Traditional Simple Model Research Articles

Development of maximum relevant prior feature ensemble (MRPFE) index to characterize future drought using global climate models

Drought is one of the foremost outcomes of global warming and global climate change. It is a serious threat to humans and other living beings. To reduce the adverse impact of drought, mitigation strategies as well as sound projections of extreme events are essential. This research aims to strengthen the robustness of anticipated twenty-first century drought by combining different Global Climate Models (GCMs). In this article, we develop a new drought index, named Maximum Relevant Prior Feature Ensemble index that is based on the newly proposed weighting scheme, called weighted ensemble (WE). In the application, this study considers 32 randomly scattered grid points within the Tibetan Plateau region and 18 GCMs of Coupled Model Intercomparison Project Phase 6 (CMIP6) of precipitation. In this study, the comparative inferences of the WE scheme are made with the traditional simple model averaging (SMA). To investigate the trend and long-term probability of various classes, this research employs Markov chain steady states probability, Mann–Kendall trend test, and Sen’s Slope estimator. The outcomes of this research are twofold. Firstly, the comparative inference shows that the proposed weighting scheme has greater efficiency than SMA to conflate GCMs. Secondly, the research indicates that the Tibetan Plateau is projected to experience “moderate drought (MD)” in the twenty-first century.

Implementation of fitness and health management system utilising deep learning neural network and internet of things technology

The purpose is to implement fitness and health management services more scientifically, enhance people's awareness of health management, prevent diseases caused by long-term sub-health, and comprehensively improve people's fitness and health status physically and mentally. Specifically, the data of people's health indicators are analysed, and a fitness and health management service system is established using deep learning and Internet of Things (IoT) technologies. First, people's fitness and health indicators are detected using IoT technology and integrated and pre-classified into text, number, and image. Afterward, the pre-classified data are input into the Convolutional Neural Network (CNN), their features are extracted for modelling and analysis, and the results are input into the constructed BP BackPropagation Neural Network (BPNN) model. Consequently, a preliminary prediction result about the user's fitness and health is obtained for the user's fitness and health status. The results show that the constructed fitness and health management system based on the proposed ensemble prediction model is more optimised than those constructed by a traditional simple model. With the proposed intelligent fitness and health management system composed of IoT devices, users can gain a better health status by self-monitoring, self-control, self-discovery, self-analysis and self-search.

A hybrid model of stacked autoencoder and modified particle swarm optimization for multivariate chaotic time series forecasting

Phase space reconstruction (PSR) is an effective method for chaotic system modeling, which can reveal the implicit evolution information in a complex system. However, the reconstructed time series tend to have a high dimension and contain some redundant information. It is difficult for a traditional simple model to directly forecast the reconstructed time series. In this paper, we propose a hybrid model of stacked autoencoder (SAE) and modified particle swarm optimization (MPSO) for multivariate chaotic time series forecasting. We utilize SAE to extract the reconstructed time series and adopt feedforward neural network (FNN) to forecast time series. In the proposed hybrid model, the SAE is followed by FNN, and we make the MPSO to train the output weights of the model, which is a large-scale optimization problem. To enhance the generalization ability and prevent over-fitting, we add a regularization item to the objective function when MPSO trains the weights of the model. Experimental results show that MPSO algorithm has advantages in the exploration and exploitation in large-scale optimization problems. Then, experiments on Lorenz time series and two real-world time series datasets verify the effectiveness of the hybrid model in multivariate chaotic time series forecasting.

Microdosimetric calculations by simulating monoenergetic electrons in voxel models of human normal individual cells

This work proposes two kinds of voxel model of human normal individual cells, and the Monte Carlo software GATE is used to describe and analyze the effects of some factors on the microdosimetric quantity--specific energy, such as shape, volume and physical models for interaction. In this paper, “Livermore” and “Penelope”, two of low energy electromagnetic models in the Monte Carlo code Geant4 and adopted in GATE, are used to estimate the specific energies and their distribution of a lung epithelial cell (BEAS-2B), a renal epithelial cell (293T) and their size-like simple ellipsoids (hereinafter referred to as “simple geometry”) respectively. According to the irradiation conditions in radiobiology, four irradiation geometries, the source isotropically irradiated within the cell, the source irradiated axially outside the cell (x-axis positive and z-axis negative) and the cell surface covered with a polypropylene film for external irradiation for monoenergetic electrons beams from 50 keV to 1 MeV are simulated. The results show that the influence of the physical models on the specific energy of the voxel phantom is 27.35% smaller than that of the simple ellipsoid. The BEAS-2B cell shows large differences between phantom and simple geometry in both cytoplasm and nucleus under the condition of external irradiation. For the 293T cell, even if the shape of the cell is relatively regular, there is a deviation between two kinds of geometry under certain conditions, the maximum is 17.78%, while the minimum is 1.19%. These statistical results indicate that shape, volume and position can have a certain impact on the specific energy, and demonstrate that in terms of exploring the mechanism of radiation biological effects, human real cell voxel phantoms may be more practical and valuable than traditional simple models from the aspect of physical modeling. It can be expected that the microdosimetric assessment based on the real cell voxel model and the establishment of relevant databases will play a unique role in predicting the dose of target cell volumes accurately under given conditions in the radiation protection and clinical radiotherapy.

Homogenization of braided fabric composite for reliable large deformation analysis of reinforced rubber hose

High pressure rubber hose is in the lamination structure composed of pure rubbers and braided fabric composite layers to have the sufficient strength against the excessive radial expansion and the large deformation, in which the braided fabric layer is woven with wrap and fill tows inclined to each other with the predefined helix angle in the complex periodic pattern. The consideration of detailed geometry of braided fabric layer in the numerical analysis leads to a huge number of finite elements so that the braided fabric layer has been traditionally simplified as an isotropic cylindrical one with the homogeneous isotropic material properties of braid spun tread. However, this simple model leads to the numerical prediction and design with the questionable reliability. In this context, this paper addresses the development of an in-house module, which is able to be interfaced with commercial FEM code, for the reliable large deformation analysis of the reinforced rubber hose with the element number at the level of the traditional simple model. The in-house module is able to not only automatically generate 3-D unit cell (or RVE) model of the braided fabric layer but evaluate the homogenized orthotropic material properties by automatically performing a serious of unit cell finite element analyses based on the superposition method. The validity of the in-house module and the reliability of the homogenization method are verified through the illustrative numerical experiments.

Experimental Evaluation of Balance Prediction Models for Sit-to-Stand Movement in the Sagittal Plane

Evaluation of balance control ability would become important in the rehabilitation training. In this paper, in order to make clear usefulness and limitation of a traditional simple inverted pendulum model in balance prediction in sit-to-stand movements, the traditional simple model was compared to an inertia (rotational radius) variable inverted pendulum model including multiple-joint influence in the balance predictions. The predictions were tested upon experimentation with six healthy subjects. The evaluation showed that the multiple-joint influence model is more accurate in predicting balance under demanding sit-to-stand conditions. On the other hand, the evaluation also showed that the traditionally used simple inverted pendulum model is still reliable in predicting balance during sit-to-stand movement under non-demanding (normal) condition. Especially, the simple model was shown to be effective for sit-to-stand movements with low center of mass velocity at the seat-off. Moreover, almost all trajectories under the normal condition seemed to follow the same control strategy, in which the subjects used extra energy than the minimum one necessary for standing up. This suggests that the safety considerations come first than the energy efficiency considerations during a sit to stand, since the most energy efficient trajectory is close to the backward fall boundary.

Adiabatic approximations of coupled dipole-proton model for hydrogen-bonded ferroelectrics

In several hydrogen-bonded ferroelectrics, such as ${\mathrm{KH}}_{2}{\mathrm{PO}}_{4}$-type ferroelectrics, the protons are strongly coupled to the dipoles produced in the heavy-ion sublattice. It is not clear whether such a coupled dipole-proton system can be described by two traditional simple models, the model of interacting tunneling protons and the model of interacting dipoles, and which one is more appropriate. We show that both models follow from the coupled dipole-proton model under the opposite adiabatic approximations, and that the model of interacting dipoles seems to correspond better with the experiments.

Effect of fish shape on gillnet selectivity: a study with Fulton’s condition factor

The Eurasian perch, Perca fluviatilis (L.), was fished with Nordic multimesh gillnets, the mesh size combination of which was based on geometric series. From the test fishing data the fish girth was found to be linearly related to the third root of fish weight and therefore the fish girth could be estimated indirectly with Fulton’s condition factor K. Two different response surface models based on B-type gillnet selectivity model were fitted to the empirical data: one model with Fulton’s K and one without (simple model). The Fulton’s K-model had narrower Monte Carlo simulated 95% confidence interval than the simple model. Simulation studies showed that the traditional simple model without Fulton’s K does not have a linear relationship between mesh size and fish length, which violates the classical principle of Baranov’s theorem on geometric similarity of fish of different sizes. Therefore the simple model derived from one population is not applicable to another population if there are differences in fish condition. However, if as is the case for Nordic multimesh gillnets with a mesh size combination based on geometric series like Nordic multimesh gillnets, this error is minimal because adjacent mesh sizes cover each other and correct this error.

Thickness of the Earth's Crust in Antarctica and the Surrounding Oceans: A Reply

The paper of Evison, Ingham, Orr & Le Fort on the dispersion of earthquake waves traversing Antarctica has recently been criticized by Bentley & Ostenso and by Kovach & Press. The discovery that the crust of eastern Antarctica is of continental thickness whilst that of Marie Byrd Land is some 10 km thinner is accepted by these critics, but they object to the two-layer and three-layer models used in obtaining this result, and also to the values that were assigned to the velocity parameters. For detecting large differences in crustal thickness, however, the traditional simple models have not been invalidated by the advent of the digital computer, which comes into its own with subtler problems; but the velocities appropriate to a simple model are not necessarily those indicated by refracted waves. Kovach & Press also criticize the use of Love waves rather than Rayleigh waves for investigating the oceanic crust around Antarctica. Their arguments on this point carry the unsatisfactory implications that the average velocity in the oceanic crust ought to increase with the thickness, and that there should be gross regional departures from isostasy at sea.