Search results for "Engineering sciences"
showing 10 items of 2347 documents
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…
Efficient linear fusion of partial estimators
2018
Abstract Many signal processing applications require performing statistical inference on large datasets, where computational and/or memory restrictions become an issue. In this big data setting, computing an exact global centralized estimator is often either unfeasible or impractical. Hence, several authors have considered distributed inference approaches, where the data are divided among multiple workers (cores, machines or a combination of both). The computations are then performed in parallel and the resulting partial estimators are finally combined to approximate the intractable global estimator. In this paper, we focus on the scenario where no communication exists among the workers, de…
Adaptive Importance Sampling: The past, the present, and the future
2017
A fundamental problem in signal processing is the estimation of unknown parameters or functions from noisy observations. Important examples include localization of objects in wireless sensor networks [1] and the Internet of Things [2]; multiple source reconstruction from electroencephalograms [3]; estimation of power spectral density for speech enhancement [4]; or inference in genomic signal processing [5]. Within the Bayesian signal processing framework, these problems are addressed by constructing posterior probability distributions of the unknowns. The posteriors combine optimally all of the information about the unknowns in the observations with the information that is present in their …
A new image segmentation approach using community detection algorithms
2015
Image segmentation has an important role in many image processing applications. Several methods exist for segmenting an image. However, this technique is still a relatively open topic for which various research works are regularly presented. With the recent developments on complex networks theory, image segmentation techniques based on graphs has considerably improved. In this paper, we present a new perspective of image segmentation, by applying three of the most efficient community detection algorithms, Louvain, infomap and stability optimization based on the louvain algorithm, and we extract communities in which the highest modularity feature is achieved. After we show that this measure …
A video-based real-time vehicle counting system using adaptive background method
2008
International audience; This paper presents a video-based solution for real time vehicle detection and counting system, using a surveillance camera mounted on a relatively high place to acquire the traffic video stream.The two main methods applied in this system are: the adaptive background estimation and the Gaussian shadow elimination. The former allows a robust moving detection especially in complex scenes. The latter is based on color space HSV, which is able to deal with different size and intensity shadows. After these two operations, it obtains an image with moving vehicle extracted, and then operation counting is effected by a method called virtual detector.
Green food processing: concepts, strategies, and tools
2019
Abstract One of the developmental aspects of food science is testing and adapting advanced technologies for food production, which save resources and improve food quality. More often than not, this includes technologies operating at lower temperatures, shorter time, and resulting in better preservation of the thermolabile compounds in the foods, as compared to conventional technologies. Nutritionally rich but thermally sensitive raw materials such as fruit, vegetables, meats, and others can particularly benefit from the application of such advanced food technologies. Technologies with the most tested potential for industrial implementation include nonthermal plasma, pulsed electric field, h…
Unsupervised image processing scheme for transistor photon emission analysis in order to identify defect location
2015
International audience; The study of the light emitted by transistors in a highly scaled complementary metal oxide semiconductor (CMOS) integrated circuit (IC) has become a key method with which to analyze faulty devices, track the failure root cause, and have candidate locations for where to start the physical analysis. The localization of defective areas in IC corresponds to a reliability check and gives information to the designer to improve the IC design. The scaling of CMOS leads to an increase in the number of active nodes inside the acquisition area. There are also more differences between the spot’s intensities. In order to improve the identification of all of the photon emission sp…
Progress in EU Breeding Blanket design and integration
2018
Abstract In Europe (EU), in the frame of the EUROfusion consortium activities, four Breeding Blanket (BB) concepts are being developed with the aim of fulfilling the performances required by a near-term fusion power demonstration plant (DEMO) in terms of tritium self-sufficiency and electricity production. The four blanket options cover a wide range of technological possibilities, as water and helium are considered as possible coolants and solid ceramic breeder in combination with beryllium and PbLi as tritium breeder and neutron multipliers. The strategy for the BB selection and operation has to account for the challenging schedule of the EU DEMO, the ambitious operational requirements of …
Adaptive Population Importance Samplers: A General Perspective
2016
Importance sampling (IS) is a well-known Monte Carlo method, widely used to approximate a distribution of interest using a random measure composed of a set of weighted samples generated from another proposal density. Since the performance of the algorithm depends on the mismatch between the target and the proposal densities, a set of proposals is often iteratively adapted in order to reduce the variance of the resulting estimator. In this paper, we review several well-known adaptive population importance samplers, providing a unified common framework and classifying them according to the nature of their estimation and adaptive procedures. Furthermore, we interpret the underlying motivation …
Distributed Particle Metropolis-Hastings Schemes
2018
We introduce a Particle Metropolis-Hastings algorithm driven by several parallel particle filters. The communication with the central node requires the transmission of only a set of weighted samples, one per filter. Furthermore, the marginal version of the previous scheme, called Distributed Particle Marginal Metropolis-Hastings (DPMMH) method, is also presented. DPMMH can be used for making inference on both a dynamical and static variable of interest. The ergodicity is guaranteed, and numerical simulations show the advantages of the novel schemes.