Paper Title, Authors, Abstract (Issue 1, Volume 3, 2009)

Pages

Numerical Simulation of Indonesian Tsunami 2004 at Penang Island in Peninsular Malaysia Using a Nested Grid Model
Md. Fazlul Karim, Ahmad Izani M Ismail, Mohammed Ashaque Meah

Abstract: Nested grid modelling techniques are increasingly being recognized as methodologies to aid in multiscale modelling of a variety of atmospheric and oceanic phenomena. A nested grid model with a fine resolution is used to simulate the Indonesian tsunami of 2004 along the coastal belt of Penang Island. The basic primitive model is depth averaged shallow water equations. A fine mesh numerical scheme for the Peninsular Malaysia covering the region between 5?10/ to 5?35/N and 100? to 100?30/E to record fine orographical detail of the region of Penang Island has been nested into a coarse mesh scheme covering the region approximately between 2° N to 14° N and 91° E to 100.5° E which includes the source region of the Indonesian tsunami of 2004. The nesting is accomplished using a scheme Arakawa C staggered grid arrangement. The solutions are obtained for two categories: (a) coarse mesh solution, and (b) nested solution. A nested model is employed in which a coarse grid model is used to supply the open boundary conditions for a finer grid. The major features of the event 2004 along Penang have been successfully simulated by the nested model.
 

FCM & FPCM Algorithm Based on Unsupervised Mahalanobis Distances with Better Initial Values and Separable Criterion
Jeng-Ming Yih, Yuan-Horng Lin, Hsiang-Chuan Liu

Abstract: The fuzzy partition clustering algorithms are most based on Euclidean distance function, which can only be used to detect spherical structural clusters. Gustafson-Kessel (GK) clustering algorithm and Gath-Geva (GG) clustering algorithm, were developed to detect non-spherical structural clusters, but both of them based on semi-supervised Mahalanobis distance needed additional prior information. An improved Fuzzy CMean algorithm based on unsupervised Mahalanobis distance, FCM-M, was proposed by our previous work, but it didn’t consider the relationships between cluster centers in the objective function. In this paper, we proposed an improved Fuzzy C-Mean algorithm, FCM-MS, which is not only based on unsupervised Mahalanobis distance, but also considering the relationships between cluster centers, and the relationships between the center of all points and the cluster centers in the objective function, the singular and the initial values problems were also solved. Two real data sets was applied to prove that the performance of the FCMMS algorithm gave more accurate clustering results than the FCM and FCM-M methods, and the ratio method which is proposed by us is the better of the two methods for selecting the initial values.
 

The Transmission Model of P.falciparum and P.Vivax Malaria between Thai and Burmese
P. Pongsumpun, I. M. Tang

Abstract: The transmission of Plasmodium falciparum and Plasmodium vivax malaria of Thais and Burmese is studied through a mathematical model. The population is separated into two groups, Thai and Burmese. Each population is divided into susceptible and infectious subclasses. The loss of immunity by individuals in the infectious class causes them to move back into the susceptible class. Standard dynamical method is used to analyze the behavior of the model. Two stable equilibrium states, a disease free state and an epidemic state are found to be possible in each population. A disease free equilibrium state in the Thai population occurs when there are no infected Burmese entering into the community. When there are infected Burmese enters into the Thai community, the epidemic state can occur. It is found that the disease free state is stable when the threshold number R0 is less than one. The epidemic state is stable when (where these threshold numbers are for the individual populations) are greater than one. The numerical simulations of our model illustrate what the results would be for our theoretical model.
 

The Influence of Noise Kurtosis on the Dynamics of a Harmonic Oscillator with Fluctuating Frequency
Katrin Laas, Romi Mankin, Astrid Rekker

Abstract: The influence of noise kurtosis on underdamped motion of a harmonic oscillator with fluctuating frequency subjected to an external periodic force and an additive thermal noise is considered. The colored fluctuations of the oscillator frequency are modeled as a trichotomous noise. It is established that the spectral amplification and variance of the output signal exhibits a nonmonotonic dependence on the noise kurtosis, thus demonstrating the phenomenon of noise kurtosis controlled stochastic resonance. Some unexpected effects such as hypersensitive response of spectral amplification to small variations of noise amplitude, encountered in the case of a large kurtosis of colored noise are also discussed.
 

Computer-Aided Simulation on the Reversing Operation of the Two-Phase Induction Machine
Alecsandru Simion, Leonard Livadaru, Dorin Lucache

Abstract: The paper presents a new mathematical model of the two-phase induction machine, called "in total fluxes", which is very appropriate for the study of the reversing regime. The equations of the model use as main quantities the rotation angle and the total fluxes of the windings and exclude the rotation speed, which now become a secondary quantity that can be calculated from rotation angle expression. On the basis of this model, the computer simulation looks into the behavior of a two-phase induction servomotor with low inertia when the supply voltages of the two separate windings have the same magnitude but a different frequency, under load and no load operation. The reversing regime is also simulated under unbalanced supply conditions. The results offer the perspective to design electromechanical systems with speed or rotation angle expressed as harmonic, quasi-harmonic or even random variation laws.
 

The Methods of Multi Attribute Analysis in Application to Assess Optimal Factor Combination in One Experiment
D. Randjelovic, C. Dolicanin

Abstract: Experiments are used by scientists to affirm their hypothesis, these experiments are called tests in research, or to choose the best from available possibilities, these experiments are called valuations in research in which group belongs also optimal factor combination choice in one multifactor and often multivariate experiments. For decreasing influence ever present uncontrolled factors i.e. experimental error researchers make different plans. Mathematical instruments of most effective plans for experiment organization are possible to search on the basis of total random distribution, random block distribution and some special organized block distribution while they can most effectively represent complex multifactor and multivariate experiments. Statistic analysis for any experiment plan is very complex in the standard way with analysis of variance and multiple linear regression and especially in the case of the optimal factor combination choice. From other side multiple criteria analysis like modern science discipline enables an easier way to make analysis of results of one experiment just in the case of optimal factor combination choice of one multifactor and multivariate experiment. Therefore authors propose multiple criteria analysis application in analysis of experiment results and in this paper authors consider application of one subgroup of these methods, so called multi attribute decision methods, to which belong and ELECTRA method. One example of multiple attribute analysis application in analysis of results of one experiment is given in the end of this paper.
 

Efficient Mixing in Microchannel by using Magnetic Nanoparticles
T. N. Le, Y. K. Suh, S. Kang

Abstract: Rapid and efficient mixing in microchannel using magnetic nanoparticles has been numerically investigated. The magnetic nanoparticles are introduced into the microchannel and are exerted by the external magnetic force to cause the vortex motion of the fluid for mixing. The velocity field of the flow and trajectories of the particles are solved implicitly by using the Finite Volume Method (FVM). The obtained results illustrate the significant effects of the magnetic actuation force, the switching frequency, number of magnetic nanoparticles on the mixing efficiency. The mixing properties of the flow predicted by numerical simulation are studied under the concentration field, mixing index and Poincare section.
 

Excitation Control of Self Excited Induction Generator using Genetic Algorithm and Artificial Neural Network
Dheeraj Joshi, K. S. Sandhu

Abstract: Induction generators which may be operated in grid or self-excited mode, are found to be successful machines for wind energy conversion. Out of these two self-excited mode is gaining importance due to its ability to convert the wind energy into electrical energy for large variations in operating speed. However it has been found that these machine exhibits a poor voltage regulation. Steady-state analysis of self excited induction generator reveals that such generators are not capable to maintain the terminal voltage and frequency in the absence of expensive controllers. In turn addition of such controllers may result into a fall in popularity of this machine due to its simplicity. Another simple way to control the terminal voltage is through excitation control using series compensation. In this paper artificial intelligent techniques are used to model the control strategy for proper reactive compensation under different operating conditions. Genetic algorithm along with artificial neural network has been proposed to estimate the values of shunt and series excitation capacitance to maintain the terminal and load voltage. Simulated results as found using proposed control technique are verified using experimental results on a test machine. Simulated results are found to be in close agreement with experimental results.
 

    Paper Title, Authors, Abstract (Issue 2, Volume 3, 2009)

Pages

Estimate to the Trajectory of Maneuvering Targets by Combining Sensor Scheduling with Energy Efficient in WSNs
Joy Iong-Zong Chen, Chih-Chung Yu

Abstract: An algorithm by combining sensor scheduling with energy efficient for tracking the maneuvering targets with mobile sensor deployed in WSNs (wireless sensor networks) is proposed to investigate the tracking performance in the article. In order to minimize the estimated error, the sensor sequence and the optimal sensor movement are scheduled previously and determined first. Thus, the sensor scheduling is depending on the results from the evaluation of energy efficient of a sensor node. Moreover, due to the targets is varying with time in the estimation process the EKF (extended Kalman filtering) technique is applied to predict MSE (mean square error) of a predicted target. Finally, simulations by using of the scenario with two and four maneuvering targets tracking are held to validate the accuracy of the proposed algorithm, and the results definitely show the fact that the MSE will decrease when the right way of the sensor scheduling is arranged previously.
 

Time Series Modeling using an Adaptive Gene Expression Programming Algorithm
Alina Barbulescu, Elena Bautu

Abstract: Meteorological time series are characterized by important spatial and temporal variation. Model determination and the prediction of evolution of such series is of high importance for different practical purposes, even if discovering evolution patterns in such series is a very difficult problem. In this article we describe an adaptive evolutionary technique and we apply it for modeling the precipitation and temperatures collected in a region of Romania. The results are promising for the analysis of such time series.
 

A Multi-Item Production Lot Size Inventory Model with Cycle Dependent Parameters
Zaid T. Balkhi, Abdelaziz Foul

Abstract: In this paper, a multi-item production inventory model is considered within a given time horizon that consists of different time periods. For each product, production, demand, and deterioration rates in each period are known. Shortage for each product is allowed but it is completely backlogged . The objective is to find the optimal production and restarting times for each product in each period so that the overall total inventory cost for all products is minimized. In this paper, a formulation of the problem is developed and optimization techniques are performed to show uniqueness and global optimality of the solution.
 

Stochastic Geolithological Reconstruction coupled with Artificial Neural Networks Approach for Hydrogeological Modeling
Claudia Cherubini, Fausta Musci, Nicola Pastore

Abstract: When simulating fluid flow and solute transport a more accurate modeling of the lithologic, geological and structural characters of an aquifer is of extreme importance in order to improve the reliability of the numerical simulations. On the other hand the information available for the setting up of a hydrogeological model is subjected to ambiguities due to not univocal interpretations or to uncertainties linked to the methodologies of measurement of the variables of interest. Therefore, hydrogeological characterization of heterogeneous aquifers, if carried out up to a high degree of detail, should not identify a univocal model but a set of “equifinal” solutions. In the present paper the application of Artificial Neural Network approach coupled with a Nested Sequential Indicator simulation has allowed to obtain the distribution of hydrogeologic parameters that are not only conditioned by the in situ measured values but also by the soft information coming from geolithology. The results show a fairly good relationship between parameters such as Transmissivity and Storage coefficient and the geolithologic architecture of the examined aquifer.
 

Formal Transformation from NFA to Z Notation by Constructing Union of Regular Languages
Nazir Ahmad Zafar, Nabeel Sabir, Amir Ali

Abstract: Capturing functionalities and modeling control behavior are primary requirements in design and development of a complex system. Automata theory plays a vital role in modeling behavior while Z notation is an ideal specification language for describing state space of a system. Consequently, integration of automata and Z notation will be a useful tool facilitating and increasing modeling power for complex systems. Further, nondeterministic finite automata (NFA) may have different implementations and therefore it is needed to verify the transformation from diagrams to code. If we describe formal specification of a given nondeterministic finite automata before implementing then confidence over transformation can be increased. In this paper, we have combined NFA and Z and a linkage is established between these approaches. At this level of integration, we have given a formal procedure to transform NFA to Z. A string accepter is designed and then extended to the language accepter. Finally, NFA accepting union of two regular languages is constructed by describing formal specification of their relationships. The specification is analyzed and validated using Z/EVES tool.
 

Identification of the De-synchronization, Synchronization and Forced Oscillation Phenomenon of a Nonlinear System
Marius-Constantin O.S. Popescu, Onisifor V. Olaru, Valentina E. Balas

Abstract: The phenomena of de-synchronization, synchronization, and forced oscillation has been investigation using describing function theory for a two input and two output nonlinear system containing saturation-type nonlinearities and subjected to high-frequency deterministic signal for the purpose of limit cycle quenching. The analytical results have been compared with the results of digital simulation Matlab-Simulink for a typical example varying the nonlinear element.
 

Equilibrium Dynamic Systems Intelligence
Marius-Constantin O.S. Popescu, Onisifor V. Olaru, Nikos E. Mastorakis

Abstract: Most work in Artificial Intelligence reviews the balance of classic game theory to predict agent behavior in different positions. In this paper we introduce steady competitive analysis. This approach bridges the gap between the standards of desired paths of artificial intelligence, where a strategy must be selected in order to ensure an end result and a balanced analysis. We show that a strategy without risk level is able to guarantee the value obtained in the Nash equilibrium, by more scientific methods of classical computers. Then we will discuss the concept of competitive strategy and illustrate how it is used in a decentralized load balanced position, typical for network problems. In particular, we will show that when there are many agents, it is possible to guarantee an expected final result, which is a 8/9 factor of the final result obtained in the Nash equilibrium. Finally, we will discuss about extending the above concept in Bayesian game and illustrate its use in a basic structure of an auction.
 

Suggestions of Nanotechnology Park and Observations on Industrial Challenges
Ahmet Karakas

Abstract: This study aims to clarify the establishment of the Nanotechnology Park in South Wales .The feasibility is observed through a survey, and reliability of the survey participants is justified with question structures. As the idea is a unique concept, the survey outcome is analyzed together with recent research and it is aimed to fill the gap in the field. Due to the nature of nanotechnology organizations, the challenges of the industry as well as the researchers are observed. Financial and organizational difficulties of the start-up companies are observed, including the constraints of the industry and research institutions. The outline and proposed issues to be considered are addressed for a nanotechnology park. Multi-disciplined field structure is observed and criticized with the current applications. Further research recommendations are pointed out through finalizing this study.
 

Checking Simulations of a Geolithological Model Obtained by Means of Nested Truncated Bigaussian Method
Claudia Cherubini, Fausta Musci, Nicola Pastore

Abstract: Characterizing the spatial distribution of major lithotypes and their relationships is a key aspect in the process of hydrogeological modeling of aquifers in that assignment of lithotypes-specific hydraulic and hydrochemical properties requires the knowledge of the layout of the lithotypes themselves. Truncated bigaussian simulation is a procedure derived from the truncated Gaussian model, used to simulate random sets, and, in particular, variable geological characteristics, expressed as categorical variables. Anyway, in cases of many lithotypes having not homogeneous spatial behaviors, this methodology might not explain at best the relations existing among the lithotypes themselves; a more general method is therefore required to represent this variability. In this paper, that concerns a site whose geologic asset has already been reconstructed, in order to better characterize the aquifer geolithological architecture, nested simulation for a macro-unit of the previously realized geolithologic model has been carried out, together with a check phase of the results obtained by the mentioned simulation. The proposed methodology can represent a useful instrument for the modeling of complex geological layouts other than in the detailed characterizations of hydrogeological studies, for a better interpretation of the complex phenomena that take place in groundwater circulation and contaminant propagation.
 

A Simulation Study of Additive Outlier in ARMA (1, 1) Model
Azami Zaharim, Rafizah Rajali, Raden Mohamad Atok, Ibrahim Mohamed, Khamisah Jafar

Abstract: Abnormal observation due to an isolated incident such as a recording error is known as additive outlier and it is often found in time series. Since extreme value of additive outliers may contribute to the inaccuracy of model specification, proper detection procedure is significant to avoid such error. Equations that explain the nature of an additive outlier and the test statistics pertaining to it are discussed in this article. This is followed by two separate simulation studies that are conducted to investigate the sampling behavior and detection performance of the test statistics in ARMA (1, 1) models. Results for the first simulation study show that the test statistics is an increasing function of sample size. Whilst in the other simulation study we see that the performance of the test statistics improves as large magnitudes of outlier effect are used.
 

    Paper Title, Authors, Abstract (Issue 3, Volume 3, 2009)

Pages

Short Term Electricity Load Demand Forecasting in Indonesia by Using Double Seasonal Recurrent Neural Networks
Suhartono, Alfonsus Julanto Endharta

Abstract: Neural networks have apparently enjoyed con-siderable success in practice for predicting short-term hourly electricity demands in many countries. Forecasting of short-term hourly electricity in some countries usually is done by employing classical time series methods such as Winter’s method and Double Seasonal ARIMA model. Recently, Feed-Forward Neural Net-works (FFNN) is also applied for electricity demand forecasting, including in Indonesia. The application of Double Seasonal ARIMA for forecasting short-term electricity load demands in most cities in Indonesia shows that the model contains both order of autoregressive and moving average. Moving average order can not be represented by FFNN. In this paper, we use an architecture of Neural Network that able to represent moving average order, i.e. Elman-Recurrent Neural Network (RNN). As a case study, we use data of hourly electricity load demand in Mengare, Gresik, Indo-nesia. The results show that the best ARIMA model for forecasting these data is ARIMA ([1,2,3,4,6,7,9,10,14,21,33],1,8)(0,1,1)24(1, 1,0)168. There are 14 innovational outliers detected from this ARIMA model. We use 4 different architectures of RNN particu-larly for the inputs, i.e. the input units are similar to ARIMA model predictors, similar to ARIMA predictors plus 14 dummy outliers, the 24 multiplied lagged of the data, and the combination of 1 lagged and the 24 multiplied lagged plus minus 1. The results show that the best network is the last one, i.e., Elman-RNN(22,3,1). The comparison of forecast accuracy shows that Elman-RNN yields less MAPE than ARIMA model. Thus, Elman-RNN(22,3,1) is the best method for forecasting hourly electricity load demands in Mengare, Gresik, Indonesia.
 

A Handling Management System for Freight with the Ambient Calculus
Toru Kato, Masahiro Higuchi

Abstract: This paper proposes a freight management system that ensures the correctness of container handling during shipping. The system determines the correctness by comparing container handling, which is sensed by IC tags, with formal models (formulae) written in the ambient calculus. The ambient calculus is a formal description language that is suitable for expressing freight systems with nested structures that dynamically change. The management system generates formulae automatically from several documents used in real freight systems. An implementation of the system and the results of a simple experiment using it are presented.
 

A General and Dynamic Production Lot Size Inventory Model
Zaid T. Balkhi, Ali S. Haj Bakry

Abstract: A dynamic inventory model with deteriorating items in which each of the production ,the demand and the deterioration rates, as well as all cost parameters are assumed to be general functions of time is considered in this paper. Besides, shortages are allowed but are partially backordered. . Both inflation and time value of money are taken into account. The objective is to minimize the total net inventory cost . The relevant model is built , solved Necessary and sufficient conditions for a unique and global optimal solution are derived. An illustrative example is provided and numerically verified.
 

Monitoring and Control System of a Separation Column for 13C Enrichment by Cryogenic Distillation of Carbon Monoxide
Eva-Henrietta Dulf, Clement Festila, Francisc Dulf

Abstract: In incipient stage for laboratory experiments, a monitoring and control based on human operators is usual. Using the acquired experience, a computer monitoring and even control is necessary and possible. In the actual developing plan to apply the cryogenic technology for the production of the 13C isotope by industrial scale, an efficient and safe operation is a strong reason to conceive and to apply a modern computer based monitoring and control strategy. The actual hardware possibilities of the computer systems and valuable interfaces enable cheap, easy-to-apply and efficient monitoring and control systems. For a complex equipment like a cryogenic isotope separation column, it was selected a common PC interfaced with a series of robust input-output modules, ICP-CON, I-7000 Series, from ICP-DAS as data acquisition and control functions. Based on general separation process and column operation descriptions, this particular application is developed using the intuitive Labview visual programming language. The front panel of the monitoring system has numerical and graphical indicators, buttons for available options, alarms to warn the user that a problem appeared in the process. The control system is conceived for the liquid nitrogen level control and the liquid carbon monoxide level control. In the actual stage, the control functions are analyzed only by simulation.
 

The Proposed Fuzzy Logic Navigation Approach of Autonomous Mobile Robots in Unknown Environments
O. Hachour

Abstract: In this paper we discuss the ability to deal with a fuzzy logic navigation approach for intelligent autonomous mobile robots in unknown environments. The aim of this work is to develop hybrid intelligent system combining Fuzzy Logic (FL) and Expert System (ES). This combination provides the robot the possibility to move from the initial position to the final position (target) without collisions. This combination is necessary to bring the machine behaviour near the human one in reasoning, decision-making and action. That was the current reason to replace the classical approaches related to navigation problems by the current approaches based on the fuzzy logic and expert system. The robot moves within the environment by sensing and avoiding the obstacles coming across its way towards the unknown target. The focus is on the ability to move and on being self-sufficient to evolve in an unknown environment. The proposed hybrid navigation strategy is designed in a grid-map form of an unknown environment with static unknown obstacles. This approach must make the robot able to achieve these tasks: to avoid obstacles, and to make ones way toward its target by ES_FL system capturing the behavior of a human expert. The integration of ES and FL has proven to be a way to develop useful real-world applications, and hybrid systems involving robust adaptive control. The proposed approach has the advantage of being generic and can be changed at the user demand. The results are satisfactory to see the great number of environments treated. The results are satisfactory and promising.
 

Nonlinear Spatiotemporal Analysis and Modeling of Signal Transduction Pathways Involving G Protein Coupled Receptors
Chontita Rattanakul, Titiwat Sungkaworn , Yongwimon Lenbury, Meechoke Chudoung, Varanuj Chatsudthipong, Wannapong Triampo, Boriboon Novaprateep

Abstract: Cell behavior and communication are regulated by a complex network of intracellular and extracellular signal transduction pathways. In this paper, a model of signaling process involving G proteins is analyzed. The model incorporates reaction-diffusion mechanisms involving reactants that interact with each other on the cellular membrane surface and its proximity. The ligand-receptor complexes and the inhibiting agents in the process may diffuse over the cell membrane, and the signal transduction is mediated by the membrane bound G protein leading to biochemical intra-cellular reaction and the production of the second messenger or other desired functional responses. Weakly nonlinear stability analysis is carried out in order to investigate the dynamic and steady-state properties of the model. Turing-type patterns are shown to robustly form under conditions on the system parameters which characterize the formation of stationary symmetry breaking structures; stripes and hexagonal arrays of spots or nets. Some recent experimental studies are then mentioned in support of our theoretical predictions.
 

Evaluating a Maintenance Department in a Service Company
Mª C. Carnero

Abstract: Maintenance has evolved from a tactical subject to being considered a strategic one due to its implications in availability, safety, quality and costs. Once maintenance policies have been set-up, different factors must be controlled so that the appearance and development of deficiencies in the maintenance department can be detected; for this purpose an evaluating maintenance process is developed in this paper by means of an additive model constructed by Hiview software. The audit is applied to a hospital where these areas are especially relevant as a result of their direct influence on the quality of the patients/ welfare service.
 

Adaptation of a k-epsilon Model to a Cartesian Grid Based Methodology
Stephen M. Ruffin, Jae-Doo Lee

Abstract: Despite the high cost of memory and CPU time required to resolve the boundary layer, a viscous unstructured grid solver has many advantages over a structured grid solver such as the convenience in automated grid generation and vortex capturing by solution adaption. In present study, an unstructured Cartesian grid solver is developed on the basis of the existing viscous solver, NASCART-GT. Instead of a cut-cell approach, an immersed boundary approach is applied with ghost cell boundary condition, which can be easily applied to a moving grid solver. The standard k-e model by Launder and Spalding is employed for the turbulence modeling, and a new wall function approach is devised for the unstructured Cartesian grid solver. In this study, the methodology is validated and the efficiency of the developed boundary condition is tested in 2-D flow field around a flat plate, NACA0012 airfoil, and axisymmetric hemispheroid.
 

Rotorcraft Flowfield Prediction Accuracy and Efficiency using a Cartesian Grid Framework
Stephen M. Ruffin, Jae-Doo Lee

Abstract: Despite the high cost of memory and CPU time required to resolve the boundary layer, a viscous unstructured grid solver has many advantages over a structured grid solver such as the convenience in automated grid generation and shock or vortex capturing by solution adaption. In present study, an unstructured Cartesian grid solver is applied and results evaluated in rotorcraft flowfields. Recently, an existing solver, NASCART-GT was modified to use an immersed boundary approach (instead of a cut-cell approach). This approach is applied with ghost cell boundary condition, which increases the accuracy and minimizes unphysical fluctuations of the flow properties. The standard k-epsilon model by Launder and Spalding is employed for the turbulence modeling, and a new wall function was incorporated for the unstructured Cartesian grid solver. This model was previously only validated for 2-D flows, but in the present paper is applied to 3-D rotorcraft flowfields. For rotor modeling, an actuator disk model is chosen, since it is efficient and is widely verified in the study of the rotor-fuselage interaction. The full three dimensional calculations of Euler and RANS equations are performed for the GT rotor model and ROBIN configuration to test implemented actuator disk model along with the developed turbulence modeling.
 

A Distributed Algorithm for XOR-Decompression with Stimulus Fragment Move to Reduce Chip Testing Costs
Mohammed Almulla, Ozgur Sinanoglu

Abstract: Various techniques were used to reduce the test time and cost of chip development, some of which achieved their objective by reducing the test data volume through the implementation of compression technologies such as XOR-based decompressors. In the presence of XOR decompressor, the delivery of acceptable (encodable) test patterns can be challenging. To overcome this problem, the Align-Encode technique was introduced to manipulate the distribution of care bits in the test pattern in aim to increase the delivery of more encodable test patterns. The implementation of the Align-Encode algorithm proved that this algorithm suffers a major drawback when applied on large test patterns. In this paper, we propose a distributed algorithm for realizing the Align-Encode objectives but for large scale problems. This algorithm is designed to run on a scalable distributed environment. Moreover, it exploits the nature of the problem in order to make significant improvements in performance with respect to chip testing time as well as the number of encodable test patterns generated, which reflects positively on the cost of chip development and in test data compression as a result.
 

The Effect of some Physical and Geometrical Parameters on Improvement of the Impact Response of Smart Composite Structures
F. Ashenai Ghasemi, A. Shokuhfar, S. M. R. Khalili, G. H. Payganeh, K. Malekzadeh

Abstract: This article presents a complete analytical model to study the role of the shape memory alloys (SMAs) on improvement the impact response of the smart composite structures. The role of some physical and geometrical parameters such as the volume fraction, the orientation and the location of the SMA wires on the contact force history, the deflection, the in-plane strains and stresses of the structures is investigated in details. Also the effect of density of the impactor to the plate ratio and the elastic modulus of the impactor to the plate ratio on the contact force history and the deflection of the plate is studied. The first order shear deformation theory as well as the Fourier series method was utilized to solve the governing equations of the composite plate analytically. The interaction between the impactor and the plate was modeled with the help of two degrees of freedom system consisting of springs-masses. The Choi's linearized contact model was used in the analysis. The results of the above research indicated that the use of the SMA wires inside the smart composite structures improve the global behavior of the structure against the impact. The smart composite structures damp more uniformly and rapidly after the impact.
 

Transmission Network Dynamics of Plasmodium Vivax Malaria
P. Pongsumpun, I. M. Tang

Abstract: One of the top ten killer diseases in the world is Malaria. In each year, there are between 300 to 500 million clinical episodes of malaria and 1.5 to 2.7 million deaths worldwide. The malaria disease is caused by the multiplication of protozoa parasite of the genus Plasmodium. Malaria in humans is due to 4 types of malaria parasites such that Plasmodium falciparum, Plasmodium vivax, Plasmodium malariae and Plasmodium ovale. P.vivax malaria differs from P. falciparum malaria in that a person suffering from P. vivax malaria can experience relapses of the disease. Between the relapses, the malaria parasite will remain dormant in the liver of the patient, leading to the patient being classified as being in the dormant class. In this paper, the dynamical model of P. vivax malaria is formulated to see the network distribution of this disease.
 

Mathematical Model of Plasmodium Vivax and Plasmodium Falciparum Malaria
P. Pongsumpun, I. M. Tang

Abstract: Malaria is transmitted to the person by the biting of infectious Anopheles mosquitoes. This infectious disease caused by the parasite genus Plasmodium. Four species of this parasite cause human malaria, namely, Plasmodium vivax, Plasmodium falciparum, Plasmodium ovale and Plasmodium malariae. The difference between P.vivax and P. falciparum is that a person suffering from P. vivax infection can suffer relapses of the disease. This is due the parasite being able to remain dormant in the liver of the cases where it is able to re-infect the case after a passage of time. During this stage, the case is classified as being in the dormant class. The model to describe the transmission between falciparum and vivax malaria consists of a human population divided into four classes, the susceptible, the infectious, the dormant and the recovered classes. The vector population is separated into two classes, the susceptible and infectious classes. We analyze our model by using standard dynamic modeling method. Two stable equilibrium states, a disease free state E0 and an endemic state E1, are found to be possible. It is found that the E0 state is stable when a basic reproductive number R0 is less than one. If R0 is greater than one, the endemic state E1 is stable. The conditions for the local stability of each equilibrium state are established. The numerical simulations are shown to confirm the results.
 

Practical Approaches for the Design of an Agricultural Machine
Zhiying Zhu, Toshio Eisaka

Abstract: The precision agriculture has been progressing rapidly to improve the efficiency of operation with the quality and consistency of products. Intelligent machines with high-tech sensors have been developed exploiting information technology and getting widely used. On most of farms, however, there still works simple inexpensive agricultural machines. From cost saving and sustainable development point of view, utilization of existing facilities can be significant alternative strategy. In this paper, we propose two design methods to improve an existing agricultural machine. One is modifying relevant structural parameters of the existing machine by numerical optimization. The other is appending an actuator and a controller to a machine and then employing simultaneous optimization of both controller and machine parameters. We also compared their performance and robustness.
 

Dynamic of Electrical Drive Systems with Heating Consideration
Boteanu Niculae, Popescu Marius-Constantin, Manolea Gheorghe, Anca Petrisor

Abstract: In this paper it is considered an electric drive with static torque with constant component and speed proportional component. Using the classic calculus of variations is determined the extremal control and trajectory and the overheating that ensures maximum exploitation of the system resources represented by the achievement of a maximum variation of speed in the acceleration processes
 

H-infinity Approach Control for Regulation of Active Car Suspension
Jamal Ezzine, Francesco Tedesco

Abstract: There are many types of car suspensions control. H1 control of vehicle suspension is studied in the literature for a brave time ago. We can define active suspensions as control systems incorporating a parallel spring and an electronically controlled damper. The contribution of this paper relies on H1 control design to improve comfort and road holding of the car, and on control validation through simulation on an quarter Car and Half Car model with seat-passengers of the suspensions system. In this paper an H1 controller is designed for a actuated active suspension system of a quarter-modelled and half-modelled with seat-passengers vehicle in a cascade feedback structure. In this paper we will make a comparison between application of quarter car and half car model. In the framework of Linear Matrix Inequality (LMI) optimization, constrained H1 active suspensions are designed on half-car models.
 

    Paper Title, Authors, Abstract (Issue 4, Volume 3, 2009)

Pages

Redefining Chaos: Devaney-Chaos for Piecewise Continuous Dynamical Systems
Byungik Kahng

Abstract: One of the most widely accepted definition of chaos is the one by Devaney, which we will call Devaney-chaos. The purpose of our research is to investigate how the first two characteristic properties of Devaney-chaos are affected by the presence of the discontinuity, and subsequently, what kind of adjustments must be made to improve Devaney-chaos so that it can be applied to discontinuous dynamical systems as well as continuous systems. Under the aforementioned adjustments, we prove that the first two adjusted conditions of Devaney-chaos can be successfully used to characterize the complex orbit-behavior of piecewise continuous dynamical systems. Also, we show that the straightforward application of unadjusted Devaney-chaos is too inclusive when the system is discontinuous, consequently necessitating the afore-mentioned adjustments. We use the classification theorems of the singularities of the invertible planar piecewise isometric dynamical systems as the main tools.
 

Fuzzy Logic Control System Modelling
Jelenka B.Savkovic-Stevanovic

Abstract: In this paper fuzzy logic theory was studied and applied to the process control system. The paper presents an intelligent control system design. In order to perform the state prediction necessary to the fuzzy logic controller the system was developed based on input/output data. The investigation was performed by simulation. As a case study a distillation packed column was investigated. The controller has been based on the process inverse dynamic control. An advanced fuzzy control model was derived. The dynamic response has been applied to predict and control the distillate composition and distillate flow rate to feed flow rate and feed composition disturbance. The obtained results show improving products quality control, determine optimum set points, and a troubleshooting day to day operating problem.
 

Investigating the Heterodimerization Process Among Receptors by Monte Carlo Cellular Automaton Simulation
A. Wisitsorasak, W. Triampo, D. Triampo, C. Modchang, Y. Lenbury

Abstract: It has become well known that simulation can be used to investigate complex biomedical systems in situations where traditional methodologies are difficult or too costly to be used. In this paper, Monte Carlo cellular automaton simulation is employed to study heterodimerization of receptor proteins. A computer program, based on a simple random walk of receptor molecules over a fixed lattice, has been written to simulate the diffusion and association of receptors over a two-dimensional membrane. The interaction and dynamics of these particles is in the form of the lattice Hamiltonian. The formation of two-dimensional clusters of receptors in a defined area of surface membrane is investigated. In particular, we measure the number of dimers throughout the dynamics and try to define the power law that governs the process.
 

Modelling of Oil-filled Transformer
Marius-Constantin O. S. Popescu, Nikos E. Mastorakis, Liliana N. Popescu-Perescu

Abstract: The purpose of this article is to analyse the tansformer thermal and loss of life models will be studied. Based on the thermal model adopted by International Standards, small improvements to increase model accuracy are presented and a comparative study of resulted accuracy under different load and ambient temperature profiles is performed.
 

Applications of Genetic Algorithms in Electrical Engineering
Marius-Constantin O. S. Popescu, Nikos E. Mastorakis, Liliana Popescu-Perescu

Abstract: In this paper were presented the main directions of genetic algorithms. There is a large class of interesting problems that have not yet been developed fast algorithms. Many of these problems are problems which occur frequently optimized in applications. The studies of this work will allow us to compare the results from different methods of determining these parameters and especially those based on genetic algorithms.
 

Design of a Configurable All Terrain Mobile Robot Platform
Gokhan Bayar, A. Bugra Koku, E. Ilhan Konukseven

Abstract: With the increased funding from various agencies, research conducted in the field of mobile robotics has significantly increased during the last couple of decades. Due to wide range of applications mobile robots of different sizes and capabilities are required in the field. Despite the wide spectrum of applications to be developed for mobile robots, available platforms on the market for research purposes are very few in number, and limited in their capability for multi-purpose use. Evidently purchasing new platforms for different applications is not a feasible solution for conducting research. Driven by the motive of having a configurable research platform, a mobile robot referred to as CoMoRAT (Configurable Mobile Robot for All Terrain Applications) has been designed and manufactured at METU. CoMoRAT can be driven by wheels, tracks or both. Besides its ability to ride effectively on various terrains, robot body is designed in such a way that adding new hardware to the platform requires minimal manufacturing and installation effort. This paper presents the design and construction details as well as the performance tests conducted on CoMoRAT.