10,291 research outputs found
NumGfun: a Package for Numerical and Analytic Computation with D-finite Functions
This article describes the implementation in the software package NumGfun of
classical algorithms that operate on solutions of linear differential equations
or recurrence relations with polynomial coefficients, including what seems to
be the first general implementation of the fast high-precision numerical
evaluation algorithms of Chudnovsky & Chudnovsky. In some cases, our
descriptions contain improvements over existing algorithms. We also provide
references to relevant ideas not currently used in NumGfun
Statistical Mechanics and Information-Theoretic Perspectives on Complexity in the Earth System
Peer reviewedPublisher PD
Regularized adaptive long autoregressive spectral analysis
This paper is devoted to adaptive long autoregressive spectral analysis when
(i) very few data are available, (ii) information does exist beforehand
concerning the spectral smoothness and time continuity of the analyzed signals.
The contribution is founded on two papers by Kitagawa and Gersch. The first one
deals with spectral smoothness, in the regularization framework, while the
second one is devoted to time continuity, in the Kalman formalism. The present
paper proposes an original synthesis of the two contributions: a new
regularized criterion is introduced that takes both information into account.
The criterion is efficiently optimized by a Kalman smoother. One of the major
features of the method is that it is entirely unsupervised: the problem of
automatically adjusting the hyperparameters that balance data-based versus
prior-based information is solved by maximum likelihood. The improvement is
quantified in the field of meteorological radar
CATHEDRAL: A Fast and Effective Algorithm to Predict Folds and Domain Boundaries from Multidomain Protein Structures
We present CATHEDRAL, an iterative protocol for determining the location of previously observed protein folds in novel multidomain protein structures. CATHEDRAL builds on the features of a fast secondary-structure–based method (using graph theory) to locate known folds within a multidomain context and a residue-based, double-dynamic programming algorithm, which is used to align members of the target fold groups against the query protein structure to identify the closest relative and assign domain boundaries. To increase the fidelity of the assignments, a support vector machine is used to provide an optimal scoring scheme. Once a domain is verified, it is excised, and the search protocol is repeated in an iterative fashion until all recognisable domains have been identified. We have performed an initial benchmark of CATHEDRAL against other publicly available structure comparison methods using a consensus dataset of domains derived from the CATH and SCOP domain classifications. CATHEDRAL shows superior performance in fold recognition and alignment accuracy when compared with many equivalent methods. If a novel multidomain structure contains a known fold, CATHEDRAL will locate it in 90% of cases, with <1% false positives. For nearly 80% of assigned domains in a manually validated test set, the boundaries were correctly delineated within a tolerance of ten residues. For the remaining cases, previously classified domains were very remotely related to the query chain so that embellishments to the core of the fold caused significant differences in domain sizes and manual refinement of the boundaries was necessary. To put this performance in context, a well-established sequence method based on hidden Markov models was only able to detect 65% of domains, with 33% of the subsequent boundaries assigned within ten residues. Since, on average, 50% of newly determined protein structures contain more than one domain unit, and typically 90% or more of these domains are already classified in CATH, CATHEDRAL will considerably facilitate the automation of protein structure classification
Nonlinear heart rate variability features for real-life stress detection. Case study : students under stress due to university examination
Background:
This study investigates the variations of Heart Rate Variability (HRV) due to a real-life stressor and proposes a classifier based on nonlinear features of HRV for automatic stress detection.
Methods:
42 students volunteered to participate to the study about HRV and stress. For each student, two recordings were performed: one during an on-going university examination, assumed as a real-life stressor, and one after holidays. Nonlinear analysis of HRV was performed by using Poincaré Plot, Approximate Entropy, Correlation dimension, Detrended Fluctuation Analysis, Recurrence Plot. For statistical comparison, we adopted the Wilcoxon Signed Rank test and for development of a classifier we adopted the Linear Discriminant Analysis (LDA).
Results:
Almost all HRV features measuring heart rate complexity were significantly decreased in the stress session. LDA generated a simple classifier based on the two Poincaré Plot parameters and Approximate Entropy, which enables stress detection with a total classification accuracy, a sensitivity and a specificity rate of 90%, 86%, and 95% respectively.
Conclusions:
The results of the current study suggest that nonlinear HRV analysis using short term ECG recording could be effective in automatically detecting real-life stress condition, such as a university examination
ViSpec: A graphical tool for elicitation of MTL requirements
One of the main barriers preventing widespread use of formal methods is the
elicitation of formal specifications. Formal specifications facilitate the
testing and verification process for safety critical robotic systems. However,
handling the intricacies of formal languages is difficult and requires a high
level of expertise in formal logics that many system developers do not have. In
this work, we present a graphical tool designed for the development and
visualization of formal specifications by people that do not have training in
formal logic. The tool enables users to develop specifications using a
graphical formalism which is then automatically translated to Metric Temporal
Logic (MTL). In order to evaluate the effectiveness of our tool, we have also
designed and conducted a usability study with cohorts from the academic student
community and industry. Our results indicate that both groups were able to
define formal requirements with high levels of accuracy. Finally, we present
applications of our tool for defining specifications for operation of robotic
surgery and autonomous quadcopter safe operation.Comment: Technical report for the paper to be published in the 2015 IEEE/RSJ
International Conference on Intelligent Robots and Systems held in Hamburg,
Germany. Includes 10 pages and 19 figure
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