Asymptotic Stabilization of an Active Magnetic Bearing System using LMI-based Sliding Mode Control

In this paper, stabilization of an Active Magnetic Bearing (AMB) system with varying rotor speed using Sliding Mode Control (SMC) technique is considered. The gyroscopic effect inherited in the system is proportional to rotor speed in which this nonlinearity effect causes high system instability as the rotor speed increases. Also, transformation of the AMB dynamic model into a new class of uncertain system shows that this gyroscopic effect lies in the mismatched part of the system matrix. Moreover, the current gain parameter is allowed to be varied in a known bound as an uncertainty in the input matrix. SMC design method is proposed in which the sufficient condition that guarantees the global exponential stability of the reduced-order system is represented in Linear Matrix Inequality (LMI). Then, a new chattering-free control law is established such that the system states are driven to reach the switching surface and stay on it thereafter. The performance of the controller applied to the AMB model is demonstrated through simulation works under various system conditions.

Optimizing of Fuzzy C-Means Clustering Algorithm Using GA

Fuzzy C-means Clustering algorithm (FCM) is a method that is frequently used in pattern recognition. It has the advantage of giving good modeling results in many cases, although, it is not capable of specifying the number of clusters by itself. In FCM algorithm most researchers fix weighting exponent (m) to a conventional value of 2 which might not be the appropriate for all applications. Consequently, the main objective of this paper is to use the subtractive clustering algorithm to provide the optimal number of clusters needed by FCM algorithm by optimizing the parameters of the subtractive clustering algorithm by an iterative search approach and then to find an optimal weighting exponent (m) for the FCM algorithm. In order to get an optimal number of clusters, the iterative search approach is used to find the optimal single-output Sugenotype Fuzzy Inference System (FIS) model by optimizing the parameters of the subtractive clustering algorithm that give minimum least square error between the actual data and the Sugeno fuzzy model. Once the number of clusters is optimized, then two approaches are proposed to optimize the weighting exponent (m) in the FCM algorithm, namely, the iterative search approach and the genetic algorithms. The above mentioned approach is tested on the generated data from the original function and optimal fuzzy models are obtained with minimum error between the real data and the obtained fuzzy models.

A Finite Volume Procedure on Unstructured Meshes for Fluid-Structure Interaction Problems

Flow through micro and mini channels requires relatively high driving pressure due to the large fluid pressure drop through these channels. Consequently the forces acting on the walls of the channel due to the fluid pressure are also large. Due to these forces there are displacement fields set up in the solid substrate containing the channels. If the movement of the substrate is constrained at some points, then stress fields are established in the substrate. On the other hand, if the deformation of the channel shape is sufficiently large then its effect on the fluid flow is important to be calculated. Such coupled fluid-solid systems form a class of problems known as fluidstructure interactions. In the present work a co-located finite volume discretization procedure on unstructured meshes is described for solving fluid-structure interaction type of problems. A linear elastic solid is assumed for which the effect of the channel deformation on the flow is neglected. Thus the governing equations for the fluid and the solid are decoupled and are solved separately. The procedure is validated by solving two benchmark problems, one from fluid mechanics and another from solid mechanics. A fluid-structure interaction problem of flow through a U-shaped channel embedded in a plate is solved.

Persistence of Termination for Term Rewriting Systems with Ordered Sorts

A property is persistent if for any many-sorted term rewriting system , has the property if and only if term rewriting system , which results from by omitting its sort information, has the property. Zantema showed that termination is persistent for term rewriting systems without collapsing or duplicating rules. In this paper, we show that the Zantema's result can be extended to term rewriting systems on ordered sorts, i.e., termination is persistent for term rewriting systems on ordered sorts without collapsing, decreasing or duplicating rules. Furthermore we give the example as application of this result. Also we obtain that completeness is persistent for this class of term rewriting systems.

Solving Fully Fuzzy Linear Systems by use of a Certain Decomposition of the Coefficient Matrix

In this paper, we give a certain decomposition of the coefficient matrix of the fully fuzzy linear system (FFLS) to obtain a simple algorithm for solving these systems. The new algorithm can solve FFLS in a smaller computing process. We will illustrate our method by solving some examples.

Proteomic Analysis of Tumor Tissue after Treatment with Ascorbic Acid

Tumor cells have an invasive and metastatic phenotype that is the main cause of death for cancer patients. Tumor establishment and penetration consists of a series of complex processes involving multiple changes in gene expression. In this study, intraperitoneal administration of a high concentration of ascorbic acid inhibited tumor establishment and decreased tumor mass in BALB/C mice implanted with S-180 sarcoma cancer cells. To identify proteins involved in the ascorbic acid-mediated inhibition of tumor progression, changes in the tumor proteome associated with ascorbic acid treatment of BALB/C mice implanted with S-180 were investigated using two-dimensional gel electrophoresis and mass spectrometry. Twenty protein spots were identified whose expression was different between control and ascorbic acid treatment groups.

Development of New Control Techniques for Vibration Isolation of Structures using Smart Materials

In this paper, the effects of the restoring force device on the response of a space frame structure resting on sliding type of bearing with a restoring force device is studied. The NS component of the El - Centro earthquake and harmonic ground acceleration is considered for earthquake excitation. The structure is modeled by considering six-degrees of freedom (three translations and three rotations) at each node. The sliding support is modeled as a fictitious spring with two horizontal degrees of freedom. The response quantities considered for the study are the top floor acceleration, base shear, bending moment and base displacement. It is concluded from the study that the displacement of the structure reduces by the use of the restoring force device. Also, the peak values of acceleration, bending moment and base shear also decreases. The simulation results show the effectiveness of the developed and proposed method.

A New Biologically Inspired Pattern Recognition Spproach for Face Recognition

This paper reports a new pattern recognition approach for face recognition. The biological model of light receptors - cones and rods in human eyes and the way they are associated with pattern vision in human vision forms the basis of this approach. The functional model is simulated using CWD and WPD. The paper also discusses the experiments performed for face recognition using the features extracted from images in the AT & T face database. Artificial Neural Network and k- Nearest Neighbour classifier algorithms are employed for the recognition purpose. A feature vector is formed for each of the face images in the database and recognition accuracies are computed and compared using the classifiers. Simulation results show that the proposed method outperforms traditional way of feature extraction methods prevailing for pattern recognition in terms of recognition accuracy for face images with pose and illumination variations.

Finite Element and Subspace Identification Approaches to Model Development of a Smart Acoustic Box with Experimental Verification

Two approaches for model development of a smart acoustic box are suggested in this paper: the finite element (FE) approach and the subspace identification. Both approaches result in a state-space model, which can be used for obtaining the frequency responses and for the controller design. In order to validate the developed FE model and to perform the subspace identification, an experimental set-up with the acoustic box and dSPACE system was used. Experimentally obtained frequency responses show good agreement with the frequency responses obtained from the FE model and from the identified model.

Concepts for Designing Low Power Wireless Sensor Network

Wireless sensor networks have been used in wide areas of application and become an attractive area for researchers in recent years. Because of the limited energy storage capability of sensor nodes, Energy consumption is one of the most challenging aspects of these networks and different strategies and protocols deals with this area. This paper presents general methods for designing low power wireless sensor network. Different sources of energy consumptions in these networks are discussed here and techniques for alleviating the consumption of energy are presented.

Self-evolving Artificial Immune System via Developing T and B Cell for Permutation Flow-shop Scheduling Problems

Artificial Immune System is applied as a Heuristic Algorithm for decades. Nevertheless, many of these applications took advantage of the benefit of this algorithm but seldom proposed approaches for enhancing the efficiency. In this paper, a Self-evolving Artificial Immune System is proposed via developing the T and B cell in Immune System and built a self-evolving mechanism for the complexities of different problems. In this research, it focuses on enhancing the efficiency of Clonal selection which is responsible for producing Affinities to resist the invading of Antigens. T and B cell are the main mechanisms for Clonal Selection to produce different combinations of Antibodies. Therefore, the development of T and B cell will influence the efficiency of Clonal Selection for searching better solution. Furthermore, for better cooperation of the two cells, a co-evolutional strategy is applied to coordinate for more effective productions of Antibodies. This work finally adopts Flow-shop scheduling instances in OR-library to validate the proposed algorithm.

Mobile Velocity Based Bidirectional Call Overflow Scheme in Hierarchical Cellular System

In the age of global communications, heterogeneous networks are seen to be the best choice of strategy to ensure continuous and uninterruptible services. This will allow mobile terminal to stay in connection even they are migrating into different segment coverage through the handoff process. With the increase of teletraffic demands in mobile cellular system, hierarchical cellular systems have been adopted extensively for more efficient channel utilization and better QoS (Quality of Service). This paper presents a bidirectional call overflow scheme between two layers of microcells and macrocells, where handoffs are decided by the velocity of mobile making the call. To ensure that handoff calls are given higher priorities, it is assumed that guard channels are assigned in both macrocells and microcells. A hysteresis value introduced in mobile velocity is used to allow mobile roam in the same cell if its velocity changes back within the set threshold values. By doing this the number of handoffs is reduced thereby reducing the processing overhead and enhancing the quality of service to the end user.

Experimental Study of Light Crude Oil-Water Emulsions

This paper made an attempt to investigate the problem associated with enhancement of emulsions of light crude oil-water recovery in an oil field of Algerian Sahara. Measurements were taken through experiments using RheoStress (RS600). Factors such as shear rate, temperature and light oil concentration on the viscosity behavior were considered. Experimental measurements were performed in terms of shear stress–shear rate, yield stress and flow index on mixture of light crude oil–water. The rheological behavior of emulsion showed Non-Newtonian shear thinning behavior (Herschel-Bulkley). The experiments done in the laboratory showed the stability of some water in light crude oil emulsions form during consolidate oil recovery process. To break the emulsion using additives may involve higher cost and could be very expensive. Therefore, further research should be directed to find solution of these problems that have been encountered.

Development of Autonomous Cable Inspection Robot for Nuclear Power Plant

The cables in a nuclear power plant are designed to be used for about 40 years in safe operation environment. However, the heat and radiation in the nuclear power plant causes the rapid performance deterioration of cables in nuclear vessels and heat exchangers, which requires cable lifetime estimation. The most accurate method of estimating the cable lifetime is to evaluate the cables in a laboratory. However, removing cables while the plant is operating is not allowed because of its safety and cost. In this paper, a robot system to estimate the cable lifetime in nuclear power plants is developed and tested. The developed robot system can calculate a modulus value to estimate the cable lifetime even when the nuclear power plant is in operation.

Mining Network Data for Intrusion Detection through Naïve Bayesian with Clustering

Network security attacks are the violation of information security policy that received much attention to the computational intelligence society in the last decades. Data mining has become a very useful technique for detecting network intrusions by extracting useful knowledge from large number of network data or logs. Naïve Bayesian classifier is one of the most popular data mining algorithm for classification, which provides an optimal way to predict the class of an unknown example. It has been tested that one set of probability derived from data is not good enough to have good classification rate. In this paper, we proposed a new learning algorithm for mining network logs to detect network intrusions through naïve Bayesian classifier, which first clusters the network logs into several groups based on similarity of logs, and then calculates the prior and conditional probabilities for each group of logs. For classifying a new log, the algorithm checks in which cluster the log belongs and then use that cluster-s probability set to classify the new log. We tested the performance of our proposed algorithm by employing KDD99 benchmark network intrusion detection dataset, and the experimental results proved that it improves detection rates as well as reduces false positives for different types of network intrusions.

Numerical Simulation of Interfacial Flow with Volume-Of-Fluid Method

In this article, various models of surface tension force (CSF, CSS and PCIL) for interfacial flows have been applied to dynamic case and the results were compared. We studied the Kelvin- Helmholtz instabilities, which are produced by shear at the interface between two fluids with different physical properties. The velocity inlet is defined as a sinusoidal perturbation. When gravity and surface tension are taking into account, we observe the development of the Instability for a critic value of the difference of velocity of the both fluids. The VOF Model enables to simulate Kelvin-Helmholtz Instability as dynamic case.

A Study on Flammability of Bio Oil Combustible Vapour Mixtures

Study of fire and explosion is very important mainly in oil and gas industries due to several accidents which have been reported in the past and present. In this work, we have investigated the flammability of bio oil vapour mixtures. This mixture may contribute to fire during the storage and transportation process. Bio oil sample derived from Palm Kernell shell was analysed using Gas Chromatography Mass Spectrometry (GC-MS) to examine the composition of the sample. Mole fractions of 12 selected components in the liquid phase were obtained from the GC-FID data and used to calculate mole fractions of components in the gas phase via modified Raoult-s law. Lower Flammability Limits (LFLs) and Upper Flammability Limits (UFLs) for individual components were obtained from published literature. However, stoichiometric concentration method was used to calculate the flammability limits of some components which their flammability limit values are not available in the literature. The LFL and UFL values for the mixture were calculated using the Le Chatelier equation. The LFLmix and UFLmix values were used to construct a flammability diagram and subsequently used to determine the flammability of the mixture. The findings of this study can be used to propose suitable inherently safer method to prevent the flammable mixture from occurring and to minimizing the loss of properties, business, and life due to fire accidents in bio oil productions.

Semisolid Structure and Parameters for A360 Aluminum Alloy Prepared by Mechanical Stirring

Semisolid metal processing uses solid–liquid slurries containing fine and globular solid particles uniformly distributed in a liquid matrix, which can be handled as a solid and flow like a liquid. In the recent years, many methods have been introduced for the production of semisolid slurries since it is scientifically sound and industrially viable with such preferred microstructures called thixotropic microstructures as feedstock materials. One such process that needs very low equipment investment and running costs is the cooling slope. In this research by using a mechanical stirrer slurry maker constructed by the authors, the effects of mechanical stirring parameters such as: stirring time, stirring temperature and stirring Speed on micro-structure and mechanical properties of A360 aluminum alloy in semi-solid forming, are investigated. It is determined that mold temperature and holding time of part in temperature of 580ºC have a great effect on micro-structure and mechanical properties(stirring temperature of 585ºC, stirring time of 20 minutes and stirring speed of 425 RPM). By optimizing the forming parameters, dendrite microstructure changes to globular and mechanical properties improves. This is because of breaking and globularzing dendrites of primary α-AL.

On the Mathematical Structure and Algorithmic Implementation of Biochemical Network Models

Modeling and simulation of biochemical reactions is of great interest in the context of system biology. The central dogma of this re-emerging area states that it is system dynamics and organizing principles of complex biological phenomena that give rise to functioning and function of cells. Cell functions, such as growth, division, differentiation and apoptosis are temporal processes, that can be understood if they are treated as dynamic systems. System biology focuses on an understanding of functional activity from a system-wide perspective and, consequently, it is defined by two hey questions: (i) how do the components within a cell interact, so as to bring about its structure and functioning? (ii) How do cells interact, so as to develop and maintain higher levels of organization and functions? In recent years, wet-lab biologists embraced mathematical modeling and simulation as two essential means toward answering the above questions. The credo of dynamics system theory is that the behavior of a biological system is given by the temporal evolution of its state. Our understanding of the time behavior of a biological system can be measured by the extent to which a simulation mimics the real behavior of that system. Deviations of a simulation indicate either limitations or errors in our knowledge. The aim of this paper is to summarize and review the main conceptual frameworks in which models of biochemical networks can be developed. In particular, we review the stochastic molecular modelling approaches, by reporting the principal conceptualizations suggested by A. A. Markov, P. Langevin, A. Fokker, M. Planck, D. T. Gillespie, N. G. van Kampfen, and recently by D. Wilkinson, O. Wolkenhauer, P. S. Jöberg and by the author.

Political Preconditions for National Values of the Kazakhstan Nation

Article is devoted to the problem of Kazakhstan people national values in the conditions of the Republic of Kazakhstan independence. Formation of ethnos national values is viewed as the mandatory constituent of this process in contemporary conditions. The article shows the dynamics of forming socialspiritual basis of Kazakhstan people-s national values. It depicts peculiarities of interethnic relations in poly-ethnic and multiconfessional Kazakhstan. The study reviews in every detail various directions of the state social policy development in the sphere of national values. It is aimed to consolidation of the society to achieve the shared objective, i.e. building democratic and civilized state. The author discloses peculiarities of ethnos national values development using specific sources. It is underlined that renewal and modernization of Kazakhstan society represents new stage in the national value development, and its typical feature is integration process based on peoples- friendship, cultural principles of interethnic communication.