Search results for: Wave Vortex Parameters

Authors: Gurju Awgichew, G. Radhakrishnamacharya

Abstract:

Steady incompressible couple stress fluid flow through two dimensional symmetric channel with stenosis is investigated. The flow consisting of a core region to be a couple stress fluid and a peripheral layer of plasma (Newtonian fluid). Assuming the stenosis to be mild, the equations governing the flow of the proposed model are solved using the slip boundary condition and closed form expressions for the flow characteristics (the dimensionless resistance to flow and wall shear stress at the maximum height of stenosis) are derived. The effects of various parameters on these flow variables have been studied. It is observed that the resistance to flow as well as the wall shear stress increase with the height of stenosis, viscosity ratio and Darcy number. However, the trend is reversed as the slip and the couple stress parameter increase.

Keywords: Stenosis, Couple stress fluid, Slip condition, Peripheral layer.

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Authors: Yuanyuan Chai, Limin Jia, Zundong Zhang

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Hybrid algorithm is the hot issue in Computational Intelligence (CI) study. From in-depth discussion on Simulation Mechanism Based (SMB) classification method and composite patterns, this paper presents the Mamdani model based Adaptive Neural Fuzzy Inference System (M-ANFIS) and weight updating formula in consideration with qualitative representation of inference consequent parts in fuzzy neural networks. M-ANFIS model adopts Mamdani fuzzy inference system which has advantages in consequent part. Experiment results of applying M-ANFIS to evaluate traffic Level of service show that M-ANFIS, as a new hybrid algorithm in computational intelligence, has great advantages in non-linear modeling, membership functions in consequent parts, scale of training data and amount of adjusted parameters.

Keywords: Fuzzy neural networks, Mamdani fuzzy inference, M-ANFIS

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Authors: Karolina Grzeszczuk-Kuć, Jolanta Bujok, Tomasz Walski, Małgorzata Komorowska

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Haemodialysis (HD) is a procedure saving patient lives around the world, unfortunately it brings numerous complications. Oxidative stress is one of the major factors which lead to erythrocytes destruction during extracorporeal circulation. Repeated HD procedures destroy blood elements and the organism is not able to keep up with their production. 30 HD procedures on healthy sheep were performed to evaluate effects of such treatment. Oxidative stress study was performed together with an analysis of basic blood parameters and empirical assessment of dialyzer condition after the procedure. A reversible decline in absolute leukocyte count, during first 30 min of HD, was observed. Blood clots were formed in the area of the blood inlet and outlet of the dialyzer. Our results are consistent with outcomes presented throughout the literature specifically with respect to the effects observed in humans and will provide a basis to evaluate methods for blood protection during haemodialysis.

Keywords: Animal model, blood components, haemodialysis, leukocytes, oxidative stress, sheep.

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Authors: A. Perolini

Abstract:

Feature and model selection are in the center of attention of many researches because of their impact on classifiers- performance. Both selections are usually performed separately but recent developments suggest using a combined GA-SVM approach to perform them simultaneously. This approach improves the performance of the classifier identifying the best subset of variables and the optimal parameters- values. Although GA-SVM is an effective method it is computationally expensive, thus a rough method can be considered. The paper investigates a joined approach of Genetic Algorithm and kernel matrix criteria to perform simultaneously feature and model selection for SVM classification problem. The purpose of this research is to improve the classification performance of SVM through an efficient approach, the Kernel Matrix Genetic Algorithm method (KMGA).

Keywords: Feature and model selection, Genetic Algorithms, Support Vector Machines, kernel matrix.

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Authors: Il Young Song, Du Yong Kim, Vladimir Shin

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This paper reports on a receding horizon filtering for mobile robot systems with cross-correlated sensor noises and uncertainties. Also, the effect of uncertain parameters in the state of the tracking error model performance is considered. A distributed fusion receding horizon filter is proposed. The distributed fusion filtering algorithm represents the optimal linear combination of the local filters under the minimum mean square error criterion. The derivation of the error cross-covariances between the local receding horizon filters is the key of this paper. Simulation results of the tracking mobile robot-s motion demonstrate high accuracy and computational efficiency of the distributed fusion receding horizon filter.

Keywords: Distributed fusion, fusion formula, Kalman filter, multisensor, receding horizon, wheeled mobile robot

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Authors: Nermin Sökmen

Abstract:

An effort estimation model is needed for softwareintensive projects that consist of hardware, embedded software or some combination of the two, as well as high level software solutions. This paper first focuses on functional decomposition techniques to measure functional complexity of a computer system and investigates its impact on system development effort. Later, it examines effects of technical difficulty and design team capability factors in order to construct the best effort estimation model. With using traditional regression analysis technique, the study develops a system development effort estimation model which takes functional complexity, technical difficulty and design team capability factors as input parameters. Finally, the assumptions of the model are tested.

Keywords: Functional complexity, functional decomposition, development effort, technical difficulty, design team capability, regression analysis.

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Authors: R. Ziaie Moayed , S. Tamassoki , E. Izadi

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Investigation of sandy clay behavior is important since urban development demands mean that sandy clay areas are increasingly encountered, especially for transportation infrastructures. This paper presents the results of the finite element analysis of the direct shear test (under three vertical loading 44, 96 and 192 kPa) and discusses the effects of different parameters such as cohesion, friction angle and Young's modulus on the shear strength of sandy clay. The numerical model was calibrated against the experimental results of large-scale direct shear tests. The results have shown that the shear strength was increased with increase in friction angle and cohesion. However, the shear strength was not influenced by raising the friction angle at normal stress of 44 kPa. Also, the effect of different young's modulus factors on stress-strain curve was investigated.

Keywords: Shear strength, Finite element analysis, Large direct shear test, Sandy clay.

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Authors: Mohammad Reza Ghasemi, Amin Ghorbani

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The main goal of the present work is to decrease the computational burden for optimum design of steel frames with frequency constraints using a new type of neural networks called Wavelet Neural Network. It is contested to train a suitable neural network for frequency approximation work as the analysis program. The combination of wavelet theory and Neural Networks (NN) has lead to the development of wavelet neural networks. Wavelet neural networks are feed-forward networks using wavelet as activation function. Wavelets are mathematical functions within suitable inner parameters, which help them to approximate arbitrary functions. WNN was used to predict the frequency of the structures. In WNN a RAtional function with Second order Poles (RASP) wavelet was used as a transfer function. It is shown that the convergence speed was faster than other neural networks. Also comparisons of WNN with the embedded Artificial Neural Network (ANN) and with approximate techniques and also with analytical solutions are available in the literature.

Keywords: Weight Minimization, Frequency Constraints, Steel Frames, ANN, WNN, RASP Function.

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Authors: J. Mehena, M. C. Adhikary

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Edge detection is one of the most important tasks in image processing. Medical image edge detection plays an important role in segmentation and object recognition of the human organs. It refers to the process of identifying and locating sharp discontinuities in medical images. In this paper, a neuro-fuzzy based approach is introduced to detect the edges for noisy medical images. This approach uses desired number of neuro-fuzzy subdetectors with a postprocessor for detecting the edges of medical images. The internal parameters of the approach are optimized by training pattern using artificial images. The performance of the approach is evaluated on different medical images and compared with popular edge detection algorithm. From the experimental results, it is clear that this approach has better performance than those of other competing edge detection algorithms for noisy medical images.

Keywords: Edge detection, neuro-fuzzy, image segmentation, artificial image, object recognition.

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Authors: I. Made Gatot Karohika, Shigeyuki Haruyama, Ken Kaminishi, Oke Oktavianty, Didik Nurhadiyanto

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Contact width and contact stress are important parameters related to the leakage behavior of corrugated metal gasket. In this study, contact width and contact stress of three-layer corrugated metal gasket are investigated due to the modulus of elasticity and thickness of surface layer for 2 type gasket (0-MPa and 400-MPa mode). A finite element method was employed to develop simulation solution to analysis the effect of each parameter. The result indicated that lowering the modulus of elasticity ratio of surface layer will result in better contact width but the average contact stresses are smaller. When the modulus of elasticity ratio is held constant with thickness ratio increase, its contact width has an increscent trend otherwise the average contact stress has decreased trend.

Keywords: Contact width, contact stress, layer, metal gasket, corrugated, simulation.

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Authors: P. Subbaraj, V. Rajasekaran

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This paper presents a new approach using Combined Artificial Neural Network (CANN) module for daily peak load forecasting. Five different computational techniques –Constrained method, Unconstrained method, Evolutionary Programming (EP), Particle Swarm Optimization (PSO), and Genetic Algorithm (GA) – have been used to identify the CANN module for peak load forecasting. In this paper, a set of neural networks has been trained with different architecture and training parameters. The networks are trained and tested for the actual load data of Chennai city (India). A set of better trained conventional ANNs are selected to develop a CANN module using different algorithms instead of using one best conventional ANN. Obtained results using CANN module confirm its validity.

Keywords: Combined ANN, Evolutionary Programming, Particle Swarm Optimization, Genetic Algorithm and Peak load forecasting.

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Authors: Hidir S. Nogay

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In this study, two systems were created to predict interior temperature in induction motor. One of them consisted of a simple ANN model which has two layers, ten input parameters and one output parameter. The other one consisted of eight ANN models connected each other as cascaded. Cascaded ANN system has 17 inputs. Main reason of cascaded system being used in this study is to accomplish more accurate estimation by increasing inputs in the ANN system. Cascaded ANN system is compared with simple conventional ANN model to prove mentioned advantages. Dataset was obtained from experimental applications. Small part of the dataset was used to obtain more understandable graphs. Number of data is 329. 30% of the data was used for testing and validation. Test data and validation data were determined for each ANN model separately and reliability of each model was tested. As a result of this study, it has been understood that the cascaded ANN system produced more accurate estimates than conventional ANN model.

Keywords: Cascaded neural network, internal temperature, three-phase induction motor, inverter.

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Authors: Gholamhosein Khosravi, Mohammad Azadi, Hamidreza Ghezavati

Abstract:

In this paper, vibration of a nonlinear composite beam is analyzed and then an active controller is used to control the vibrations of the system. The beam is resting on a Winkler-Pasternak elastic foundation. The composite beam is reinforced by single walled carbon nanotubes. Using the rule of mixture, the material properties of functionally graded carbon nanotube-reinforced composites (FG-CNTRCs) are determined. The beam is cantilever and the free end of the beam is under follower force. Piezoelectric layers are attached to the both sides of the beam to control vibrations as sensors and actuators. The governing equations of the FG-CNTRC beam are derived based on Euler-Bernoulli beam theory Lagrange- Rayleigh-Ritz method. The simulation results are presented and the effects of some parameters on stability of the beam are analyzed.

Keywords: Carbon nanotubes, vibration control, piezoelectric layers, elastic foundation.

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Authors: Habtu Alemayehu, G. Radhakrishnamacharya

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The paper presents an analytical solution for dispersion of a solute in the peristaltic motion of a couple stress fluid through a porous medium with slip condition in the presence of both homogeneous and heterogeneous chemical reactions. The average effective dispersion coefficient has been found using Taylor-s limiting condition and long wavelength approximation. The effects of various relevant parameters on the average coefficient of dispersion have been studied. The average effective dispersion coefficient tends to increase with permeability parameter but tends to decrease with homogeneous chemical reaction rate parameter, couple stress parameter, slip parameter and heterogeneous reaction rate parameter.

Keywords: Dispersion, Peristalsis, Couple stress fluid, Porousmedium, Chemical reaction, Slip condition.

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Authors: Mike Sewell, Jagath Samarabandu, Ranga Rodrigo, Kenneth McIsaac

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A novel method of individual level adaptive mutation rate control called the rank-scaled mutation rate for genetic algorithms is introduced. The rank-scaled mutation rate controlled genetic algorithm varies the mutation parameters based on the rank of each individual within the population. Thereby the distribution of the fitness of the papulation is taken into consideration in forming the new mutation rates. The best fit mutate at the lowest rate and the least fit mutate at the highest rate. The complexity of the algorithm is of the order of an individual adaptation scheme and is lower than that of a self-adaptation scheme. The proposed algorithm is tested on two common problems, namely, numerical optimization of a function and the traveling salesman problem. The results show that the proposed algorithm outperforms both the fixed and deterministic mutation rate schemes. It is best suited for problems with several local optimum solutions without a high demand for excessive mutation rates.

Keywords: Genetic algorithms, mutation rate control, adaptive mutation.

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Authors: Leonardo Herrera, Shield B. Lin, Stephen J. Montgomery-Smith, Ziraguen O. Williams

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A one-directional dynamic model of a Stewart Platform was developed to assist NASA in analyzing the dynamic response in spacecraft docking operations. A simplified mechanical drawing was created, capturing the physical structure's main features. A simplified schematic diagram was developed into a lumped mass model from the mechanical drawing. Three differential equations were derived according to the schematic diagram. A Simulink diagram was created using MATLAB to represent the three equations. System parameters, including spring constants and masses, are derived in detail from the physical system. The model can be used for further analysis via computer simulation in predicting dynamic response in its main docking direction, i.e., up-and-down motion.

Keywords: Stewart platform, docking operation, spacecraft, spring constant.

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Authors: Yeqing Guan, Fen Yang

Abstract:

To learn about China-s future energy demand, this paper first proposed GM(1,1) model group based on recursive solutions of parameters estimation, setting up a general solving-algorithm of the model group. This method avoided the problems occurred on the past researches that remodeling, loss of information and large amount of calculation. This paper established respectively all-data-GM(1,1), metabolic GM(1,1) and new information GM (1,1)model according to the historical data of energy consumption in China in the year 2005-2010 and the added data of 2011, then modeling, simulating and comparison of accuracies we got the optimal models and to predict. Results showed that the total energy demand of China will be 37.2221 billion tons of equivalent coal in 2012 and 39.7973 billion tons of equivalent coal in 2013, which are as the same as the overall planning of energy demand in The 12th Five-Year Plan.

Keywords: energy demands, GM(1, 1) model group, least square estimation, prediction

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Authors: A. Benmakhlouf, A. Bentabet

Abstract:

In this paper, we investigated the athermal pressure behavior of the structural and elastic properties of scheelite BaWO4 phase up to 7 GPa using the ab initio pseudo-potential method. The calculated lattice parameters pressure relation have been compared with the experimental values and found to be in good agreement with these results. Moreover, we present for the first time the investigation of the elastic properties of this compound using the density functional perturbation theory (DFPT). It is shown that this phase is mechanically stable up to 7 GPa after analyzing the calculated elastic constants. Other relevant quantities such as bulk modulus, pressure derivative of bulk modulus, shear modulus; Young’s modulus, Poisson’s ratio, anisotropy factors, Debye temperature and sound velocity have been calculated. The obtained results, which are reported for the first time to the best of the author’s knowledge, can facilitate assessment of possible applications of the title material.

Keywords: Pseudo-potential method, pressure, structural and elastic properties, scheelite BaWO4 phase.

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Authors: Alvise Pellegrini, Ernesto Benini

Abstract:

The design of a steam turbine is a very complex engineering operation that can be simplified and improved thanks to computer-aided multi-objective optimization. This process makes use of existing optimization algorithms and losses correlations to identify those geometries that deliver the best balance of performance (i.e. Pareto-optimal points). This paper deals with a one-dimensional multi-objective and multi-point optimization of a single-stage steam turbine. Using a genetic optimization algorithm and an algebraic one-dimensional ideal gas-path model based on loss and deviation correlations, a code capable of performing the optimization of a predefined steam turbine stage was developed. More specifically, during this study the parameters modified (i.e. decision variables) to identify the best performing geometries were solidity and angles both for stator and rotor cascades, while the objective functions to maximize were totalto- static efficiency and specific work done. Finally, an accurate analysis of the obtained results was carried out.

Keywords: Steam turbine, optimization, genetic algorithms.

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Authors: Ghassan A. Abed, Mahamod Ismail, Samir I. Badrawi, Bayan M. Sabbar

Abstract:

Long Term Evolution Advanced (LTE-Advanced) LTE-Advanced is not new as a radio access technology, but it is an evolution of LTE to enhance the performance. This generation is the continuation of 3GPP-LTE (3GPP: 3rd Generation Partnership Project) and it is targeted for advanced development of the requirements of LTE in terms of throughput and coverage. The performance evaluation process of any network should be based on many models and simulations to investigate the network layers and functions and monitor the employment of the new technologies especially when this network includes large-bandwidth and low-latency links such as LTE and LTE-Advanced networks. Therefore, it’s necessary to enhance the proposed models of high-speed and high-congested link networks to make these links and traffics fulfill the needs of the huge data which transferred over the congested links. This article offered an innovative model of the most correlated links of LTE-Advanced system using the Network Simulator 2 (NS-2) with investigation of the link parameters.

Keywords: 3GPP, LTE, LTE-Advanced, NS-2.

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Authors: Ji Hyung Park, Dong-Hyun Seo, Young-Jin Jung, Han Sung Kim

Abstract:

The aim of this study is to evaluate the effects of the laser and partial vibration stimulation on the mice tibia with morphological characteristics. Twenty female C57BL/6 mice (12 weeks old) were used for the experiment. The study was carried out on four groups of animals each consisting of five mice. Four groups of mice were ovariectomized. Animals were scanned at 0 and 2 weeks after ovariectomy by using micro computed tomography to estimate morphological characteristics of tibial trabecular bone. Morphological analysis showed that structural parameters of multi-stimuli group appear significantly better phase in BV/TV, BS/BV, Tb.Th, Tb.N, Tb.Sp, and Tb.pf than single stimulation groups. However, single stimulation groups didn’t show significant effect on tibia with Sham group. This study suggests that multi-stimuli may restrain the change as the degenerate phase on osteoporosis in the mice tibia.

Keywords: Laser, Partial Vibration, Osteoporosis, in vivo micro-CT, mice.

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Authors: M. Debyeche, J.P Haton, A. Houacine

Abstract:

The paper presents a complete discrete statistical framework, based on a novel vector quantization (VQ) front-end process. This new VQ approach performs an optimal distribution of VQ codebook components on HMM states. This technique that we named the distributed vector quantization (DVQ) of hidden Markov models, succeeds in unifying acoustic micro-structure and phonetic macro-structure, when the estimation of HMM parameters is performed. The DVQ technique is implemented through two variants. The first variant uses the K-means algorithm (K-means- DVQ) to optimize the VQ, while the second variant exploits the benefits of the classification behavior of neural networks (NN-DVQ) for the same purpose. The proposed variants are compared with the HMM-based baseline system by experiments of specific Arabic consonants recognition. The results show that the distributed vector quantization technique increase the performance of the discrete HMM system.

Keywords: Hidden Markov Model, Vector Quantization, Neural Network, Speech Recognition, Arabic Language

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Authors: Sidhartha Panda, C. Ardil

Abstract:

Power system stabilizers (PSS) are now routinely used in the industry to damp out power system oscillations. In this paper, particle swarm optimization (PSO) technique is applied to coordinately design multiple power system stabilizers (PSS) in a multi-machine power system. The design problem of the proposed controllers is formulated as an optimization problem and PSO is employed to search for optimal controller parameters. By minimizing the time-domain based objective function, in which the deviation in the oscillatory rotor speed of the generator is involved; stability performance of the system is improved. The non-linear simulation results are presented for various severe disturbances and small disturbance at different locations as well as for various fault clearing sequences to show the effectiveness and robustness of the proposed controller and their ability to provide efficient damping of low frequency oscillations.

Keywords: Low frequency oscillations, Particle swarm optimization, power system stability, power system stabilizer, multimachine power system.

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Authors: M. A. Badr, A. N. Mohib, M. M. Ibrahim

Abstract:

The objective of this research is to study the technical and economic performance of wind/diesel/battery (W/D/B) system supplying a remote small gathering of six families using HOMER software package. The electrical energy is to cater for the basic needs for which the daily load pattern is estimated. Net Present Cost (NPC) and Cost of Energy (COE) are used as economic criteria, while the  measure of performance is % of power shortage. Technical and economic parameters are defined to estimate the feasibility of the system under study. Optimum system configurations are estimated for two sites. Using HOMER software, the simulation results showed that W/D/B systems are economical for the assumed community sites as the price of generated electricity is about 0.308 $/kWh, without taking external benefits into considerations. W/D/B systems are more economical than W/B or diesel alone systems, as the COE is 0.86 $/kWh for W/B and 0.357 $/kWh for diesel alone.

Keywords: Optimum energy systems, Remote electrification, Renewable energy, Wind turbine systems.

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Authors: Sisuwan Kaseamsawat, Sivapan Choo-In

Abstract:

This study aimed to evaluated the surface water quality for agriculture and consumption in the Amphawa District. The surface water quality parameters in this study included water temperature, turbidity, conductivity, salinity, pH, dissolved oxygen, BOD, nitrate, suspended solids, phosphorus, total dissolved solids (TDS), iron (Fe), copper (Cu), zinc (Zn), manganese (Mn), lead (Pb) and cadmium (Cd). The water samples were collected from small excavation, Lychee, Pomelo and Coconut orchards for 3 seasons from January to December 2011.

The surface water quality from small excavation, Lychee, pomelo and coconut orchards were met the type III of surface water quality standard. The concentration of heavy metal and did not differ significantly at 0.05 level, except dissolved oxygen.

The surface water was suitable for consumption by the usual sterile and generally improving water quality through the process before and was suitable for agriculture.

Keywords: Water Quality, Surface Water Quality.

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Authors: Jandot Aurélia

Abstract:

As the nuclear power is a sensitive field leading to controversy, the quality of the communication about it is important. Between 1965 and 1981, in France, this one had gradually changed. This change is studied here in the main French news magazine L’Express, in connection with several parameters. As this represents a huge number of copies and occurrences, thus a considerable amount of information; this paper is focused on the main articles as well as the main “mental images”. These ones are important, as their aim is to direct the thought of the readers, and as they have led the public awareness to evolve. Over this 17 years, two trends are in confrontation: The first one is promoting the perception of the nuclear power, while the second one is discrediting it. These trends are organized in two axes: the evolution of engineering, and the risks. In both cases, the changes in the language allow discerning the deepest intentions of the magazine editing, over a period when the nuclear technology, to there a laboratory object accompanied with mystery and secret, has become a social issue seemingly open to all.

Keywords: French news magazine, mental images, nuclear power, public awareness.

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Authors: A. Zidani, M. Yahia K. Belhadi, S. Benbia

Abstract:

Hepatitis C is an infectious disease transmitted by blood and due to hepatitis C virus (HCV), which attacks the liver. The infection is characterized by liver inflammation (hepatitis) that is often asymptomatic but can progress to chronic hepatitis and later cirrhosis and liver cancer. Our problem tends to highlight on the one hand the prevalence of infectious disease in the population of the region of Batna and on other hand the biological characteristics of this disease by a screening and a specific diagnosis based on serological tests, liver checkup (measurement of haematological and biochemical parameters). The results showed: The serology of hepatitis C establishes the diagnosis of infection with hepatitis C. In this study and with the serological test, 24 cases of the disease of hepatitis C were found in 1000 suspected cases (7 cases with normal transaminases and 17 cases with elevated transaminases). The prevalence of this disease in this study population was 2.4%. The presence of hepatitis C disrupts liver function including the onset of cytolysis, cholestasis, jaundice, thrombocytopenia, and coagulation disorders.

Keywords: Disease hepatitis C, serology, liver checkup

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Authors: Abdur Rosyid, Mohamed El-Madany, Mohanad Alata

Abstract:

Due to simplicity and low cost, rotordynamic system is often modeled by using lumped parameters. Recently, finite elements have been used to model rotordynamic system as it offers higher accuracy. However, it involves high degrees of freedom. In some applications such as control design, this requires higher cost. For this reason, various model reduction methods have been proposed. This work demonstrates the quality of model reduction of rotor-bearing-support system through substructuring. The quality of the model reduction is evaluated by comparing some first natural frequencies, modal damping ratio, critical speeds, and response of both the full system and the reduced system. The simulation shows that the substructuring is proven adequate to reduce finite element rotor model in the frequency range of interest as long as the number and the location of master nodes are determined appropriately. However, the reduction is less accurate in an unstable or nearly-unstable system.

Keywords: Finite element model, rotordynamic system, model reduction, substructuring.

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Authors: Mário C. Ricci

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An alternative iterative computational procedure is proposed for internal normal ball loads calculation in statically loaded single-row, angular-contact ball bearings, subjected to a known thrust load, which is applied in the inner ring at the geometric bearing center line. An accurate method for curvature radii at contacts with inner and outer raceways in the direction of the motion is used. Numerical aspects of the iterative procedure are discussed. Numerical examples results for a 218 angular-contact ball bearing have been compared with those from the literature. Twenty figures are presented showing the geometrical features, the behavior of the convergence variables and the following parameters as functions of the thrust load: normal ball loads, contact angle, distance between curvature centers, and normal ball and axial deflections.

Keywords: Ball, Bearing, Static, Load, Iterative, Numerical, Method.

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Authors: Nora Taghavi, Ali Sadr

Abstract:

System identification is the process of creating models of dynamic process from input- output signals. The aim of system identification can be identified as “ to find a model with adjustable parameters and then to adjust them so that the predicted output matches the measured output". This paper presents a method of modeling and simulating with system identification to achieve the maximum fitness for transformation function. First by using optimized KLM equivalent circuit for PVDF piezoelectric transducer and assuming different inputs including: sinuside, step and sum of sinusides, get the outputs, then by using system identification toolbox in MATLAB, we estimate the transformation function from inputs and outputs resulted in last program. Then compare the fitness of transformation function resulted from using ARX,OE(Output- Error) and BJ(Box-Jenkins) models in system identification toolbox and primary transformation function form KLM equivalent circuit.

Keywords: PVDF modeling, ARX, BJ(Box-Jenkins), OE(Output-Error), System Identification.

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