New Models for Calculating the Maximum Compressive Force of Paper in Its Plane.

The main objective of the presented research was to find a model that describes the maximum compressive force of paper in its plane. The research began with crushing tests of a number of packaging paper samples of various lengths. It was shown that due to the specific structure of the paper and the high heterogeneity of its structure, packaging paper is material where it is difficult to determine the maximum compressive stress. Next, three analytical models describing the load capacity of a flat paper web were investigated and an alternative empirical model was proposed. The results of the performed tests are directly applicable in the calculation of the mechanical properties of corrugated cardboard and the determination of the load capacity of cardboard packaging.

Numerical and Experimental Study into Paper Compression Test.

The study aims to present the results of paper compression under an axial load. Different heights of samples subjected to compression were taken into account. The main goal of the analysis was to determine experimentally the maximum compression load. In addition, numerical models based on the finite element method (FEM) were validated to refer to empirical results. The performed numerical simulations were founded on Green-Lagrangian nonlinear equations for large displacements and strains. The progressive failure of the compressed orthotropic material after exceeding maximum stresses was based on Hill's anisotropy theory. Nonlinear calculations were conducted by using a typical Newton-Raphson algorithm for achieving a sequence convergence. The accuracy of the developed model was confirmed experimentally in compression tests. The technique of analysing the shape of the compressed paper sample on the basis of images recorded during the measurement was used. The obtained test results are directly applicable in practice, especially in the calculation of the mechanical properties of corrugated cardboard and in determining the load capacity of cardboard packaging. Knowing the maximum compressive stress that packaging paper can withstand allows packaging to be properly designed and its strength assessed in the context of the transport and storage of goods.

Numerical and Experimental Study of Five-Layer Non-Symmetrical Paperboard Panel Stiffness.

This paper concerns the analysis of five-layer corrugated paperboard subjected to a four-point bending test. The segment of paperboard was tested to determine the bending stiffness. The investigations were conducted experimentally and numerically. The non-damaging tests of bending were carried out in an elastic range of samples. The detailed layers of paperboard were modelled as an orthotropic material. The simulation of flexure was based on a finite element method using Ansys® software. Several material properties and thicknesses of papers in the samples were taken into account to analyse the influence on general stiffness. Two different discrete models based on two geometries of paperboard were considered in this study to validate the experimental stiffness. The present analysis shows the possibility of numerical modelling to achieve a good correlation with experimental results. Moreover, the results of numerical estimations indicate that modelling of the perfect structure gives a lower bending stiffness and some corrections of geometry should be implemented. The discrepancy in stiffness between both methods ranged from 3.04 to 32.88% depending on the analysed variant.

Adolescent age estimation using voice features.

In this paper, a method for evaluating the chronological age of adolescents on the basis of their voice signal is presented. For every examined child, the vowels a, e, i, o and u were recorded in extended phonation. Sixty voice parameters were extracted from each recording. Voice recordings were supplemented with height measurement in order to check if it could improve the accuracy of the proposed solution. Predictor selection was performed using the LASSO (least absolute shrinkage and selection operator) algorithm. For age estimation, the random forest (RF) for regression method was employed and it was tested using a 10-fold cross-validation. The lowest absolute error (0.37 year ± 0.28) was obtained for boys only when all selected features were included into prediction. In all cases, the achieved accuracy was higher for boys than for girls, which results from the fact that the change of voice with age is larger for men than for women. The achieved results suggest that the presented approach can be employed for accurate age estimation during rapid development in children.

Linear sound attenuation model for assessing external stimuli in prenatal period.

The popularization of acoustic stimulation during the prenatal period encourages the analysis of sounds reaching the inside of the uterus. To assess the distortion of any sound stimuli, a mathematical model of attenuation has to be used. In this paper a mathematical model is proposed on the basis of data from a physical model. The physical model consisted of muscle slices of two different thicknesses placed in a tank filled with water. The amplitudes of sinusoidal waves between 160 and 2000 Hz were measured under the water surface. Using the collected data, a linear mathematical model of sound attenuation on the way to the fetal ear was created. The results indicated a rise in the amount of sound attenuation for increasing frequencies. Analysis of slope coefficients for two muscle thicknesses revealed that there is no significant difference between attenuation by the thinner and the thicker tissue. Finally, the model was verified with data obtained during experiments on animals. The proposed model of the sound transmission allowed assessment of the attenuation by a soft tissue. It reveals changes in the sound reaching fetal ears, which can make acoustic stimulation different than what is heard in postnatal life. The model can be used to simulate the distortion of any sound which is proposed to prenatal stimulation and to assess its quality.

Prediction of menarcheal status of girls using voice features.

A method for evaluating the menarcheal status of girls on the basis of their voice features is presented in the paper. The registration procedure consists of voice recording and measuring 20 anthropological features. The input feature vector is a combination of voice and anthropometric parameters, counting 220 features. The optimal set of parameters was selected using five different methods: Method A - stepwise regression (first forward, then backward regression) performed on features with statistically different means/medians; Method B - stepwise regression (forward and backward) on all features, with age; Method C - stepwise regression as in B; including age, Method D - all features with statistically different means/medians, Method E - all features excluding age. For classification purposes three methods were employed: random forest (RF), support vector machine (SVM) and linear discriminant analysis (LDA) classifier. They were tested with 10-fold cross validation. The classification accuracy for RF using only voice features is higher than using only anthropometric data: 86.86% vs. 81.02% respectively. For the other two classifiers, the results do not show as large a difference: 80.60% vs. 82.80% for SVM and 80.66% vs. 82.34% for LDA. The advantage of voice features is more noticeable with sensitivity: 91.92% vs. 83.06% for RF. The obtained results suggest that the presented method can be used for automatic recognition of girls' menarcheal status using voice signal.