scholarly journals The Performance Evolution of Match Play Styles in the Spanish Professional Basketball League

2020 ◽  
Vol 10 (20) ◽  
pp. 7056
Author(s):  
Miguel-Ángel Gómez ◽  
Ramón Medina ◽  
Anthony S. Leicht ◽  
Shaoliang Zhang ◽  
Alejandro Vaquera
Keyword(s):  
Mean Squared Error ◽  
Temporal Trends ◽  
Statistical Modelling ◽  
Positive Trend ◽  
Match Play ◽  
Professional Basketball ◽  
The Matrix ◽  
Point Field ◽  
Stable Performance ◽  
Play Styles

The aim of this study is to analyse the performance evolution of all, and the dominant, team’s performances throughout an eight-season period within the Spanish professional basketball league. Match-related statistics were gathered from all regular season matches (n = 2426) played during the period 2009–2010 to 2016–2017. The non-metric multidimensional scaling model was used to examine the team’s profiles across seasons and for the most successful (playoff) teams. The main results showed that: 3-point field goals made (effect size, d = 0.61; 90% confidence interval, CI = 0.23; 1.37) and missed (d = 0.72; 90% CI = 0.35; 1.46), and assists (d = 1.27; 90% CI = 0.82; 1.86) presented a positive trend with an increased number of actions across the seasons; 2-point field goals made (d = 0.21; 90% CI = −1.25; 2.02) and missed (d = 0.27; 90% CI = −0.52; 0.92) were decreased; free throws made and missed, rebounds, fouls, blocks, steals and turnovers showed a relatively stable performance. The matrix solution (stress = 0.22, rmse (root mean squared error) = 7.9 × 104, maximum residual = 5.8 × 103) indicated minimal season-to-season evolution with the ordination plot and convex hulls overlapping. The two most dominant teams exhibited unique match patterns with the most successful team’s pattern, a potential benchmark for others who exhibited more dynamic evolutions (and less success). The current findings identified the different performances of teams within the Spanish professional basketball league over eight seasons with further statistical modelling of match play performances useful to identify temporal trends and support coaches with training and competition preparations.

scholarly journals Indicadores de desempenho registrados em função do tempo no basquetebol brasileiro

2018 ◽  
Vol 20 (2) ◽  
pp. 172-181
Author(s):  
Yura Yuka Sato dos Santos ◽  
Lucas Antônio Monezi ◽  
Milton Shoiti Misuta ◽  
Luciano Allegretti Mercadante
Keyword(s):  
Performance Analysis ◽  
Normal Distribution ◽  
Professional Basketball ◽  
Technical Indicators ◽  
Point Field ◽  
Emerging Issues ◽  
Kolmogorov Smirnov ◽  
The Difference ◽  
The Moment ◽  
Smirnov Test

Basketball performance analysis using technical indicators dissociated from the moment they occurred in the game seems to no longer respond to emerging issues of the game as it does not identify the periods when a team’s offensive efficiency has increased or decreased. The aim was to characterize and compare the technical indicators in the positive and negative periods and in the whole game of winning and losing teams in men’s professional basketball. Fourteen games of professional men’s teams of the “Novo Basquete Brasil” Championship in the regular 2011/2012 season were filmed and analyzed. The Kolmogorov-Smirnov test was used to verify data normality. The independent T test was used for variables with normal distribution and the Mann-Whitney test for variables that did not present normal distribution, in order to compare teams’ performance. Analysis in the whole game showed that winning teams had significantly higher averages in successful 3-point field goals but in the positive periods, they showed higher averages for successful free throws, successful layups, defensive rebounds and defensive fouls, and in negative periods, losing teams made more defensive and offensive fouls. The teams’ performance in the whole game may not elucidate the determinant indicators for building the difference in the scoreboard. It is suggested that coaches should identify the periods of best and worst teams’ performance in the game and the indicators involved, preparing teams to overcome the negative periods and obtain more positive periods in the game. 

scholarly journals Space–time clustering and temporal trends of hospitalizations due to pulmonary tuberculosis: potential strategy for assessing health care policies

2020 ◽  
Author(s):  
João Almeida Santos ◽  
Danielle T Santos ◽  
Ricardo A Arcencio ◽  
Carla Nunes
Keyword(s):  
Pulmonary Tuberculosis ◽  
Hospital Admissions ◽  
Temporal Trends ◽  
Space Time ◽  
Public Hospitals ◽  
Percentage Change ◽  
Ambulatory Setting ◽  
Spatial And Temporal Variation ◽  
Positive Trend ◽  
Annual Percentage Change

Abstract Background Tuberculosis (TB) causes pressure on healthcare resources, especially in terms of hospital admissions, despite being considered an ambulatory care-sensitive condition for which timely and effective care in ambulatory setting could prevent the need for hospitalization. Our objectives were to describe the spatial and temporal variation in pulmonary tuberculosis (PTB) hospitalizations, identify critical geographic areas at municipality level and characterize clusters of PTB hospitalizations to help the development of tailored disease management strategies that could improve TB control. Methods Ecologic study using sociodemographic, geographical and clinical information of PTB hospitalization cases from continental Portuguese public hospitals, between 2002 and 2016. Descriptive statistics, spatiotemporal cluster analysis and temporal trends were conducted. Results The space–time analysis identified five clusters of higher rates of PTB hospitalizations (2002–16), including the two major cities in the country (Lisboa and Porto). Globally, we observed a −7.2% mean annual percentage change in rate with only one of the identified clusters (out of six) with a positive trend (+4.34%). In the more recent period (2011–16) was obtained a mean annual percentage change in rate of −8.12% with only one cluster identified with an increase trend (+9.53%). Conclusions Our results show that space–time clustering and temporal trends analysis can be an invaluable resource to monitor the dynamic of the disease and contribute to the design of more effective, focused interventions. Interventions such as enhancing the detection of active and latent infection, improving monitoring and evaluation of treatment outcomes or adjusting the network of healthcare providers should be tailored to the specific needs of the critical areas identified.

On the geodesic property of strain field patterns in elastoplastic composites

2008 ◽  
Vol 464 (2093) ◽  
pp. 1217-1227 ◽  
Author(s):  
Dominique Jeulin ◽  
Wei Li ◽  
Martin Ostoja-Starzewski
Keyword(s):  
Plastic Flow ◽  
Response Pattern ◽  
Computational Mechanics ◽  
Strain Fields ◽  
Field Patterns ◽  
The Matrix ◽  
Point Field ◽  
Perfect Bonding ◽  
Plastic Hardening ◽  
Sequential Inhibition

Under study is the geodesic (i.e. shortest path) character of strain fields occurring in inelastic response of matrix-inclusion composites. The spatially random morphology of composites is created by generating the inclusions centres through a sequential inhibition process based on a planar Poisson point field preventing any disc overlaps. Both phases (inclusions and matrix) are elastic–plastic hardening with the matrix being more compliant and weaker than the inclusions, and perfect bonding holding everywhere, so that the plastic flow occurs between the inclusions. A quantitative comparison of a response pattern obtained by computational mechanics with that found only by mathematical morphology indicates that (i) the regions of plastic flow are close (or even very close) to geodesics and (ii) a purely geometric (and orders of magnitude more rapid than by computational mechanics) assessment of these regions is possible.

Particle Distribution Design in a Self-Flow Alumina Refractory Castable without Cement

2006 ◽  
Vol 45 ◽  
pp. 2260-2265 ◽  
Author(s):  
Abílio P. Silva ◽  
Ana M. Segadães ◽  
Tessaleno C. Devezas
Keyword(s):  
Mechanical Strength ◽  
Particle Distribution ◽  
Fine Particles ◽  
Rheological Behaviour ◽  
Statistical Modelling ◽  
Coarse Particles ◽  
The Matrix ◽  
Firing Shrinkage ◽  
Refractory Cement ◽  
Alumina Refractory

A self-flow refractory castable (SFRC) without cement requires a matrix of fine particles and a broad size distribution of coarse particles (aggregate). The matrix ensures the rheological behaviour and performs the binding role of the absent refractory cement. The presence of the aggregate coarse particles hinders the flowability index (FI), but improves the castable mechanical strength and reduces firing shrinkage. A new methodology of SFRC particle distribution design was developed, using response surface statistical modelling and commercial alumina powders (reactive and tabular). First, the composition of the fine matrix was optimised, seeking minimum water content and maximum IF. To this matrix, various aggregate distributions, combining six tabular alumina size fractions and with different Andreasen distribution modulus, q, between 0.18 to 0.28, were added, to identify the composition with maximum FI. The results obtained show that a minimum specific surface area (SSA) of 2.22m2/g is necessary to reach the self-flow turning point, after which the largest FI requires the maximisation of the aggregate maximum paste thickness (MPT), corresponding to a distribution with q=0.22. The optimised castable composition presents high mechanical strength (>60MPa) and low shrinkage.

scholarly journals A new modified ridge-type estimator for the beta regression model: simulation and application

2021 ◽  
Vol 7 (1) ◽  
pp. 1035-1057
Author(s):  
Muhammad Nauman Akram ◽  
◽  
Muhammad Amin ◽  
Ahmed Elhassanein ◽  
Muhammad Aman Ullah ◽  
...  
Keyword(s):  
Regression Model ◽  
Mean Squared Error ◽  
Model Simulation ◽  
Beta Regression ◽  
Explanatory Variables ◽  
Squared Error ◽  
The Matrix ◽  
Biased Estimators ◽  
Highly Correlated ◽  
Beta Regression Model

<abstract> <p>The beta regression model has become a popular tool for assessing the relationships among chemical characteristics. In the BRM, when the explanatory variables are highly correlated, then the maximum likelihood estimator (MLE) does not provide reliable results. So, in this study, we propose a new modified beta ridge-type (MBRT) estimator for the BRM to reduce the effect of multicollinearity and improve the estimation. Initially, we show analytically that the new estimator outperforms the MLE as well as the other two well-known biased estimators i.e., beta ridge regression estimator (BRRE) and beta Liu estimator (BLE) using the matrix mean squared error (MMSE) and mean squared error (MSE) criteria. The performance of the MBRT estimator is assessed using a simulation study and an empirical application. Findings demonstrate that our proposed MBRT estimator outperforms the MLE, BRRE and BLE in fitting the BRM with correlated explanatory variables.</p> </abstract>

Design of the Particle Size Composition of an Alumina Powder Matrix for Maximum Flowability and Minimum Water Content

2006 ◽  
Vol 530-531 ◽  
pp. 425-430 ◽  
Author(s):  
Abílio P. Silva ◽  
Ana M. Segadães ◽  
Tessaleno C. Devezas
Keyword(s):  
Particle Size ◽  
Water Content ◽  
Raw Materials ◽  
Size Composition ◽  
Statistical Modelling ◽  
Linear Shrinkage ◽  
Response Surfaces ◽  
Alumina Powder ◽  
Particle Size Composition ◽  
The Matrix

In this work, commercial alumina fine powders were used as raw materials, namely two tabular alumina fractions (–500 mesh and –230 mesh) and a reactive alumina. Statistical modelling and the Response Surface Methodology (Statistica, Mixtures Designs and Triangular Surfaces module) were applied to three-component mixtures and used to calculate the various property-composition surfaces. To that aim, the various mixtures were prepared, cast, dried, fired and characterised. The particle size distribution modulus, q, was determined for all mixtures using the software LISA. The various response surfaces were then combined, so that the water content in the mixture could be minimised and the matrix flowability maximised. The properties of the resulting test-bricks (linear shrinkage, mechanical strength, apparent density and porosity) were also modelled and response surfaces were obtained. Combined results enabled the definition of an optimised particle size composition range, which guarantees the presence of a low water flow-bed that enables the aggregate self-flow.

scholarly journals Statistical modelling of agrometeorological time series by exponential smoothing

2016 ◽  
Vol 30 (1) ◽  
pp. 57-65 ◽  
Author(s):  
Małgorzata Murat ◽  
Iwona Malinowska ◽  
Holger Hoffmann ◽  
Piotr Baranowski
Keyword(s):  
Time Series ◽  
Mean Squared Error ◽  
Statistical Modelling ◽  
Absolute Error ◽  
Exponential Smoothing ◽  
Growth And Yield ◽  
Climate Change Scenarios ◽  
Autocorrelation Functions ◽  
Using Data

Abstract Meteorological time series are used in modelling agrophysical processes of the soil-plant-atmosphere system which determine plant growth and yield. Additionally, long-term meteorological series are used in climate change scenarios. Such studies often require forecasting or projection of meteorological variables, eg the projection of occurrence of the extreme events. The aim of the article was to determine the most suitable exponential smoothing models to generate forecast using data on air temperature, wind speed, and precipitation time series in Jokioinen (Finland), Dikopshof (Germany), Lleida (Spain), and Lublin (Poland). These series exhibit regular additive seasonality or non-seasonality without any trend, which is confirmed by their autocorrelation functions and partial autocorrelation functions. The most suitable models were indicated by the smallest mean absolute error and the smallest root mean squared error.

scholarly journals AN ENHANCED IMAGE STEGANOGRAPHY TECHNIQUE FOR HIGH-SECURITY COMMUNICATION

2021 ◽  
Vol 9 (2) ◽  
pp. 1-6
Author(s):  
Apoorv Mahajan ◽  
Arpan Singh Rajput
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Data Hiding ◽  
Mean Squared Error ◽  
Signal To Noise Ratio ◽  
Image Steganography ◽  
Discrete Wavelet ◽  
Minimum Mean Squared Error ◽  
The Matrix ◽  
Value Decomposition

Purpose of the study: We propose an approach to hide data in an image with minimum Mean Squared Error (MSE) and maximum Signal-to-Noise ratio (SNR) using Discrete Wavelet Transform (DWT). Methodology: The methodology used by us considers the application of Discrete Wavelet transform to transform the values of the image into a different domain for embedding the information to be hidden in the image and then using Singular Value decomposition we decomposed the matrix values of the image for better data hiding. Main Findings: The application of the SVD function gave the model a better performance and also RED pixel values with the High-High frequency domain are a better cover for hiding data. Applications of this study: This article can be used for further research on applications of mathematical and frequency transformation functions on data hiding. It can also be used to implement a highly secure image steganography model. Novelty/Originality of this study: The application of Discrete Wavelet Transform has been used before but the application of SVD and hiding data in the H-H domain to obtain better results is original.

scholarly journals Practical Aspects of Log-ratio Coordinate Representations in Regression with Compositional Response

2016 ◽  
Vol 16 (5) ◽  
pp. 235-243 ◽  
Author(s):  
Eva Fišerová ◽  
Sandra Donevska ◽  
Karel Hron ◽  
Ondřej Bábek ◽  
Kristýna Vaňkátová
Keyword(s):  
Compositional Data ◽  
Mean Squared Error ◽  
Statistical Modelling ◽  
Parameters Estimation ◽  
Squared Error ◽  
Regression Parameters ◽  
Orthonormal Coordinates ◽  
The Mean ◽  
Log Ratio

AbstractRegression analysis with compositional response, observations carrying relative information, is an appropriate tool for statistical modelling in many scientific areas (e.g. medicine, geochemistry, geology, economics). Even though this technique has been recently intensively studied, there are still some practical aspects that deserve to be further analysed. Here we discuss the issue related to the coordinate representation of compositional data. It is shown that linear relation between particular orthonormal coordinates and centred log-ratio coordinates can be utilized to simplify the computation concerning regression parameters estimation and hypothesis testing. To enhance interpretation of regression parameters, the orthogonal coordinates and their relation with orthonormal and centred log-ratio coordinates are presented. Further we discuss the quality of prediction in different coordinate system. It is shown that the mean squared error (MSE) for orthonormal coordinates is less or equal to the MSE for log-transformed data. Finally, an illustrative real-world example from geology is presented.

scholarly journals The Structure of Oxide Film on the Porous Silicon Surface

2020 ◽  
Vol 65 (1) ◽  
pp. 75
Author(s):  
O. I. Zavalistyi ◽  
O. V. Makarenko ◽  
V. A. Odarych ◽  
A. L. Yampolskyi
Keyword(s):  
Refractive Index ◽  
Surface Layer ◽  
Porous Silicon ◽  
Structural Changes ◽  
Mean Squared Error ◽  
Single Layer ◽  
Prolonged Stay ◽  
Near Surface ◽  
Squared Error ◽  
The Matrix

A prolonged stay of porous silicon in the air environment gives rise to structural changes in its surface layer, and the standard single-layer model is not sufficiently accurate to describe them. In this work, the structure of the near-surface layer in porous silicon is studied using the polygonal ellipsometry method. A combined approach is proposed to analyze the angular ellipsometry data for the parameters ф and Δ. It consists in the application of the multilayer medium model and the matrix method, while simulating the propagation of optical radiation in this medium in order to obtain the theoretical angular dependences of tan ф and cosΔ. In this method, the dependence of the sought optical profile on the specimen depth is an additional condition imposed on the multilayer model. Evolutionary numerical methods are used for finding the global minimum of the mean squared error (MSE) between the corresponding theoretical and experimental dependences, and the parameters of an optical profile are determined. A model in which the inner non-oxidized layer of porous silicon is homogeneous, whereas the refractive index in the outer oxidized layer has a linear profile, is analyzed. It is shown that the linear and two-step models for the refractive index of an oxidized film provided the best agreement with the experimental ellipsometric functions. The adequacy of the theoretical model is also confirmed by determining the color coordinates of the specimen.

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