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Image smoothing is a long-studied research area with tremendous approaches proposed. However, how to perform high-quality image smoothing with less computational cost still remains a challenging problem. In this paper, we try to solve this problem with a newly proposed global optimization based method named quasi weighted least squares. In our method, the 2D image is first re-ordered into a 1D vector via a newly proposed 2D-to-1D transformation. We then properly remove some original 2D neighborhood connections. The remaining neighboring pixels can simply form 1D neighborhood connections in the transformed 1D vector while they still contain the 2D neighborhood information in the original 2D image space. These together result in a quite compact linear system that can be easily and efficiently solved, which makes our method a fast global image smoothing approach. Our method is on par with the fastest approaches in terms of processing speed, however, it is able to yield comparable performance with the state-of-the-art ones in terms of smoothing quality. Our method can also work as a solver to approximate the weighted least squares problem in complex systems, and it can achieve similar results but runs much faster. The efficiency and effectiveness of our method are validated through comprehensive experiments in several tasks. Our code is publicly available at: https://github.com/wliusjtu/Q-WLS. [ABSTRACT FROM AUTHOR]

This paper focuses on theoretical analytical models to calculate the limit support pressure and vertical earth pressure on the cutting face for tunnels. The failure zone is divided into two parts: a sliding failure zone and an upper loosen zone, and the limit support pressure calculation equation is derived. To verify the rationality of the theoretical model, it was compared with the existing theory, numerical simulation, and centrifugal test, and then the parameter analysis was carried out. The results show that the results of this paper agree well with the existing theory, numerical simulation, and centrifugal test. The inclination angle of the proposed mechanism is determined based on the results of the existing centrifuge test, and the recommended inclination angle is between 52° + φ/2 and 54° + φ/2. The method is proven to be safe and accurate. It can provide a theoretical basis for similar projects.

Football is one of the best known and most practiced sports in the world, promoting direct and indirect involvement in all it players, of different ages and social classes, influencing their entire environment and indirectly everything around them.In this sense our study comes to make a survey with professionals who work with the football modality and be able to observe if the methodologies used have evolved in the practical context, and as a Qualitative Descriptive field surveywas carried out in the form of a questionnaire with fifteen coaches and teachers of football teams. The results shows that the coaches have experience in different methodologies of teaching football and the most used method to teaching football is the Global-functional, instead that the most know method is the analytical-synthetic showed by the results of the coaches so in 2020 there is a tendency to work with methodologies that involves the group of young athletesleaving theymore motivated.

Adulteration of olive oil during the packaging process may take place by accidental contamination. The development of analytical methodologies which enable detection of adulterations is warranted, since the addition of refined vegetable oils to refined olive oil (ROO) at low percentages could be a very challenging task. For this purpose, refined soybean, sunflower, corn and rapeseed oil are used for ROO fraudulent operation. ΔECN42 could be used as a parameter for the detection of ROO fraud with 0.5% refined corn oil (RCO), 0.5% refined soybean oil (RSbO), 0.4% refined rapeseed oil (RRO) and 0.1% refined sunflower oil (RSfO). The global method can be used as an effective parameter in refined olive oil adulteration even at low levels: 0.4% of RCO and RRO, 0.3% of RSbO and 0.1% of RSfO. The sterol composition can be considered as good markers of purity. Linear discriminant analysis could represent the most discriminant variable and fast tool for evaluation of ROO adulteration. [ABSTRACT FROM AUTHOR]

In this paper, we propose a Projected Inexact Quasi-Newton Method (PIQN) to solve nonlinear systems of equations with nonnegative constraints and we develop its respective global convergence theory. Particularly, we show that the method enjoys superlinear convergence rate. In addition, we show the good numerical performance of the method when applied to problems that arise in chemistry, engineering and mathematics. We highlight the efficiency of the method to solve Nonlinear Complementarity Problems (NCP), which appear in many application fields and are recognized as hard problems. [ABSTRACT FROM AUTHOR]

Power spectral analysis of short-term heart rate variability (HRV) can provide instant valuable information to understand the functioning of autonomic control over the cardiovascular system. In this study, an adaptive continuous Morlet wavelet transform (ACMWT) method has been used to describe the time-frequency characteristics of the HRV using band power spectra and the median value of interquartile range. Adaptation of the method was based on the measurement of maximum energy concentration. The ACMWT has been validated on synthetic signals (i.e. stationary, non-stationary as slow varying and fast changing frequency with time) modeled as closest to dynamic changes in HRV signals. This method has been also tested in the presence of additive white Gaussian noise (AWGN) to show its robustness towards the noise. From the results of testing on synthetic signals, the ACMWT was found to be an enhanced energy concentration estimator for assessment of power spectral of short-term HRV time series compared to adaptive Stockwell transform (AST), adaptive modified Stockwell transform (AMST), standard continuous Morlet wavelet transform (CMWT) and Stockwell transform (ST) estimators at statistical significance level of 5%. Further, the ACMWT was applied to real HRV data from Fantasia and MIT-BIH databases, grouped as healthy young group (HYG), healthy elderly group (HEG), arrhythmia controlled medication group (ARCMG), and supraventricular tachycardia group (SVTG) subjects. The global results demonstrate that spectral indices of low frequency power (LFp) and high frequency power (HFp) of HRV were decreased in HEG compared to HYG subjects (p

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Summary Based on the global method, an approach is proposed to consider the effect of anchor reinforcement on slope stability, where equilibrium conditions are formulated in terms of the whole slip body. Anchor pre‐tension is assumed to be undertaken by the whole slip body instead of individual slices, causing internal force within slope more realistic. Meanwhile, the optimization model for locating the critical slip surface is of weak nonlinearity and easy to solve using the conventional optimization procedures. The effects of anchoring orientation and position are thoroughly investigated, and interesting results are obtained. [ABSTRACT FROM AUTHOR]

• An advanced three-dimensional (3D) base isolation system was proposed. • A high-precision numerical simulation method for soil-structure interaction (SSI) was developed. • A three-way coupling analysis of the 3D base-isolated nuclear power plants (NPPs) was implemented. • An important influence of SSI on the effectiveness of NPPs with 3D base isolation in complex-layered sites was fully determined. • The rocking effects should be accounted in the 3D base isolation design of NPPs. The application of three-dimensional (3D) base isolation for nuclear structures is advantageous. In this study, an advanced 3D base isolation technique was developed and the nonlinear seismic response of 3D base-isolated nuclear structures in complex layered sites was investigated using a global method. The study first designed a novel 3D isolation system, including horizontal and vertical isolation, based on the disc spring theory, which can flexibly adjust the structural stiffness and vertical bearing capacity. To verify the applicability of 3D base isolation, the dynamic behaviour of a 3D base-isolated nuclear island building in complex-layered sites subjected to beyond-design basis ground motion was investigated using a proposed high-precision simulation program of soil-structure interaction (SSI) based on the global method. The findings demonstrate that in complex-layered sites, the SSI increases the horizontal floor response spectra (FRS) but decreases the vertical FRS of 3D base-isolated nuclear power plants, and both the horizontal and vertical isolation rates remarkably decrease. The influence of the SSI becomes more evident as the intensity of the ground motion increases. The proposed 3D base isolation system exhibits excellent isolation effects. When the vertical stiffness is reduced, the vertical isolation effect becomes more significant. However, the adverse rocking motion of the island building should be effectively controlled. The research results support the practical application of 3D base isolation technology for nuclear structures located in complex-layered sites with high seismic intensities. [ABSTRACT FROM AUTHOR]

Power spectral analysis of short-term heart rate variability (HRV) can provide instant valuable information to understand the functioning of autonomic control over the cardiovascular system. In this study, an adaptive continuous Morlet wavelet transform (ACMWT) method has been used to describe the time-frequency characteristics of the HRV using band power spectra and the median value of interquartile range. Adaptation of the method was based on the measurement of maximum energy concentration. The ACMWT has been validated on synthetic signals (i.e. stationary, nonstationary as slow varying and fast changing frequency with time) modeled as closest to dynamic changes in HRV signals. This method has been also tested in the presence of additive white Gaussian noise (AWGN) to show its robustness towards the noise. From the results of testing on synthetic signals, the ACMWT was found to be an enhanced energy concentration estimator for assessment of power spectral of short-term HRV time series compared to adaptive Stockwell transform (AST), adaptive modified Stockwell transform (AMST), standard continuous Morlet wavelet transform (CMWT) and Stockwell transform (ST) estimators at statistical significance level of 5%. Further, the ACMWT was applied to real HRV data from Fantasia and MIT-BIH databases, grouped as healthy young group (HYG), healthy elderly group (HEG), arrhythmia controlled medication group (ARCMG), and supraventricular tachycardia group (SVTG) subjects. The global results demonstrate that spectral indices of low frequency power (LFp) and high frequency power (HFp) of HRV were decreased in HEG compared to HYG subjects (p<0.0001). While LFp and HFp indices were increased in ARCMG compared to HEG (p<0.00001). The LFp and HFp components of HRV obtained from SVTG were reduced compared to other group subjects (p<0.00001). [ABSTRACT FROM AUTHOR]

Resumen Se examinaron los efectos comparados de dos métodos para la enseñanza de la escritura en el nivel inicial: global y silábico y su interacción con el estilo cognitivo en la dimensión de dependencia-independencia de campo (DIC), en 31 niños de dos grupos escolares de primer grado de primaria, de dos instituciones diferentes, en donde cada uno de los métodos de venían implementando. Se aplicaron la prueba CEFT para la determinación del estilo cognitivo y la prueba de escritura ''ejercicio de creación de texto'' al inicio del año escolar del primer grado y cuatro meses después. Los resultados finales fueron examinados a través de análisis de covarianza en los que se controlaron, como covariables, los logros registrados cuatro meses antes. Los datos muestran evidentes ventajas del método global sobre el método silábico en términos generales, y muy específicamente para los niños de estilo dependiente de campo o intermedio en seis de los ocho los indicadores examinados. Estos resultados son explicados a partir de características distintivas del estilo cognitivo en esta dimensión.Abstract Comparative effects of two methods used for teaching writing at the initial level were examined: the global and syllabic approaches and their interaction with cognitive style in the field dependence-independence dimension (FDI), in 31 first-grade children from two school groups and from two different institutions, where each one of the methods were implemented. CEFT test was applied to determine the cognitive style, and a writing test called "text-building exercise" was also used at the beginning of the academic year and four months later. The final results were esamined through covariance analysis, in which the achievements recorded four months earlier were controlled as covariates. In general, data show clear advantages of the global method over the syllabic method, specifically for field-dependent and intermediate style children in six out of eight indicators examined. These results are explained on the basis of distinctive features of the cognitive style in this dimension.

Sensitivity analysis is an important tool in building energy assessment to determine the key factors influencing energy use or carbon emissions for buildings. This research is focused on comparing the characteristics of four global sensitivity analysis: SRC (standardized regression coefficient), Morris design, extended FAST (Fourier Amplitude Sensitivity Test) and TGP (treed Gaussian process) method. A retail building located at Harbin (China) is used as a case study to demonstrate the advantages and drawbacks for these four methods. The results indicate that the TGP method (one of meta-modelling approaches) is the best choice in terms of both accuracy and computationally cost. Note that the TGP method needs more time to calculate the sensitivity index although it needs only moderate time for running building energy models. At least two fundamentally different methods for sensitivity analysis are recommended to be performed to provide more robust results in building energy assessment. [ABSTRACT FROM AUTHOR]

Two data elaboration approaches for evaluating olive oils authenticity were compared: (I) determination of the difference between the theoretical and actual amounts of triacylglycerols with partition number 42 (ΔECN42 ⩽ |0.2|); and (II) the global method, which considers also partition numbers 44 and 46 (returning a “ correct ”/“ not correct ” result). Analysis of 31 genuine extra virgin olive oil samples was performed using different analytical methods, namely liquid chromatography (LC) coupled with a refractive index detector (RID) and LC coupled with a mass spectrometry (MS), and the results compared. Several false positives were highlighted using the ΔECN42 limit with both instrumental approaches. The global method algorithm returned “ correct ” results for all the samples analysed (except two that gave no results) with LC–MS; on the other hand, 10 false positives were obtained elaborating data deriving from NARP-LC-RID analysis. [ABSTRACT FROM AUTHOR]

In this paper, we mainly focus on applying the global CGLS and GMRES methods for computing numerical approximate solutions of large-scale linear discrete ill-posed problems arising from image restoration. As is well known, global Krylov subspace methods are very popular iterative methods for solving linear systems of equations with multiple right-hand sides. These methods are based on global projections of the initial matrix residual onto a matrix Krylov subspace. It is shown in this paper that when equipped with a suitable stopping rule based on the discrepancy principle, the two global methods act as good regularization methods for ill-posed image restoration problems. To accelerate the convergence of the global methods, we project the computed approximate solutions onto the set of matrices with nonnegative entries before restarting. Some numerical examples from image restoration are given to illustrate the efficiency of the global methods. [ABSTRACT FROM AUTHOR]

Utilizing the global DEA (data envelopment analysis), this paper analyzes China's energy efficiency from both static and dynamic perspectives based on China's provincial panel data for the period of 2001–2010. We present the evolution of energy efficiency in China from 2001 to 2010, and identify the key factors influencing the energy efficiency from the aspects of technical progress, productive scale and management level. The results show that there was an overall declining trend for China's energy efficiency from 2001 to 2005, and technical regress and the decrease in scale efficiency were the main reasons for this decline. Then an overall rising trend appeared during 2005–2010, and technical progress was the most important motivation for this increase. Moreover, among the three main regions in China, the eastern China was leading in the energy efficiency during the sample period, while the energy efficiency in western China fell far behind since the beginning. And the energy efficiency in central China was in the middle. This indicates that west region may be China's promising growth engine of energy efficiency in the future, and further technical progress is thought to be the key motivation for this improvement. [ABSTRACT FROM AUTHOR]

Abstract: Sensitivity analysis plays an important role in building energy analysis. It can be used to identify the key variables affecting building thermal performance from both energy simulation models and observational study. This paper is focused on the application of sensitivity analysis in the field of building performance analysis. First, the typical steps of implementation of sensitivity analysis in building analysis are described. A number of practical issues in applying sensitivity analysis are also discussed, such as the determination of input variations, the choice of building energy programs, how to reduce computational time for energy models. Second, the sensitivity analysis methods used in building performance analysis are reviewed. These methods can be categorized into local and global sensitivity analysis. The global methods can be further divided into four approaches: regression, screening-based, variance-based, and meta-model sensitivity analysis. Recent research has been concentrated on global methods because they can explore the whole input space and most of them allow the self-verification, i.e., how much variance of the model output (building energy consumption) has been explained by the method used in the analysis. Third, we discuss several important topics, which are often overlooked in the domain of building performance analysis. These topics include the application of sensitivity analysis in observational study, how to deal with correlated inputs, the computation of the variations of sensitivity index, and the software issues. Lastly, the practical guidance is given based on the advantages and disadvantaged of different sensitivity analysis methods in assessing building thermal performance. The recommendations for further research in the future are made to provide more robust analysis in assessing building energy performance. [Copyright &y& Elsevier]

The incidence and the prevalence of end-stage renal disease (ESRD) in Taiwan are the highest in the world. Therefore, hemodialysis (HD) therapy is a major concern and an important challenge due to the shortage of donated organs for transplantation. Previous researchers developed various forecasting models based on statistical methods and artificial intelligence techniques to address the real-world problems of HD therapy that are faced by ESRD patients and their doctors in the healthcare services. Because the performance of these forecasting models is highly dependent on the context and the data used, it would be valuable to develop more suitable methods for applications in this field. This study presents an integrated procedure that is based on rough set classifiers and aims to provide an alternate method for predicting the urea reduction ratio for assessing HD adequacy for ESRD patients and their doctors. The proposed procedure is illustrated in practice by examining a dataset from a specific medical center in Taiwan. The experimental results reveal that the proposed procedure has better accuracy with a low standard deviation than the listed methods. The output created by the rough set LEM2 algorithm is a comprehensible decision rule set that can be applied in knowledge-based healthcare services as desired. The analytical results provide useful information for both academics and practitioners. [ABSTRACT FROM AUTHOR]