Narrow Results

This paper concerns the modeling of smart health sensors for data monitoring, where the data are eventually noisy, with correlated noise. In this work, we applied Clifford-based wavelets/multiwavelets for correlated noise in multi-sensors health data monitoring by estimating the set of sensor nodes minimizing an eventual error computed by the signal values at the selected nodes mostly caused by the correlated noise. Instead of directly minimizing the estimation error, we focused on evaluating a multi-level scheme based on multiwavelets for the estimation of the error between the parameter vector and its sub-vector of those nodes. Numerical simulations are provided with a comparison to some recent existing works. This model showed a performance and a fast time execution compared to those existing works. This model exceeds these models by the non-necessity to assume a priory structure of the data. Wavelets are capable to detect, localize, and eliminate the noise, even correlated, efficiently via the independent uncorrelated multiwavelets’ components.

A two-dimensional numerical model was developed^1–3 to simulate the sediment and pollutant transport in a shallow basin. The developed model consist of two modules: Hydrodynamic module and sediment/pollutant transport module. A numerical hydrodynamic module based on the Saint-Venant equations, is resolved by a MacCormack numerical scheme and is used to simulate the circulation pattern in the basin. The obtained flow circulation is used as an input to the sediment/pollutant transport module to simulate the transport and dispersion of a pollutant emitted into the basin. To calibrate the numerical model, the distorted scale model of the Windermere Basin⁴ was used. In this physical model, the flow visualization and pollutant transport experiments provide a good calibration. The simulated results were found to be in good agreement with the experimental measurements and the results in Ref. 4. With the aid of the validated model, the influence of the construction of dikes on the residence time distributions in the basin was examined.

A quasi-three-dimensional mathematical model has been developed to study the morphological processes based on equilibrium sediment transport method. The flow velocities are computed by a two-dimensional horizontal depth-averaged flow model (H2D) in combination with logarithmic velocity profiles. The transport of sediment particles by a flow water has been considered in the form of bed load and suspended load. The bed load transport rate is defined as the transport of particles by rolling and saltating along the bed surface and is given by the Van Rijn relationship (1987). The equilibrium suspended load transport is described in terms of an equilibrium sediment concentration profile (ce) and a logarithmic velocity (u). Based on the equilibrium transport, the bed change rate is given by integration of the sediment mass-balance equation. The model results have been compared with a Van Rijn results (equilibrium approach) and good agreement has been found.

We simulate the interplay between productive and financial activity using a model that considers equal opportunities among individuals of a society. As the simulation evolves in time, three qualitative wealth distribution profiles are generated according to the flux of productive capital. We relate these curves to different socioeconomic structures: a primitive equalitarian society; a medieval society having a distribution of wealth with castes and discontinuities; and a modern society where this distribution is roughly exponential.

In this paper we adopt a phenomenological approach in order to develop a suitable Cellular Automata (CA) model capable to satisfactory mimic city growth and urban sprawl. The use of CA in urban expansion modeling is well known since many years, but very rarely it has been related with a down-top approach which considers inhabitants' preferences as a driving tool to characterize the CA algorithm. In addition, we consider as a control mechanism of the cell conversion rate (i.e. the number of cells experiencing conversion into urban use) the logistic function. This function is tuned on the free space (cells) at disposal for the urban development.

In this paper we present the basics of the model and we perform a simple simulation in the case of a generic geographic pattern.

In this paper, the behavior of a genetic algorithm is modeled to enhance its applicability as a modeling tool of biological systems. A new description model for selection mechanism is introduced which operates on a portion of individuals of population. The extinction and recolonization mechanism is modeled, and solving the dynamics analytically shows that the genetic drift in the population with extinction/recolonization is doubled. The mathematical analysis of the interaction between selection and extinction/recolonization processes is carried out to assess the dynamics of motion of the macroscopic statistical properties of population. Computer simulations confirm that the theoretical predictions of described models are in good approximations. A mathematical model of GA dynamics was also examined, which describes the anti-predator vigilance in an animal group with respect to a known analytical solution of the problem, and showed a good agreement between them to find the evolutionarily stable strategies.

The purpose of this paper is to establish a direct methanol fuel cell (DMFC) prediction model by using the support vector regression (SVR) approach combined with particle swarm optimization (PSO) algorithm for its parameter selection. Two variables, cell temperature and cell current density were employed as input variables, cell voltage value of DMFC acted as output variable. Using leave-one-out cross-validation (LOOCV) test on 21 samples, the maximum absolute percentage error (APE) yields 5.66%, the mean absolute percentage error (MAPE) is only 0.93% and the correlation coefficient (R²) as high as 0.995. Compared with the result of artificial neural network (ANN) approach, it is shown that the modeling ability of SVR surpasses that of ANN. These suggest that SVR prediction model can be a good predictor to estimate the cell voltage for DMFC system.

Following the introduction of a phenomenological cellular automata (CA) model capable to reproduce city growth and urban sprawl, we develop a toy model simulation considering a realistic framework. The main characteristic of our approach is an evolution algorithm based on inhabitants preferences. The control of grown cells is obtained by means of suitable functions which depend on the initial condition of the simulation. New born urban settlements are achieved by means of a logistic evolution of the urban pattern while urban sprawl is controlled by means of the population evolution function. In order to compare model results with a realistic urban framework we have considered, as the area of study, the island of Capri (Italy) in the Mediterranean Sea. Two different phases of the urban evolution on the island have been taken into account: a new born initial growth as induced by geographic suitability and the simulation of urban spread after 1943 induced by the population evolution after this date.

The present work is related to the study of a water intake projected into a dam reservoir, located in northern Morocco. The object sought is to examine the natural conditions surrounding a water intake and their possible repercussions on its operation. Thus, a two-dimensional numerical model is developed to simulate the sediment transport in a reservoir dam. The developed model consists of hydrodynamic module based on the Saint–Venant equations and sediment transport module based on the mass-balance equation, where there are resolved by a MacCormack numerical scheme and upwind scheme, respectively. The analysis using the numerical model has made it possible to predict the shutdown periods of the drinking water production station with respect to the rate of suspended solids (SS) for extreme rainfall events.

Intermolecular interaction energies for molecular dimers of benzene, indene, naphthalene, phenanthrene, cholesterol and glycyrrhetinic acid have been calculated according to the CVFF empirical force field of the DISCOVER program. The parallel orientations (side by-side) turned out to be the energetically most favourable ones, in agreement with the parametrization of Gay–Berne potentials. The energies of the T-shape and in-plane (end-to-end) orientations of the entirely asymmetric molecules cholesterol and glycyrrhetinic acid depend strongly on the actual atomic positions. This shows the extent to which the shape and charges of molecules determine all possible orientations and interaction energies in molecular ensembles.

Electroencephalograph (EEG) data for normal individuals with eyes-closed and under stimuli is analyzed. The stimuli consisted of photo, audio, motor and mental activity. We use several measures from nonlinear dynamics to analyze and characterize the data. We find that the dynamics of the EEG signal is deterministic and chaotic but it is not a low dimensional chaotic system. The evoked responses lead to a redistribution of strengths relative to eyes-closed data. Basically, strength in α waves decreases whereas that in β wave increases. We also carried out simulations separately and in combination for δ, θ, α and β waves to understand the data. From the simulation results, it appears that the characteristics of EEG data are consequences of filtering the data with a relatively small range of frequency (0.5–32 Hz). In view of this, we believe that calculation of known nonlinear measures is not likely to be very useful for studying the dynamics of EEG data. We have also successfully modeled the EEG time series using the concept of state space reconstruction in the framework of artificial neural network. It gives us confidence that one would be able to understand, in a more basic way, how collectivity in EEG signal arises.

Permeability is an important hydraulic parameter for characterizing heat and mass transfer properties of fibrous porous media. However, it is difficult to be quantitatively predicted due to the complex and irregular pore structure of fibrous porous media. Fractal geometry has been verified to be an effective method for determining the permeability of fibrous porous media. In this study, recent works on the permeability of fibrous porous media by means of fractal geometry are reviewed, the advances for each presented fractal model are analyzed and summarized, parameter equations used in available fractal permeability models are also briefly compared and reviewed. Future work for more generalized permeability model of fibrous porous media need to conducted by considering the special characters of fibrous materials, uniform pore structure parameter model and the influence factor of capillary pressure, electrokinetic phenomena, etc.

In recent years, unconventional reservoirs have drawn tremendous attention worldwide. This special issue collects a series of recent works on various fractal-based approaches in unconventional reservoirs. The topics covered in this introduction include fractal characterization of pore (throat) structure and its influences on the physical properties of unconventional rocks, fractal characteristics of crack propagation in coal and fluid flow in rock fracture network under shearing, porous flow phenomena and gas adsorption mechanism, fractal geophysical method in reservoirs.

This paper introduces a new technique for analyzing the behavior of global interconnects in FPGAs, for nanoscale technologies. Using this new enhanced modeling method, new enhanced accurate expressions for calculating the propagation delay of global interconnects in nano-FPGAs have been derived. In order to verify the proposed model, we have performed the delay simulations in 45 nm, 65 nm, 90 nm, and 130 nm technology nodes, with our modeling method and the conventional Pi-model technique. Then, the results obtained from these two methods have been compared with HSPICE simulation results. The obtained results show a better match in the propagation delay computations for global interconnects between our proposed model and HSPICE simulations, with respect to the conventional techniques such as Pi-model. According to the obtained results, the difference between our model and HSPICE simulations in the mentioned technology nodes is (0.29–22.92)%, whereas this difference is (11.13–38.29)% for another model.

Dual radio frequency (RF) powers are widely used with commercial plasma etchers for various nanoscale patterns. However, it is challenging to understand the relationship among the dual RF powers and the etching processes. In this work, the effect of the dual RF bias powers on SiO₂ sputter etching was investigated in inductively coupled plasma (ICP). The relationship was studied among 2MHz and 27.12MHz RF bias powers, a 13.56MHz ICP source power, the ion bombardment energy, the ion density and the etching rate. The results show that the ion density of Ar plasma can be controlled in the region of 10⁹–10${}^{11}$ ions/cm³, and DC self-bias can be controlled by controlling the ratio of dual RF bias powers while the ion density is maintained with the operation of source power. This work reveals that the dual RF bias powers expand the process window of the ion density and the ion bombardment energy independently in the ICP plasma source. The sputter etching rate is also modeled using the ion-enhanced etching model, and the model shows good agreement with the etching rate data.

Due to the various applications of nanocantilevers as nanosensors and nanoactuators in nanoelectromechanical systems, understanding their behavior is of particular importance. In operating environments, nanocantilevers are simultaneously exposed to mechanical forces and heat. This study aims to examine the behavior of an Euler–Bernoulli nanocantilever when it is placed under mechanical loads and exposed to heat at the same time. The effects of size, temperature, and force on the flexural behavior of the nanocantilever were investigated and the following characteristics were obtained via molecular dynamics simulation: nanocantilever displacement versus time, maximum bending, nanocantilever yielding time, and the minimum acceptable working frequency range for nanocantilever-based nanoswitches. It was found that applying forces greater than 0.00005eV/A, the studied nanocantilevers would rapidly undergo plastic deformation. For applied forces less than 0.00005eV/A, the nanocantilevers with length of 40nm, 30nm and 20nm can withstand upto 750K, 600K and 300K in 200ns to more than 1.5$\mu$s time period, respectively.

In this paper, we concern with the dynamic behaviors of a high speed mass measurement system with conveyor belt (a checkweigher). The goal of this paper is to construct a simple model of the measurement system so as to duplicate a response of the system. The checkweigher with electromagnetic force compensation can be approximated by the combined spring-mass-damper systems as the physical model, and the equation of motion is derived. The model parameters (a damping coefficient and a spring constant) can be obtained from the experimental data for open-loop system. Finally, the validity of the proposed model can be confirmed by comparison of the simulation results with the realistic responses. The simple dynamic model obtained offers practical and useful information to examine control scheme.