Search results for "artificial intelligence"
showing 10 items of 6122 documents
Conceptualization of relative size by honeybees
2014
The ability to process visual information using relational rules allows for decisions independent of the specific physical attributes of individual stimuli. Until recently, the manipulation of relational concepts was considered as a prerogative of large mammalian brains. Here we show that individual free flying honeybees can learn to use size relationship rules to choose either the larger or smaller stimulus as the correct solution in a given context, and subsequently apply the learnt rule to novel colors and shapes providing that there is sufficient input to the long wavelength (green) photoreceptor channel. Our results add a novel, size-based conceptual rule to the set of relational conce…
Forecast of Study Success in the STEM Disciplines Based Solely on Academic Records
2020
We present an approach to the forecast of the study success in selected STEM disciplines (computer science, mathematics, physics, and meteorology), solely based on the academic record of a student so far, without access to demographic or socioeconomic data. The purpose of the analysis is to improve student counseling, which may be essential for finishing a study program in one of the above mentioned fields. Technically, we show the successful use of propositionalization on relational data from educational data mining, based on standard aggregates and basic LSTM-trained aggregates.
Relaxation of certain integral functionals depending on strain and chemical composition
2012
We provide a relaxation result in $BV \times L^q$, $1\leq q < +\infty$ as a first step towards the analysis of thermochemical equilibria.
Non-linear System Identification with Composite Relevance Vector Machines
2007
Nonlinear system identification based on relevance vector machines (RVMs) has been traditionally addressed by stacking the input and/or output regressors and then performing standard RVM regression. This letter introduces a full family of composite kernels in order to integrate the input and output information in the mapping function efficiently and hence generalize the standard approach. An improved trade-off between accuracy and sparsity is obtained in several benchmark problems. Also, the RVM yields confidence intervals for the predictions, and it is less sensitive to free parameter selection. Teoría de la Señal y Comunicaciones
Generalized Entropies, Variance and Applications
2020
The generalized cumulative residual entropy is a recently defined dispersion measure. In this paper, we obtain some further results for such a measure, in relation to the generalized cumulative residual entropy and the variance of random lifetimes. We show that it has an intimate connection with the non-homogeneous Poisson process. We also get new expressions, bounds and stochastic comparisons involving such measures. Moreover, the dynamic version of the mentioned notions is studied through the residual lifetimes and suitable aging notions. In this framework we achieve some findings of interest in reliability theory, such as a characterization for the exponential distribution, various resul…
On Distinguishing between Reliable and Unreliable Sensors Without a Knowledge of the Ground Truth
2015
In many applications, data from different sensors are aggregated in order to obtain more reliable information about the process that the sensors are monitoring. However, the quality of the aggregated information is intricately dependent on the reliability of the individual sensors. In fact, unreliable sensors will tend to report erroneous values of the ground truth, and thus degrade the quality of the fused information. Finding strategies to identify unreliable sensors can assist in having a counter-effect on their respective detrimental influences on the fusion process, and this has has been a focal concern in the literature. The purpose of this paper is to propose a solution to an extreme…
On Solving the Problem of Identifying Unreliable Sensors Without a Knowledge of the Ground Truth: The Case of Stochastic Environments.
2017
The purpose of this paper is to propose a solution to an extremely pertinent problem, namely, that of identifying unreliable sensors (in a domain of reliable and unreliable ones) without any knowledge of the ground truth. This fascinating paradox can be formulated in simple terms as trying to identify stochastic liars without any additional information about the truth. Though apparently impossible, we will show that it is feasible to solve the problem, a claim that is counterintuitive in and of itself. One aspect of our contribution is to show how redundancy can be introduced, and how it can be effectively utilized in resolving this paradox. Legacy work and the reported literature (for exam…
Multispectral, Fluorescent and Photoplethysmographic Imaging for Remote Skin Assessment
2017
Optical tissue imaging has several advantages over the routine clinical imaging methods, including non-invasiveness (does not change the structure of tissues), remote operation (avoids infection) and ability to quantify the tissue condition by means of specific image parameters. Dermatologists and other skin experts need compact (preferably pocket-size), self-sustained and easy-to-use imaging devices. The operational principles and designs of ten portable in-vivo skin imaging prototypes developed at the Biophotonics Laboratory of Institute of Atomic Physics and Spectroscopy, University of Latvia during the recent five years are presented in this paper. Four groups of imaging devices are con…
Kernel Spectral Angle Mapper
2016
This communication introduces a very simple generalization of the familiar spectral angle mapper (SAM) distance. SAM is perhaps the most widely used distance in chemometrics, hyperspectral imaging, and remote sensing applications. We show that a nonlinear version of SAM can be readily obtained by measuring the angle between pairs of vectors in a reproducing kernel Hilbert spaces. The kernel SAM generalizes the angle measure to higher-order statistics, it is a valid reproducing kernel, it is universal, and it has consistent geometrical properties that permit deriving a metric easily. We illustrate its performance in a target detection problem using very high resolution imagery. Excellent re…
Characterization of Radio Frequency Echo using frequency sweeping and power analysis
2014
International audience; Coupling between repeater's antennas, called Radio Frequency Echo (RFE) deteriorates signal quality and compromises system stability. If the channel insulation is insufficient, the power in the closed-loop raises with time according to the gain margin value. Multiple methods of echo cancellation exists. Generally, these techniques are based on correlation calculation and adaptive filtering. However, their efficiency and algorithm's convergence speed are calling into question under signal's modulation and real-time constraints, specially with narrow band signals having frequency hopping as GSM or TETRA. This paper describes a real time method of RFE detection and esti…