scholarly journals AN APPROXIMATE ANALYTICAL EXPRESSION FOR RESISTANCE OF THE VERTICAL GROUNDING ELECTRODE PLACED IN MULTILAYERED MEDIA

2018 ◽  
Vol 8 (1) ◽  
Author(s):  
DEJAN JOVANOVIĆ ◽  
NENAD CVETKOVIĆ ◽  
MIODRAG STOJANOVIĆ ◽  
MARINKO BARUKČIĆ ◽  
ŽELJKO HEDERIĆ ◽  
...  
Keyword(s):  
Method Of Moments ◽  
Specific Conductivity ◽  
Optimization Procedure ◽  
Optimization Methods ◽  
Data Sets ◽  
Multilayered Media ◽  
Approximate Analytical Expression ◽  
Vertical Electrode ◽  
Grounding Electrode

An expression for the resistance of the grounding electrode placed in the in homogeneous ground approximated by a finite number of homogeneous layers of constant specific conductivity has been evaluated and proposed in the paper. The expression is obtained by optimization procedure, based on processing of data sets obtained as a result of the analysis which includes using of the Green’s function for the point source in multilayered soil and the Method of Moments. The approach has been applied to the characterization of a vertical electrode placed in the three-layered soil. Key words: Green’s functions methods, Grounding, Optimization methods.

Auto-weighted concept factorization for joint feature map and data representation learning

2021 ◽  
pp. 1-13
Author(s):  
Yikai Zhang ◽  
Yong Peng ◽  
Hongyu Bian ◽  
Yuan Ge ◽  
Feiwei Qin ◽  
...  
Keyword(s):  
Objective Function ◽  
Optimization Procedure ◽  
Feature Space ◽  
Representation Learning ◽  
Data Representation ◽  
Data Sets ◽  
Reconstruction Process ◽  
Factorization Model ◽  
Efficient Data ◽  
Concept Factorization

Concept factorization (CF) is an effective matrix factorization model which has been widely used in many applications. In CF, the linear combination of data points serves as the dictionary based on which CF can be performed in both the original feature space as well as the reproducible kernel Hilbert space (RKHS). The conventional CF treats each dimension of the feature vector equally during the data reconstruction process, which might violate the common sense that different features have different discriminative abilities and therefore contribute differently in pattern recognition. In this paper, we introduce an auto-weighting variable into the conventional CF objective function to adaptively learn the corresponding contributions of different features and propose a new model termed Auto-Weighted Concept Factorization (AWCF). In AWCF, on one hand, the feature importance can be quantitatively measured by the auto-weighting variable in which the features with better discriminative abilities are assigned larger weights; on the other hand, we can obtain more efficient data representation to depict its semantic information. The detailed optimization procedure to AWCF objective function is derived whose complexity and convergence are also analyzed. Experiments are conducted on both synthetic and representative benchmark data sets and the clustering results demonstrate the effectiveness of AWCF in comparison with the related models.

Aerodynamic Characterization of Transonic Turbine Vanes Optimized to Attenuate Rotor Forcing

2011 ◽  
Author(s):  
R. Puente ◽  
G. Paniagua ◽  
T. Verstraete
Keyword(s):  
High Efficiency ◽  
Prediction Method ◽  
Optimization Procedure ◽  
3D Design ◽  
Turbine Vanes ◽  
Turbine Vane ◽  
Loss Prediction ◽  
Transonic Turbine ◽  
Characteristic Features

A multi-objective optimization procedure is applied to the 3D design of a transonic turbine vane row, considering efficiency and stator outlet pressure distortion, which is directly related to induced rotor forcing. The characteristic features that define different individuals along the Pareto Front are described, analyzing the differences between high efficiency airfoils and low interaction. Pressure distortion is assessed by means of a model that requires only of the computation the steady flow field in the domain of the stator. The reduction of aerodynamic rotor forcing is checked via unsteady multistage aerodynamic computations. A well known loss prediction method is used to drive the efficiency of one optimization run, while CFD analysis is used for another, in order to assess the reliability of both methods. In both cases, the decomposition of total losses is performed to quantify the influence on efficiency of reducing rotor forcing. Results show that when striving for efficiency, the rotor is affected by few, but intense shocks. On the other hand, when the objective is the minimization of distortion, multiple shocks will appear.

Nondegenerate Piecewise Linear Systems: A Finite Newton Algorithm and Applications in Machine Learning

2012 ◽  
Vol 24 (4) ◽  
pp. 1047-1084 ◽  
Author(s):  
Xiao-Tong Yuan ◽  
Shuicheng Yan
Keyword(s):  
Linear Systems ◽  
Optimization Problems ◽  
Piecewise Linear ◽  
Optimization Methods ◽  
Coefficient Matrix ◽  
Learning Problems ◽  
Support Vector ◽  
Data Sets ◽  
Piecewise Linear Systems ◽  
Vector Machines

We investigate Newton-type optimization methods for solving piecewise linear systems (PLSs) with nondegenerate coefficient matrix. Such systems arise, for example, from the numerical solution of linear complementarity problem, which is useful to model several learning and optimization problems. In this letter, we propose an effective damped Newton method, PLS-DN, to find the exact (up to machine precision) solution of nondegenerate PLSs. PLS-DN exhibits provable semiiterative property, that is, the algorithm converges globally to the exact solution in a finite number of iterations. The rate of convergence is shown to be at least linear before termination. We emphasize the applications of our method in modeling, from a novel perspective of PLSs, some statistical learning problems such as box-constrained least squares, elitist Lasso (Kowalski & Torreesani, 2008 ), and support vector machines (Cortes & Vapnik, 1995 ). Numerical results on synthetic and benchmark data sets are presented to demonstrate the effectiveness and efficiency of PLS-DN on these problems.

Migration‐based traveltime waveform inversion of 2-D simple structures: A synthetic example

Geophysics ◽  
2001 ◽  
Vol 66 (3) ◽  
pp. 845-860 ◽  
Author(s):  
François Clément ◽  
Guy Chavent ◽  
Susana Gómez
Keyword(s):  
Least Squares ◽  
Waveform Inversion ◽  
Domain Of Attraction ◽  
Optimization Methods ◽  
Data Sets ◽  
Seismic Reflection Data ◽  
Prestack Migration ◽  
Reflection Data ◽  
Full Wave ◽  
The Time Domain

Migration‐based traveltime (MBTT) formulation provides algorithms for automatically determining background velocities from full‐waveform surface seismic reflection data using local optimization methods. In particular, it addresses the difficulty of the nonconvexity of the least‐squares data misfit function. The method consists of parameterizing the reflectivity in the time domain through a migration step and providing a multiscale representation for the smooth background velocity. We present an implementation of the MBTT approach for a 2-D finite‐difference (FD) full‐wave acoustic model. Numerical analysis on a 2-D synthetic example shows the ability of the method to find much more reliable estimates of both long and short wavelengths of the velocity than the classical least‐squares approach, even when starting from very poor initial guesses. This enlargement of the domain of attraction for the global minima of the least‐squares misfit has a price: each evaluation of the new objective function requires, besides the usual FD full‐wave forward modeling, an additional full‐wave prestack migration. Hence, the FD implementation of the MBTT approach presented in this paper is expected to provide a useful tool for the inversion of data sets of moderate size.

Anti-Geometry and NeutroGeometry Characterization of Non-Euclidean Data

2021 ◽  
pp. 24-33
Author(s):  
Prem Kumar Singh ◽  
Keyword(s):  
Euclidean Geometry ◽  
Current Paper ◽  
Data Sets ◽  
Knowledge Processing ◽  
Non Euclidean Geometry ◽  
Precise Representation

Recently, a problem is addressed while dealing with fourth dimensional or non-Euclidean data sets. These are the data sets does not follow one of the postulates established by Euclid specially the parallel postulates. In this case, the precise representation of these data sets is major issues for knowledge processing tasks. Hence, the current paper tried to introduce some non-Euclidean geometry or Anti-Geometry methods and its examples for various applications.

scholarly journals Irradiance Variability Quantification and Small-Scale Averaging in Space and Time: A Short Review

Atmosphere ◽  
2018 ◽  
Vol 9 (7) ◽  
pp. 264 ◽  
Author(s):  
Gerald Lohmann
Keyword(s):  
Short Review ◽  
Power Grids ◽  
Small Scale ◽  
Stable Operation ◽  
Data Sets ◽  
Spatial Smoothing ◽  
Spatial And Temporal Scales ◽  
Output Variability ◽  
Temporal Averaging

The ongoing world-wide increase of installed photovoltaic (PV) power attracts notice to weather-induced PV power output variability. Understanding the underlying spatiotemporal volatility of solar radiation is essential to the successful outlining and stable operation of future power grids. This paper concisely reviews recent advances in the characterization of irradiance variability, with an emphasis on small spatial and temporal scales (respectively less than about 10 km and 1 min), for which comprehensive data sets have recently become available. Special attention is given to studies dealing with the quantification of variability using such unique data, the analysis and modeling of spatial smoothing, and the evaluation of temporal averaging.

scholarly journals A mixed thinning based geometric INAR(1) model

Filomat ◽  
2017 ◽  
Vol 31 (13) ◽  
pp. 4009-4022 ◽  
Author(s):  
Aleksandar Nastic ◽  
Miroslav Ristic ◽  
Ana Janjic
Keyword(s):  
Parameter Estimation ◽  
Method Of Moments ◽  
Negative Binomial ◽  
Real Life ◽  
Binomial Thinning ◽  
Conditional Least Squares ◽  
Counting Data ◽  
Parameter Estimators ◽  
Thinning Operator

In this article a geometrically distributed integer-valued autoregressive model of order one based on the mixed thinning operator is introduced. This new thinning operator is defined as a probability mixture of two well known thinning operators, binomial and negative binomial thinning. Some model properties are discussed. Method of moments and the conditional least squares are considered as possible approaches in model parameter estimation. Asymptotic characterization of the obtained parameter estimators is presented. The adequacy of the introduced model is verified by its application on a certain kind of real-life counting data, while its performance is evaluated by comparison with two other INAR(1) models that can be also used over the observed data.

scholarly journals Bayesian Classification of Microbial Communities Based on 16S rRNA Metagenomic Data

2018 ◽  
Author(s):  
Arghavan Bahadorinejad ◽  
Ivan Ivanov ◽  
Johanna W Lampe ◽  
Meredith AJ Hullar ◽  
Robert S Chapkin ◽  
...  
Keyword(s):  
16S Rrna ◽  
Sample Size ◽  
Microbial Communities ◽  
State Of The Art ◽  
Metagenomic Data ◽  
Data Sets ◽  
Sequencing Data ◽  
Sample Data

AbstractWe propose a Bayesian method for the classification of 16S rRNA metagenomic profiles of bacterial abundance, by introducing a Poisson-Dirichlet-Multinomial hierarchical model for the sequencing data, constructing a prior distribution from sample data, calculating the posterior distribution in closed form; and deriving an Optimal Bayesian Classifier (OBC). The proposed algorithm is compared to state-of-the-art classification methods for 16S rRNA metagenomic data, including Random Forests and the phylogeny-based Metaphyl algorithm, for varying sample size, classification difficulty, and dimensionality (number of OTUs), using both synthetic and real metagenomic data sets. The results demonstrate that the proposed OBC method, with either noninformative or constructed priors, is competitive or superior to the other methods. In particular, in the case where the ratio of sample size to dimensionality is small, it was observed that the proposed method can vastly outperform the others.Author summaryRecent studies have highlighted the interplay between host genetics, gut microbes, and colorectal tumor initiation/progression. The characterization of microbial communities using metagenomic profiling has therefore received renewed interest. In this paper, we propose a method for classification, i.e., prediction of different outcomes, based on 16S rRNA metagenomic data. The proposed method employs a Bayesian approach, which is suitable for data sets with small ration of number of available instances to the dimensionality. Results using both synthetic and real metagenomic data show that the proposed method can outperform other state-of-the-art metagenomic classification algorithms.

scholarly journals Approaches to improve the robustness of the Comparison Model Method for the inverse problem of groundwater hydrology

2021 ◽  
Author(s):  
Alessandro Comunian ◽  
Mauro Giudici
Keyword(s):  
Geometric Mean ◽  
Optimization Methods ◽  
Forward Problem ◽  
Data Sets ◽  
Direct Inversion ◽  
Model Method ◽  
Comparison Model ◽  
Multiple Data ◽  
Hydraulic Gradients ◽  
Multiple Data Sets

<p>Indirect inversion approaches are widely used in Geosciences, and in particular also for the identification of the hydraulic properties of aquifers. Nevertheless, their application requires a substantial number of model evaluation (forward problem) runs, a task that for complex problems can be computationally intensive. Reducing this computational burden is an active research topic, and many solutions, including the use of hybrid optimization methods, the use of physical proxies or again machine-learning tools <span>allow to avoid</span> considering the full physics of the problem when running a numerical implementation of the forward problem.</p><p>Direct inversion approaches represent computationally frugal alternatives to indirect approaches, because in general they require a smaller number of runs of the forward problem. The classical drawbacks of these methods can be alleviated by some implementation approaches and in particular by using multiple sets of data, when available.</p><p>This work is an effort to improve the robustness of the Comparison Model Method (CMM), a direct inversion approach aimed at the identification of the hydraulic transmissivity of a confined aquifer. The robustness of the CMM is here ameliorated by (i) improving the parameterization required to handle small hydraulic gradients; (ii) investigating the role of different criteria aimed at merging multiple data-sets corresponding to different flow conditions.</p><p>On a synthetic case study, it is demonstrated that correcting a small percentage of the small hydraulic gradients (about 10%) allows to obtain reliable results, and that a criteria based on the geometric mean is adequate to merge the results coming from multiple data-sets. In addition, the use of multiple-data sets allows to noticeably improve the robustness of the CMM when the input data are affected by noise.</p><p>All the tests are performed by using open source and widely <span>used</span> tools like the USGS Modflow6 and its Python interface flopy to foster the application of the <span>CMM. The scripts and corresponding package</span>, named <em>cmmpy</em>, is available on the Python Package Index (PyPI) and on bitbucket at the following address: https://bitbucket.org/alecomunian/cmmpy.</p>

scholarly journals A ocupação humana antiga (11-7 mil anos atrás) do Planalto Meridional Brasileiro: caracterização geomorfológica, geológica, paleoambiental e tecnológica de sítios arqueológicos relacionados a três distintas indústrias líticas

2020 ◽  
Vol 13 (6) ◽  
pp. 2553
Author(s):  
Pedro Michelutti Cheliz ◽  
João Carlos Moreno de Sousa ◽  
Gabriela Sartori Mingatos ◽  
Mercedes Okumura ◽  
Astolfo Gomes de Mello Araujo
Keyword(s):  
Significant Variation ◽  
Raw Materials ◽  
Archaeological Sites ◽  
Data Sets ◽  
Human Settlement ◽  
Human Occupation ◽  
Natural Landscapes ◽  
Lithic Artifacts ◽  
The Relationship

Com o objetivo de ponderar conexões entre quadros naturais e a ocupação humana pré-colonial, caracterizou-se os artefatos e a contextualização geomorfológica e ambiental de quatro sítios líticos vinculados a antigos registros de grupos caçadores-coletores do sul e sudeste do Brasil, associados a três distintas indústrias líticas. Elencou-se associação dos sítios com terrenos de baixos declives e altimetrias em seus respectivos contextos (terrenos mais estáveis para fixação humana), adjacentes a córregos e próximos de faixas do terreno que registram maiores inclinações e desníveis verticais, mais propensas a apresentarem afloramentos rochosos (fontes potenciais de matérias-primas para a confecção de ferramentas lascadas). Elencou-se fontes de matérias-primas nos entornos de cada sítio e as matérias-primas associadas aos artefatos, e ponderou-se a correlação entre os dois conjuntos de dados. Analisou-se a relação dos padrões tecnológicos de artefatos líticos com a caracterização petrográfica das matérias-primas, verificando-se quais silcretes semelhantes foram usadas para produção de artefatos distintos. Ainda, verificou-se que alguns dos produtos líticos de um dos sítios analisados mostram padrões tecnológicos semelhantes, mesmo quando obtidos a partir de silcretes distintos. Caracterizou-se ausência de variação significativa dos atributos tecnológicos dos artefatos registrados em diferentes posicionamentos verticais nos perfis das unidades de escavação nas quais foram registrados, mesmo quando mostram-se associados a registros paleoambientais distintos (alternâncias entre climas mais secos que os atuais e condições caracterizadas por incrementos de umidade no intervalo de 11 a 7 mil anos atrás).Palavras chave: sítios arqueológicos líticos; Holoceno Inicial, paleoclimas, ameríndios, geoarqueologia The ancient human occupation (11-7 thousand years ago) of the Southern Brazilian Plateau: geomorphological, geological, paleoenvironmental and technological characterization of archaeological sites related to three distinct lithic industries A B S T R A C T In order to discuss connections between the natural landscapes and pre-colonial human occupation, were characterized the artifacts and the geomorphological and environmental contextualization of four lithic sites linked to ancient records of hunter-gatherer groups from the south and southeast of Brazil, associated with three distinct lithic industries. The association of sites with low slopes and altimetry in their respective contexts (more stable terrains for human settlement), adjacent to rivers and close to terrains that register greater inclinations and vertical unevenness, more likely to present rocky outcrops (potential sources of raw materials for making chipped tools) was listed. Were characterized sources of raw materials in the surroundings of each site, the raw materials associated with the artifacts, and the correlation between the two data sets was considered. The relationship between the technological standards of lithic artifacts and the petrographic characterization of the raw materials was analyzed, verifying which similar raw materials were used to produce different artifacts. Also, it was found that some of the lithic products from one of the analyzed sites show similar technological patterns, even when obtained from different raw materials. There was a lack of significant variation in the technological attributes of the artifacts recorded in different vertical positions in the profiles of the excavation units in which they were recorded, even when they are associated with different paleoenvironmental records (alternations between drier climates than current and others characterized by increments in the moisture between 11 to 7 thousand years ago).Keywords: lithic archaeological sites; Initial Holocene, paleoclimates, amerindians, geoarchaeology 

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