Search results for: Random Variable
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1359

Search results for: Random Variable

1119 Throughflow Effects on Thermal Convection in Variable Viscosity Ferromagnetic Liquids

Authors: G. N. Sekhar, P. G. Siddheshwar, G. Jayalatha, R. Prakash

Abstract:

The problem of thermal convection in temperature and magnetic field sensitive Newtonian ferromagnetic liquid is studied in the presence of uniform vertical magnetic field and throughflow. Using a combination of Galerkin and shooting techniques the critical eigenvalues are obtained for stationary mode. The effect of Prandtl number (Pr > 1) on onset is insignificant and nonlinearity of non-buoyancy magnetic parameter M3 is found to have no influence on the onset of ferroconvection. The magnetic buoyancy number, M1 and variable viscosity parameter, V have destabilizing influences on the system. The effect of throughflow Peclet number, Pe is to delay the onset of ferroconvection and this effect is independent of the direction of flow.

Keywords: Ferroconvection, throughflow, temperature dependent viscosity, magnetic field dependent viscosity.

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1118 Fast and Accuracy Control Chart Pattern Recognition using a New cluster-k-Nearest Neighbor

Authors: Samir Brahim Belhaouari

Abstract:

By taking advantage of both k-NN which is highly accurate and K-means cluster which is able to reduce the time of classification, we can introduce Cluster-k-Nearest Neighbor as "variable k"-NN dealing with the centroid or mean point of all subclasses generated by clustering algorithm. In general the algorithm of K-means cluster is not stable, in term of accuracy, for that reason we develop another algorithm for clustering our space which gives a higher accuracy than K-means cluster, less subclass number, stability and bounded time of classification with respect to the variable data size. We find between 96% and 99.7 % of accuracy in the lassification of 6 different types of Time series by using K-means cluster algorithm and we find 99.7% by using the new clustering algorithm.

Keywords: Pattern recognition, Time series, k-Nearest Neighbor, k-means cluster, Gaussian Mixture Model, Classification

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1117 The Efficiency of Multimedia Educational Tools in Sport Gymnastics for The Students of Physical Education at Universities

Authors: G. Bago, P. Hedbávný

Abstract:

This contribution was developed from a research within the doctoral thesis. Its object was to create multimedia materials for sport gymnastics. Consequently we surveyed the influence of its practical application on the efficiency of schooling at a university. We verified the prescribed hypothesis of the efficiency of the teaching process using the method of single-factor experiment, where the entrance independent variable was the change of system of tuition and the outgoing dependent variable was the change of level of acquired motor skills. The results confirmed the positive impact of using multimedia materials on the efficiency of the teaching process. Further, with the aid of questionnaires, we evaluated how the tested subjects perceive the innovative methods in sport gymnastics. The responses showed that the students rate the application of multimedia materials very positively.

Keywords: efficiency of education, means of education, multimedia materials, sports gymnastics

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1116 Image Modeling Using Gibbs-Markov Random Field and Support Vector Machines Algorithm

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

Abstract:

This paper introduces a novel approach to estimate the clique potentials of Gibbs Markov random field (GMRF) models using the Support Vector Machines (SVM) algorithm and the Mean Field (MF) theory. The proposed approach is based on modeling the potential function associated with each clique shape of the GMRF model as a Gaussian-shaped kernel. In turn, the energy function of the GMRF will be in the form of a weighted sum of Gaussian kernels. This formulation of the GMRF model urges the use of the SVM with the Mean Field theory applied for its learning for estimating the energy function. The approach has been tested on synthetic texture images and is shown to provide satisfactory results in retrieving the synthesizing parameters.

Keywords: Image Modeling, MRF, Parameters Estimation, SVM Learning.

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1115 Quintic Spline Solution of Fourth-Order Parabolic Equations Arising in Beam Theory

Authors: Reza Mohammadi, Mahdieh Sahebi

Abstract:

We develop a method based on polynomial quintic spline for numerical solution of fourth-order non-homogeneous parabolic partial differential equation with variable coefficient. By using polynomial quintic spline in off-step points in space and finite difference in time directions, we obtained two three level implicit methods. Stability analysis of the presented method has been carried out. We solve four test problems numerically to validate the derived method. Numerical comparison with other methods shows the superiority of presented scheme.

Keywords: Fourth-order parabolic equation, variable coefficient, polynomial quintic spline, off-step points, stability analysis.

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1114 Design of Moving Sliding Surfaces in A Variable Structure Plant and Chattering Phenomena

Authors: T.C. Manjunath

Abstract:

This paper deals with the design of a moving sliding surface in a variable structure plant for a second order system. The chattering phenomena is also dealt with during the switching process for an unstable sliding surface condition. The simulation examples considered in this paper shows the effectiveness of the sliding mode control method used for the design of the moving sliding surfaces. A simulink model of the continuous system was also developed in MATLAB-SIMULINK for the design and hence demonstrated. The phase portraits and the state plots shows the demonstration of the powerful control technique which can be applied for second order systems.

Keywords: Sliding mode control, VSC, Reaching phase, Sliding phase, Moving surfaces, Chattering, Trajectories.

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1113 A Study of Under Actuator Dynamic System by Comparing between Minimum Energy and Minimum Jerk Problems

Authors: Tawiwat V., Phermsak S., Noppasit C.

Abstract:

This paper deals with under actuator dynamic systems such as spring-mass-damper system when the number of control variable is less than the number of state variable. In order to apply optimal control, the controllability must be checked. There are many objective functions to be selected as the goal of the optimal control such as minimum energy, maximum energy and minimum jerk. As the objective function is the first priority, if one like to have the second goal to be applied; however, it could not fit in the objective function format and also avoiding the vector cost for the objective, this paper will illustrate the problem of under actuator dynamic systems with the easiest to deal with comparing between minimum energy and minimum jerk.

Keywords: Under actuator, Dynamic optimal control, Minimumjerk, Minimum energy.

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1112 Support Vector Machine Approach for Classification of Cancerous Prostate Regions

Authors: Metehan Makinacı

Abstract:

The objective of this paper, is to apply support vector machine (SVM) approach for the classification of cancerous and normal regions of prostate images. Three kinds of textural features are extracted and used for the analysis: parameters of the Gauss- Markov random field (GMRF), correlation function and relative entropy. Prostate images are acquired by the system consisting of a microscope, video camera and a digitizing board. Cross-validated classification over a database of 46 images is implemented to evaluate the performance. In SVM classification, sensitivity and specificity of 96.2% and 97.0% are achieved for the 32x32 pixel block sized data, respectively, with an overall accuracy of 96.6%. Classification performance is compared with artificial neural network and k-nearest neighbor classifiers. Experimental results demonstrate that the SVM approach gives the best performance.

Keywords: Computer-aided diagnosis, support vector machines, Gauss-Markov random fields, texture classification.

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1111 Firm Ownership and Performance: Evidence for Croatian Listed Firms

Authors: M. Pervan, I. Pervan, M. Todoric

Abstract:

Using data of listed Croatian firms from the Zagreb Stock Exchange we analyze the relationship between firm ownership (ownership concentration and type) and performance (ROA). Empirical research was conducted for the period 2003-2010, yielding with the total of 1,430 observations. Empirical findings based on dynamic panel analysis indicate that ownership concentration variable - CR4 is negatively related with performance, i.e. listed firms with dispersed ownership perform better than firms with concentrated ownership. Also, the research indicated that foreign controlled listed firms perform better than domestically controlled firms. Majority state owned firms perform worse than privately held firms but dummy variable for privately controlled firms was not statistically significant in the estimated panel model.

Keywords: Croatia, firm, ownership, performance

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1110 Variable Responses of Leaf C, N and P to Climatic Factors in Different Regions and Growth Forms

Authors: Li Wu

Abstract:

Plant ecological stoichiometry, which is one of the most important tools to connect the components among different levels of ecosystem, has obtained increasingly extensive concern, especially on its responses to the environmental gradients. Based on the published literatures and datasets, this article focused on reviewing the variable responses of plant foliar ecological stoichiometry to the climatic factors, such as temperature, water, elevated CO2, and found that foliar ecological stoichiometry responded dynamically to climatic variations among different regions and different growth forms. Then, research status and deficiency were summarized and the expectation on studying the relationships between plant C, N and P ecological stoichiometry and environmental variations which can provide a reference to understand how plants will respond to global change in the future was pointed out.

Keywords: Climatic variations, terrestrial plant, foliar ecological stoichiometry, temperature, precipitation, drought, elevated CO2.

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1109 A Comparison of Marginal and Joint Generalized Quasi-likelihood Estimating Equations Based On the Com-Poisson GLM: Application to Car Breakdowns Data

Authors: N. Mamode Khan, V. Jowaheer

Abstract:

In this paper, we apply and compare two generalized estimating equation approaches to the analysis of car breakdowns data in Mauritius. Number of breakdowns experienced by a machinery is a highly under-dispersed count random variable and its value can be attributed to the factors related to the mechanical input and output of that machinery. Analyzing such under-dispersed count observation as a function of the explanatory factors has been a challenging problem. In this paper, we aim at estimating the effects of various factors on the number of breakdowns experienced by a passenger car based on a study performed in Mauritius over a year. We remark that the number of passenger car breakdowns is highly under-dispersed. These data are therefore modelled and analyzed using Com-Poisson regression model. We use the two types of quasi-likelihood estimation approaches to estimate the parameters of the model: marginal and joint generalized quasi-likelihood estimating equation approaches. Under-dispersion parameter is estimated to be around 2.14 justifying the appropriateness of Com-Poisson distribution in modelling underdispersed count responses recorded in this study.

Keywords: Breakdowns, under-dispersion, com-poisson, generalized linear model, marginal quasi-likelihood estimation, joint quasi-likelihood estimation.

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1108 Performance of a Connected Random Covered Energy Efficient Wireless Sensor Network

Authors: M. Mahdavi, M. Ismail, K. Jumari, Z. M. Hanapi

Abstract:

For the sensor network to operate successfully, the active nodes should maintain both sensing coverage and network connectivity. Furthermore, scheduling sleep intervals plays critical role for energy efficiency of wireless sensor networks. Traditional methods for sensor scheduling use either sensing coverage or network connectivity, but rarely both. In this paper, we use random scheduling for sensing coverage and then turn on extra sensor nodes, if necessary, for network connectivity. Simulation results have demonstrated that the number of extra nodes that is on with upper bound of around 9%, is small compared to the total number of deployed sensor nodes. Thus energy consumption for switching on extra sensor node is small.

Keywords: Wireless sensor networks, energy efficient network, performance analysis, network coverage.

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1107 Comparison of Data Reduction Algorithms for Image-Based Point Cloud Derived Digital Terrain Models

Authors: M. Uysal, M. Yilmaz, I. Tiryakioğlu

Abstract:

Digital Terrain Model (DTM) is a digital numerical representation of the Earth's surface. DTMs have been applied to a diverse field of tasks, such as urban planning, military, glacier mapping, disaster management. In the expression of the Earth' surface as a mathematical model, an infinite number of point measurements are needed. Because of the impossibility of this case, the points at regular intervals are measured to characterize the Earth's surface and DTM of the Earth is generated. Hitherto, the classical measurement techniques and photogrammetry method have widespread use in the construction of DTM. At present, RADAR, LiDAR, and stereo satellite images are also used for the construction of DTM. In recent years, especially because of its superiorities, Airborne Light Detection and Ranging (LiDAR) has an increased use in DTM applications. A 3D point cloud is created with LiDAR technology by obtaining numerous point data. However recently, by the development in image mapping methods, the use of unmanned aerial vehicles (UAV) for photogrammetric data acquisition has increased DTM generation from image-based point cloud. The accuracy of the DTM depends on various factors such as data collection method, the distribution of elevation points, the point density, properties of the surface and interpolation methods. In this study, the random data reduction method is compared for DTMs generated from image based point cloud data. The original image based point cloud data set (100%) is reduced to a series of subsets by using random algorithm, representing the 75, 50, 25 and 5% of the original image based point cloud data set. Over the ANS campus of Afyon Kocatepe University as the test area, DTM constructed from the original image based point cloud data set is compared with DTMs interpolated from reduced data sets by Kriging interpolation method. The results show that the random data reduction method can be used to reduce the image based point cloud datasets to 50% density level while still maintaining the quality of DTM.

Keywords: DTM, unmanned aerial vehicle, UAV, random, Kriging.

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1106 Node Insertion in Coalescence Hidden-Variable Fractal Interpolation Surface

Authors: Srijanani Anurag Prasad

Abstract:

The Coalescence Hidden-variable Fractal Interpolation Surface (CHFIS) was built by combining interpolation data from the Iterated Function System (IFS). The interpolation data in a CHFIS comprise a row and/or column of uncertain values when a single point is entered. Alternatively, a row and/or column of additional points are placed in the given interpolation data to demonstrate the node added CHFIS. There are three techniques for inserting new points that correspond to the row and/or column of nodes inserted, and each method is further classified into four types based on the values of the inserted nodes. As a result, numerous forms of node insertion can be found in a CHFIS.

Keywords: Fractal, interpolation, iterated function system, coalescence, node insertion, knot insertion.

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1105 Ensembling Classifiers – An Application toImage Data Classification from Cherenkov Telescope Experiment

Authors: Praveen Boinee, Alessandro De Angelis, Gian Luca Foresti

Abstract:

Ensemble learning algorithms such as AdaBoost and Bagging have been in active research and shown improvements in classification results for several benchmarking data sets with mainly decision trees as their base classifiers. In this paper we experiment to apply these Meta learning techniques with classifiers such as random forests, neural networks and support vector machines. The data sets are from MAGIC, a Cherenkov telescope experiment. The task is to classify gamma signals from overwhelmingly hadron and muon signals representing a rare class classification problem. We compare the individual classifiers with their ensemble counterparts and discuss the results. WEKA a wonderful tool for machine learning has been used for making the experiments.

Keywords: Ensembles, WEKA, Neural networks [NN], SupportVector Machines [SVM], Random Forests [RF].

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1104 Chaos Theory and Application in Foreign Exchange Rates vs. IRR (Iranian Rial)

Authors: M. A. Torkamani, S. Mahmoodzadeh, S. Pourroostaei, C. Lucas

Abstract:

Daily production of information and importance of the sequence of produced data in forecasting future performance of market causes analysis of data behavior to become a problem of analyzing time series. But time series that are very complicated, usually are random and as a result their changes considered being unpredictable. While these series might be products of a deterministic dynamical and nonlinear process (chaotic) and as a result be predictable. Point of Chaotic theory view, complicated systems have only chaotically face and as a result they seem to be unregulated and random, but it is possible that they abide by a specified math formula. In this article, with regard to test of strange attractor and biggest Lyapunov exponent probability of chaos on several foreign exchange rates vs. IRR (Iranian Rial) has been investigated. Results show that data in this market have complex chaotic behavior with big degree of freedom.

Keywords: Chaos, Exchange Rate, Nonlinear Models.

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1103 Heat and Mass Transfer over an Unsteady Stretching Surface Embedded in a Porous Medium in the Presence of Variable Chemical Reaction

Authors: T. G. Emam

Abstract:

The effect of variable chemical reaction on heat and mass transfer characteristics over unsteady stretching surface embedded in a porus medium is studied. The governing time dependent boundary layer equations are transformed into ordinary differential equations containing chemical reaction parameter, unsteadiness parameter, Prandtl number and Schmidt number. These equations have been transformed into a system of first order differential equations. MATHEMATICA has been used to solve this system after obtaining the missed initial conditions. The velocity gradient, temperature, and concentration profiles are computed and discussed in details for various values of the different parameters.

Keywords: Heat and mass transfer, stretching surface, chemical reaction, porus medium.

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1102 A Statistical Model for the Dynamics of Single Cathode Spot in Vacuum Cylindrical Cathode

Authors: Po-Wen Chen, Jin-Yu Wu, Md. Manirul Ali, Yang Peng, Chen-Te Chang, Der-Jun Jan

Abstract:

Dynamics of cathode spot has become a major part of vacuum arc discharge with its high academic interest and wide application potential. In this article, using a three-dimensional statistical model, we simulate the distribution of the ignition probability of a new cathode spot occurring in different magnetic pressure on old cathode spot surface and at different arcing time. This model for the ignition probability of a new cathode spot was proposed in two typical situations, one by the pure isotropic random walk in the absence of an external magnetic field, other by the retrograde motion in external magnetic field, in parallel with the cathode surface. We mainly focus on developed relationship between the ignition probability density distribution of a new cathode spot and the external magnetic field.

Keywords: Cathode spot, vacuum arc discharge, transverse magnetic field, random walk.

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1101 Basic Tendency Model in Complete Factor Synergetics of Complex Systems

Authors: Li Zong-Cheng

Abstract:

The deviation between the target state variable and the practical state variable should be used to form the state tending factor of complex systems, which can reflect the process for the complex system to tend rationalization. Relating to the system of basic equations of complete factor synergetics consisting of twenty nonlinear stochastic differential equations, the two new models are considered to set, which should be called respectively the rationalizing tendency model and the non- rationalizing tendency model. Therefore we can extend the theory of programming with the objective function & constraint condition suitable only for the realm of man-s activities into the new analysis with the tendency function & constraint condition suitable for all the field of complex system.

Keywords: complex system, complete factor synergetics, basicequation, rationalizing tendency model, non-rationalizing tendencymodel.

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1100 Gaussian Particle Flow Bernoulli Filter for Single Target Tracking

Authors: Hyeongbok Kim, Lingling Zhao, Xiaohong Su, Junjie Wang

Abstract:

The Bernoulli filter is a precise Bayesian filter for single target tracking based on the random finite set theory. The standard Bernoulli filter often underestimates the number of the targets. This study proposes a Gaussian particle flow (GPF) Bernoulli filter employing particle flow to migrate particles from prior to posterior positions to improve the performance of the standard Bernoulli filter. By employing the particle flow filter, the computational speed of the Bernoulli filters is significantly improved. In addition, the GPF Bernoulli filter provides more accurate estimation compared with that of the standard Bernoulli filter. Simulation results confirm the improved tracking performance and computational speed in two- and three-dimensional scenarios compared with other algorithms.

Keywords: Bernoulli filter, particle filter, particle flow filter, random finite sets, target tracking.

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1099 Smart Energy Consumers: An Empirical Investigation on the Intention to Adopt Innovative Consumption Behaviour

Authors: Cecilia Perri, Vincenzo Corvello

Abstract:

The aim of the present study is to investigate consumers' determinants of intention toward the adoption of Smart Grid solutions and technologies. Ajzen's Theory of Planned Behaviour (TPB) model is applied and tested to explain the formation of such adoption intention. An exogenous variable, taking into account the resistance to change of individuals, was added to the basic model. The elicitation study allowed obtaining salient modal beliefs, which were used, with the support of literature, to design the questionnaire. After the screening phase, data collected from the main survey were analysed for evaluating measurement model's reliability and validity. Consistent with the theory, the results of structural equation analysis revealed that attitude, subjective norm, and perceived behavioural control positively, which affected the adoption intention. Specifically, the variable with the highest estimate loading factor was found to be the perceived behavioural control, and, the most important belief related to each construct was determined (e.g., energy saving was observed to be the most significant belief linked with attitude). Further investigation indicated that the added exogenous variable has a negative influence on intention; this finding confirmed partially the hypothesis, since this influence was indirect: such relationship was mediated by attitude. Implications and suggestions for future research are discussed.

Keywords: Adoption of innovation, consumers behaviour, energy management, smart grid, theory of planned behaviour.

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1098 Emotional Security in Relationship to Tikrit University Students' Emotional Efficiency

Authors: Ibtisam Mahmoud Mohammed Sultan

Abstract:

The present research aims at identifying the level of both emotional security and emotional competence among Tikrit University students. It also meant to know the statistically significant differences according to variables such as gender variables (m-f) and specialization variables (scientific-humanities). The research also attempts to learn what kind of relationship is there between emotional security and emotional efficiency Tikrit University students have achieved. We constructed emotional security measure which consists of 54 items as well as a measure of emotional competence consisting of 46 items. We extracted full psychometric characteristics of both scales. The research sample consisted of 600 students selected randomly and applying the scales on a basic research sample and processed statistical data using a variety of methods, including statistical measure Pearson correlation coefficient, we found a set of results as follows: Tikrit University students possess a high level of emotional security, males enjoy more emotional security than females, there is no difference between students of scientific and humanitarian specialization in variable emotional security, Tikrit University students enjoy a high level of emotional competence, females outperform males in emotional competence level, the humanitarian specialization students excel in emotional competence more than those specialized in non-humanitarian sciences. Furthermore, the research comes up with a positive correlative relationship between these two variables. Through research results, we developed a set of conclusions, proposals, and recommendations.

Keywords: Emotional security, gender variable, specialization variable, Tikrit University students.

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1097 Anticipation of Bending Reinforcement Based on Iranian Concrete Code Using Meta-Heuristic Tools

Authors: Seyed Sadegh Naseralavi, Najmeh Bemani

Abstract:

In this paper, different concrete codes including America, New Zealand, Mexico, Italy, India, Canada, Hong Kong, Euro Code and Britain are compared with the Iranian concrete design code. First, by using Adaptive Neuro Fuzzy Inference System (ANFIS), the codes having the most correlation with the Iranian ninth issue of the national regulation are determined. Consequently, two anticipated methods are used for comparing the codes: Artificial Neural Network (ANN) and Multi-variable regression. The results show that ANN performs better. Predicting is done by using only tensile steel ratio and with ignoring the compression steel ratio.

Keywords: Concrete design code, anticipate method, artificial neural network, multi-variable regression, adaptive neuro fuzzy inference system.

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1096 Performance of Random Diagonal Codes for Spectral Amplitude Coding Optical CDMA Systems

Authors: Hilal A. Fadhil, Syed A. Aljunid, R. Badlishah Ahmed

Abstract:

In this paper we study the use of a new code called Random Diagonal (RD) code for Spectral Amplitude Coding (SAC) optical Code Division Multiple Access (CDMA) networks, using Fiber Bragg-Grating (FBG), FBG consists of a fiber segment whose index of reflection varies periodically along its length. RD code is constructed using code level and data level, one of the important properties of this code is that the cross correlation at data level is always zero, which means that Phase intensity Induced Phase (PIIN) is reduced. We find that the performance of the RD code will be better than Modified Frequency Hopping (MFH) and Hadamard code It has been observed through experimental and theoretical simulation that BER for RD code perform significantly better than other codes. Proof –of-principle simulations of encoding with 3 channels, and 10 Gbps data transmission have been successfully demonstrated together with FBG decoding scheme for canceling the code level from SAC-signal.

Keywords: FBG, MFH, OCDMA, PIIN, BER.

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1095 Multivariate Analysis of Spectroscopic Data for Agriculture Applications

Authors: Asmaa M. Hussein, Amr Wassal, Ahmed Farouk Al-Sadek, A. F. Abd El-Rahman

Abstract:

In this study, a multivariate analysis of potato spectroscopic data was presented to detect the presence of brown rot disease or not. Near-Infrared (NIR) spectroscopy (1,350-2,500 nm) combined with multivariate analysis was used as a rapid, non-destructive technique for the detection of brown rot disease in potatoes. Spectral measurements were performed in 565 samples, which were chosen randomly at the infection place in the potato slice. In this study, 254 infected and 311 uninfected (brown rot-free) samples were analyzed using different advanced statistical analysis techniques. The discrimination performance of different multivariate analysis techniques, including classification, pre-processing, and dimension reduction, were compared. Applying a random forest algorithm classifier with different pre-processing techniques to raw spectra had the best performance as the total classification accuracy of 98.7% was achieved in discriminating infected potatoes from control.

Keywords: Brown rot disease, NIR spectroscopy, potato, random forest.

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1094 An Enhanced Particle Swarm Optimization Algorithm for Multiobjective Problems

Authors: Houda Abadlia, Nadia Smairi, Khaled Ghedira

Abstract:

Multiobjective Particle Swarm Optimization (MOPSO) has shown an effective performance for solving test functions and real-world optimization problems. However, this method has a premature convergence problem, which may lead to lack of diversity. In order to improve its performance, this paper presents a hybrid approach which embedded the MOPSO into the island model and integrated a local search technique, Variable Neighborhood Search, to enhance the diversity into the swarm. Experiments on two series of test functions have shown the effectiveness of the proposed approach. A comparison with other evolutionary algorithms shows that the proposed approach presented a good performance in solving multiobjective optimization problems.

Keywords: Particle swarm optimization, migration, variable neighborhood search, multiobjective optimization.

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1093 Existence of Periodic Solution for p-Laplacian Neutral Rayleigh Equation with Sign-variable Coefficient of Non Linear Term

Authors: Aomar Anane, Omar Chakrone, Loubna Moutaouekkil

Abstract:

As p-Laplacian equations have been widely applied in field of the fluid mechanics and nonlinear elastic mechanics, it is necessary to investigate the periodic solutions of functional differential equations involving the scalar p-Laplacian. By using Mawhin’s continuation theorem, we study the existence of periodic solutions for p-Laplacian neutral Rayleigh equation (ϕp(x(t)−c(t)x(t − r))) + f(x(t)) + g1(x(t − τ1(t, |x|∞))) + β(t)g2(x(t − τ2(t, |x|∞))) = e(t), It is meaningful that the functions c(t) and β(t) are allowed to change signs in this paper, which are different from the corresponding ones of known literature.

Keywords: periodic solution, neutral Rayleigh equation, variable sign, Deviating argument, p-Laplacian, Mawhin’s continuation.

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1092 Performance, Emission and Combustion Characteristics of a Variable Compression Ratio Diesel Engine Fueled with Karanj Biodiesel and Its Blends

Authors: Ajay V. Kolhe, R. E. Shelke, S. S. Khandare

Abstract:

The use of biodiesel in conventional diesel engines results in substantial reduction of unburned hydrocarbon, carbon monoxide and particulate matters. The performance, emission and combustion characteristics of a single cylinder four stroke variable compression ratio engine when fueled with Karanja (Pongamia) methyl ester and its 10-50 % blends with diesel (on a volume basis) are investigated and compared with standard diesel. The suitability of karanja methyl ester as a biofuel has been established in this study. The useful brake power obtained is similar to diesel fuel for all loads. Experiment has been conducted at a fixed engine speed of 1500 rpm, variable load and at compression ratios of 17.5:1 and 18.5:1. The impact of compression ratio on fuel consumption, combustion pressures and exhaust gas emissions has been investigated and presented. Optimum compression ratio which gives best performance has been identified. The results indicate longer ignition delay, maximum rate of pressure rise, lower heat release rate and higher mass fraction burnt at higher compression ratio for pongamia oil methyl ester when compared to that of diesel. The brake thermal efficiency for pongamia oil methyl ester blends and diesel has been calculated and the blend B20 is found to give maximum thermal efficiency. The blends when used as fuel results in reduction of carbon monoxide, hydrocarbon and increase in nitrogen oxides emissions. PME as an oxygenated fuel generated more complete combustion, which means increased torque and power. This is also supported with higher thermal efficiencies of the PME blends. NOx is slightly increased due to the higher combustion temperature and the presence of fuel oxygen with the blend at full load. PME as a new Biodiesel and its blends can be used in diesel engines without any engine modification.

Keywords: Variable compression ratio CI engine, performance, combustion, emissions, biodiesel.

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1091 Sensorless Sliding Power Control of Doubly Fed Induction Wind Generator Based on MRAS Observer

Authors: Hicham Serhoud, Djilani Benattous

Abstract:

In this paper present a sensorless maximum wind power extraction for variable speed constant frequency (VSCF) wind power generation systems with a doubly-fed induction generators (DFIG), to ensure stability and to impose the ideal feedback control solution despite of model uncertainties , using the principles of an active and reactive power controller (DPC) a robust sliding mode power control has been proposed to guarantees fast response times and precise control actions for control the active and reactive power independently. The simulation results in MATLAB/Simulink platform confirmed the good dynamic performance of power control approach for DFIGbased variable speed wind turbines.

Keywords: Doubly fed induction generator , sliding modecontrol, maximal wind energy capture, MRAS estimator

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1090 Students´ Knowledge, or Random Choice in ESP?

Authors: Ivana Šimonová

Abstract:

As widely accepted, didactic multiple-choice tests are referred as a tool providing feedback easily and quickly. Despite the final test scores are corrected by a special formula and number of high plausibility distractors is taken into consideration, the results may be influenced by the random choice. The survey was held in three academic years at the Faculty of Informatics and Management, University of Hradec Kralove, Czech Republic, where the multiple-choice test scores were compared to the open-answer ones. The research sample included 567 respondents. The collected data were processed by the NCSS2007 statistic software by the method of frequency and multiple regression analysis and presented in the form of figures and tables. The results proved statistically significant differences in test scores in academic years 2 and 3, and were discussed from the point of the credit system and conditions for teaching/learning English in the Czech education system.

Keywords: ESP, higher education, multiple-choice test, open-answer test.

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