Search results for "Information"
showing 10 items of 14916 documents
Graph-theoretical derivation of brain structural connectivity
2020
Brain connectivity at the single neuron level can provide fundamental insights into how information is integrated and propagated within and between brain regions. However, it is almost impossible to adequately study this problem experimentally and, despite intense efforts in the field, no mathematical description has been obtained so far. Here, we present a mathematical framework based on a graph-theoretical approach that, starting from experimental data obtained from a few small subsets of neurons, can quantitatively explain and predict the corresponding full network properties. This model also changes the paradigm with which large-scale model networks can be built, from using probabilisti…
On stability of linear dynamic systems with hysteresis feedback
2020
The stability of linear dynamic systems with hysteresis in feedback is considered. While the absolute stability for memoryless nonlinearities (known as Lure's problem) can be proved by the well-known circle criterion, the multivalued rate-independent hysteresis poses significant challenges for feedback systems, especially for proof of convergence to an equilibrium state correspondingly set. The dissipative behavior of clockwise input-output hysteresis is considered with two boundary cases of energy losses at reversal cycles. For upper boundary cases of maximal (parallelogram shape) hysteresis loop, an equivalent transformation of the closed-loop system is provided. This allows for the appli…
Enriching standards-based digital thread by fusing as-designed and as-inspected data using knowledge graphs
2020
Abstract Realizing the digital thread is essential for linking and orchestrating data across the product lifecycle in smart manufacturing. Linking heterogeneous lifecycle data is critical to maintain associativity and traceability in a digital thread. Recently, researchers have successfully leveraged ontology models with knowledge graphs in engineering domains for threading different lifecycle data. One of the most successful of such efforts is OntoSTEP which enables the formal capture of information embedded in the STandard for Exchange of Product model data (STEP) data representation, or ISO 10303. Meanwhile, an emerging inspection standard, called the Quality Information Framework (QIF),…
Wind component estimation for UAS flying in turbulent air
2019
One of the most important problem of autonomous flight for UAS is the wind identification, especially for small scale vehicles. This research focusses on an identification methodology based on the Extended Kalman Filter (EKF). In particular authors focus their attention on.the filter tuning problem. The proposed procedure requires low computational power, so it is very useful for UAS. Besides it allows a robust wind component identification even when, as it is usually, the measurement data set is affected by noticeable noises. (C) 2019 Elsevier Masson SAS. All rights reserved.
Beyond cells – The virome in the human holobiont
2019
Viromics, or viral metagenomics, is a relatively new and burgeoning field of research that studies the complete collection of viruses forming part of the microbiota in any given niche. It has strong foundations rooted in over a century of discoveries in the field of virology and recent advances in molecular biology and sequencing technologies. Historically, most studies have deconstructed the concept of viruses into a simplified perception of viral agents as mere pathogens, which demerits the scope of large-scale viromic analyses. Viruses are, in fact, much more than regular parasites. They are by far the most dynamic and abundant entity and the greatest killers on the planet, as well as th…
Adjusted bat algorithm for tuning of support vector machine parameters
2016
Support vector machines are powerful and often used technique of supervised learning applied to classification. Quality of the constructed classifier can be improved by appropriate selection of the learning parameters. These parameters are often tuned using grid search with relatively large step. This optimization process can be done computationally more efficiently and more precisely using stochastic search metaheuristics. In this paper we propose adjusted bat algorithm for support vector machines parameter optimization and show that compared to the grid search it leads to a better classifier. We tested our approach on standard set of benchmark data sets from UCI machine learning repositor…
Do terrorism, organized crime (drug production), and state weakness affect contemporary armed conflicts? An empirical analysis
2015
ABSTRACTIn 2014, the UN Security Council emphasized the dangers of terrorism, criminal activity (especially drug production and trafficking), and state weakness in conflict areas. However, neither policy debates nor scholarly analyses have focussed on the potential impact of these elements on conflict dynamics and characteristics, and the investigated partial relationships have led to inconclusive results. This article explores the presence in armed conflicts of terrorist groups among fighting parties, major drug production (indicating the presence of activities typical of criminal organizations), and state failure in the period 1990–2011. Focussing on intrastate conflicts, this article hig…
A predictive learning approach to optimal load sharing in energy management systems
2019
Given the total power demand, $P_{d}$ , current practice of equal load sharing in the process industry is to distribute the load among power supply units and machines (e.g., diesel/aas/wind turbines) in proportion to the maximum power, i.e., $P_{i}=\frac{p_{\max}^{i}}{\sum_{j}P_{\max}^{j}}P_{d}$ , where $P_{\max}^{i}$ denotes the maximum power of the ithunit. However, the efficiency of power supply units, vary in time and are highly individual, even in the case of units from same brand and model. Thus, by considering and utilizing these individual differences, it is possible to share the load in a more fuel/cost/energy optimal manner. To capture this potential, the work presented in this pa…
Algebraic parameter estimation of a multi-sinusoidal waveform signal from noisy data
2013
International audience; In this paper, we apply an algebraic method to estimate the amplitudes, phases and frequencies of a biased and noisy sum of complex exponential sinusoidal signals. Let us stress that the obtained estimates are integrals of the noisy measured signal: these integrals act as time-varying filters. Compared to usual approaches, our algebraic method provides a more robust estimation of these parameters within a fraction of the signal's period. We provide some computer simulations to demonstrate the efficiency of our method.
Gradient-based time to contact on paracatadioptric camera
2013
International audience; The problem of time to contact or time to collision (TTC) estimation is largely discussed in perspective images. However, a few works have dealt with images of catadioptric sensors despite of their utility in robotics applications. The objective of this paper is to develop a novel model for estimating TTC with catadioptric images relative to a planar surface, and to demonstrate that TTC can be estimated only with derivative brightness and image coordinates. This model, called "gradient based time to contact", does not need high processing such as explicit estimation of optical flow and feature detection/or tracking. The proposed method allows to estimate TTC and give…