Search results for "signal processing"
showing 10 items of 2451 documents
Using electric fields to prevent mirror-trapped antiprotons in antihydrogen studies
2013
The signature of trapped antihydrogen ($\overline{\mathrm{H}}$) atoms is the annihilation signal detected when the magnetic trap that confines the atoms is suddenly switched off. This signal would be difficult to distinguish from the annihilation signal of any trapped $\overline{p}$ that is released when the magnetic trap is switched off. This work deduces the large cyclotron energy ($g$137 eV) required for magnetic trapping of $\overline{p}$, considers the possibility that such $\overline{p}$ are produced, and explores the effectiveness of an electric field applied to clear charged particles from the trapping volume before $\overline{\mathrm{H}}$ detection. No mechanisms are found that can…
Tunable and reconfigurable microwave filter by use of a Bragg-grating-based acousto-optic superlattice modulator
2005
We present an all-optical novel configuration for implementing multitap transversal filters by use of a broadband source sliced by fiber Bragg grating arrays generated by propagating an acoustic wave along a strong uniform fiber Bragg grating. The tunability and reconfigurability of the microwave filter are demonstrated.
Influence of enhancement filters in apical bone loss measurement: A cone-beam computed tomography study
2016
Background The use of cone-beam computed tomography images (CBCT) providing a better assessment of bone injuries, although the sensibility of lesions measurement might be improved by the use of enhancement filters. Objective: This study aimed to analyze the influence of enhancement filters in apical bone loss measurement. Material and Methods Eighteen CBCT cases randomly selected of apical bone loss were evaluated. The analyses were carried out following the evaluation in axial, coronal and sagittal protocols, using enhancement filters as Hard, Normal, and Very Sharp. The variables were statistically analyzed by Friedman and Wilcoxon test, Spearman’s rho, and intraclass correlation coeffici…
Extracting modular-based backbones in weighted networks
2021
Abstract Networks are an adequate representation for modeling and analyzing a great variety of complex systems. However, understanding networks with millions of nodes and billions of connections can be pretty challenging due to memory and time constraints. Therefore, selecting the relevant nodes and edges of these large-scale networks while preserving their core information is a major issue. In most cases, the so-called backbone extraction methods are based either on coarse-graining or filtering approaches. Coarse-graining techniques reduce the network size by gathering similar nodes into super-nodes, while filter-based methods eliminate nodes or edges according to a statistical property.In…
Energy saving in WWTP: Daily benchmarking under uncertainty and data availability limitations
2016
Efficient management of Waste Water Treatment Plants (WWTPs) can produce significant environmental and economic benefits. Energy benchmarking can be used to compare WWTPs, identify targets and use these to improve their performance. Different authors have performed benchmark analysis on monthly or yearly basis but their approaches suffer from a time lag between an event, its detection, interpretation and potential actions. The availability of on-line measurement data on many WWTPs should theoretically enable the decrease of the management response time by daily benchmarking. Unfortunately this approach is often impossible because of limited data availability. This paper proposes a methodolo…
The neural basis of sublexical speech and corresponding nonspeech processing: a combined EEG-MEG study.
2014
Abstract We addressed the neural organization of speech versus nonspeech sound processing by investigating preattentive cortical auditory processing of changes in five features of a consonant–vowel syllable (consonant, vowel, sound duration, frequency, and intensity) and their acoustically matched nonspeech counterparts in a simultaneous EEG–MEG recording of mismatch negativity (MMN/MMNm). Overall, speech–sound processing was enhanced compared to nonspeech sound processing. This effect was strongest for changes which affect word meaning (consonant, vowel, and vowel duration) in the left and for the vowel identity change in the right hemisphere also. Furthermore, in the right hemisphere, spe…
Density as a constraint and the separation of internal excitation energy in TDHF
1985
We present a fast and efficient constrained Hartree-Fock iteration scheme which constraints the complete density distribution to remain constant. The scheme is particularly suited to a coordinate- or momentum-space representation. The technique is applied to separate the collective and the internal energy in a propagating TDHF state. We study the behavior of these two energies in an16O+16O collision.
LoRa-Based Sensor Node Energy Consumption with Data Compression
2021
In this paper simple temporal compression algorithms' efficiency to reduce LoRa-based sensor node energy consumption has been evaluated and measured. It is known that radio transmission is the most energy consuming operation in a wireless sensor node. In this paper three lightweight compression algorithms are implemented in an embedded LoRa platform to compress sensor data in on-line mode and the overall energy consumption is measured. Energy consumption is compared to the situation without implementing any compression algorithm. The results show that a simple compression algorithm is an effective method to improve the battery powered sensor node lifetime. Despite the radio transmission's h…
A pattern recognition approach for peak prediction of electrical consumption
2016
Predicting and mitigating demand peaks in electrical networks has become a prevalent research topic. Demand peaks pose a particular challenge to energy companies because these are difficult to foresee and require the net to support abnormally high consumption levels. In smart energy grids, time-differentiated pricing policies that increase the energy cost for the consumers during peak periods, and load balancing are examples of simple techniques for peak regulation. In this paper, we tackle the task of predicting power peaks prior to their actual occurrence in the context of a pilot Norwegian smart grid network.
Novel Energy Modelling and Forecasting Tools for Smart Energy Networks
2015
A novel Energy Modelling and Forecasting Tool (EMFT) has been adopted for use in the VIM SEN (Virtual Microgrids for Smart Energy Networks) project and this paper gives an insight of the techniques used to provide vital support to the energy market, in particular to energy aggregators. A brief description of one of the test sites where data has been collected for validation of the EMFT will be outlined and some examples shown. The information and predictions will then be used by a decision support system to dynamically adjust energy delivery and consumption, by giving advice to users and operators on actions they can take to obtain a better match between energy supply and demand that increa…