http://www.hindawi.comThe latest articles from Hindawi Publishing Corporation© 2008, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/GetArticle.aspx?doi=10.1155/2008/358748Better understanding of stresses and flow characteristics in the human airways is very important for many clinical applications such as aerosol drug therapy, inhalation toxicology, and airway remodeling process. The bifurcation geometry of airway generations 3 to 5 based on the ICRP tracheobronchial model was chosen to analyze the flow characteristics and stresses during inhalation. A computational model was developed to investigate the airway tissue flexibility effect on stresses and flow characteristics in the airways. The finite-element method with the fluid-structure interaction analysis was employed to investigate the transient responses of the flow characteristics and stresses in the airways during inhalation. The simulation results showed that tissue flexibility affected the maximum airflow velocity, airway pressure, and wall shear stress about 2%, 7%, and 6%, respectively. The simulation results also showed that the differences between the orthotropic and isotropic material models on the airway stresses were in the ranges of 25–52%. The results from the present study suggest that it is very important to incorporate the orthotropic tissue properties into a computational model for studying flow characteristics and stresses in the airways.Kittisak Koombua and Ramana M. Pidaparti© 2008, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/GetArticle.aspx?doi=10.1155/2008/427926One of the clinical examinations performed to evaluate the autonomic nervous system (ANS) activity is the tilt test, which consists in studying the cardiovascular response to the change of a patient's position from a supine to a head-up position. The analysis of heart rate variability signals during tilt tests has been shown to be useful for risk stratification and diagnosis on different pathologies. However, the interpretation of such signals is a difficult task. The application of physiological models to assist the interpretation of these data has already been proposed in the literature, but this requires, as a previous step, the identification of patient-specific model parameters. In this paper, a model-based approach is proposed to reproduce individual heart rate signals acquired during tilt tests. A new physiological model adapted to this problem and coupling the ANS, the cardiovascular system (CVS), and global ventricular mechanics is presented. Evolutionary algorithms are used for the identification of patient-specific parameters in order to reproduce heart rate signals obtained during tilt tests performed on eight healthy subjects and eight diabetic patients. The proposed approach is able to reproduce the main components of the observed heart rate signals and represents a first step toward a model-based interpretation of these signals.Virginie Le Rolle, Alfredo I. Hernández, Pierre-Yves Richard, and Guy Carrault© 2008, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/GetArticle.aspx?doi=10.1155/2008/756436An estimation methodology is presented to determine the breast tumor parameters using the surface temperature profile that may be obtained by infrared thermography. The estimation methodology involves evolutionary algorithms using artificial neural network (ANN) and genetic algorithm (GA). The ANN is used to map the relationship of tumor parameters (depth, size, and heat generation) to the temperature profile over the idealized breast model. The relationship obtained from ANN is compared to that obtained by finite element software. Results from ANN training/testing were in good agreement with those obtained from finite element model. After ANN validation, GA is used to estimate tumor parameters by minimizing a fitness function involving comparing the temperature profiles from simulated or clinical data to those obtained by ANN. Results show that it is possible to determine the depth, diameter, and heat generation rate from the surface temperature data (with 5% random noise) with good accuracy for the 2D model. With 10% noise, the accuracy of estimation deteriorates for deep-seated tumors with low heat generation. In order to further develop this methodology for use in a clinical scenario, several aspects such as 3D breast geometry and the effects of nonuniform cooling should be considered in future investigations.Manu Mital and Ramana M. Pidaparti© 2008, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/GetArticle.aspx?doi=10.1155/2008/628120Experimental and numerical methods are used to explore the stresses generated around bone screws used in rigid internal fixation of mandibular fractures. These results are intended to aid in decisions concerning both the design and the use of these bone screws. A finite element (FE) model of a human mandible is created with a fixated fracture in the parasymphyseal region. The mandibular model is anatomically loaded, and the forces exerted by the fixation plate onto the simplified screws are obtained and transferred to another finite element submodel of a screw implant embedded in a trilaminate block with material properties of cortical and cancellous bone. The stress in the bone surrounding the screw implant is obtained and compared for different screw configurations. The submodel analyses are further compared to and validated with simple axial experimental and numerical screw pull-out models. Results of the screw FE analysis (FEA) submodel show that a unicortical screw of 2.6 mm major diameter and 1.0 mm pitch will cause less bone damage than a bicortical screw of 2.3 mm major diameter and 1.0 mm pitch. The results of this study suggest that bicortical drilling can be avoided by using screws of a larger major diameter.Naresh Chaudhary, Scott T. Lovald, Jon Wagner, Tariq Khraishi, and Bret Baack© 2008, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/GetArticle.aspx?doi=10.1155/2008/871479Desulphurization of flue gases from various chemical industries in a techno-econo-enviro manner is a demanding technology. The concentrations of sulphur dioxide in and around these plants overshoot the danger point. In recent years, the process analysis of chemical absorption in a slurry has become important in rational design and development of wet scrubbing processes for the removal of SO2 from flue gases. The elementary steps encountered in wet scrubbing by slurries are diffusion and reaction of gaseous species and solid dissolution in liquid film. In the present work, the process of the absorption of sulphur dioxide into wet magnesia slurry was theoretically analyzed according to the two-reaction plane model incorporating the solid dissolution promoted by the reactions with absorbed sulphur dioxide in the liquid film. A model based on Fick's second law has been developed to calculate enhancement factor for absorption of Sulphur dioxide into Mg(OH)2 slurry. The concentration of accumulated species in the bulk of the liquid phase (sulphite ions for this case) which substantially control the absorption rates was included in the model for the prediction of theoretical enhancement factor. The values of theoretical enhancement factors obtained from model were compared with experimental enhancement factors available in literature. The model values of enhancement factors agreed well with the values of experimental enhancement factor available in literature.M. K. Mondal© 2008, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/GetArticle.aspx?doi=10.1155/2008/238305Screening mammograms is a repetitive task that causes fatigue and eye strain since for every thousand cases analyzed by a radiologist, only 3–4 are cancerous and thus an abnormality may be overlooked. Computer-aided detection (CAD) algorithms were developed to assist radiologists in detecting mammographic lesions. In this paper, a computer-aided detection and diagnosis (CADD) system for breast cancer is developed. The framework is based on combining principal component analysis (PCA), independent component analysis (ICA), and a fuzzy classifier to identify and label suspicious regions. This is a novel approach since it uses a fuzzy classifier integrated into the ICA model. Implemented and tested using MIAS database. This algorithm results in the classification of a mammogram as either normal or abnormal. Furthermore, if abnormal, it differentiates it into a benign or a malignant tissue. Results show that this system has 84.03% accuracy in detecting all kinds of abnormalities and 78% diagnosis accuracy.Ikhlas Abdel-Qader and Fadi Abu-Amara© 2008, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/GetArticle.aspx?doi=10.1155/2008/798395We present a numerical study of an example of piecewise linear systems that constitute a class of hybrid systems. Precisely, we study the chaotic dynamics of the voltage-mode controlled buck converter circuit in an open loop. By considering the voltage input as a bifurcation parameter, we observe that the obtained simulations show that the buck converter is prone to have subharmonic behavior and chaos. We also present the corresponding bifurcation diagram. Our modeling techniques are based on the new French native modeler and simulator for hybrid systems called Scicos (Scilab connected object simulator) which is a Scilab (scientific laboratory) package. The followed approach takes into account the hybrid nature of the circuit.Fatima El Guezar and Hassane Bouzahir© 2008, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/GetArticle.aspx?doi=10.1155/2008/937542A case study of open-source (OS) development of the computational research software MFIX, used for multiphase computational fluid dynamics simulations, is presented here. The verification and validation steps required for constructing modern computational software and the advantages of OS development in those steps are discussed. The infrastructure used for enabling the OS development of MFIX is described. The impact of OS development on computational research and education in gas-solids flow, as well as the dissemination of information to other areas such as geophysical and volcanology research, is demonstrated. This study shows that the advantages of OS development were realized in the case of MFIX: verification by many users, which enhances software quality; the use of software as a means for accumulating and exchanging information; the facilitation of peer review of the results of computational research.Madhava Syamlal, Thomas J. O'Brien, Sofiane Benyahia, Aytekin Gel, and Sreekanth Pannala© 2008, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/GetArticle.aspx?doi=10.1155/2007/28456To date, most speech synthesis techniques have relied upon the representation of the vocal tract by some form of filter, a typical example being linear predictive coding (LPC). This paper describes the development of a physiologically realistic model of the vocal tract using the well-established technique of transmission line modelling (TLM). This technique is based on the principle of wave scattering at transmission line segment boundaries and may be used in one, two, or three dimensions. This work uses this technique to model the vocal tract using a one-dimensional transmission line. A six-port scattering node is applied in the region separating the pharyngeal, oral, and the nasal parts of the vocal tract.A. Benkrid, A. Benallal, and K. Benkrid© 2008, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/GetArticle.aspx?doi=10.1155/2007/27521The textile fibre mixture as a multicomponent blend of variable fibres imposes regarding the proper method to predict the characteristics of the final blend. The length diagram and the fibrogram of cotton are generated. Then the length distribution, the length diagram, and the fibrogram of a blend of different categories of cotton are determined. The length distributions by weight of five different categories of cotton (Egyptian, USA (Pima), Brazilian, USA (Upland), and Uzbekistani) are measured by AFIS. From these distributions, the length distribution, the length diagram, and the fibrogram by weight of four binary blends are expressed. The length parameters of these cotton blends are calculated and their variations are plotted against the mass fraction x of one component in the blend .These calculated parameters are compared to those of real blends. Finally, the selection of the optimal blends using the linear programming method, based on the hypothesis that the cotton blend parameters vary linearly in function of the components rations, is proved insufficient.B. Azzouz, M. Ben Hassen, and F. Sakli© 2008, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/GetArticle.aspx?doi=10.1155/2007/92717Surface roughness, an indicator of surface quality, is one of the most specified customer requirements in machining of parts. In this study, the experimental results corresponding to the effects of different insert nose radii of cutting tools (0.4, 0.8, 1.2 mm), various depth of cuts (0.75, 1.25, 1.75, 2.25, 2.75 mm), and different feedrates (100, 130, 160, 190, 220 mm/min) on the surface quality of the AISI 1030 steel workpieces have been investigated using multiple regression analysis and artificial neural networks (ANN). Regression analysis and neural network-based models used for the prediction of surface roughness were compared for various cutting conditions in turning. The data set obtained from the measurements of surface roughness was employed to and tests the neural network model. The trained neural network models were used in predicting surface roughness for cutting conditions. A comparison of neural network models with regression model was carried out. Coefficient of determination was 0.98 in multiple regression model. The scaled conjugate gradient (SCG) model with 9 neurons in hidden layer has produced absolute fraction of variance (R2) values of 0.999 for the training data, and 0.998 for the test data. Predictive neural network model showed better predictions than various regression models for surface roughness. However, both methods can be used for the prediction of surface roughness in turning.Muammer Nalbant, Hasan Gokkaya, and İhsan Toktaş© 2008, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/GetArticle.aspx?doi=10.1155/2007/85150Experimental and theoretical analyses of mouldability for feedstocks used in powder injection moulding are performed. This study covers two main analyses. (i) The experimental analysis: the barrel temperature, injection pressure, and flow rate are factors for powder injection moulding (PIM). Powder-binder mixture used as feedstock in PIM requires a little more attention and sensitivity. Obtaining the balance among pressure, temperature, and especially flow rate is the most important aspect of undesirable conclusions such as powder-binder separation, sink marks, and cracks in moulded party structure. In this study, available feedstocks used in PIM were injected in three different cavities which consist of zigzag form, constant cross-section, and stair form (in five different thicknesses) and their mouldability is measured. Because of the difference between material and binder, measured lengths were different. These were measured as 533 mm, 268 mm, 211 mm, and 150 mm in advanced materials trade marks Fe–2Ni, BASF firm Catamould A0-F, FN02, and 316L stainless steel, respectively. (ii) The theoretical analysis: the use of artificial neural network (ANN) has been proposed to determine the mouldability for feedstocks used in powder injection moulding using results of experimental analysis. The back-propagation learning algorithm with two different variants and logistic sigmoid transfer function were used in the network. In order to train the neural network, limited experimental measurements were used as training and test data. The best fitting training data set was obtained with three and four neurons in the hidden layer, which made it possible to predict yield length with accuracy at least as good as that of the experimental error, over the whole experimental range. After training, it was found that the R2 values are 0.999463, 0.999445, 0.999574, and 0.999593 for Fe–2Ni, BASF firm Catamould A0-F, FN02, and 316L stainless steel, respectively. Similarly, these values for testing data are 0.999129, 0.999666, 0.998612, and 0.997512, respectively. As seen from the results of mathematical modeling, the calculated yield lengths are obviously within acceptable uncertainties.Çetin Karataş, Adnan Sözen, Erol Arcaklioglu, and Sami Erguney© 2008, Hindawi Publishing Corporation. All rights reserved.http://www.hindawi.com/GetArticle.aspx?doi=10.1155/2007/50586This paper presents a study on trajectory tracking problem for an AC synchronous servomotor. A mathematical model for the system including AC synchronous servomotor, gearbox, and a load is developed to examine the systems dynamic behavior. The system is controlled by a traditional PID (proportional + integral + derivative) controller. The required values for the controller settings are found experimentally. Different motion profiles are designed, and trapezoidal ones are implemented. Thus, the experimental validation of the model is achieved using the experimental setup. The simulation and experimental results are presented. The tracking performance of an AC servomotor system is illustrated with proposed PID controller.L. Canan Dülger and Ali Kireçci© 2008, Hindawi Publishing Corporation. All rights reserved.