Search results for: Parameter linear programming

Authors: Yeong-Hwa Chang, Chia-Wen Chang, Hung-Wei Lin, C.W. Tao

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In this paper, an improved ant colony optimization (ACO) algorithm is proposed to enhance the performance of global optimum search. The strategy of the proposed algorithm has the capability of fuzzy pheromone updating, adaptive parameter tuning, and mechanism resetting. The proposed method is utilized to tune the parameters of the fuzzy controller for a real beam and ball system. Simulation and experimental results indicate that better performance can be achieved compared to the conventional ACO algorithms in the aspect of convergence speed and accuracy.

Keywords: Ant colony algorithm, Fuzzy control, ball and beamsystem

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Authors: Jörg Linde, Ekaterina Buyko, Robert Altwasser, Udo Hahn, Reinhard Guthke

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Reverse engineering of full-genomic interaction networks based on compendia of expression data has been successfully applied for a number of model organisms. This study adapts these approaches for an important non-model organism: The major human fungal pathogen Candida albicans. During the infection process, the pathogen can adapt to a wide range of environmental niches and reversibly changes its growth form. Given the importance of these processes, it is important to know how they are regulated. This study presents a reverse engineering strategy able to infer fullgenomic interaction networks for C. albicans based on a linear regression, utilizing the sparseness criterion (LASSO). To overcome the limited amount of expression data and small number of known interactions, we utilize different prior-knowledge sources guiding the network inference to a knowledge driven solution. Since, no database of known interactions for C. albicans exists, we use a textmining system which utilizes full-text research papers to identify known regulatory interactions. By comparing with these known regulatory interactions, we find an optimal value for global modelling parameters weighting the influence of the sparseness criterion and the prior-knowledge. Furthermore, we show that soft integration of prior-knowledge additionally improves the performance. Finally, we compare the performance of our approach to state of the art network inference approaches.

Keywords: Pathogen, network inference, text-mining, Candida albicans, LASSO, mutual information, reverse engineering, linear regression, modelling.

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Authors: Mauricio Pe˜na, Adriana Luna, Carol Rodr´ıguez

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In the following article we begin from a multi-parameter unstable nonlinear model of a Quadrotor. We design a control to stabilize and assure the attitude of the device, starting off a linearized system at the equilibrium point of the null angles of Euler (hover), which provides us a control with limited capacities at small angles of rotation of the vehicle in three dimensions. In order to clear this obstacle, we propose the identification of models in different angles by means of simulations and the design of a controller specifically implemented for the identification task, that in future works will allow the development of controllers according to fast and agile angles of Euler for Quadrotor.

Keywords: Quadrotor, model, control, identification.

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Authors: Eva Eggeling, Dieter W. Fellner, Torsten Ullrich

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The objective of global optimization is to find the globally best solution of a model. Nonlinear models are ubiquitous in many applications and their solution often requires a global search approach; i.e. for a function f from a set A ⊂ Rn to the real numbers, an element x0 ∈ A is sought-after, such that ∀ x ∈ A : f(x0) ≤ f(x). Depending on the field of application, the question whether a found solution x0 is not only a local minimum but a global one is very important. This article presents a probabilistic approach to determine the probability of a solution being a global minimum. The approach is independent of the used global search method and only requires a limited, convex parameter domain A as well as a Lipschitz continuous function f whose Lipschitz constant is not needed to be known.

Keywords: global optimization, probability theory, probability of globality

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Authors: Mehdi Alilou, Mehdi Dehghan

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Routing in mobile ad hoc networks is a challenging task because nodes are free to move randomly. In DSR like all On- Demand routing algorithms, route discovery mechanism is associated with great delay. More Clearly in DSR routing protocol to send route reply packet, when current route breaks, destination seeks a new route. In this paper we try to change route selection mechanism proactively. We also define a link stability parameter in which a stability value is assigned to each link. Given this feature, destination node can estimate stability of routes and can select the best and more stable route. Therefore we can reduce the delay and jitter of sending data packets.

Keywords: DSR, MANET, proactive, routing.

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Authors: Joanna Sooknanan, Donna Comissiong

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We propose a phenomenological model for the process of polymer desorption. In so doing, we omit the usual theoretical approach of incorporating a fictitious viscoelastic stress term into the flux equation. As a result, we obtain a model that captures the essence of the phenomenon of trapping skinning, while preserving the integrity of the experimentally verified Fickian law for diffusion. An appropriate asymptotic analysis is carried out, and a parameter is introduced to represent the speed of the desorption front. Numerical simulations are performed to illustrate the desorption dynamics of the model. Recommendations are made for future modifications of the model, and provisions are made for the inclusion of experimentally determined frontal speeds.

Keywords: Phenomenological Model, Polymer, Desorption, Trapping Skinning

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Authors: Sajjad Rahmany, Abdolali Basiri

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The link between Gröbner basis and linear algebra was described by Lazard [4,5] where he realized the Gr┬¿obner basis computation could be archived by applying Gaussian elimination over Macaulay-s matrix . In this paper, we indicate how same technique may be used to SAGBI- Gröbner basis computations in invariant rings.

Keywords: Gröbner basis, SAGBI- Gröbner basis, reduction, Invariant ring, permutation groups.

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Authors: T. O. Olwal, K. Djouani, B. J. van Wyk, Y. Hamam, P. Siarry

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Multi-Radio Multi-Channel Wireless Mesh Networks (MRMC-WMNs) operate at the backbone to access and route high volumes of traffic simultaneously. Such roles demand high network capacity, and long “online" time at the expense of accelerated transmission energy depletion and poor connectivity. This is the problem of transmission power control. Numerous power control methods for wireless networks are in literature. However, contributions towards MRMC configurations still face many challenges worth considering. In this paper, an energy-efficient power selection protocol called PMMUP is suggested at the Link-Layer. This protocol first divides the MRMC-WMN into a set of unified channel graphs (UCGs). A UCG consists of multiple radios interconnected to each other via a common wireless channel. In each UCG, a stochastic linear quadratic cost function is formulated. Each user minimizes this cost function consisting of trade-off between the size of unification states and the control action. Unification state variables come from independent UCGs and higher layers of the protocol stack. The PMMUP coordinates power optimizations at the network interface cards (NICs) of wireless mesh routers. The proposed PMMUP based algorithm converges fast analytically with a linear rate. Performance evaluations through simulations confirm the efficacy of the proposed dynamic power control.

Keywords: Effective band inference based power control algorithm (EBIA), Power Selection MRMC Unification Protocol (PMMUP), MRMC State unification Variable Prediction (MRSUP), Wireless Mesh Networks (WMNs).

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Authors: M. F. Omar, R. A. Salam, R. Abdullah, N. A. Rashid

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Proteins or genes that have similar sequences are likely to perform the same function. One of the most widely used techniques for sequence comparison is sequence alignment. Sequence alignment allows mismatches and insertion/deletion, which represents biological mutations. Sequence alignment is usually performed only on two sequences. Multiple sequence alignment, is a natural extension of two-sequence alignment. In multiple sequence alignment, the emphasis is to find optimal alignment for a group of sequences. Several applicable techniques were observed in this research, from traditional method such as dynamic programming to the extend of widely used stochastic optimization method such as Genetic Algorithms (GAs) and Simulated Annealing. A framework with combination of Genetic Algorithm and Simulated Annealing is presented to solve Multiple Sequence Alignment problem. The Genetic Algorithm phase will try to find new region of solution while Simulated Annealing can be considered as an alignment improver for any near optimal solution produced by GAs.

Keywords: Simulated annealing, genetic algorithm, sequence alignment, multiple sequence alignment.

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Authors: Sunho Ki, Daehwan Kim, Seongwon Cho, Sun-Tae Chung, Jaemin Kim, Yun-Kwang Hong, Chang Joon Park, Dongmin Kwon, Minhee Kang, Yusung Kim, Younghan Yoon

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AAM (active appearance model) has been successfully applied to face and facial feature localization. However, its performance is sensitive to initial parameter values. In this paper, we propose a two-stage AAM for robust face alignment, which first fits an inner face-AAM model to the inner facial feature points of the face and then localizes the whole face and facial features by optimizing the whole face-AAM model parameters. Experiments show that the proposed face alignment method using two-stage AAM is more reliable to the background and the head pose than the standard AAM-based face alignment method.

Keywords: AAM, Face Alignment, Feature Extraction, PCA

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Authors: Weerachi Sarakorn, I-Ming Tang

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A mathematical model for the transmission of SARS is developed. In addition to dividing the population into susceptible (high and low risk), exposed, infected, quarantined, diagnosed and recovered classes, we have included a class called untraced. The model simulates the Gompertz curves which are the best representation of the cumulative numbers of probable SARS cases in Hong Kong and Singapore. The values of the parameters in the model which produces the best fit of the observed data for each city are obtained by using a differential evolution algorithm. It is seen that the values for the parameters needed to simulate the observed daily behaviors of the two epidemics are different.

Keywords: SARS, mathematical modelling, differential evolution algorithm.

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Authors: Khalid Abdelmoumen, Mustapha Najmeddine, Hussain Ben-Azza

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We present linear codes over finite commutative rings which are not necessarily Frobenius. We treat the notion of syndrome decoding by using Pontrjagin duality. We also give a version of Delsarte-s theorem over rings relating trace codes and subring subcodes.

Keywords: Codes, Finite Rings, Pontrjagin Duality, Trace Codes.

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Authors: I. Lolic, P. Soric, M. Cizmesija

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Based on Business and Consumer Survey (BCS) data, the European Commission (EC) regularly publishes the monthly Economic Sentiment Indicator (ESI) for each EU member state. ESI is conceptualized as a leading indicator, aimed ad tracking the overall economic activity. In calculating ESI, the EC employs arbitrarily chosen weights on 15 BCS response balances. This paper raises the predictive quality of ESI by applying nonlinear programming to find such weights that maximize the correlation coefficient of ESI and year-on-year GDP growth. The obtained results show that the highest weights are assigned to the response balances of industrial sector questions, followed by questions from the retail trade sector. This comes as no surprise since the existing literature shows that the industrial production is a plausible proxy for the overall Croatian economic activity and since Croatian GDP is largely influenced by the aggregate personal consumption.

Keywords: Business and Consumer Survey, Economic Sentiment Indicator, Leading Indicator, Nonlinear Optimization with Constraints.

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Authors: A.Qaderi, A. Heydarinasab, M. Ardjmand

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Poly-β-hydroxybutyrate (PHB) is one of the most famous biopolymers that has various applications in production of biodegradable carriers. The most important strategy for enhancing efficiency in production process and reducing the price of PHB, is the accurate expression of kinetic model of products formation and parameters that are effective on it, such as Dry Cell Weight (DCW) and substrate consumption. Considering the high capabilities of artificial neural networks in modeling and simulation of non-linear systems such as biological and chemical industries that mainly are multivariable systems, kinetic modeling of microbial production of PHB that is a complex and non-linear biological process, the three layers perceptron neural network model was used in this study. Artificial neural network educates itself and finds the hidden laws behind the data with mapping based on experimental data, of dry cell weight, substrate concentration as input and PHB concentration as output. For training the network, a series of experimental data for PHB production from Hydrogenophaga Pseudoflava by glucose carbon source was used. After training the network, two other experimental data sets that have not intervened in the network education, including dry cell concentration and substrate concentration were applied as inputs to the network, and PHB concentration was predicted by the network. Comparison of predicted data by network and experimental data, indicated a high precision predicted for both fructose and whey carbon sources. Also in present study for better understanding of the ability of neural network in modeling of biological processes, microbial production kinetic of PHB by Leudeking-Piret experimental equation was modeled. The Observed result indicated an accurate prediction of PHB concentration by artificial neural network higher than Leudeking- Piret model.

Keywords: Kinetic Modeling, Poly-β-Hydroxybutyrate (PHB), Hydrogenophaga Pseudoflava, Artificial Neural Network, Leudeking-Piret

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Authors: Talib Hashim Hasan

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This paper describes simple implementation of homotopy (also called continuation) algorithm for determining the proper resistance of the resistor to dissipate energy at a specified rate of an electric circuit. Homotopy algorithm can be considered as a developing of the classical methods in numerical computing such as Newton-Raphson and fixed point methods. In homoptopy methods, an embedding parameter is used to control the convergence. The method purposed in this work utilizes a special homotopy called Newton homotopy. Numerical example solved in MATLAB is given to show the effectiveness of the purposed method

Keywords: electrical circuit homotopy, methods, MATLAB, Newton homotopy

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Authors: Hidemi Ogasawara, Kiyoshi Akama, Hiroshi Mabuchi

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The purpose of this paper is to propose a framework for constructing correct parallel processing programs based on Equivalent Transformation Framework (ETF). ETF regards computation as In the framework, a problem-s domain knowledge and a query are described in definite clauses, and computation is regarded as transformation of the definite clauses. Its meaning is defined by a model of the set of definite clauses, and the transformation rules generated must preserve meaning. We have proposed a parallel processing method based on “specialization", a part of operation in the transformations, which resembles substitution in logic programming. The method requires “Memo-tree", a history of specialization to maintain correctness. In this paper we proposes the new method for the specialization-base parallel processing without Memo-tree.

Keywords: Parallel processing, Program correctness, Equivalent transformation, Specializer generation rule

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Authors: J. G. Batista, K. N. Sousa, J. L. Nunes, R. L. S. Sousa, G. A. P. Thé

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This work deals with parameter identification of permanent magnet motors, a class of ac motor which is particularly important in industrial automation due to characteristics like applications high performance, are very attractive for applications with limited space and reducing the need to eliminate because they have reduced size and volume and can operate in a wide speed range, without independent ventilation. By using experimental data and genetic algorithm we have been able to extract values for both the motor inductance and the electromechanical coupling constant, which are then compared to measured and/or expected values.

Keywords: Modeling, AC servomotor, Permanent Magnet Synchronous Motor-PMSM, Genetic Algorithm, Vector Control, Robotic Manipulator, Control.

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Authors: Mehdi Ghommem, Daniel Garcia, Nathan Collier, Victor Calo

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We develop a fast, user-friendly implementation of a potential flow solver based on the unsteady vortex lattice method (UVLM). The computational framework uses the Python programming language which has easy integration with the scripts requiring computationally-expensive operations written in Fortran. The mixed-language approach enables high performance in terms of solution time and high flexibility in terms of easiness of code adaptation to different system configurations and applications. This computational tool is intended to predict the unsteady aerodynamic behavior of multiple moving bodies (e.g., flapping wings, rotating blades, suspension bridges...) subject to an incoming air. We simulate different aerodynamic problems to validate and illustrate the usefulness and effectiveness of the developed computational tool.

Keywords: Unsteady aerodynamics, numerical simulations, mixed-language approach, potential flow.

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Authors: S. M. Monavari, P. Hoasami, S. Tajziehchi, N. Khorramichokami.

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The practice of burying the solid waste under the ground is one of the waste disposal methods and dumping is known as an ultimate method in the fastest-growing cities like Rasht city in Iran. Some municipalities select the solid waste landfills without feasibility studies, programming, design and management plans. Therefore, several social and environmental impacts are created by these sites. In this study, the suitability of solid waste landfill in Rasht city, capital of Gilan Province is reviewed using Regional Screening Method (RSM), Geographic Information System (GIS) and Analytical Hierarchy Process (AHP). The results indicated that according to the suitability maps, the value of study site is midsuitable to suitable based on RSM and mid-suitable based on AHP.

Keywords: Analytical Hierarchy Process (AHP), Geographic Information System (GIS), Rasht City, Regional Screening Method (RSM), Solid Waste Landfill

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Authors: Ali Taee Zade, Siamak Rasulzadeh, Reza Torkashvan

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Although Model Driven Architecture has taken successful steps toward model-based software development, this approach still faces complex situations and ambiguous questions while applying to real world software systems. One of these questions - which has taken the most interest and focus - is how model transforms between different abstraction levels, MDA proposes. In this paper, we propose an approach based on Story Driven Modeling and Aspect Oriented Programming to ease these transformations. Service Oriented Architecture is taken as the target model to test the proposed mechanism in a functional system. Service Oriented Architecture and Model Driven Architecture [1] are both considered as the frontiers of their own domain in the software world. Following components - which was the greatest step after object oriented - SOA is introduced, focusing on more integrated and automated software solutions. On the other hand - and from the designers' point of view - MDA is just initiating another evolution. MDA is considered as the next big step after UML in designing domain.

Keywords: SOA, MDA, SDM, Model Transformation, Middleware Transparency, Aspects and Jini.

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Authors: Kejun Zhuang, Hailong Zhu

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The dynamics of a delayed mathematical model for Hes1 oscillatory expression are investigated. The linear stability of positive equilibrium and existence of local Hopf bifurcation are studied. Moreover, the global existence of large periodic solutions has been established due to the global bifurcation theorem.

Keywords: Hes1, Hopf bifurcation, time delay, transcriptional repression loop

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Authors: Anwar H. Jarndal, Ahmed S. Elwakil

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In this paper, a fraction-order model for pad parasitic effect of GaN HEMT on Si substrate is developed and validated. Open de-embedding structure is used to characterize and de-embed substrate loading parasitic effects. Unbiased device measurements are implemented to extract parasitic inductances and resistances. The model shows very good simulation for S-parameter measurements under different bias conditions. It has been found that this approach can improve the simulation of intrinsic part of the transistor, which is very important for small- and large-signal modeling process.

Keywords: Fractional-order modeling, GaN HEMT, Si-substrate, open de-embedding structure.

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Authors: M. Raciti Castelli, S. De Betta, E. Benini

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The optimal grid spacing and turbulence model for the 2D numerical analysis of a vertical-axis water turbine (VAWaterT) operating in a 2 m/s freestream current has been investigated. The results of five different spatial domain discretizations and two turbulence models (k-ω SST and k-ε RNG) have been compared, in order to gain the optimal y+ parameter distribution along the blade walls during a full rotor revolution. The resulting optimal mesh has appeared to be quite similar to that obtained for the numerical analysis of a vertical-axis wind turbine.

Keywords: CFD, vertical axis water turbine, NACA 0025, blade y+.

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Authors: E. Ardil, Erdem Uçar, Parvinder S. Sandhu

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As the majority of faults are found in a few of its modules so there is a need to investigate the modules that are affected severely as compared to other modules and proper maintenance need to be done on time especially for the critical applications. In this paper, we have explored the different predictor models to NASA-s public domain defect dataset coded in Perl programming language. Different machine learning algorithms belonging to the different learner categories of the WEKA project including Mamdani Based Fuzzy Inference System and Neuro-fuzzy based system have been evaluated for the modeling of maintenance severity or impact of fault severity. The results are recorded in terms of Accuracy, Mean Absolute Error (MAE) and Root Mean Squared Error (RMSE). The results show that Neuro-fuzzy based model provides relatively better prediction accuracy as compared to other models and hence, can be used for the maintenance severity prediction of the software.

Keywords: Software Metrics, Fuzzy, Neuro-Fuzzy, SoftwareFaults, Accuracy, MAE, RMSE.

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Authors: Guangbin Wang, Fuping Tan

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In this paper, we investigate two parallel alternating methods for solving the system of linear equations Ax = b and give convergence theorems for the parallel alternating methods when the coefficient matrix is a nonsingular H-matrix. Furthermore, we give one example to show our results.

Keywords: Nonsingular H-matrix, parallel alternating method, convergence.

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Authors: Robert Cep, Adam Janasek, Lenka Cepova, Josef Prochazka

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The paper is dealing by testing of ceramic cutting tools with an interrupted machining. Tests will be provided on fixture – interrupted cut simulator. This simulator has 4 mouldings on circumference and cutting edge is put a shocks during 1 revolution. Criteria of tool wear are destruction of cutting tool or 6000 shocks. Like testing cutting tool material will be products of Sandvik Coromant 6190, 620, 650 and 670. Machined materials was be steels 15 128 (13MoCrV6). Cutting speed (408 m.min-1 and 580 m.min-1) and cutting feed (0,15 mm; 0,2 mm; 0,25 mm and 0,3 mm) were variable parameters and cutting depth was constant parameter.

Keywords: Ceramic Cutting Tools, Interrupted Cut, Machining, Cutting Tests.

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Authors: Mami Sugiura, Shinichi Arakawa, Masayuki Murata, Satoshi Imai, Toru Katagiri, Motoyoshi Sekiya

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API (Application Programming Interface) economy, where many participants join/interact and form the economy, is expected to increase collaboration between information services through API, and thereby, it is expected to increase market value from the service collaborations. In this paper, we introduce API evaluators, which are the activator of API economy by reviewing and/or evaluating APIs, and develop a multi-sided API economy model that formulates interactions among platform provider, API developers, consumers, and API evaluators. By obtaining the equilibrium that maximizes utility of all participants, the impact of API evaluators on the utility of participants in the API economy is revealed. Numerical results show that, with the existence of API evaluators, the number of developers and consumers increase by 1.5% and the utility of platformer increases by 2.3%. We also discuss the strategies of platform provider to maximize its utility under the existence of API evaluators.

Keywords: API economy, multi-sided markets, API evaluator, platform, platform provider.

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Authors: Ahtesham Javaid, Costin S. Bildea

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The design and plantwide control of an integrated plant where the endothermic 1,4-butanediol dehydrogenation and the exothermic furfural hydrogenation is simultaneously performed in a single reactor is studied. The reactions can be carried out in an adiabatic reactor using small hydrogen excess and with reduced parameter sensitivity. The plant is robust and flexible enough to allow different production rates of γ-butyrolactone and 2-methyl furan, keeping high product purities. Rigorous steady state and dynamic simulations performed in AspenPlus and AspenDynamics to support the conclusions.

Keywords: Dehydrogenation and hydrogenation, Reaction coupling, Design and control, Process integration.

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Authors: Sin Yin Teh, Abdul Rahman Othman, Michael Boon Chong Khoo

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In this paper, the concepts of dichotomous logistic regression (DLR) with leave-one-out (L-O-O) were discussed. To illustrate this, the L-O-O was run to determine the importance of the simulation conditions for robust test of spread procedures with good Type I error rates. The resultant model was then evaluated. The discussions included 1) assessment of the accuracy of the model, and 2) parameter estimates. These were presented and illustrated by modeling the relationship between the dichotomous dependent variable (Type I error rates) with a set of independent variables (the simulation conditions). The base SAS software containing PROC LOGISTIC and DATA step functions can be making used to do the DLR analysis.

Keywords: Dichotomous logistic regression, leave-one-out, testof spread.

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Authors: Maryam Momeni Feili, Mahvash Zandy Navgaran

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The wave function at the origin is an important quantity in studying many physical problems concerning heavy quarkonia. This is because that it is using for calculating spin state hyperfine splitting and also crucial to evaluating the production and decay amplitude of the heavy quarkonium. In this paper, we present the variational method by using the single-parameter wave function to estimate the WFO for the ground state of heavy mesons.

Keywords: Wave function at the origin, heavy mesons, bound states, variational method, non-relativistic quark model, potential model, trial wave function.

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