Algorithm engineering for expression dag based number types

Magdeburg, Univ., Fak. für Informatik, Diss., 2015

Fast and furious: a look at the death of animals on the highway MS-080, Southwestern Brazil

Several factors, such as hunting and the pet trade, are responsible for the worldwide decline of wildlife populations. In addition, fatal collisions with vehicles on highways have also taken one of the largest tolls. This study aimed to quantify the richness and abundance of vertebrate roadkill along highway MS-080 in Mato Grosso do Sul, Central-West Brazil. We compare the amount of roadkill to the distance between cities, moon phases and the flow of vehicles on the highway. Samples were collected weekly between March and September 2011, totaling 257 individuals, belonging to 32 families and 52 species, resulting in an index of 0.13 individuals hit/km. Birds were the most frequently hit taxa, followed by mammals. The most affected species was Cariama cristata (Cariamidae), followed by Cerdocyon thous (Canidae). The sections of highway closest to cities had the highest number of individual animals killed. Our observations indicate that the density of the vegetation next to the highway positively influences the amount of roadkill.

A note on parallelizing the parameterized expectations algorithm

The parameterized expectations algorithm (PEA) involves a long simulation and a nonlinear least squares (NLS) fit, both embedded in a loop. Both steps are natural candidates for parallelization. This note shows that parallelization can lead to important speedups for the PEA. I provide example code for a simple model that can serve as a template for parallelization of more interesting models, as well as a download link for an image of a bootable CD that allows creation of a cluster and execution of the example code in minutes, with no need to install any software.

Object recognition for autonomous objects: comparison of two approaches

Report for the scientific sojourn at the Swiss Federal Institute of Technology Zurich, Switzerland, between September and December 2007. In order to make robots useful assistants for our everyday life, the ability to learn and recognize objects is of essential importance. However, object recognition in real scenes is one of the most challenging problems in computer vision, as it is necessary to deal with difficulties. Furthermore, in mobile robotics a new challenge is added to the list: computational complexity. In a dynamic world, information about the objects in the scene can become obsolete before it is ready to be used if the detection algorithm is not fast enough. Two recent object recognition techniques have achieved notable results: the constellation approach proposed by Lowe and the bag of words approach proposed by Nistér and Stewénius. The Lowe constellation approach is the one currently being used in the robot localization project of the COGNIRON project. This report is divided in two main sections. The first section is devoted to briefly review the currently used object recognition system, the Lowe approach, and bring to light the drawbacks found for object recognition in the context of indoor mobile robot navigation. Additionally the proposed improvements for the algorithm are described. In the second section the alternative bag of words method is reviewed, as well as several experiments conducted to evaluate its performance with our own object databases. Furthermore, some modifications to the original algorithm to make it suitable for object detection in unsegmented images are proposed.

Fast numerical algorithms for the computation of invariant tori in Hamiltonian systems

In this paper, we develop numerical algorithms that use small requirements of storage and operations for the computation of invariant tori in Hamiltonian systems (exact symplectic maps and Hamiltonian vector fields). The algorithms are based on the parameterization method and follow closely the proof of the KAM theorem given in [LGJV05] and [FLS07]. They essentially consist in solving a functional equation satisfied by the invariant tori by using a Newton method. Using some geometric identities, it is possible to perform a Newton step using little storage and few operations. In this paper we focus on the numerical issues of the algorithms (speed, storage and stability) and we refer to the mentioned papers for the rigorous results. We show how to compute efficiently both maximal invariant tori and whiskered tori, together with the associated invariant stable and unstable manifolds of whiskered tori. Moreover, we present fast algorithms for the iteration of the quasi-periodic cocycles and the computation of the invariant bundles, which is a preliminary step for the computation of invariant whiskered tori. Since quasi-periodic cocycles appear in other contexts, this section may be of independent interest. The numerical methods presented here allow to compute in a unified way primary and secondary invariant KAM tori. Secondary tori are invariant tori which can be contracted to a periodic orbit. We present some preliminary results that ensure that the methods are indeed implementable and fast. We postpone to a future paper optimized implementations and results on the breakdown of invariant tori.

An objective anisotropic elastic plastic model and Algorithm applicable to bone mechanics

The implicit projection algorithm of isotropic plasticity is extended to an objective anisotropic elastic perfectly plastic model. The recursion formula developed to project the trial stress on the yield surface, is applicable to any non linear elastic law and any plastic yield function.A curvilinear transverse isotropic model based on a quadratic elastic potential and on Hill's quadratic yield criterion is then developed and implemented in a computer program for bone mechanics perspectives. The paper concludes with a numerical study of a schematic bone-prosthesis system to illustrate the potential of the model.

Rigorous derivation of a nonlinear diffusion equation as fast-reaction limit of a continuous coagulation-fragmentation model with diffusion

Weak solutions of the spatially inhomogeneous (diffusive) Aizenmann-Bak model of coagulation-breakup within a bounded domain with homogeneous Neumann boundary conditions are shown to converge, in the fast reaction limit, towards local equilibria determined by their mass. Moreover, this mass is the solution of a nonlinear diffusion equation whose nonlinearity depends on the (size-dependent) diffusion coefficient. Initial data are assumed to have integrable zero order moment and square integrable first order moment in size, and finite entropy. In contrast to our previous result [CDF2], we are able to show the convergence without assuming uniform bounds from above and below on the number density of clusters.

A drug administration decision support system

Drug delivery is one of the most common clinical routines in hospitals, and is critical to patients' health and recovery. It includes a decision making process in which a medical doctor decides the amount (dose) and frequency (dose interval) on the basis of a set of available patients' feature data and the doctor's clinical experience (a priori adaptation). This process can be computerized in order to make the prescription procedure in a fast, objective, inexpensive, non-invasive and accurate way. This paper proposes a Drug Administration Decision Support System (DADSS) to help clinicians/patients with the initial dose computing. The system is based on a Support Vector Machine (SVM) algorithm for estimation of the potential drug concentration in the blood of a patient, from which a best combination of dose and dose interval is selected at the level of a DSS. The addition of the RANdom SAmple Consensus (RANSAC) technique enhances the prediction accuracy by selecting inliers for SVM modeling. Experiments are performed for the drug imatinib case study which shows more than 40% improvement in the prediction accuracy compared with previous works. An important extension to the patient features' data is also proposed in this paper.

Fast screening and confirmation of doping agents by UHPLC-QTOF-MS/MS

Introduction: The general strategy to perform anti-doping analysis starts with a screening followed by a confirmatory step when a sample is suspected to be positive. The screening step should be fast, generic and able to highlight any sample that may contain a prohibited substance by avoiding false negative and reducing false positive results. The confirmatory step is a dedicated procedure comprising a selective sample preparation and detection mode. Aim: The purpose of the study is to develop rapid screening and selective confirmatory strategies to detect and identify 103 doping agents in urine. Methods: For the screening, urine samples were simply diluted by a factor 2 with ultra-pure water and directly injected ("dilute and shoot") in the ultrahigh- pressure liquid chromatography (UHPLC). The UHPLC separation was performed in two gradients (ESI positive and negative) from 5/95 to 95/5% of MeCN/Water containing 0.1% formic acid. The gradient analysis time is 9 min including 3 min reequilibration. Analytes detection was performed in full scan mode on a quadrupole time-of-flight (QTOF) mass spectrometer by acquiring the exact mass of the protonated (ESI positive) or deprotonated (ESI negative) molecular ion. For the confirmatory analysis, urine samples were extracted on SPE 96-well plate with mixed-mode cation (MCX) for basic and neutral compounds or anion exchange (MAX) sorbents for acidic molecules. The analytes were eluted in 3 min (including 1.5 min reequilibration) with a S1-25 Ann Toxicol Anal. 2009; 21(S1) Abstracts gradient from 5/95 to 95/5% of MeCN/Water containing 0.1% formic acid. Analytes confirmation was performed in MS and MS/MS mode on a QTOF mass spectrometer. Results: In the screening and confirmatory analysis, basic and neutral analytes were analysed in the positive ESI mode, whereas acidic compounds were analysed in the negative mode. The analyte identification was based on retention time (tR) and exact mass measurement. "Dilute and shoot" was used as a generic sample treatment in the screening procedure, but matrix effect (e.g., ion suppression) cannot be avoided. However, the sensitivity was sufficient for all analytes to reach the minimal required performance limit (MRPL) required by the World Anti Doping Agency (WADA). To avoid time-consuming confirmatory analysis of false positive samples, a pre-confirmatory step was added. It consists of the sample re-injection, the acquisition of MS/MS spectra and the comparison to reference material. For the confirmatory analysis, urine samples were extracted by SPE allowing a pre-concentration of the analyte. A fast chromatographic separation was developed as a single analyte has to be confirmed. A dedicated QTOF-MS and MS/MS acquisition was performed to acquire within the same run a parallel scanning of two functions. Low collision energy was applied in the first channel to obtain the protonated molecular ion (QTOF-MS), while dedicated collision energy was set in the second channel to obtain fragmented ions (QTOF-MS/MS). Enough identification points were obtained to compare the spectra with reference material and negative urine sample. Finally, the entire process was validated and matrix effects quantified. Conclusion: Thanks to the coupling of UHPLC with the QTOF mass spectrometer, high tR repeatability, sensitivity, mass accuracy and mass resolution over a broad mass range were obtained. The method was sensitive, robust and reliable enough to detect and identify doping agents in urine. Keywords: screening, confirmatory analysis, UHPLC, QTOF, doping agents

A numerical algorithm for finding solutions of a generalized Nash equilibrium problem

A family of nonempty closed convex sets is built by using the data of the Generalized Nash equilibrium problem (GNEP). The sets are selected iteratively such that the intersection of the selected sets contains solutions of the GNEP. The algorithm introduced by Iusem-Sosa (2003) is adapted to obtain solutions of the GNEP. Finally some numerical experiments are given to illustrate the numerical behavior of the algorithm.

An algorithm for semi-infinite polynomial optimization

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