ischemia. Good outcome was defined by mRS 0-2 at 3 months.Results: Among 242 events (115 male, mean NIHSS 18.1, SD 5.8, mean age 66, SD 15), 42% were treated with intravenous thrombolysis, and 3% with intraarterial thrombolysis. Collateral status was rated as poor in 53% of events and proximal M1 occlusion was present in 64%. Recanalization determined at 24 hours with CTA was complete in 26% events and partial/absent in 54%.CTP was available for 212 events. Mean penumbra was 88.6 cm3 (median 84.4, SD 53.8), mean core was 54.1 cm3 (median 46.2, SD 45.7) and stroke index was 64% (median 68%, SD 25%). Good outcome was observed in 87 events (36%) and was associated in multivariate logistic regression with thrombolysis (p_0.02, OR_2.5, 95% CI 1.2-5.4), recanalization (p_0.001, OR_4.1, 95% CI 1.9-8.9), lower NIHSS (p_0.001, OR_0.84, 95% CI 0.78-0.91), male gender (p_0.01, OR_2.8, 95% CI 1.3-5.9), mRS prior to stroke (p_0.02, OR_0.5, 95% CI 0.28-0.9) and good collateral status (p_0.005, OR_3, 95% CI 1.4-6.4). Nor penumbra, nor core, nor stroke index were significant in the multivariate model, even if an association was present in the univariate model between good functional outcome and penumbra (p_0.004, OR_1.008, 95% CI 1.003-1.01), core (p_0.001, OR_0.98, 95% CI 0.976-0.99) and strokeindex (p_0.001, OR_16.7, 95% CI 4.6 59.9).Conclusion: MCA recanalization is the best predictor for good functional outcome, followed by collateral status. CTP data did not predict the functional outcome in our large group of M1 occlusion. Author Disclosures: C. Odier: None. P. Michel: Research Grant; Significant; Paion, Lundbeck. Speakers; Modest; Boehringer-Ingelheim. Consultant/Advisory Board; Modest; Boehringer- Ingelheim. Consultant/Advisory Board; Significant; Servier, Lundbeck.

Algorithm creation and optimization for the crew pairing problem

Algoritmo que optimiza y crea pairings para tripulaciones de líneas aéreas mediante la posterior programación en Java.

The Effect Of Induced Intraocular Straylight (cataract Simulation) On Sensitivity Measures Of Standard Automated Perimetry, Pulsar Perimetry And Moorfields Motion Displacement Test

Purpose: To investigate the effect of incremental increases in intraocular straylight on threshold measurements made by three modern forms of perimetry: Standard Automated Perimetry (SAP) using Octopus (Dynamic, G-Pattern), Pulsar Perimetry (PP) (TOP, 66 points) and the Moorfields Motion Displacement Test (MDT) (WEBS, 32 points).Methods: Four healthy young observers were recruited (mean age 26yrs [25yrs, 28yrs]), refractive correction [+2 D, -4.25D]). Five white opacity filters (WOF), each scattering light by different amounts were used to create incremental increases in intraocular straylight (IS). Resultant IS values were measured with each WOF and at baseline (no WOF) for each subject using a C-Quant Straylight Meter (Oculus, Wetzlar, Germany). A 25 yr old has an IS value of ~0.85 log(s). An increase of 40% in IS to 1.2log(s) corresponds to the physiological value of a 70yr old. Each WOFs created an increase in IS between 10-150% from baseline, ranging from effects similar to normal aging to those found with considerable cataract. Each subject underwent 6 test sessions over a 2-week period; each session consisted of the 3 perimetric tests using one of the five WOFs and baseline (both instrument and filter were randomised).Results: The reduction in sensitivity from baseline was calculated. A two-way ANOVA on mean change in threshold (where subjects were treated as rows in the block and each increment in fog filters was treated as column) was used to examine the effect of incremental increases in straylight. Both SAP (p<0.001) and Pulsar (p<0.001) were significantly affected by increases in straylight. The MDT (p=0.35) remained comparatively robust to increases in straylight.Conclusions: The Moorfields MDT measurement of threshold is robust to effects of additional straylight as compared to SAP and PP.

La place de l'émotion dans la clinique psychiatrique : présentation orale

Biologie et médecine - Les podcasts de l'UNIL

A genetic algorithm to ensemble feature selection

We are going to implement the "GA-SEFS" by Tsymbal and analyse experimentally its performance depending on the classifier algorithms used in the fitness function (NB, MNge, SMO). We are also going to study the effect of adding to the fitness function a measure to control complexity of the base classifiers.