Search results for: Renewal function

Authors: Randle O. A., Olugbara, O. O., Lall M.

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In this paper we describe a hybrid technique of Minimax search and aggregate Mahalanobis distance function synthesis to evolve Awale game player. The hybrid technique helps to suggest a move in a short amount of time without looking into endgame database. However, the effectiveness of the technique is heavily dependent on the training dataset of the Awale strategies utilized. The evolved player was tested against Awale shareware program and the result is appealing.

Keywords: Minimax Search, Mahalanobis Distance, Strategic Game, Awale

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Authors: F. Bayatbabolghani, K. Parand

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In this paper, we propose Hermite collocation method for solving Thomas-Fermi equation that is nonlinear ordinary differential equation on semi-infinite interval. This method reduces the solution of this problem to the solution of a system of algebraic equations. We also present the comparison of this work with solution of other methods that shows the present solution is more accurate and faster convergence in this problem.

Keywords: Collocation method, Hermite function, Semi-infinite, Thomas-Fermi equation.

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Authors: Ricardo C. Silva, Luiza A. P. Cantao, Akebo Yamakami

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Based on the fuzzy set theory this work develops two adaptations of iterative methods that solve mathematical programming problems with uncertainties in the objective function and in the set of constraints. The first one uses the approach proposed by Zimmermann to fuzzy linear programming problems as a basis and the second one obtains cut levels and later maximizes the membership function of fuzzy decision making using the bound search method. We outline similarities between the two iterative methods studied. Selected examples from the literature are presented to validate the efficiency of the methods addressed.

Keywords: Fuzzy Theory, Nonlinear Optimization, Fuzzy Mathematics Programming.

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Authors: Young-Seok Choi

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This work presents a new type of the affine projection (AP) algorithms which incorporate the sparsity condition of a system. To exploit the sparsity of the system, a weighted l1-norm regularization is imposed on the cost function of the AP algorithm. Minimizing the cost function with a subgradient calculus and choosing two distinct weighting for l1-norm, two stochastic gradient based sparsity regularized AP (SR-AP) algorithms are developed. Experimental results exhibit that the SR-AP algorithms outperform the typical AP counterparts for identifying sparse systems.

Keywords: System identification, adaptive filter, affine projection, sparsity, sparse system.

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Authors: Saif Ul Haq

Abstract:

The current study intends to examine the safety and quality considerations of clients of housing projects and their impact on the adoption of Quality Function Deployment (QFD) by the construction firm. Mixed method research technique has been used to collect and analyze the data wherein a survey was conducted to collect the data from 220 clients of housing projects in Saudi Arabia. Then, the telephonic and Skype interviews were conducted to collect data of 15 professionals working in the top ten real estate companies of Saudi Arabia. Data were analyzed by using partial least square (PLS) and thematic analysis techniques. Findings reveal that today’s customer prioritizes the safety and quality requirements of their houses and as a result, construction firms adopt QFD to address the needs of customers. The findings are of great importance for the clients of housing projects as well as for the construction firms as they could apply QFD in housing projects to address the safety and quality concerns of their clients.

Keywords: Construction industry, quality considerations, quality function deployment, safety considerations.

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Authors: Wanhyun Cho, Soonja Kang, Sangkyoon Kim, Soonyoung Park

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In this paper, we propose the variational EM inference algorithm for the multi-class Gaussian process classification model that can be used in the field of human behavior recognition. This algorithm can drive simultaneously both a posterior distribution of a latent function and estimators of hyper-parameters in a Gaussian process classification model with multiclass. Our algorithm is based on the Laplace approximation (LA) technique and variational EM framework. This is performed in two steps: called expectation and maximization steps. First, in the expectation step, using the Bayesian formula and LA technique, we derive approximately the posterior distribution of the latent function indicating the possibility that each observation belongs to a certain class in the Gaussian process classification model. Second, in the maximization step, using a derived posterior distribution of latent function, we compute the maximum likelihood estimator for hyper-parameters of a covariance matrix necessary to define prior distribution for latent function. These two steps iteratively repeat until a convergence condition satisfies. Moreover, we apply the proposed algorithm with human action classification problem using a public database, namely, the KTH human action data set. Experimental results reveal that the proposed algorithm shows good performance on this data set.

Keywords: Bayesian rule, Gaussian process classification model with multiclass, Gaussian process prior, human action classification, laplace approximation, variational EM algorithm.

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Authors: G. C. Mahata, A. Goswami

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This paper deals with infinite time horizon fuzzy Economic Order Quantity (EOQ) models for deteriorating items with  stock dependent demand rate and nonlinear holding costs by taking deterioration rate θ0 as a triangular fuzzy number  (θ0 −δ 1, θ0, θ0 +δ 2), where 1 2 0 0 <δ ,δ <θ are fixed real numbers. The traditional parameters such as unit cost and ordering  cost have been kept constant but holding cost is considered to vary. Two possibilities of variations in the holding cost function namely, a non-linear function of the length of time for which the item is held in stock and a non-linear function of the amount of on-hand inventory have been used in the models. The approximate optimal solution for the fuzzy cost functions in both these cases have been obtained and the effect of non-linearity in holding costs is studied with the help of a numerical example.

Keywords: Inventory Model, Deterioration, Holding Cost, Fuzzy Total Cost, Extension Principle.

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Authors: Zhizhong Jiang, Peter Naudé, Binghua Jiang

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Effective evaluation of software development effort is an important issue during project plan. This study provides a model to predict development effort based on the software size estimated with function points. We generalize the average amount of effort spent on each phase of the development, and give the estimates for the effort used in software building, testing, and implementation. Finally, this paper finds a strong correlation between software defects and software size. As the size of software constantly increases, the quality remains to be a matter which requires major concern.

Keywords: Development effort, function points, software quality, software size.

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Authors: Ram Kumar Soni, Alok Jain, Rajiv Saxena

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This paper proposes an efficient method for the design of two channel quadrature mirror filter (QMF) bank. To achieve minimum value of reconstruction error near to perfect reconstruction, a linear optimization process has been proposed. Prototype low pass filter has been designed using Kaiser window function. The modified algorithm has been developed to optimize the reconstruction error using linear objective function through iteration method. The result obtained, show that the performance of the proposed algorithm is better than that of the already exists methods.

Keywords: Filterbank, near perfect reconstruction, Kaiserwindow, QMF.

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Authors: Jatinderdeep Kaur

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In this paper, the results of Kano from one dimensional cosine and sine series are extended to two dimensional cosine and sine series. To extend these results, some classes of coefficient sequences such as class of semi convexity and class R are extended from one dimension to two dimensions. Further, the function f(x, y) is two dimensional Fourier Cosine and Sine series or equivalently it represents an integrable function or not, has been studied. Moreover, some results are obtained which are generalization of Moricz’s results.

Keywords: Conjugate Dirichlet kernel, conjugate Fejer kernel, Fourier series, Semi-convexity.

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Authors: Shuen-Tai Wang, Chin-Hung Li, Ying-Chuan Chen

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In recent years there has been renewal of interest in the relation between Green IT and Cloud Computing. The growing use of computers in cloud platform has caused marked energy consumption, putting negative pressure on electricity cost of cloud data center. This paper proposes an effective mechanism to reduce energy utilization in cloud computing environments. We present initial work on the integration of resource and power management that aims at reducing power consumption. Our mechanism relies on recalling virtualization services dynamically according to user-s virtualization request and temporarily shutting down the physical machines after finish in order to conserve energy. Given the estimated energy consumption, this proposed effort has the potential to positively impact power consumption. The results from the experiment concluded that energy indeed can be saved by powering off the idling physical machines in cloud platforms.

Keywords: Green IT, Cloud Computing, virtualization, power consumption.

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Authors: Peter Benneth, Tsaroh N. Theophilus, Prince Benjamin

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This research work aims at studying the application of Legendre Transformation Method (LTM) to Hamilton Jacobi Bellman (HJB) equation which is an example of optimal control problem. We discuss the steps involved in modelling the HJB equation as it relates to mathematical finance by applying the Ito’s lemma and maximum principle theorem. By applying the LTM and dual theory, the resultant HJB equation is transformed to a linear Partial Differential Equation (PDE). Also, the Optimal Investment Strategy (OIS) and the optimal value function were obtained under the exponential utility function. Furthermore, some numerical results were also presented with observations that the OIS under exponential utility is directly proportional to the appreciation rate of the risky asset and inversely proportional to the instantaneous volatility, predetermined interest rate, risk averse coefficient. Finally, it was observed that the optimal fund size is an increasing function of the risk free interest rate. This result is consistent with some existing results.

Keywords: Legendre transformation method, Optimal investment strategy, Ito’s lemma, Hamilton Jacobi Bellman equation, Geometric Brownian motion, financial market.

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Authors: M. Momeni Feyli

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Many recent high energy physics calculations involving charm and beauty invoke wave function at the origin (WFO) for the meson bound state. Uncertainties of charm and beauty quark masses and different models for potentials governing these bound states require a simple numerical algorithm for evaluation of the WFO's for these bound states. We present a simple algorithm for this propose which provides WFO's with high precision compared with similar ones already obtained in the literature.

Keywords: Mesons, Bound states, Schrodinger equation, Nonrelativistic quark model.

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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: Adekitan I. Aderibigbe, Fakolujo A. Olaosebikan

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The parameters of a two-layer soil can be determined by processing resistivity data obtained from resistivity measurements carried out on the soil of interest. The processing usually entails applying the resistivity data as inputs to an optimisation function. This paper proposes an algorithm which utilises the square error as an optimisation function. Resistivity data from previous works were applied to test the accuracy of the new algorithm developed and the result obtained conforms significantly to results from previous works.

 

Keywords: Algorithm, earthing, resistivity, two-layer soil-model.

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Authors: Zhazira Kuanyshbayeva

Abstract:

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.

Keywords: Interethnic relation, Kazakhstan people, national policy, national values.

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Authors: Shilan Li, Ivan Arokiam, Peter Jarvis, Wendy Garner, Gazelleh Moradi, Stuart Wakefield

Abstract:

Development of a Robust Supply Chain for Dynamic Operating Environment as we move further into the twenty first century, organisations are under increasing pressure to deliver a high product variation at a reasonable cost without compromise in quality. In a number of cases this will take the form of a customised or high variety low volume manufacturing system that requires prudent management of resources, among a number of functions, to achieve competitive advantage. Purchasing and Supply Chain management is one of such function and due to the substantial interaction with external elements needs to be strategically managed. This requires a number of primary and supporting tools that will enable the appropriate decisions to be made rapidly. This capability is especially vital in a dynamic environment as it provides a pivotal role in increasing the profit margin of the product. The management of this function can be challenging by itself and even more for Small and Medium Enterprises (SMEs) due to the limited resources and expertise available at their disposal. This paper discusses the development of tools and concepts towards effectively managing the purchasing and supply chain function. The developed tools and concepts will provide a cost effective way of managing this function within SMEs. The paper further shows the use of these tools within Contechs, a manufacturer of luxury boat interiors, and the associated benefits achieved as a result of this implementation. Finally a generic framework towards use in such environments is presented.

Keywords: Lean, Supply Chain, High variety Low volume, Small and Medium Enterprises.

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Authors: Hironobu Murayama, Shohei Shimizu, Masakazu Ohnuki, Hisanori Mihara, Tohru Kanada

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Disordered function of maniphalanx and difficulty with ambulation will occur insofar as a human has a failure in the spinal marrow. Cervical spondylotic myelopathy as one of the myelopathy emanates from not only external factors but also increased age. In addition, the diacrisis is difficult since cervical spondylotic myelopathy is evaluated by a doctor-s neurological remark and imaging findings. As a quantitative method for measuring the degree of disability, hand-operated triangle step test (for short, TST) has formulated. In this research, a full automatic triangle step counter apparatus is designed and developed to measure the degree of disability in an accurate fashion according to the principle of TST. The step counter apparatus whose shape is a low triangle pole displays the number of stepping upon each corner. Furthermore, the apparatus has two modes of operation. Namely, one is for measuring the degree of disability and the other for rehabilitation exercise. In terms of usefulness, clinical practice should be executed before too long.

Keywords: Cervical spondylotic myelopathy, disorder of lower limbs, measuringfunction, rehabilitation function, full automatic apparatus, triangle step test.

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Authors: M. Sedighizadeh, A. Rezazadeh

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A self tuning PID control strategy using reinforcement learning is proposed in this paper to deal with the control of wind energy conversion systems (WECS). Actor-Critic learning is used to tune PID parameters in an adaptive way by taking advantage of the model-free and on-line learning properties of reinforcement learning effectively. In order to reduce the demand of storage space and to improve the learning efficiency, a single RBF neural network is used to approximate the policy function of Actor and the value function of Critic simultaneously. The inputs of RBF network are the system error, as well as the first and the second-order differences of error. The Actor can realize the mapping from the system state to PID parameters, while the Critic evaluates the outputs of the Actor and produces TD error. Based on TD error performance index and gradient descent method, the updating rules of RBF kernel function and network weights were given. Simulation results show that the proposed controller is efficient for WECS and it is perfectly adaptable and strongly robust, which is better than that of a conventional PID controller.

Keywords: Wind energy conversion systems, reinforcementlearning; Actor-Critic learning; adaptive PID control; RBF network.

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Authors: Y. A. Mahmood, A. Ahmadi, R. Karim, U. Kumar, A.K. Verma, N. Fransson

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The purpose of this paper isunavailability of the two main types of conveSwedish traction power supply (TPS) system, i.e.static converter. The number of outages and the ouused to analyze and compare the unavailability oconverters. The mean cumulative function (MCF)analyze the number of outages and the unavailabthe forced outage rate (FOR) concept has been uoutage rates. The study shows that the outagesfailure occur at a constant rate by calendar timconverter stations, while very few stations havedecreasing rate. It has also been found that the stata higher number of outages and a higher outage ratcompared to the rotary converter types. The resultsthat combining the number of outages and the fgives a better view of the converters performasupport for the maintenance decision. In fact, usingdoes not reflect reality. Comparing these two indein identifying the areas where extra resources are maintenance planning and where improvementsoutage in the TPS system.KeywordsFrequency Converter, Forced OuCumulative Function, Traction Power Supply, ESystems.

Keywords: Frequency Converter, Forced Outage Rate, Mean Cumulative Function, Traction Power Supply, Electrified Railway Systems.

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Authors: Norsinnira Zainul Azlan, Hiroshi Yamaura

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This study is concerned with a new adaptive impedance control strategy to compensate for unknown time-varying environment stiffness and position. The uncertainties are expressed by Function Approximation Technique (FAT), which allows the update laws to be derived easily using Lyapunov stability theory. Computer simulation results are presented to validate the effectiveness of the proposed strategy.

Keywords: Adaptive Impedance Control, Function Approximation Technique (FAT), unknown time-varying environment position and stiffness.

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Authors: Wojciech Rejchel

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The problem of ranking (rank regression) has become popular in the machine learning community. This theory relates to problems, in which one has to predict (guess) the order between objects on the basis of vectors describing their observed features. In many ranking algorithms a convex loss function is used instead of the 0-1 loss. It makes these procedures computationally efficient. Hence, convex risk minimizers and their statistical properties are investigated in this paper. Fast rates of convergence are obtained under conditions, that look similarly to the ones from the classification theory. Methods used in this paper come from the theory of U-processes as well as empirical processes.

Keywords: Convex loss function, empirical risk minimization, empirical process, U-process, boosting, euclidean family.

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Authors: Peyman Sindareh Esfahani, Jeffery Kurt Pieper

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In this paper, the problem of robust model predictive control (MPC) for discrete-time linear systems in linear fractional transformation form with structured uncertainty and norm-bounded disturbance is investigated. The problem of minimization of the cost function for MPC design is converted to minimization of the worst case of the cost function. Then, this problem is reduced to minimization of an upper bound of the cost function subject to a terminal inequality satisfying the l₂-norm of the closed loop system. The characteristic of the linear fractional transformation system is taken into account, and by using some mathematical tools, the robust predictive controller design problem is turned into a linear matrix inequality minimization problem. Afterwards, a formulation which includes an integrator to improve the performance of the proposed robust model predictive controller in steady state condition is studied. The validity of the approaches is illustrated through a robust control benchmark problem.

Keywords: Linear fractional transformation, linear matrix inequality, robust model predictive control, state feedback control.

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Authors: Aries Susanty

Abstract:

The inability to implement the principles of good corporate governance (GCG) as demonstrated in the surveys is due to a number of constraints which can be classified into three; namely internal constraints, external constraints, and constraints coming from the structure of ownership. The issues in the internal constraints mentioned are related to the function of several elements of the company. As a business organization, corporation is unable to achieve its goal to successfully implement GCG principles since it is not support by its internal elements- functions. Two of several numbers of internal elements of a company are ethical work climate and leadership style of the top management. To prove the correlation between internal function of organization (in this case ethical work climate and transformational leadership) and the successful implementation of GCG principles, this study proposes two hypotheses to be empirically tested on thirty surveyed organizations; eleven of which are state-owned companies and nineteen are private companies. These thirty corporations are listed in the Jakarta Stock Exchange. All state-owned companies in the samples are those which have been privatized. The research showed that internal function of organization give support to the successful implementation of GCG principle. In this research we can prove that : (i) ethical work climate has positive significance of correlation with the successful implementation of social awareness principle (one of principles on GCG) and, (ii) only at the state-owned companies, transformational leadership have positive significance effect to forming the ethical work climate.

Keywords: Good Corporate Governance Principles, Ethical Work Climate, Transformational Leadership

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Authors: Refaat M Mohamed, Ayman El-Baz, Aly A. Farag

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This paper presents a new approach for the prob-ability density function estimation using the Support Vector Ma-chines (SVM) and the Expectation Maximization (EM) algorithms.In the proposed approach, an advanced algorithm for the SVM den-sity estimation which incorporates the Mean Field theory in the learning process is used. Instead of using ad-hoc values for the para-meters of the kernel function which is used by the SVM algorithm,the proposed approach uses the EM algorithm for an automatic optimization of the kernel. Experimental evaluation using simulated data set shows encouraging results.

Keywords: Density Estimation, SVM, Learning Algorithms, Parameters Estimation.

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Authors: Marina Franulovic, Robert Basan, Bozidar Krizan

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Constitutive modeling of material behavior is becoming increasingly important in prediction of possible failures in highly loaded engineering components, and consequently, optimization of their design. In order to account for large number of phenomena that occur in the material during operation, such as kinematic hardening effect in low cycle fatigue behavior of steels, complex nonlinear material models are used ever more frequently, despite of the complexity of determination of their parameters. As a method for the determination of these parameters, genetic algorithm is good choice because of its capability to provide very good approximation of the solution in systems with large number of unknown variables. For the application of genetic algorithm to parameter identification, inverse analysis must be primarily defined. It is used as a tool to fine-tune calculated stress-strain values with experimental ones. In order to choose proper objective function for inverse analysis among already existent and newly developed functions, the research is performed to investigate its influence on material behavior modeling.

Keywords: Genetic algorithm, kinematic hardening, material model, objective function

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Authors: A. Gutiérrez, A. Castillo, J. M. Gómez, J. M. Gutiérrez, A. García-Cabot

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Road signs are the elements of roads with a lot of influence in driver-s behavior. So that signals can fulfill its function, they must overcome visibility and durability requirements, particularly needed at night, when the coefficient of retroreflection becomes a decisive factor in ensuring road safety. Accepting that the visibility of the signage has implications for people-s safety, we understand the importance to fulfill its function: to foster the highest standards of service and safety in drivers. The usual conditions of perception of any sign are determined by: age of the driver, reflective material, luminosity, vehicle speed and emplacement. In this way, this paper evaluates the different signals to increase the safety road.

Keywords: Luminosity, orientation, retroreflection, traffic signs.

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Authors: Yuichi Masukake, Yoshihisa Ishida

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In this paper, we proposed a method to design a model-following adaptive controller for linear/nonlinear plants. Radial basis function neural networks (RBF-NNs), which are known for their stable learning capability and fast training, are used to identify linear/nonlinear plants. Simulation results show that the proposed method is effective in controlling both linear and nonlinear plants with disturbance in the plant input.

Keywords: Linear/nonlinear plants, neural networks, radial basisfunction networks.

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Authors: O. Soji-Omoniwa, N. O. Muhammad, L. A. Usman, B. P. Omoniwa

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This study was conducted to investigate the effect of the leaf essential oil of C. sinensis harvested at 7.00a.m and 4.00p.m on some Liver and Kidney function indices of diabetic rats as well as investigate the effect of time of harvest on the observed effect. Experimental animals were divided into 4 groups (A, B, C and D). Diabetes mellitus was induced in all animals, except the normal control group (Group A), by injecting 150mg/kg body weight of alloxan monohydrate intraperitoneally. Group A received distilled water while group B (diabetic control group) was not treated. Group C and D were treated with leaf essential oil of C. sinensis harvested at 7.00 a.m and 4.00p.m respectively at a dose of 110 mg/kg body weight every other day for 15 days. Alkaline phosphatase (ALP), Alanine Transaminase (ALT) and Aspartate Transaminase (AST) activity was evaluated in the serum, Liver and Kidney of studied animals. Total and Direct Bilirubin level, Total Protein and Globulin, Creatinine and Urea level were also evaluated. Result showed that creatinine and urea, serum ALP, AST and ALT levels was significantly reduced (p < 0.05), while the levels of total Protein and Globulin increased significantly (p < 0.05) for the treated animals compared to the diabetic control group. In conclusion, the leaf essential oil of Citrus sinensis ameliorated the impaired renal and liver function; however, the time of harvest of the leaf does not significantly affect its ameliorative effect.

Keywords: C. sinensis, Function indices, Harvest time, Leaf essential oil.

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Authors: M. A. Rubio, A. Urquia

Abstract:

Genetic algorithms (GA) are applied to the solution of high-dimensional optimization problems. Additionally, sensitivity analysis (SA) is usually carried out to determine the effect on optimal solutions of changes in parameter values of the objective function. These two analyses (i.e., optimization and sensitivity analysis) are computationally intensive when applied to high-dimensional functions. The approach presented in this paper consists in performing the SA during the GA execution, by statistically analyzing the data obtained of running the GA. The advantage is that in this case SA does not involve making additional evaluations of the objective function and, consequently, this proposed approach requires less computational effort than conducting optimization and SA in two consecutive steps.

Keywords: Optimization, sensitivity, genetic algorithms, model calibration.

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