Relevant bibliographies by topics / Ensemble source width

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Ensemble source width'

Author: Grafiati
Published: 6 September 2023

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Journal articles on the topic "Ensemble source width"

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Imamura, Hidetaka, and Sungyoung Kim. "Efficacy of a new spatial ear training program for “Ensemble width” and “Individual source width”." Journal of the Acoustical Society of America 140, no. 4 (October 2016): 2987. http://dx.doi.org/10.1121/1.4969251.

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Allen, Douglas R., Karl W. Hoppel, Gerald E. Nedoluha, Stephen D. Eckermann, and Cory A. Barton. "Ensemble-Based Gravity Wave Parameter Retrieval for Numerical Weather Prediction." Journal of the Atmospheric Sciences 79, no. 3 (March 2022): 621–48. http://dx.doi.org/10.1175/jas-d-21-0191.1.

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Abstract Gravity wave (GW) momentum and energy deposition are large components of the momentum and heat budgets of the stratosphere and mesosphere, affecting predictability across scales. Since weather and climate models cannot resolve the entire GW spectrum, GW parameterizations are required. Tuning these parameterizations is time-consuming and must be repeated whenever model configurations are changed. We introduce a self-tuning approach, called GW parameter retrieval (GWPR), applied when the model is coupled to a data assimilation (DA) system. A key component of GWPR is a linearized model of the sensitivity of model wind and temperature to the GW parameters, which is calculated using an ensemble of nonlinear forecasts with perturbed parameters. GWPR calculates optimal parameters using an adaptive grid search that reduces DA analysis increments via a cost-function minimization. We test GWPR within the Navy Global Environmental Model (NAVGEM) using three latitude-dependent GW parameters: peak momentum flux, phase-speed width of the Gaussian source spectrum, and phase-speed weighting relative to the source-level wind. Compared to a baseline experiment with fixed parameters, GWPR reduces analysis increments and improves 5-day mesospheric forecasts. Relative to the baseline, retrieved parameters reveal enhanced source-level fluxes and westward shift of the wave spectrum in the winter extratropics, which we relate to seasonal variations in frontogenesis. The GWPR reduces stratospheric increments near 60°S during austral winter, compensating for excessive baseline nonorographic GW drag. Tropical sensitivity is weaker due to significant absorption of GW in the stratosphere, resulting in less confidence in tropical GWPR values.
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Connelly, Ryan, and Brian A. Colle. "Validation of Snow Multibands in the Comma Head of an Extratropical Cyclone Using a 40-Member Ensemble." Weather and Forecasting 34, no. 5 (September 11, 2019): 1343–63. http://dx.doi.org/10.1175/waf-d-18-0182.1.

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Abstract This paper investigates the ability of the Weather Research and Forecasting (WRF) Model in simulating multiple small-scale precipitation bands (multibands) within the extratropical cyclone comma head using four winter storm cases from 2014 to 2017. Using the model output, some physical processes are explored to investigate band prediction. A 40-member WRF ensemble was constructed down to 2-km grid spacing over the Northeast United States using different physics, stochastic physics perturbations, different initial/boundary conditions from the first five perturbed members of the Global Forecast System (GFS) Ensemble Reforecast (GEFSR), and a stochastic kinetic energy backscatter scheme (SKEBS). It was found that 2-km grid spacing is adequate to resolve most snowbands. A feature-based verification is applied to hourly WRF reflectivity fields from each ensemble member and the WSR-88D radar reflectivity at 2-km height above sea level. The Method for Object-Based Diagnostic Evaluation (MODE) tool is used for identifying multibands, which are defined as two or more bands that are 5–20 km in width and that also exhibit a >2:1 aspect ratio. The WRF underpredicts the number of multibands and has a slight eastward position bias. There is no significant difference in frontogenetical forcing, vertical stability, moisture, and vertical shear between the banded versus nonbanded members. Underpredicted band members tend to have slightly stronger frontogenesis than observed, which may be consolidating the bands, but overall there is no clear linkage in ambient condition errors and band errors, thus leaving the source for the band underprediction motivation for future work.
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Jongaramrungruang, Siraput, Christian Frankenberg, Georgios Matheou, Andrew K. Thorpe, David R. Thompson, Le Kuai, and Riley M. Duren. "Towards accurate methane point-source quantification from high-resolution 2-D plume imagery." Atmospheric Measurement Techniques 12, no. 12 (December 17, 2019): 6667–81. http://dx.doi.org/10.5194/amt-12-6667-2019.

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Abstract. Methane is the second most important anthropogenic greenhouse gas in the Earth climate system but emission quantification of localized point sources has been proven challenging, resulting in ambiguous regional budgets and source category distributions. Although recent advancements in airborne remote sensing instruments enable retrievals of methane enhancements at an unprecedented resolution of 1–5 m at regional scales, emission quantification of individual sources can be limited by the lack of knowledge of local wind speed. Here, we developed an algorithm that can estimate flux rates solely from mapped methane plumes, avoiding the need for ancillary information on wind speed. The algorithm was trained on synthetic measurements using large eddy simulations under a range of background wind speeds of 1–10 m s−1 and source emission rates ranging from 10 to 1000 kg h−1. The surrogate measurements mimic plume mapping performed by the next-generation Airborne Visible/Infrared Imaging Spectrometer (AVIRIS-NG) and provide an ensemble of 2-D snapshots of column methane enhancements at 5 m spatial resolution. We make use of the integrated total methane enhancement in each plume, denoted as integrated methane enhancement (IME), and investigate how this IME relates to the actual methane flux rate. Our analysis shows that the IME corresponds to the flux rate nonlinearly and is strongly dependent on the background wind speed over the plume. We demonstrate that the plume width, defined based on the plume angular distribution around its main axis, provides information on the associated background wind speed. This allows us to invert source flux rate based solely on the IME and the plume shape itself. On average, the error estimate based on randomly generated plumes is approximately 30 % for an individual estimate and less than 10 % for an aggregation of 30 plumes. A validation against a natural gas controlled-release experiment agrees to within 32 %, supporting the basis for the applicability of this technique to quantifying point sources over large geographical areas in airborne field campaigns and future space-based observations.
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Kang, Sarah M., Clara Deser, and Lorenzo M. Polvani. "Uncertainty in Climate Change Projections of the Hadley Circulation: The Role of Internal Variability." Journal of Climate 26, no. 19 (September 24, 2013): 7541–54. http://dx.doi.org/10.1175/jcli-d-12-00788.1.

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Abstract The uncertainty arising from internal climate variability in climate change projections of the Hadley circulation (HC) is presently unknown. In this paper it is quantified by analyzing a 40-member ensemble of integrations of the Community Climate System Model, version 3 (CCSM3), under the Special Report on Emissions Scenarios (SRES) A1B scenario over the period 2000–60. An additional set of 100-yr-long time-slice integrations with the atmospheric component of the same model [Community Atmosphere Model, version 3.0 (CAM3)] is also analyzed. Focusing on simple metrics of the HC—its strength, width, and height—three key results emerge from the analysis of the CCSM3 ensemble. First, the projected weakening of the HC is almost entirely confined to the Northern Hemisphere, and is stronger in winter than in summer. Second, the projected widening of the HC occurs only in the winter season but in both hemispheres. Third, the projected rise of the tropical tropopause occurs in both hemispheres and in all seasons and is, by far, the most robust of the three metrics. This paper shows further that uncertainty in future trends of the HC width is largely controlled by extratropical variability, while those of HC strength and height are associated primarily with tropical dynamics. Comparison of the CCSM3 and CAM3 integrations reveals that ocean–atmosphere coupling is the dominant source of uncertainty in future trends of HC strength and height and of the tropical mean meridional circulation in general. Finally, uncertainty in future trends of the hydrological cycle is largely captured by the uncertainty in future trends of the mean meridional circulation.
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UNNIKRISHNAN, C. S., and C. P. SAFVAN. "EXPERIMENTAL TEST OF A QUANTUM-LIKE THEORY: MOTION OF ELECTRONS IN A UNIFORM MAGNETIC FIELD, IN A VARIABLE POTENTIAL WELL." Modern Physics Letters A 14, no. 07 (March 7, 1999): 479–90. http://dx.doi.org/10.1142/s0217732399000535.

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We describe an experiment to test a quantum-like theory which predicts quantum-like behavior for an ensemble of electrons in a classical configuration with static magnetic and electric fields. Some of the earlier experiments had supporting evidence for anomalous, quantum-like effects in such a situation showing systematic modulations of electron current when a retarding potential is varied, even though the quantum wavelength of the electrons in such a configuration was less than a billionth of the spatial width of the potential well. Our experiment conclusively rules out any nonclassical, quantum-like behavior in electron transmission through simple electric barriers, when magnetic fields are present. We identify secondary electrons generated at various electrodes as the main source of apparent anomalous behavior. We also present a classical derivation of the quantum-like equation describing the modulations.
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Trier, Stanley B., Glen S. Romine, David A. Ahijevych, Robert J. Trapp, Russ S. Schumacher, Michael C. Coniglio, and David J. Stensrud. "Mesoscale Thermodynamic Influences on Convection Initiation near a Surface Dryline in a Convection-Permitting Ensemble." Monthly Weather Review 143, no. 9 (August 31, 2015): 3726–53. http://dx.doi.org/10.1175/mwr-d-15-0133.1.

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Abstract In this study, the authors examine initiation of severe convection along a daytime surface dryline in a 10-member ensemble of convection-permitting simulations. Results indicate that the minimum buoyancy Bmin of PBL air parcels must be small (Bmin > −0.5°C) for successful deep convection initiation (CI) to occur along the dryline. Comparing different ensemble members reveals that CAPE magnitudes (allowing for entrainment) and the width of the zone of negligible Bmin extending eastward from the dryline act together to influence CI. Since PBL updrafts that initiate along the dryline move rapidly northeast in the vertically sheared flow as they grow into the free troposphere, a wider zone of negligible Bmin helps ensure adequate time for incipient storms to mature, which, itself, is hastened by larger CAPE. Local Bmin budget calculations and trajectory analysis are used to quantify physical processes responsible for the reduction of negative buoyancy prior to CI. Here, the grid-resolved forcing and forcing from temperature and moisture tendencies in the PBL scheme (arising from surface fluxes) contribute about equally in ensemble composites. However, greater spatial variability in grid-resolved forcing focuses the location of the greatest net forcing along the dryline. The grid-resolved forcing is influenced by a thermally direct vertical circulation, where time-averaged ascent at the east edge of the dryline results in locally deeper moisture and cooler conditions near the PBL top. Horizontal temperature advection spreads the cooler air eastward above higher equivalent potential temperature air at source levels of convecting air parcels, resulting in a wider zone of negligible Bmin that facilitates sustained CI.
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Rieznik, Olena. "Children’s orchestral set “Harmonika” by H. T. Statyvkin as a source of developing initial skills of ensemble and orchestral music playing for preschool children." Problems of Interaction Between Arts, Pedagogy and the Theory and Practice of Education 64, no. 64 (December 7, 2022): 75–91. http://dx.doi.org/10.34064/khnum1-64.05.

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The figure of Hennadii Tymofiyovych Statyvkin as a reformer of the methodology of teaching the button accordion has always interested researchers for its versatility: ideas of restructuring the educational process of primary music education; experimental introduction of new methodological principles in the educational process; introduction of a seven-year period of training for button accordionists in children’s music schools; production of special training children’s selectable and ready-made button accordions; development and publication of a new curriculum and teaching aids. The above-mentioned ranges of H. Statyvkin’s activity have been covered by scholars at different times exclusively from the point of view of changing the methodology of teaching the button accordion from a selectable to a ready-made instrument. The problem of studying the structure of children’s accordion instruments created by H. Statyvkin has never acquired the format of a special separate study. The proposed article aims to reveal the design activity H. Statyvkin by analysing the design features of children’s musical instruments created by him for ensemble and orchestral music for preschool children. The scientific novelty of the research results is due to the introduction of some facts about the design features of the children’s orchestra set “Harmonika” into the scientific circulation of musicology, which made it possible to reveal the specifics of H. Statyvkin’s design thinking. Based on the analysis of the system of sound disposition at the right keyboards of the “Solo-1” and “Solo-2” instruments, we can conclude that H. Statyvkin’s system corresponds to the right keyboard of the piano-type accordion, but in the button version. Unusual for the button accordion disposition of the sounds at the right keyboard and grouping of major and minor triads in one row of the left keyboard is based on ergonomic and physiological data of preschool children (height and width of the chest, length of hands and forearms). It was this design that made it possible to reduce the overall sizes of the instruments and to make them in accordance with the physiology of a preschool children.
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Timme, Nicholas M., David Linsenbardt, and Christopher C. Lapish. "A Method to Present and Analyze Ensembles of Information Sources." Entropy 22, no. 5 (May 21, 2020): 580. http://dx.doi.org/10.3390/e22050580.

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Information theory is a powerful tool for analyzing complex systems. In many areas of neuroscience, it is now possible to gather data from large ensembles of neural variables (e.g., data from many neurons, genes, or voxels). The individual variables can be analyzed with information theory to provide estimates of information shared between variables (forming a network between variables), or between neural variables and other variables (e.g., behavior or sensory stimuli). However, it can be difficult to (1) evaluate if the ensemble is significantly different from what would be expected in a purely noisy system and (2) determine if two ensembles are different. Herein, we introduce relatively simple methods to address these problems by analyzing ensembles of information sources. We demonstrate how an ensemble built of mutual information connections can be compared to null surrogate data to determine if the ensemble is significantly different from noise. Next, we show how two ensembles can be compared using a randomization process to determine if the sources in one contain more information than the other. All code necessary to carry out these analyses and demonstrations are provided.
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Bécar, Ramón, P. A. González, Joel Saavedra, Yerko Vásquez, and Bin Wang. "Phase transitions in four-dimensional AdS black holes with a nonlinear electrodynamics source." Communications in Theoretical Physics 73, no. 12 (November 12, 2021): 125402. http://dx.doi.org/10.1088/1572-9494/ac3073.

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Abstract In this work we consider black hole solutions to Einstein’s theory coupled to a nonlinear power-law electromagnetic field with a fixed exponent value. We study the extended phase space thermodynamics in canonical and grand canonical ensembles, where the varying cosmological constant plays the role of an effective thermodynamic pressure. We examine thermodynamical phase transitions in such black holes and find that both first- and second-order phase transitions can occur in the canonical ensemble while, for the grand canonical ensemble, Hawking–Page and second-order phase transitions are allowed.
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Dissertations / Theses on the topic "Ensemble source width"

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Arthi, S. "Auditory Timbre and Spatialisation: Signal Analysis and Perception of Source Widening." Thesis, 2022. https://etd.iisc.ac.in/handle/2005/5988.

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In this work, auditory perception of source widening is examined in the context of different source signal timbre. Perception of widening of source or auditory source width (ASW) arises in three cases: (i) In the presence of reverberation, which has been referred to as reverberant source width (RSW); (ii) Distributed sources such as an ensemble, where multiple sources are physically placed widely, referred as ensemble source width (ESW); and (iii) In hearing disabilities, where localisation is poor in the presence of interfering sources and hence a widened or diffused source width (DSW) is perceived. Though the physics of the problem is different in each of the above cases, we observe that the perception of source widening occurs in all the three cases. We also show analytically that in the case of localised, reverb and ensemble sources located about a particular direction, binaural cross-correlation has interesting properties: (i) for localised source, cross-correlation is energy compact, followed by (ii) reverb source and (iii) ESW has highly dispersed cross-correlation compared to localised and reverb sources with the same angle of arrival and degree of decorrelation as reverb sources. Traditionally, (1-IACC) has been used as a measure for RSW and in the literature this measure is used for ESW also. We propose a combination of timbre-independent phase-based angular measure for the physical extent of the sources, localising all or many individual sources using HRIR correlation functions and timbre dependent mean time-bandwidth energy (MTBE) measure for relative perceptual weighting to compare ensemble of different timbres. This analysis gives rise to possible applications in ensemble rendering and insights into improving hearing aids for hearing impaired listeners. Frequency sensitivity to change in IACC, and hence ASW, has been studied using binaural presentation of modulated sinusoids. In this work, we observe a similar sensitivity to ESW by presenting listeners with spatially wide sources using narrow band noise signals. We observe that frequency sensitivity of ASW and ESW are similar. We also study bandwidth sensitivity and observe that with increase in bandwidth, the perceived width of the ensemble increases. We simulate ensemble-like music signals of different spectro-temporal distribution to probe the timbre dependency of human perception. The listeners are asked to rate the ESW of the simulated distributed sources. Broadly, music signals can be classified as sustained instruments, partially sustained, partially transient and predominantly transient signals. Low frequency sustained instruments give rise to a wider percept than semi-sustained and transient signals. We also explore the difference between discrete and continuous spectral sources for spatialisation. We observe that continuous spectra do give rise to stable mono- tonic width perception with change in physical width. On the other hand, in the case of discrete spectra, we do not perceive a stable monotonic perception. We developed a MUSHRA like (Multiple stimulus hidden reference and anchor) listening methodology for estimating the accuracy of direction perception of the target signals with and without interference by normal listeners. We observe that the accuracy of direction perception of the target is high without interference. In the presence of interference, we observe that the perceived target direction is away from that of interference, thus increasing the perceived angular separation. This perceptual effect may be used in the design of binaural hearing-aids to enhance binaural perception of localised sources in the presence of interference. Overall, in this work, we study the perceptual interaction of signal timbre and spatialisation in the perception of ensemble source width. We study the sensitivity of several parameters like frequency, bandwidth, spectro-temporal energy distribution and role of fine AM-FM parameters.
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Chang, Chu-Chun, and 張楚珺. "Constraining sources and sinks for trace species under an ensemble-based data assimilation framework with a regional chemical transport model: CO2 as an example." Thesis, 2013. http://ndltd.ncl.edu.tw/handle/19656452905458886617.

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碩士
國立中央大學
大氣物理研究所
101
To constrain the sources and sinks of the chemical compounds of interest at surface from limited observations, a chemical assimilation with the Local Ensemble Transform Kalman Filter (LETKF) has been developed and implemented to the WRF-Chem model. In this study, a two-tier method is used to update the meteorological and chemical states updated separately and simultaneously. To investigate the capability of the WRF-Chem/LETKF system, experiments are carried out under an observation simulation system experiments (OSSE) framework. Two scenarios of localized emissions are tested: constant emission and emission with diurnal cycle. Results indicate that the system can successfully provide reasonable estimate for the constant forcing case and improve the distribution of the chemicals. Strategies need to be applied for retrieving the time-varying emission.
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Books on the topic "Ensemble source width"

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Kumar, Alok, and Mayank Jain. Ensemble Learning for AI Developers: Learn Bagging, Stacking, and Boosting Methods with Use Cases. Apress, 2020.

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Khoruzhenko, Boris, and Hans-Jurgen Sommers. Characteristic polynomials. Edited by Gernot Akemann, Jinho Baik, and Philippe Di Francesco. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780198744191.013.19.

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This article considers characteristic polynomials and reviews a few useful results obtained in simple Gaussian models of random Hermitian matrices in the presence of an external matrix source. It first considers the products and ratio of characteristic polynomials before discussing the duality theorems for two different characteristic polynomials of Gaussian weights with external sources. It then describes the m-point correlation functions of the eigenvalues in the Gaussian unitary ensemble and how they are deduced from their Fourier transforms U(s1, … , sm). It also analyses the relation of the correlation function of the characteristic polynomials to the standard n-point correlation function using the replica and supersymmetric methods. Finally, it shows how the topological invariants of Riemann surfaces, such as the intersection numbers of the moduli space of curves, may be derived from averaged characteristic polynomials.
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Congendo, Marco, and Fernando H. Lopes da Silva. Event-Related Potentials. Edited by Donald L. Schomer and Fernando H. Lopes da Silva. Oxford University Press, 2017. http://dx.doi.org/10.1093/med/9780190228484.003.0039.

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Event-related potentials (ERPs) can be elicited by a variety of stimuli and events in diverse conditions. This chapter covers the methodology of analyzing and quantifying ERPs in general. Basic models (additive, phase modulation and resetting, potential asymmetry) that account for the generation of ERPs are discussed. The principles and requirements of ensemble time averaging are presented, along with several univariate and multivariate methods that have been proposed to improve the averaging procedure: wavelet decomposition and denoising, spatial, temporal and spatio-temporal filtering. We emphasize basic concepts of principal component analysis, common spatial pattern, and blind source separation, including independent component analysis. We cover practical questions related to the averaging procedure: overlapping ERPs, correcting inter-sweep latency and amplitude variability, alternative averaging methods (e.g., median), and estimation of ERP onset. Some specific aspects of ERP analysis in the frequency domain are surveyed, along with topographic analysis, statistical testing, and classification methods.
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Horing, Norman J. Morgenstern. Quantum Statistical Field Theory. Oxford University Press, 2018. http://dx.doi.org/10.1093/oso/9780198791942.001.0001.

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The methods of coupled quantum field theory, which had great initial success in relativistic elementary particle physics and have subsequently played a major role in the extensive development of non-relativistic quantum many-particle theory and condensed matter physics, are at the core of this book. As an introduction to the subject, this presentation is intended to facilitate delivery of the material in an easily digestible form to students at a relatively early stage of their scientific development, specifically advanced undergraduates (rather than second or third year graduate students), who are mathematically strong physics majors. The mechanism to accomplish this is the early introduction of variational calculus with particle sources and the Schwinger Action Principle, accompanied by Green’s functions, and, in addition, a brief derivation of quantum mechanical ensemble theory introducing statistical thermodynamics. Important achievements of the theory in condensed matter and quantum statistical physics are reviewed in detail to help develop research capability. These include the derivation of coupled field Green’s function equations of motion for a model electron-hole-phonon system, extensive discussions of retarded, thermodynamic and non-equilibrium Green’s functions, and their associated spectral representations and approximation procedures. Phenomenology emerging in these discussions includes quantum plasma dynamic, nonlocal screening, plasmons, polaritons, linear electromagnetic response, excitons, polarons, phonons, magnetic Landau quantization, van der Waals interactions, chemisorption, etc. Considerable attention is also given to low-dimensional and nanostructured systems, including quantum wells, wires, dots and superlattices, as well as materials having exceptional conduction properties such as superconductors, superfluids and graphene.
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Tiwari, Sandip. Nanoscale Device Physics. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198759874.001.0001.

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Nanoscale devices are distinguishable from the larger microscale devices in their specific dependence on physical phenomena and effects that are central to their operation. The size change manifests itself through changes in importance of the phenomena and effects that become dominant and the changes in scale of underlying energetics and response. Examples of these include classical effects such as single electron effects, quantum effects such as the states accessible as well as their properties; ensemble effects ranging from consequences of the laws of numbers to changes in properties arising from different magnitudes of the inter-actions, and others. These interactions, with the limits placed on size, make not just electronic, but also magnetic, optical and mechanical behavior interesting, important and useful. Connecting these properties to the behavior of devices is the focus of this textbook. Description of the book series: This collection of four textbooks in the Electroscience series span the undergraduate-to-graduate education in electrosciences for engineering and science students. It culminates in a comprehensive under-standing of nanoscale devices—electronic, magnetic, mechanical and optical in the 4th volume, and builds to it through volumes devoted to underlying semiconductor and solid-state physics with an emphasis on phenomena at surfaces and interfaces, energy interaction, and fluctuations; a volume devoted to the understanding of the variety of devices through classical microelectronic approach, and an engineering-focused understanding of principles of quantum, statistical and information mechanics. The goal is provide, with rigor and comprehensiveness, an exposure to the breadth of knowledge and interconnections therein in this subject area that derives equally from sciences and engineering. By completing this through four integrated texts, it circumvents what is taught ad hoc and incompletely in a larger number of courses, or not taught at all. A four course set makes it possible for the teaching curriculum to be more comprehensive in this and related advancing areas of technology. It ends at a very modern point, where researchers in the subject area would also find the discussion and details an important reference source.
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Book chapters on the topic "Ensemble source width"

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Khanna, Megha, Srishti Priya, and Diksha Mehra. "Software Change Prediction with Homogeneous Ensemble Learners on Large Scale Open-Source Systems." In IFIP Advances in Information and Communication Technology, 68–86. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-75251-4_7.

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Lien, Yen-Chieh, Rongting Zhang, F. Maxwell Harper, Vanessa Murdock, and Chia-Jung Lee. "Leveraging Customer Reviews for E-commerce Query Generation." In Lecture Notes in Computer Science, 190–98. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-99739-7_22.

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AbstractCustomer reviews are an effective source of information about what people deem important in products (e.g. “strong zipper” for tents). These crowd-created descriptors not only highlight key product attributes, but can also complement seller-provided product descriptions. Motivated by this, we propose to leverage customer reviews to generate queries pertinent to target products in an e-commerce setting. While there has been work on automatic query generation, it often relied on proprietary user search data to generate query-document training pairs for learning supervised models. We take a different view and focus on leveraging reviews without training on search logs, making reproduction more viable by the public. Our method adopts an ensemble of the statistical properties of review terms and a zero-shot neural model trained on adapted external corpus to synthesize queries. Compared to competitive baselines, we show that the generated queries based on our method both better align with actual customer queries and can benefit retrieval effectiveness.
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Robin, William. "All-Stars." In Industry, 138–60. Oxford University Press, 2021. http://dx.doi.org/10.1093/oso/9780190068653.003.0006.

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In 1992, Bang on a Can launched their own in-house ensemble, the All-Stars, an amplified sextet designed to take the spirit of the festival on the road. Along with building a new audience via national and international tours, the All-Stars also unlocked a new source of earned income for Bang on a Can amidst an era of declining government support. The sound and image of the extroverted ensemble facilitated a pivot in Bang on a Can’s identity, from strongly emphasizing the overcoming of stylistic divides within new music (as epitomized by the uptown–downtown binary) to instead emphasizing the blurring of genre boundaries between contemporary classical music and rock. The All-Stars also instantiated a division of labor between composers and performers that was unusual in the history of new-music ensembles and led to some significant tensions, tied to how Bang on a Can carefully positioned their new group toward the marketplace.
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Inês Pires, Maria. "O contributo do ensemble DME para o dinamismo da cena musical contemporânea." In Investigação e Ensino em Design e Música, 114–27. Edições IPCB, 2022. http://dx.doi.org/10.53681/2022.i02/02/12.

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Ensemble DME is a musical group dedicated to the interpretation and diffusion of contemporary art music, through concerts, masterclasses, conferences, gatherings, open rehearsals, and pedagogic activities. This chapter makes known the Ensemble DME’s history, the reasons for its foundation, the activities it develops, the frequency and the locations of its performances, the repertory it interprets and how the group interacts with other entities. The results come from the analysis of documentary sources originating in the activities realized between 2013 and 2021, as well as from semi-structured interviews to the artistic director and the executive director of the Ensemble DME. Thus, it is possible how the Ensemble DME contributes to the dynamics of the contemporary musical scene, in collaboration with other entities.
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Nazeer, Ishrat, Mamoon Rashid, Sachin Kumar Gupta, and Abhishek Kumar. "Use of Novel Ensemble Machine Learning Approach for Social Media Sentiment Analysis." In Research Anthology on Applying Social Networking Strategies to Classrooms and Libraries, 383–95. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-6684-7123-4.ch021.

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Twitter is a platform where people express their opinions and come with regular updates. At present, it has become a source for many organizations where data will be extracted and then later analyzed for sentiments. Many machine learning algorithms are available for twitter sentiment analysis which are used for automatically predicting the sentiment of tweets. However, there are challenges that hinder machine learning classifiers to achieve better results in terms of classification. In this chapter, the authors are proposing a novel feature generation technique to provide desired features for training model. Next, the novel ensemble classification system is proposed for identifying sentiment in tweets through weighted majority rule ensemble classifier, which utilizes several commonly used statistical models like naive Bayes, random forest, logistic regression, which are weighted according to their performance on historical data, where weights are chosen separately for each model.
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Nazeer, Ishrat, Mamoon Rashid, Sachin Kumar Gupta, and Abhishek Kumar. "Use of Novel Ensemble Machine Learning Approach for Social Media Sentiment Analysis." In Research Anthology on Implementing Sentiment Analysis Across Multiple Disciplines, 184–97. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-6684-6303-1.ch010.

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Twitter is a platform where people express their opinions and come with regular updates. At present, it has become a source for many organizations where data will be extracted and then later analyzed for sentiments. Many machine learning algorithms are available for twitter sentiment analysis which are used for automatically predicting the sentiment of tweets. However, there are challenges that hinder machine learning classifiers to achieve better results in terms of classification. In this chapter, the authors are proposing a novel feature generation technique to provide desired features for training model. Next, the novel ensemble classification system is proposed for identifying sentiment in tweets through weighted majority rule ensemble classifier, which utilizes several commonly used statistical models like naive Bayes, random forest, logistic regression, which are weighted according to their performance on historical data, where weights are chosen separately for each model.
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Nazeer, Ishrat, Mamoon Rashid, Sachin Kumar Gupta, and Abhishek Kumar. "Use of Novel Ensemble Machine Learning Approach for Social Media Sentiment Analysis." In Advances in Social Networking and Online Communities, 16–28. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-4718-2.ch002.

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Twitter is a platform where people express their opinions and come with regular updates. At present, it has become a source for many organizations where data will be extracted and then later analyzed for sentiments. Many machine learning algorithms are available for twitter sentiment analysis which are used for automatically predicting the sentiment of tweets. However, there are challenges that hinder machine learning classifiers to achieve better results in terms of classification. In this chapter, the authors are proposing a novel feature generation technique to provide desired features for training model. Next, the novel ensemble classification system is proposed for identifying sentiment in tweets through weighted majority rule ensemble classifier, which utilizes several commonly used statistical models like naive Bayes, random forest, logistic regression, which are weighted according to their performance on historical data, where weights are chosen separately for each model.
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Rajkumar S., Mary Nikitha K., Ramanathan L., Rajasekar Ramalingam, and Mudit Jantwal. "Cloud Hosted Ensemble Learning-Based Rental Apartment Price Prediction Model Using Stacking Technique." In Deep Learning Research Applications for Natural Language Processing, 229–38. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-6684-6001-6.ch015.

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In this chapter, online rental listings of the city of Hyderabad are used as a data source for mapping house rent. Data points were scraped from one of the popular Indian rental websites www.nobroker.in. With the collected information, models of rental market dynamics were developed and evaluated using regression and boosting algorithms such as AdaBoost, CatBoost, LightGBM, XGBoost, KRR, ENet, and Lasso regression. An ensemble machine learning algorithm of the best combination of the aforementioned algorithms was also implemented using the stacking technique. The results of these algorithms were compared using several performance metrics such as coefficient of determination (R2 score), mean squared error (MSE), root mean squared error (RMSE), mean absolute error (MAE), and accuracy in order to determine the most effective model. According to further examination of results, it is clear that the ensemble machine learning algorithm does outperform the others in terms of better accuracy and reduced errors.
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Azibi, Hayfa, Nida Meddouri, and Mondher Maddouri. "Survey on Formal Concept Analysis Based Supervised Classification Techniques." In Machine Learning and Artificial Intelligence. IOS Press, 2020. http://dx.doi.org/10.3233/faia200762.

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Classification is a data mining task and which is a two-phase process: learning and classification. The learning phase consists of constructing a classifier or a model from a labeled set of objects. The classification phase consists classifying new objects by using the generated classifier. Different approaches have been proposed for supervised classification problems through Formal Concept Analysis, and which is a mathematical theory to build upon hierarchies of formal concepts. The proposed approaches in literature rely on the use of single classifier and ensemble methods. Single classifier methods vary between them according to different criteria especially the number of formal concepts generated. We distinguish overall complete lattice methods, sub-lattice methods and concept cover methods. Methods based on ensemble classifiers rely on the use of many classifiers. Among these methods, there are methods based on sequential training and methods based on parallel training. However, with the large volume of data generated from various sources, the process of knowledge extraction with traditional methods becomes difficult. That’s why new methods based on distributed classifier have recently appeared. In this paper, we present a survey of many FCA-based approaches for classification by dividing them into methods based on a mono-classifier, methods based on ensemble classifiers and methods based on distributed classifiers. Different methods are presented and compared within this paper.
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Naoui, Mohamed, Flah Aymen, Ben Hamed Mouna, and Lassaad Sbita. "Brushless Motor and Wireless Recharge System for Electric Vehicle Design Modeling and Control." In Advances in Systems Analysis, Software Engineering, and High Performance Computing, 338–62. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-5788-4.ch014.

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This chapter deals with the problem of energy storage inside an electric vehicle. The main source of energy is based on a wireless system. This recharge tool regroups inside several components as the storage system, which consists of an ensemble of batteries and serving as the main power source, a special electronic converter that is based on the buck-boost principle and a coil receiver placed undo the vehicle. From the other side, one or more than coil transmitters are placed on the road, where the vehicle is. Modeling all of these components and expressing their mathematical models seems interesting for defining the possible control method that can guarantee a high autonomy when the vehicle is moving. So, taking into account if the care is driving or stopped, this recharge system is studied for verifying the effectiveness of this recharge system and showing the relationship between the vehicle situation and the quantity of received power. Using the platform Matlab/Simulink the results were shown and discussed.
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Conference papers on the topic "Ensemble source width"

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Cerdá, Salvador, Alicia Giménez, Rosa Cibrián, Jaume Segura, Radha Montell, and Arturo Barba. "Objective Evaluation of the Width of Source Ensemble in Virtual Halls." In ASME 2012 Noise Control and Acoustics Division Conference at InterNoise 2012. American Society of Mechanical Engineers, 2012. http://dx.doi.org/10.1115/ncad2012-72001.

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In this work, we study the effects of the width of the sound source in several acoustical virtual room models with different topologies, sizes and uses, calibrated with commercial software. To achieve this aim, a square distribution of sound sources with variable side length has been considered. We have auralized four channels of speech signal and musical signal in three different locations in each room. By using signal processing techniques, a comparison of multisource auralizations with the ones obtained from a single source in the middle of the stage is made. Also, the variations between the usual room parameters obtained from these simulations are analyzed, in order to show the effect of the hall in the objective evaluation according to the source width. Paper NCAD2012-72001 is available online only.
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Arthi, S., and T. V. Sreenivas. "Binaural Spatial Transform for Multi-source Localization determining Angular Extent of Ensemble Source Width." In 2022 IEEE International Conference on Signal Processing and Communications (SPCOM). IEEE, 2022. http://dx.doi.org/10.1109/spcom55316.2022.9840782.

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Arthi, S., and T. V. Sreenivas. "Multi-loudspeaker Rendering of Musical Ensemble: Role of Timbre in Source Width Perception." In TENCON 2019 - 2019 IEEE Region 10 Conference (TENCON). IEEE, 2019. http://dx.doi.org/10.1109/tencon.2019.8929725.

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He, C., Y. Chen, H. Fu, and G. Yang. "Ensemble Full Wave Inversion with Source Encoding." In 77th EAGE Conference and Exhibition 2015. Netherlands: EAGE Publications BV, 2015. http://dx.doi.org/10.3997/2214-4609.201412764.

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Flores, Enrique, Lidia Moreno, and Paolo Rosso. "Detecting Source Code Re-Use with Ensemble Models." In CERI '16: 4th Spanish Conference in Information Retrieval. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2934732.2934738.

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Fu, Haohuan, and Bingwei Chen. "Ensemble source encoding full-waveform inversion with self-adaptive regularization." In SEG Technical Program Expanded Abstracts 2016. Society of Exploration Geophysicists, 2016. http://dx.doi.org/10.1190/segam2016-13963398.1.

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He, Qi-Qiao, Patrick Cheong-Iao Pang, and Yain-Whar Si. "Multi-source Transfer Learning with Ensemble for Financial Time Series Forecasting." In 2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT). IEEE, 2020. http://dx.doi.org/10.1109/wiiat50758.2020.00034.

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Lai, Kwun-Ping, Jackie Chun-Sing Ho, and Wai Lam. "Ensemble Model for Multi-Source Cross-Domain Sentiment Classification with Little Labeled Data." In 2020 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT). IEEE, 2020. http://dx.doi.org/10.1109/wiiat50758.2020.00038.

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Zou, Quanyi, Lu Lu, Zhanyu Yang, and Hao Xu. "Multi-source Cross Project Defect Prediction with Joint Wasserstein Distance and Ensemble Learning." In 2021 IEEE 32nd International Symposium on Software Reliability Engineering (ISSRE). IEEE, 2021. http://dx.doi.org/10.1109/issre52982.2021.00019.

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Aly, Mohamed Amr, Patrizia Anastasi, Ernesto Della Rossa, Angelo Ortega, and Simona Renna. "Integration of Production Data Analysis in Ensemble History Matching." In SPE Reservoir Characterisation and Simulation Conference and Exhibition. SPE, 2023. http://dx.doi.org/10.2118/212679-ms.

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Abstract The reservoir model-based forecast uncertainty reduction requires the integration of multiple sources of information. Among them, production data are of great value. For this reason, a methodology able to manage them within the history matching process to improve the model calibration process is highly recommended. The scope of the activity is then to set up a new workflow able to fully integrate Production Data Analysis (PDA) with an Ensemble History Matching (ENHM) workflow. PDA outcomes represent evidence highlighted by the whole production history based on the collection, analysis, and integration of all available geological and dynamic data, such as injector-producer connections. A set of alternative realizations ("ensemble") needs to be created representing all the relevant uncertainties. Ensemble Screening is necessary to eliminate the non-PDA compliant realizations; comparing streamlines generated on the ensemble with the PDA outcomes and eliminating the non-representative realizations. Ensemble diagnostic tools can help to discriminate the ensemble consistency with the basic reservoir facts coming from PDA and which parameters or assumptions in the ensemble creation need to be revised because of the non-compatibility from a statistical point of view (like conflicting or insufficient parameterizations). The ensemble will be matched through the ENHM iterative process. The proposed workflow uses then the Fluid Path Conceptual Model (FPCM) derived from PDA, as a key driver to localize the model updates performed by the iterative ensemble process. The proposed workflow allows obtaining a set of realizations representative of both the main geological and dynamical features of the field. This in turn will result in a higher predictive quality of the model-based forecasts. The performed tests allow us to conclude that PDA outcomes provide significant information regarding the fluid communications that can improve the ensemble reservoir parameterization reducing the reservoir uncertainties. Ensemble distance computation based on streamline attributes, like Time of Flight and streamline normalized fraction, can find similarities among realizations reflecting the connectivity patterns relevant to the PDA perspective. The evidence highlighted from PDA can be used as firm input in the ensemble realizations generation also impacting fundamental steps, such as the geological setup. Moreover, PDA can help to identify the main uncertainty parameters characterizing the field and suggests a reasonable range of variability to be considered within the ensemble approach. Multiple ensemble diagnostic tools were developed to check the ensemble quality against PDA outcomes using different streamline attributes as a distance. Diagnostic tools, moreover, allow to identify a reduced number of model realizations representative of the ensemble variability on which run the forecast. The advantages of the proposed workflow can balance the unavoidable additional time with respect to standard ensemble history matching for its practical realizations on field cases, especially with many data and high model complexity.
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