Verification of temporal logic properties plays a crucial role in proving the desired behaviors of hybrid systems. In this paper, we propose an interval method for verifying the properties described by a bounded linear temporal logic. We relax the problem to allow outputting an inconclusive result when verification process cannot succeed with a prescribed precision, and present an efficient and...

R/qtlbim (www.qtlbim.org) provides a powerful suite of tools for model selection of the genetic architecture for traits influenced by multiple quantitative trait loci (QTL). The Markov chain Monte Carlo (MCMC) sampling approach draws samples from the more probable genetic architectures. Subsequent visualization and summary provides posterior estimates of the number and location of QTL, their ma...

Abstract. Black-box mathematical models are powerful tools in classification and regression problems. Thanks to the use of (unknown) transformations of the inputs, the outcome can be estimated, improving performance in comparison to standard statistical models. A disadvantage of these complex models however, is their lack of interpretability. This work illustrates how advanced methods can be ma...

This thesis proposes a new approach for the automated analysis of electrocardiogram (ECG) signals, based on the framework of probabilistic modelling. The approach makes use of a number of techniques from machine learning, speech recognition and time-frequency analysis. The problem is to estimate from an ECG signal a number of timing intervals which occur in every heartbeat. The accurate measure...

0377-2217/$ see front matter 2010 Elsevier B.V. A doi:10.1016/j.ejor.2010.03.039 * Corresponding author. E-mail address: [email protected] (P.J. Korho 1 The term ‘‘radial” in the traditional DEA-literature reach the efficient frontier by proportionally increasi outputs or decreasing the values of the current inputs We develop an approach to efficiency analysis to enable us to incorporate in...

The power flow is the fundamental tool for the study of power systems. The data for this problem are subject to uncertainty. This paper uses interval withmetic to solve the power flow problem. Interval arithmetic takes into consideration the uncertainty of the nodal information, and is able to provide strict bounds for the solutions to the problem: all possible solutions are included within the...

Interval arithmetic was original developed to estimate rounding errors on floating-point computations but it is used in a wide variety of applications from constraint solvers and global optimizers to power and timing analysis of software processes. The objective of interval analysis is to determine the output ranges (or interval) of a computation set. The main problem of classical interval anal...

New tools for reproducible exploratory data analysis of large datasets are important to address the rising size and complexity of genomic data. We developed the valr R package to enable flexible and efficient genomic interval analysis. valr leverages new tools available in the "tidyverse", including dplyr. Benchmarks of valr show it performs similar to BEDtools and can be used for interactive a...

This paper proposes a new approach for computing the capture basin C of a target T. The capture basin corresponds to the set of initial state vectors such that the target could be reached in finite time via an appropriate control input, before possibly leaving the target. Whereas classical capture basin characterization do not provide any guarantee on the set of state vectors that belong to the...

The paper deals with an enhanced method for matrix-based approximate symbolic analysis. The method assures the validity of approximated expressions over a certain interval of network parameters by means of the sensitivity analysis. A computationally effective algorithm is presented. Key-Words: Approximate symbolic analysis, linear circuits, computer methods