Search results for "DIR"
showing 10 items of 10242 documents
Topology of synaptic connectivity constrains neuronal stimulus representation, predicting two complementary coding strategies
2022
In motor-related brain regions, movement intention has been successfully decoded from in-vivo spike train by isolating a lower-dimension manifold that the high-dimensional spiking activity is constrained to. The mechanism enforcing this constraint remains unclear, although it has been hypothesized to be implemented by the connectivity of the sampled neurons. We test this idea and explore the interactions between local synaptic connectivity and its ability to encode information in a lower dimensional manifold through simulations of a detailed microcircuit model with realistic sources of noise. We confirm that even in isolation such a model can encode the identity of different stimuli in a lo…
Deep CNN for IIF Images Classification in Autoimmune Diagnostics
2019
The diagnosis and monitoring of autoimmune diseases are very important problem in medicine. The most used test for this purpose is the antinuclear antibody (ANA) test. An indirect immunofluorescence (IIF) test performed by Human Epithelial type 2 (HEp-2) cells as substrate antigen is the most common methods to determine ANA. In this paper we present an automatic HEp-2 specimen system based on a convolutional neural network method able to classify IIF images. The system consists of a module for features extraction based on a pre-trained AlexNet network and a classification phase for the cell-pattern association using six support vector machines and a k-nearest neighbors classifier. The class…
Teletraffic Engineering for Direct Load Control in Smart Grids
2018
International audience; The traditional paradigm for power grid operation is to continuously adapt energy production to demand. This paradigm is challenged by the increasing penetration of renewable sources, that are more variable and less predictable. An alternative approach is the direct load control of some inherently flexible electric loads to shape the demand. Direct control of deferrable loads presents analogies with flow admission control in telecommunication networks: a request for network resources (bandwidth or energy) can be delayed on the basis of the current network status in order to guarantee some performance metrics. In this paper we go beyond such an analogy, showing that u…
Effect of Demand Side Management on the Operation of PV-Integrated Distribution Systems
2020
In this new era of high electrical energy dependency, electrical energy must be abundant and reliable, thus smart grids are conducted to deliver load demands. Hence, smart grids are implemented alongside distributed generation of renewable energies to increase the reliability and controllability of the grid, but, with the very volatile nature of the Distributed Generation (DG), Demand Side Management (DSM) helps monitor and control the load shape of the consumed power. The interaction of DSM with the grid provides a wide range of mutual benefits to the user, the utility and the market. DSM methodologies such as Conservation Voltage Reduction (CVR) and Direct Load Control (DLC) collaborate i…
Characterization of DC series arc faults in PV systems based on current low frequency spectral analysis
2021
Abstract This work presents an experimental study focused on the characterization of series arc faults in direct current (DC) photovoltaic (PV) systems. The aim of the study is to identify some relevant characteristics of arcing current, which can be obtained by means of low frequency spectral analysis of current signal. On field tests have been carried out on a real PV system, in accordance with some tests requirements of UL 1699B Standard for protection devices against PV DC arc faults. Arcing and non-arcing current signals are acquired and compared and the behavior of a set of indicators proposed by authors is analyzed. Different measurement equipment have been used, in order to study th…
The integral‐direct coupled cluster singles and doubles model
1996
An efficient and highly vectorized implementation of the coupled cluster singles and doubles (CCSD) model using a direct atomic integral technique is presented. The minimal number of n6processes has been implemented for the most time consuming terms and point group symmetry is used to further reduce operation counts and memory requirements. The significantly increased application range of the CCSD method is illustrated with sample calculations on several systems with more than 500 basis functions. Furthermore, we present the basic trends of an open ended algorithm and discuss the use of integral prescreening. © 1996 American Institute of Physics.
Two Parallel Algorithms for the Analysis of Random Images
1988
Aim of the paper is to show a computational paradigm, that reduces some algorithms on undirected graphs into image analysis algorithms. In particular two parallel algorithms on undirected weighted graphs, often used in the analysis of sparse images, are described.
Extrinsic calibration of heterogeneous cameras by line images
2014
International audience; The extrinsic calibration refers to determining the relative pose of cameras. Most of the approaches for cameras with non-overlapping fields of view (FOV) are based on mirror reflection, object tracking or rigidity constraint of stereo systems whereas cameras with overlapping FOV can be calibrated using structure from motion solutions. We propose an extrinsic calibration method within structure from motion framework for cameras with overlapping FOV and its extension to cameras with partially non-overlapping FOV. Recently, omnidirectional vision has become a popular topic in computer vision as an omnidirectional camera can cover large FOV in one image. Combining the g…
Correspondences and Contrasts in Foreign Language Pedagogy and Translation Studies
2013
Correspondences and contrasts in foreign language pedagogy.- Correspondences and contrasts in translation studies.
A Comparison of Algorithms for Path Planning of Industrial Robots
2008
In this paper, the path planning problem for industrial robots in environ- ments with obstacles has been solved using four algorithms that implement different methodologies. Our objective is to analyze the characteristics of these algorithms. Consequently, the results (solutions) obtained with each of them are compared through the analysis of three operational parameters that are relevant to determine the qualities of the solutions. These parameters are: the computational time, the distance travelled by the robot and the number of generated configurations. One of the algorithms can be catalogued as indirect and the other three are variations of a direct method. The four algorithms have been…