Search results for "Statistical"

Data mining, dashboards and statistics: a powerful framework for the chemical design of molecular nanomagnets

2021

Abstract Three decades of intensive research in molecular nanomagnets have brought the magnetic memory in molecules from liquid helium to liquid nitrogen temperature. The enhancement of this operational temperature relies on a wise choice of the magnetic ion and the coordination environment. However, serendipity, oversimplified theories and chemical intuition have played the main role. In order to establish a powerful framework for statistically driven chemical design, we collected chemical and physical data for lanthanide-based nanomagnets to create a catalogue of over 1400 published experiments, developed an interactive dashboard (SIMDAVIS) to visualise the dataset, and applied inferentia…

Modeling polyethylene with the bond fluctuation model

1997

This work presents an application of recently developed ideas about how to map real polymer systems onto abstract models. In our case the abstract model is the bond fluctuation model with a Monte Carlo dynamics. We study the temperature dependence of chain dimensions and of the self-diffusion behavior in the melt from high temperatures down to 200 K. The chain conformations are equilibrated over the whole temperature range, which is possible for the abstract type of model we use. The size of the chains as measured by the characteristic ratio is within 25% of experimental data. The simulated values of the chain self-diffusion coefficient have to be matched to experimental information at one …

Contribution to modeling the viscosity Arrhenius-type equation for some solvents by statistical correlations analysis

2014

Abstract Estimation and knowledge of transport properties of fluids are essential for heat and mass flow. Viscosity is one of the important properties which are affected by temperature and pressure. In the present work, based on the use of econometric and statistical techniques for parametric and non-parametric regression analysis and statistical correlation tests, we propose an equation modeling the relationship between the two parameters of viscosity Arrhenius-type equation, such as the Arrhenius energy ( E a ) or the pre-exponential factor ( A s ). In addition, we introduce a third interesting parameter called Arrhenius temperature ( T A ), to enrich the discussion. Empirical validation …

Statistical modeling, simulation, and experimental verification of wideband indoor mobile radio channel

2018

This paper focuses on the modeling, simulation, and experimental verification of wideband single-input single-output (SISO) mobile fading channels for indoor propagation environments. The indoor reference channel model is derived from a geometrical rectangle scattering model, which consists of an infinite number of scatterers. It is assumed that the scatterers are exponentially distributed over the two-dimensional (2D) horizontal plane of a rectangular room. Analytical expressions are derived for the probability density function (PDF) of the angle of arrival (AOA), the PDF of the propagation path length, the power delay profile (PDP), and the frequency correlation function (FCF). An efficie…

Impact of a Social Constructivist Instructional Strategy on Performance in Algebra with a Focus on Secondary School Students

2020

There have been perennial concerns on the low academic performance of students among researchers and other education stakeholders. Innovative teaching strategies have, therefore, gained prominence in the field of mathematics education. The purpose of this study is to investigate the impact of a social constructivist instructional strategy on students’ performance in algebra. The present study is quasi-experimental, and its type is a posttest control group involving 154 secondary school students that are randomly selected across four intact classes. The random selection of students to treatment and control controls is assumed to improve the validity of the results. Two research questions are…

Chemical and Microbiological Characterization for PDO Labelling of Typical East Piedmont (Italy) Salami

2015

This study is focused on the characterisation of typical salami produced in Alessandria province (North West of Italy). Seventeen small or medium salami producers from this area were involved in the study and provided the samples investigated. The aim is double and consists in obtaining a screening of the characteristics of different products and following their evolution along ripening. The study involved five types of typical salami that were characterised for aroma components and nutritional features. This approach could provide a basis for a possible PDO or PGI label request. Principal Component Analysis and cluster analysis were used as multivariate statistical tools for data treatment…

Statistical tools and artificial intelligence approaches to predict fracture in bulk metal forming

2007

Biodegradability Prediction of Fragrant Molecules by Molecular Topology

2016

Biodegradability is a key property in the development of safer fragrances. In this work we present a green methodology for its preliminary assessment. The structure of various fragrant molecules is characterized by computing a large set of topological indices. Those relevant to biodegradability are selected by means of a hybrid stepwise selection method to build a linear classifier. This model is compared with a more complex artificial neural network trained with the indices previously found. After validation, the models show promise for time and cost reduction in the development of new, safer fragrances. The methodology presented could easily be adapted to many quasi-big data problems in R…

Fall Detection Based on the Instantaneous Doppler Frequency : A Machine Learning Approach

2019

Modern societies are facing an ageing problem which comes with increased cost of healthcare. A major share of this ever-increasing cost is due to fall related injuries, which urges the development of fall detection systems. In this context, this paper paves the way for building of a radio-frequency-based fall detection system. This paper presents an activity simulator that generates the complex channel gain of indoor channels in the presence of one person performing three different activities, namely, slow fall, fast fall, and walking. We built a machine learning framework for activity recognition based on the complex channel gain. We assess the recognition accuracy of three different class…

Constructing Interpretable Classifiers to Diagnose Gastric Cancer Based on Breath Tests

2017

Quick, inexpensive and accurate diagnosis of gastric cancer is a necessity, but at this moment the available methods do not hold up. One of the most promising possibilities is breath test analysis, which is quick, relatively inexpensive and comfortable to the person tested. However, this method has not yet been well explored. Therefore in this article the authors propose using transparent classification models to explain diagnostic patterns and knowledge, which is acquired in the process. The models are induced using decision tree classification algorithms and RIPPER algorithm for decision rule induction. The accuracy of these models is compared to neural network accuracy.