Search results for: finite volume method

Authors: Ali Rafiee, Ahad Salimi, Ali Reza Roosta

Abstract:

Prostate cancer is one of the most frequent cancers in men and is a major cause of mortality in the most of countries. In many diagnostic and treatment procedures for prostate disease accurate detection of prostate boundaries in transrectal ultrasound (TRUS) images is required. This is a challenging and difficult task due to weak prostate boundaries, speckle noise and the short range of gray levels. In this paper a novel method for automatic prostate segmentation in TRUS images is presented. This method involves preprocessing (edge preserving noise reduction and smoothing) and prostate segmentation. The speckle reduction has been achieved by using stick filter and top-hat transform has been implemented for smoothing. A feed forward neural network and local binary pattern together have been use to find a point inside prostate object. Finally the boundary of prostate is extracted by the inside point and an active contour algorithm. A numbers of experiments are conducted to validate this method and results showed that this new algorithm extracted the prostate boundary with MSE less than 4.6% relative to boundary provided manually by physicians.

Keywords: Prostate segmentation, stick filter, neural network, active contour.

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Authors: Awadhesh Pachauri, Manabendra Bhuyan

Abstract:

Electrocardiogram (ECG) is considered to be the backbone of cardiology. ECG is composed of P, QRS & T waves and information related to cardiac diseases can be extracted from the intervals and amplitudes of these waves. The first step in extracting ECG features starts from the accurate detection of R peaks in the QRS complex. We have developed a robust R wave detector using wavelets. The wavelets used for detection are Daubechies and Symmetric. The method does not require any preprocessing therefore, only needs the ECG correct recordings while implementing the detection. The database has been collected from MIT-BIH arrhythmia database and the signals from Lead-II have been analyzed. MatLab 7.0 has been used to develop the algorithm. The ECG signal under test has been decomposed to the required level using the selected wavelet and the selection of detail coefficient d4 has been done based on energy, frequency and cross-correlation analysis of decomposition structure of ECG signal. The robustness of the method is apparent from the obtained results.

Keywords: ECG, P-QRS-T waves, Wavelet Transform, Hard Thresholding, R-wave Detection.

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Authors: Mounira Taileb, Sid Lamrous, Sami Touati

Abstract:

In order to accelerate the similarity search in highdimensional database, we propose a new hierarchical indexing method. It is composed of offline and online phases. Our contribution concerns both phases. In the offline phase, after gathering the whole of the data in clusters and constructing a hierarchical index, the main originality of our contribution consists to develop a method to construct bounding forms of clusters to avoid overlapping. For the online phase, our idea improves considerably performances of similarity search. However, for this second phase, we have also developed an adapted search algorithm. Our method baptized NOHIS (Non-Overlapping Hierarchical Index Structure) use the Principal Direction Divisive Partitioning (PDDP) as algorithm of clustering. The principle of the PDDP is to divide data recursively into two sub-clusters; division is done by using the hyper-plane orthogonal to the principal direction derived from the covariance matrix and passing through the centroid of the cluster to divide. Data of each two sub-clusters obtained are including by a minimum bounding rectangle (MBR). The two MBRs are directed according to the principal direction. Consequently, the nonoverlapping between the two forms is assured. Experiments use databases containing image descriptors. Results show that the proposed method outperforms sequential scan and SRtree in processing k-nearest neighbors.

Keywords: K-nearest neighbour search, multi-dimensional indexing, multimedia databases, similarity search.

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Authors: M. Babaeipour, M. Vejdanihemmat

Abstract:

Optical properties of bulk and thin film of 1H-CaAlSi for two directions (1,0,0) and (0,0,1) were studied. The calculations are carried out by Density Functional Theory (DFT) method using full potential. GGA approximation was used to calculate exchange-correlation energy. The calculations are performed by WIEN2k package. The results showed that the absorption edge is shifted backward 0.82eV in the thin film than the bulk for both directions. The static values of the real part of dielectric function for four cases were obtained. The static values of the refractive index for four cases are calculated too. The reflectivity graphs have shown an intensive difference between the reflectivity of the thin film and the bulk in the ultraviolet region.

Keywords: 1H-CaAlSi, absorption, bulk, optical, thin film.

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Authors: Ziad. Sh. Al Sarraf

Abstract:

Ultrasonic metal welding has been the subject of ongoing research and development, most recently concentrating on metal joining in miniature devices, for example to allow solder-free wire bonding. As well as at the small scale, there are also opportunities to research the joining of thicker sheet metals and to widen the range of similar and dissimilar materials that can be successfully joined using this technology. This study presents the design, characterisation and test of a lateral-drive ultrasonic metal spot welding device. The ultrasonic metal spot welding horn is modelled using finite element analysis (FEA) and its vibration behaviour is characterised experimentally to ensure ultrasonic energy is delivered effectively to the weld coupon. The welding stack and fixtures are then designed and mounted on a test machine to allow a series of experiments to be conducted for various welding and ultrasonic parameters. Weld strength is subsequently analysed using tensile-shear tests. The results show how the weld strength is particularly sensitive to the combination of clamping force and ultrasonic vibration amplitude of the welding tip, but there are optimal combinations of these and also limits that must be clearly identified.

Keywords: Ultrasonic welding, vibration amplitude, welding force, weld strength.

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Authors: M. Örvös, T. Balázs, K. F. Both

Abstract:

From environmental aspect purification of ammonia containing wastewater is expected. High efficiency ammonia desorption can be done from the water by air on proper temperature. After the desorption process, ammonia can be recovered and used in another technology. The calculation method described below give some methods to find either the minimum column height or ammonia rich solution of the effluent.

Keywords: Absorber, desorber, packed column.

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Authors: M. K. Moazzam, A. Salmanpour, M. Nirouei

Abstract:

In this paper we have numerically analyzed terahertzrange wavelength conversion using nondegenerate four wave mixing (NDFWM) in a SOA integrated DFB laser (experiments reported both in MIT electronics and Fujitsu research laboratories). For analyzing semiconductor optical amplifier (SOA), we use finitedifference beam propagation method (FDBPM) based on modified nonlinear SchrÖdinger equation and for distributed feedback (DFB) laser we use coupled wave approach. We investigated wavelength conversion up to 4THz probe-pump detuning with conversion efficiency -5dB in 1THz probe-pump detuning for a SOA integrated quantum-well

Keywords: distributed feedback laser, nondegenerate fourwave mixing, semiconductor optical amplifier, wavelengthconversion

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Authors: Masoud Sadeghian, Alireza Fatehi

Abstract:

In this paper, we use nonlinear system identification method to predict and detect process fault of a cement rotary kiln. After selecting proper inputs and output, an input-output model is identified for the plant. To identify the various operation points in the kiln, Locally Linear Neuro-Fuzzy (LLNF) model is used. This model is trained by LOLIMOT algorithm which is an incremental treestructure algorithm. Then, by using this method, we obtained 3 distinct models for the normal and faulty situations in the kiln. One of the models is for normal condition of the kiln with 15 minutes prediction horizon. The other two models are for the two faulty situations in the kiln with 7 minutes prediction horizon are presented. At the end, we detect these faults in validation data. The data collected from White Saveh Cement Company is used for in this study.

Keywords: Cement Rotary Kiln, Fault Detection, Delay Estimation Method, Locally Linear Neuro Fuzzy Model, LOLIMOT.

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Authors: Watcharin Kaewapichai, Pakorn Kaewtrakulpong

Abstract:

In this paper, a method to detect multiple ellipses is presented. The technique is efficient and robust against incomplete ellipses due to partial occlusion, noise or missing edges and outliers. It is an iterative technique that finds and removes the best ellipse until no reasonable ellipse is found. At each run, the best ellipse is extracted from randomly selected edge patches, its fitness calculated and compared to a fitness threshold. RANSAC algorithm is applied as a sampling process together with the Direct Least Square fitting of ellipses (DLS) as the fitting algorithm. In our experiment, the method performs very well and is robust against noise and spurious edges on both synthetic and real-world image data.

Keywords: Direct Least Square Fitting, Ellipse Detection, RANSAC

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Authors: Anastasia Katsamaki, Nikolaos Bilalis, Vassilis Dedoussis

Abstract:

This work proposes a set of actions to assist redesign procedure in existing products of Electric and Electronic Equipment (EEE). The aim is to improve their environmental behavior after their withdrawal in the End-of-Life (EOL) phase. In the beginning data collection takes place. Then follows selection and implementation of the optimal EOL Treatment Strategy (EOL_TS) and its results- evaluation concerning the environment. In parallel, product design characteristics that can be altered are selected based on their significance for the environment in the EOL stage. All results from the previous stages are combined and possible redesign actions are formulated for further examination and afterwards configuration in the design stage. The applied method to perform these tasks is Lean Thinking (LT). At the end, results concerning the application of the proposed method on a distribution transformer are presented.

Keywords: End-of-life treatment, Lean thinking, WEEE

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Authors: Hazem M. El-Bakry

Abstract:

In this paper a new fast simplification method is presented. Such method realizes Karnough map with large number of variables. In order to accelerate the operation of the proposed method, a new approach for fast detection of group of ones is presented. Such approach implemented in the frequency domain. The search operation relies on performing cross correlation in the frequency domain rather than time one. It is proved mathematically and practically that the number of computation steps required for the presented method is less than that needed by conventional cross correlation. Simulation results using MATLAB confirm the theoretical computations. Furthermore, a powerful solution for realization of complex functions is given. The simplified functions are implemented by using a new desigen for neural networks. Neural networks are used because they are fault tolerance and as a result they can recognize signals even with noise or distortion. This is very useful for logic functions used in data and computer communications. Moreover, the implemented functions are realized with minimum amount of components. This is done by using modular neural nets (MNNs) that divide the input space into several homogenous regions. Such approach is applied to implement XOR function, 16 logic functions on one bit level, and 2-bit digital multiplier. Compared to previous non- modular designs, a clear reduction in the order of computations and hardware requirements is achieved.

Keywords: Boolean Functions, Simplification, KarnoughMap, Implementation of Logic Functions, Modular NeuralNetworks.

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Authors: Leila Vafajoo, Farhad Khorasheh, Mehrnoosh Hamzezadeh Nakhjavani, Moslem Fattahi

Abstract:

In the present study, a procedure was developed to determine the optimum reaction rate constants in generalized Arrhenius form and optimized through the Nelder-Mead method. For this purpose, a comprehensive mathematical model of a fixed bed reactor for dehydrogenation of heavy paraffins over Pt–Sn/Al2O3 catalyst was developed. Utilizing appropriate kinetic rate expressions for the main dehydrogenation reaction as well as side reactions and catalyst deactivation, a detailed model for the radial flow reactor was obtained. The reactor model composed of a set of partial differential equations (PDE), ordinary differential equations (ODE) as well as algebraic equations all of which were solved numerically to determine variations in components- concentrations in term of mole percents as a function of time and reactor radius. It was demonstrated that most significant variations observed at the entrance of the bed and the initial olefin production obtained was rather high. The aforementioned method utilized a direct-search optimization algorithm along with the numerical solution of the governing differential equations. The usefulness and validity of the method was demonstrated by comparing the predicted values of the kinetic constants using the proposed method with a series of experimental values reported in the literature for different systems.

Keywords: Dehydrogenation, Pt-Sn/Al2O3 Catalyst, Modeling, Nelder-Mead, Optimization

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Authors: Vladimir Aleksandrovich Rogov, Ghorbani Siamak

Abstract:

Determination of optimal conditions of machining parameters is important to reduce the production cost and achieve the desired surface quality. This paper investigates the influence of cutting parameters on surface roughness and natural frequency in turning of aluminum alloy AA2024. The experiments were performed at the lathe machine using two different cutting tools made of AISI 5140 and carbide cutting insert coated with TiC. Turning experiments were planned by Taguchi method L₉ orthogonal array.Three levels for spindle speed, feed rate, depth of cut and tool overhang were chosen as cutting variables. The obtained experimental data has been analyzed using signal to noise ratio and analysis of variance. The main effects have been discussed and percentage contributions of various parameters affecting surface roughness and natural frequency, and optimal cutting conditions have been determined. Finally, optimization of the cutting parameters using Taguchi method was verified by confirmation experiments.

Keywords: Turning, Cutting conditions, Surface roughness, Natural frequency, Taguchi method, ANOVA, S/N ratio.

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Authors: Design of 3-Step Skew BLAC Motor for Better Performance in Electric Power Steering System

Abstract:

In Electric Power Steering (EPS), spoke type Brushless AC (BLAC) motors offer distinct advantages over other electric motor types in terms torque smoothness, reliability and efficiency. This paper deals with the shape optimization of spoke type BLAC motor, in order to reduce cogging torque. This paper examines 3 steps skewing rotor angle, optimizing rotor core edge and rotor overlap length for reducing cogging torque in spoke type BLAC motor. The methods were applied to existing machine designs and their performance was calculated using finite- element analysis (FEA). Prototypes of the machine designs were constructed and experimental results obtained. It is shown that the FEA predicted the cogging torque to be nearly reduce using those methods.

Keywords: EPS, 3-Step skewing, spoke type BLAC, cogging torque, FEA, optimization.

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Authors: Roshan Dharshana Yapa, Koichi Harada

Abstract:

Breast skin-line estimation and breast segmentation is an important pre-process in mammogram image processing and computer-aided diagnosis of breast cancer. Limiting the area to be processed into a specific target region in an image would increase the accuracy and efficiency of processing algorithms. In this paper we are presenting a new algorithm for estimating skin-line and breast segmentation using fast marching algorithm. Fast marching is a partial-differential equation based numerical technique to track evolution of interfaces. We have introduced some modifications to the traditional fast marching method, specifically to improve the accuracy of skin-line estimation and breast tissue segmentation. Proposed modifications ensure that the evolving front stops near the desired boundary. We have evaluated the performance of the algorithm by using 100 mammogram images taken from mini-MIAS database. The results obtained from the experimental evaluation indicate that this algorithm explains 98.6% of the ground truth breast region and accuracy of the segmentation is 99.1%. Also this algorithm is capable of partially-extracting nipple when it is available in the profile.

Keywords: Mammogram, fast marching method, mathematical morphology.

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Authors: Ismail Saritas, Abdullah Adiyaman

Abstract:

In this study, a fuzzy-logic based control system was designed to ensure that time and energy is saved during the operation of load elevators which are used during the construction of tall buildings. In the control system that was devised, for the load elevators to work more efficiently, the energy interval where the motor worked was taken as the output variable whereas the amount of load and the building height were taken as input variables. The most appropriate working intervals depending on the characteristics of these variables were defined by the help of an expert. Fuzzy expert system software was formed using Delphi programming language. In this design, mamdani max-min inference mechanism was used and the centroid method was employed in the clarification procedure. In conclusion, it is observed that the system that was designed is feasible and this is supported by statistical analyses..

Keywords: Fuzzy Logic Control, DC Motor, Load Elevators, Power Control.

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Authors: Hazem M. El-Bakry

Abstract:

In this paper a new fast simplification method is presented. Such method realizes Karnough map with large number of variables. In order to accelerate the operation of the proposed method, a new approach for fast detection of group of ones is presented. Such approach implemented in the frequency domain. The search operation relies on performing cross correlation in the frequency domain rather than time one. It is proved mathematically and practically that the number of computation steps required for the presented method is less than that needed by conventional cross correlation. Simulation results using MATLAB confirm the theoretical computations. Furthermore, a powerful solution for realization of complex functions is given. The simplified functions are implemented by using a new desigen for neural networks. Neural networks are used because they are fault tolerance and as a result they can recognize signals even with noise or distortion. This is very useful for logic functions used in data and computer communications. Moreover, the implemented functions are realized with minimum amount of components. This is done by using modular neural nets (MNNs) that divide the input space into several homogenous regions. Such approach is applied to implement XOR function, 16 logic functions on one bit level, and 2-bit digital multiplier. Compared to previous non- modular designs, a clear reduction in the order of computations and hardware requirements is achieved.

Keywords: Boolean functions, simplification, Karnough map, implementation of logic functions, modular neural networks.

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Authors: Ramin Khamedi, Isa Ahmadi

Abstract:

In this study acoustic emission (AE) signals obtained during deformation and fracture of two types of ferrite-martensite dual phase steels (DPS) specimens have been analyzed in frequency domain. For this reason two low carbon steels with various amounts of carbon were chosen, and intercritically heat treated. In the introduced method, identifying the mechanisms of failure in the various phases of DPS is done. For this aim, AE monitoring has been used during tensile test of several DPS with various volume fraction of the martensite (VM) and attempted to relate the AE signals and failure mechanisms in these steels. Different signals, which referred to 2-3 micro-mechanisms of failure due to amount of carbon and also VM have been seen. By Fast Fourier Transformation (FFT) of signals in distinct locations, an excellent relationship between peak frequencies in these areas and micro-mechanisms of failure were seen. The results were verified by microscopic observations (SEM).

Keywords: Dual Phase Steel, Deformation, Acoustic Emission.

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Authors: Daekook Kang, Wooseok Jang, Hyeonjeong Lee, Hyun Joung No

Abstract:

Technology changes have been acknowledged as a critical factor in determining competitiveness of organization. Under such environment, the right anticipation of technology change has been of huge importance in strategic planning. To monitor technology change, technology forecasting (TF) is frequently utilized. In academic perspective, TF has received great attention for a long time. However, few researches have been conducted to provide overview of the TF literature. Even though some studies deals with review of TF research, they generally focused on type and characteristics of various TF, so hardly provides information about patterns of TF research and which TF method is used in certain technology industry. Accordingly, this study profile developments in and patterns of scholarly research in TF over time. Also, this study investigates which technology industries have used certain TF method and identifies their relationships. This study will help in understanding TF research trend and their application area.

Keywords: Technology forecasting, technology industry, TF trend, technology trajectory.

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Authors: Min Sang Lee, Hee Jae Shin, In Pyo Cha, Sun Ho Ko, Hyun Kyung Yoon, Hong Gun Kim, Lee Ku Kwac

Abstract:

The prepreg process among the CFRP (Carbon Fiber Reinforced Plastic) forming methods is the short term of ‘Pre-impregnation’, which is widely used for aerospace composites that require a high quality property such as a fiber-reinforced woven fabric, in which an epoxy hardening resin is impregnated the reality. However, that this process requires continuous researches and developments for its commercialization because the delamination characteristically develops between the layers when a great weight is loaded from outside to supplement such demerit, three lamination methods among the prepreg lamination methods of CFRP were designed to minimize the delamination between the layers due to external impacts. Further, the newly designed methods and the existing lamination methods were analyzed through a mechanical characteristic test, Interlaminar Shear Strength test. The Interlaminar Shear Strength test result confirmed that the newly proposed three lamination methods, i.e. the Roll, Half and Zigzag laminations, presented more excellent strengths compared to the conventional Ply lamination. The interlaminar shear strength in the roll method with relatively dense fiber distribution was approximately 1.75% higher than that in the existing ply lamination method, and in the half method, it was approximately 0.78% higher.

Keywords: Carbon Fiber Reinforced Plastic (CFRP), Pre-Impregnation, Laminating Method, Interlaminar Shear Strength (ILSS).

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Authors: A. Kawamura, K. Ishida, K. Okada, T. Sato

Abstract:

Simultaneous measurements of the curves for wear versus distance, wear rate versus distance, and coefficient of friction versus distance were performed in situ to distinguish the transition from severe running-in wear to mild wear. The effects of the initial surface roughness on the severe running-in wear volume were investigated. Disk-on-plate friction and wear tests were carried out with SUS304 austenitic stainless steel in contact with itself under repeated dry sliding conditions at room temperature. The wear volume was dependent on the initial surface roughness. The wear volume when the initial surfaces on the plate and disk had dissimilar roughness was lower than that when these surfaces had similar roughness. For the dissimilar roughness, the wear volume decreased with decreasing initial surface roughness and reached a minimum; it stayed nearly constant as the roughness was less than the mean size of the oxide particles.

Keywords: Austenitic stainless steel, initial surface roughness, running-in, severe wear.

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Authors: Yanping Liao, Congcong He, Ruigang Zhao

Abstract:

The application of magnetocardiography signals to detect cardiac electrical function is a new technology developed in recent years. The magnetocardiography signal is detected with Superconducting Quantum Interference Devices (SQUID) and has considerable advantages over electrocardiography (ECG). It is difficult to extract Magnetocardiography (MCG) signal which is buried in the noise, which is a critical issue to be resolved in cardiac monitoring system and MCG applications. In order to remove the severe background noise, the Total Variation (TV) regularization method is proposed to denoise MCG signal. The approach transforms the denoising problem into a minimization optimization problem and the Majorization-minimization algorithm is applied to iteratively solve the minimization problem. However, traditional TV regularization method tends to cause step effect and lacks constraint adaptability. In this paper, an improved TV regularization method for denoising MCG signal is proposed to improve the denoising precision. The improvement of this method is mainly divided into three parts. First, high-order TV is applied to reduce the step effect, and the corresponding second derivative matrix is used to substitute the first order. Then, the positions of the non-zero elements in the second order derivative matrix are determined based on the peak positions that are detected by the detection window. Finally, adaptive constraint parameters are defined to eliminate noises and preserve signal peak characteristics. Theoretical analysis and experimental results show that this algorithm can effectively improve the output signal-to-noise ratio and has superior performance.

Keywords: Constraint parameters, derivative matrix, magnetocardiography, regular term, total variation.

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Authors: Shao Bo Cheng, Yong-Jin Han, Se Young Park, Seong-Bae Park

Abstract:

Consumer-to-Consumer (C2C) E-commerce has been growing at a very high speed in recent years. Since identical or nearly-same kinds of products compete one another by relying on keyword search in C2C E-commerce, some sellers describe their products with spam keywords that are popular but are not related to their products. Though such products get more chances to be retrieved and selected by consumers than those without spam keywords, the spam keywords mislead the consumers and waste their time. This problem has been reported in many commercial services like ebay and taobao, but there have been little research to solve this problem. As a solution to this problem, this paper proposes a method to classify whether keywords of a product are spam or not. The proposed method assumes that a keyword for a given product is more reliable if the keyword is observed commonly in specifications of products which are the same or the same kind as the given product. This is because that a hierarchical category of a product in general determined precisely by a seller of the product and so is the specification of the product. Since higher layers of the hierarchical category represent more general kinds of products, a reliable degree is differently determined according to the layers. Hence, reliable degrees from different layers of a hierarchical category become features for keywords and they are used together with features only from specifications for classification of the keywords. Support Vector Machines are adopted as a basic classifier using the features, since it is powerful, and widely used in many classification tasks. In the experiments, the proposed method is evaluated with a golden standard dataset from Yi-han-wang, a Chinese C2C E-commerce, and is compared with a baseline method that does not consider the hierarchical category. The experimental results show that the proposed method outperforms the baseline in F1-measure, which proves that spam keywords are effectively identified by a hierarchical category in C2C E-commerce.

Keywords: Spam Keyword, E-commerce, keyword features, spam filtering.

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Authors: Mustafa Resa Becan, Ahmet Kuzucu

Abstract:

A fuzzy predictive pursuit guidance is proposed as an alternative to the conventional methods. The purpose of this scheme is to obtain a stable and fast guidance. The noise effects must be reduced in homing missile guidance to get an accurate control. An aerodynamic missile model is simulated first and a fuzzy predictive pursuit control algorithm is applied to reduce the noise effects. The performance of this algorithm is compared with the performance of the classical proportional derivative control. Stability analysis of the proposed guidance method is performed and compared with the stability properties of other guidance methods. Simulation results show that the proposed method provides the satisfying performance.

Keywords: Fuzzy, noise effect, predictive, pursuit.

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Authors: Rakesh Kumar, A. K. Ghosh

Abstract:

The paper presents the modeling of nonlinear longitudinal aerodynamics using flight data of Hansa-3 aircraft at high angles of attack near stall. The Kirchhoff-s quasi-steady stall model has been used to incorporate nonlinear aerodynamic effects in the aerodynamic model used to estimate the parameters, thereby, making the aerodynamic model nonlinear. The Maximum Likelihood method has been applied to the flight data (at high angles of attack) for the estimation of parameters (aerodynamic and stall characteristics) using the nonlinear aerodynamic model. To improve the accuracy level of the estimates, an approach of fixing the strong parameters has also been presented.

Keywords: Maximum Likelihood, nonlinear, parameters, stall.

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Authors: RajPal Garg, Kapil Sharma, Rajive Kumar, R. K. Garg

Abstract:

This paper presents a computational methodology based on matrix operations for a computer based solution to the problem of performance analysis of software reliability models (SRMs). A set of seven comparison criteria have been formulated to rank various non-homogenous Poisson process software reliability models proposed during the past 30 years to estimate software reliability measures such as the number of remaining faults, software failure rate, and software reliability. Selection of optimal SRM for use in a particular case has been an area of interest for researchers in the field of software reliability. Tools and techniques for software reliability model selection found in the literature cannot be used with high level of confidence as they use a limited number of model selection criteria. A real data set of middle size software project from published papers has been used for demonstration of matrix method. The result of this study will be a ranking of SRMs based on the Permanent value of the criteria matrix formed for each model based on the comparison criteria. The software reliability model with highest value of the Permanent is ranked at number – 1 and so on.

Keywords: Matrix method, Model ranking, Model selection, Model selection criteria, Software reliability models.

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Authors: Zhu Xiong-feng, Hou Zhong-xi, Guo Zheng, Liu Zhao-Wei

Abstract:

A method of dynamic mesh based airfoil optimization is proposed according to the drawbacks of surrogate model based airfoil optimization. Programs are designed to achieve the dynamic mesh. Boundary condition is add by integrating commercial software Pointwise, meanwhile the CFD calculation is carried out by commercial software Fluent. The data exchange and communication between the software and programs referred above have been accomplished, and the whole optimization process is performed in iSIGHT platform. A simplified airfoil optimization study case is brought out to show that aerodynamic performances of airfoil have been significantly improved, even save massive repeat operations and increase the robustness and credibility of the optimization result. The case above proclaims that dynamic mesh based airfoil optimization is an effective and high efficient method.

Keywords: unmanned air vehicles, dynamic mesh, airfoil optimization, CFD, genetic algorithm

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Authors: Takahiro Nishigaki, Takashi Onoda

Abstract:

In recent years, the number of document data has been increasing since the spread of the Internet. Many methods have been studied for extracting topics from large document data. We proposed Independent Topic Analysis (ITA) to extract topics independent of each other from large document data such as newspaper data. ITA is a method for extracting the independent topics from the document data by using the Independent Component Analysis. The topic represented by ITA is represented by a set of words. However, the set of words is quite different from the topics the user imagines. For example, the top five words with high independence of a topic are as follows. Topic1 = {"scor", "game", "lead", "quarter", "rebound"}. This Topic 1 is considered to represent the topic of "SPORTS". This topic name "SPORTS" has to be attached by the user. ITA cannot name topics. Therefore, in this research, we propose a method to obtain topics easy for people to understand by using the web search engine, topics given by the set of words given by independent topic analysis. In particular, we search a set of topical words, and the title of the homepage of the search result is taken as the topic name. And we also use the proposed method for some data and verify its effectiveness.

Keywords: Independent topic analysis, topic extraction, topic naming, web search engine.

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Authors: M. Sedighizadeh, A. Rezazadeh

Abstract:

Movable power sources of proton exchange membrane fuel cells (PEMFC) are the important research done in the current fuel cells (FC) field. The PEMFC system control influences the cell performance greatly and it is a control system for industrial complex problems, due to the imprecision, uncertainty and partial truth and intrinsic nonlinear characteristics of PEMFCs. In this paper an adaptive PI control strategy using neural network adaptive Morlet wavelet for control is proposed. It is based on a single layer feed forward neural networks with hidden nodes of adaptive morlet wavelet functions controller and an infinite impulse response (IIR) recurrent structure. The IIR is combined by cascading to the network to provide double local structure resulting in improving speed of learning. The proposed method is applied to a typical 1 KW PEMFC system and the results show the proposed method has more accuracy against to MLP (Multi Layer Perceptron) method.

Keywords: Adaptive Control, Morlet Wavelets, PEMFC.

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Authors: Israa Sh. Tawfic, Sema Koc Kayhan

Abstract:

Given a large sparse signal, great wishes are to reconstruct the signal precisely and accurately from lease number of measurements as possible as it could. Although this seems possible by theory, the difficulty is in built an algorithm to perform the accuracy and efficiency of reconstructing. This paper proposes a new proved method to reconstruct sparse signal depend on using new method called Least Support Matching Pursuit (LS-OMP) merge it with the theory of Partial Knowing Support (PSK) given new method called Partially Knowing of Least Support Orthogonal Matching Pursuit (PKLS-OMP). The new methods depend on the greedy algorithm to compute the support which depends on the number of iterations. So to make it faster, the PKLS-OMP adds the idea of partial knowing support of its algorithm. It shows the efficiency, simplicity, and accuracy to get back the original signal if the sampling matrix satisfies the Restricted Isometry Property (RIP). Simulation results also show that it outperforms many algorithms especially for compressible signals.

Keywords: Compressed sensing, Lest Support Orthogonal Matching Pursuit, Partial Knowing Support, Restricted isometry property, signal reconstruction.

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