Testing the Accuracy of ML-ANN for Harmonic Estimation in Balanced Industrial Distribution Power System

In this paper, we analyze and test a scheme for the estimation of electrical fundamental frequency signals from the harmonic load current and voltage signals. The scheme was based on using two different Multi Layer Artificial Neural Networks (ML-ANN) one for the current and the other for the voltage. This study also analyzes and tests the effect of choosing the optimum artificial neural networks- sizes which determine the quality and accuracy of the estimation of electrical fundamental frequency signals. The simulink tool box of the Matlab program for the simulation of the test system and the test of the neural networks has been used.

Effects of Polluted Water on the Metallic Water Pipelines

Corrosion of metallic water pipelines buried below ground surface is a function of the nature of the surrounding soil and groundwater. This gives the importance of knowing the physical and chemical characteristics of the pipe-s surrounding environment. The corrosion of externally – unprotected metallic water pipelines, specially ductile iron pipes, in localities with aggressive soil conditions is becoming a significant problem. Anticorrosive protection for metallic water pipelines, their fittings and accessories is very important, because they may be attached by corrosion with time. The tendency of a metallic substrate to corrode is a function of the surface characteristics of the metal and of the metal/protective film interface, the physical, electrical and electrochemical properties of the film, and the nature of the environment in which the pipelines system is placed. In this work the authors have looked at corrosion problems of water pipelines and their control. The corrosive properties of groundwater and soil environments are reviewed, and parameters affecting corrosion are discussed. The purpose of this work is to provide guidelines for materials selection in water and soil environments, and how the water pipelines can be protected against metallic corrosion.

The Study of Chain Initiation Effect on the Direct Initiation of Detonation

In this research, effect of combustion reaction mechanism on direct initiation of detonation has been studied numerically. For this purpose, reaction mechanism has been simulated by using a three-step chemical kinetics model. The reaction scheme consists sequentially of a chain-initiation and chainbranching step, followed by a temperature -independent chaintermination. In a previous research, the effect of chain-branching on the direct initiation of detonation is studied. In this research effect of chain-initiation on direct initiation of detonation is investigated. For the investigation, first a characteristic time (τ) for each step of mechanism, which includes effect of different kinetics parameters, is defined. Then the effect of characteristic time of chain-initiation (τI) on critical initiation energy is studied. It is seen that increasing τI, causes critical initiation energy to be increased. Drawing detonation's shock pressure diagrams for different cases, shows that in small value of τI , kinetics has more important effect on the behavior of the wave.

Abrupt Scene Change Detection

A number of automated shot-change detection methods for indexing a video sequence to facilitate browsing and retrieval have been proposed in recent years. This paper emphasizes on the simulation of video shot boundary detection using one of the methods of the color histogram wherein scaling of the histogram metrics is an added feature. The difference between the histograms of two consecutive frames is evaluated resulting in the metrics. Further scaling of the metrics is performed to avoid ambiguity and to enable the choice of apt threshold for any type of videos which involves minor error due to flashlight, camera motion, etc. Two sample videos are used here with resolution of 352 X 240 pixels using color histogram approach in the uncompressed media. An attempt is made for the retrieval of color video. The simulation is performed for the abrupt change in video which yields 90% recall and precision value.

Applications of Support Vector Machines on Smart Phone Systems for Emotional Speech Recognition

An emotional speech recognition system for the applications on smart phones was proposed in this study to combine with 3G mobile communications and social networks to provide users and their groups with more interaction and care. This study developed a mechanism using the support vector machines (SVM) to recognize the emotions of speech such as happiness, anger, sadness and normal. The mechanism uses a hierarchical classifier to adjust the weights of acoustic features and divides various parameters into the categories of energy and frequency for training. In this study, 28 commonly used acoustic features including pitch and volume were proposed for training. In addition, a time-frequency parameter obtained by continuous wavelet transforms was also used to identify the accent and intonation in a sentence during the recognition process. The Berlin Database of Emotional Speech was used by dividing the speech into male and female data sets for training. According to the experimental results, the accuracies of male and female test sets were increased by 4.6% and 5.2% respectively after using the time-frequency parameter for classifying happy and angry emotions. For the classification of all emotions, the average accuracy, including male and female data, was 63.5% for the test set and 90.9% for the whole data set.

Characterization of Electrohydrodynamic Force on Dielectric-Barrier-Discharge Plasma Actuator Using Fluid Simulation

Wall-surface jet induced by the dielectric barrier discharge (DBD) has been proposed as an actuator for active flow control in aerodynamic applications. Discharge plasma evolution of the DBD plasma actuator was simulated based on a simple fluid model, in which the electron, one type of positive ion and negative ion were taken into account. Two-dimensional simulation was conducted, and the results are in agreement with the insights obtained from experimental studies. The simulation results indicate that the discharge mode changes depending on applied voltage slope; when the applied voltage is positive-going with high applied voltage slope, the corona-type discharge mode turns into the streamer-type discharge mode and the threshold voltage slope is around 300 kV/ms in this simulation. The characteristics of the electrohydrodynamic (EHD) force, which is the source of the wall-surface jet, also change depending on the discharge mode; the tentative peak value of the EHD force during the positive-going voltage phase is saturated by the periodical formation of the streamer-type discharge.

Effect of Cooled EGR in Combustion Characteristics of a Direct Injection CI Engine Fuelled with Biodiesel Blend

As the demand and prices of various petroleum products have been on the rise in recent years, there is a growing need for alternative fuels. Biodiesel, which consists of alkyl monoesters of fatty acids from vegetable oils and animal fats, is considered as an alternative to petroleum diesel. Biodiesel has comparable performance with that of diesel and has lower brake specific fuel consumption than diesel with significant reduction in emissions of CO, hydrocarbons (HC) and smoke with however, a slight increase in NOx emissions. This paper analyzes the effect of cooled exhaust gas recirculation in the combustion characteristics of a direct injection compression ignition engine using biodiesel blended fuel as opposed to the conventional system. The combustion parameters such as cylinder pressure, heat release rate, delay period and peak pressure were analyzed at various loads. The maximum cylinder pressure reduces as the fraction of biodiesel increases in the blend the maximum rate of pressure rise was found to be higher for diesel at higher engine loads.

A Recommender Agent to Support Virtual Learning Activities

This article describes the implementation of an intelligent agent that provides recommendations for educational resources in a virtual learning environment (VLE). It aims to support pending (undeveloped) student learning activities. It begins by analyzing the proposed VLE data model entities in the recommender process. The pending student activities are then identified, which constitutes the input information for the agent. By using the attribute-based recommender technique, the information can be processed and resource recommendations can be obtained. These serve as support for pending activity development in the course. To integrate this technique, we used an ontology. This served as support for the semantic annotation of attributes and recommended files recovery.

Is Cognitive Dissonance an Intrinsic Property of the Human Mind? An Experimental Solution to a Half-Century Debate

Cognitive Dissonance can be conceived both as a concept related to the tendency to avoid internal contradictions in certain situations, and as a higher order theory about information processing in the human mind. In the last decades, this last sense has been strongly surpassed by the former, as nearly all experiment on the matter discuss cognitive dissonance as an output of motivational contradictions. In that sense, the question remains: is cognitive dissonance a process intrinsically associated with the way that the mind processes information, or is it caused by such specific contradictions? Objective: To evaluate the effects of cognitive dissonance in the absence of rewards or any mechanisms to manipulate motivation. Method: To solve this question, we introduce a new task, the hypothetical social arrays paradigm, which was applied to 50 undergraduate students. Results: Our findings support the perspective that the human mind shows a tendency to avoid internal dissonance even when there are no rewards or punishment involved. Moreover, our findings also suggest that this principle works outside the conscious level.

A Genetic-Algorithm-Based Approach for Audio Steganography

In this paper, we present a novel, principled approach to resolve the remained problems of substitution technique of audio steganography. Using the proposed genetic algorithm, message bits are embedded into multiple, vague and higher LSB layers, resulting in increased robustness. The robustness specially would be increased against those intentional attacks which try to reveal the hidden message and also some unintentional attacks like noise addition as well.

Solving the Economic Dispatch Problem using Novel Particle Swarm Optimization

This paper proposes an improved approach based on conventional particle swarm optimization (PSO) for solving an economic dispatch(ED) problem with considering the generator constraints. The mutation operators of the differential evolution (DE) are used for improving diversity exploration of PSO, which called particle swarm optimization with mutation operators (PSOM). The mutation operators are activated if velocity values of PSO nearly to zero or violated from the boundaries. Four scenarios of mutation operators are implemented for PSOM. The simulation results of all scenarios of the PSOM outperform over the PSO and other existing approaches which appeared in literatures.

CO2 Abatement by Methanol Production from Flue-Gas in Methanol Plant

This study investigates CO2 mitigation by methanol synthesis from flue gas CO2 and H2 generation through water electrolysis. Electrolytic hydrogen generation is viable provided that the required electrical power is supplied from renewable energy resources; whereby power generation from renewable resources is yet commercial challenging. This approach contribute to zero-emission, moreover it produce oxygen which could be used as feedstock for chemical process. At ZPC, however, oxygen would be utilized through partial oxidation of methane in autothermal reactor (ATR); this makes ease the difficulties of O2 delivery and marketing. On the other hand, onboard hydrogen storage and consumption; in methanol plant; make the project economically more competitive.

Animated Versus Static User Interfaces: A Study of Mathsigner™

In this paper we report a study aimed at determining the effects of animation on usability and appeal of educational software user interfaces. Specifically, the study compares 3 interfaces developed for the Mathsigner™ program: a static interface, an interface with highlighting/sound feedback, and an interface that incorporates five Disney animation principles. The main objectives of the comparative study were to: (1) determine which interface is the most effective for the target users of Mathsigner™ (e.g., children ages 5-11), and (2) identify any Gender and Age differences in using the three interfaces. To accomplish these goals we have designed an experiment consisting of a cognitive walkthrough and a survey with rating questions. Sixteen children ages 7-11 participated in the study, ten males and six females. Results showed no significant interface effect on user task performance (e.g., task completion time and number of errors); however, interface differences were seen in rating of appeal, with the animated interface rated more 'likeable' than the other two. Task performance and rating of appeal were not affected significantly by Gender or Age of the subjects.

Linear Stability of Convection in a Viscoelastic Nanofluid Layer

This paper presents a linear stability analysis of natural convection in a horizontal layer of a viscoelastic nanofluid. The Oldroyd B model was utilized to describe the rheological behavior of a viscoelastic nanofluid. The model used for the nanofluid incorporated the effects of Brownian motion and thermophoresis. The onset criterion for stationary and oscillatory convection was derived analytically. The effects of the Deborah number, retardation parameters, concentration Rayleigh number, Prandtl number, and Lewis number on the stability of the system were investigated. Results indicated that there was competition among the processes of thermophoresis, Brownian diffusion, and viscoelasticity which caused oscillatory rather than stationary convection to occur. Oscillatory instability is possible with both bottom- and top-heavy nanoparticle distributions. Regimes of stationary and oscillatory convection for various parameters were derived and are discussed in detail.

Unscented Transformation for Estimating the Lyapunov Exponents of Chaotic Time Series Corrupted by Random Noise

Many systems in the natural world exhibit chaos or non-linear behavior, the complexity of which is so great that they appear to be random. Identification of chaos in experimental data is essential for characterizing the system and for analyzing the predictability of the data under analysis. The Lyapunov exponents provide a quantitative measure of the sensitivity to initial conditions and are the most useful dynamical diagnostic for chaotic systems. However, it is difficult to accurately estimate the Lyapunov exponents of chaotic signals which are corrupted by a random noise. In this work, a method for estimation of Lyapunov exponents from noisy time series using unscented transformation is proposed. The proposed methodology was validated using time series obtained from known chaotic maps. In this paper, the objective of the work, the proposed methodology and validation results are discussed in detail.

The Relationship between Sheep Management and Lamb Mortality

This study was carried out to investigate lamb mortalities relating to ewes' breed and some managemental factors on 250 pregnant ewes (190-Rahmani, 30-Ossimi and 30-Romanov) at Mehallet Mousa, Animal Production Research Station, Kafr El- Sheikh Province, Egypt. These animals divided into five groups according to the managemental factors used. The results revealed that the lamb mortality was higher in Ossimi breed and lower in Romanov one. In addition, the highest lamb mortality occurred among lambs for unsupplemented ewes, for those had body condition score two and for lambs which born outdoor. Moreover, the lamb survivability was increased by the parity of ewes. From this study it can be concluded that the lamb mortality depends on ewes' body condition score, parity, lambing system (indoor or outdoor), nutrition during pregnancy period and selected breed. In addition, the most important period for lamb survival is the first week of age.

On the outlier Detection in Nonlinear Regression

The detection of outliers is very essential because of their responsibility for producing huge interpretative problem in linear as well as in nonlinear regression analysis. Much work has been accomplished on the identification of outlier in linear regression, but not in nonlinear regression. In this article we propose several outlier detection techniques for nonlinear regression. The main idea is to use the linear approximation of a nonlinear model and consider the gradient as the design matrix. Subsequently, the detection techniques are formulated. Six detection measures are developed that combined with three estimation techniques such as the Least-Squares, M and MM-estimators. The study shows that among the six measures, only the studentized residual and Cook Distance which combined with the MM estimator, consistently capable of identifying the correct outliers.

Bifurcation Method for Solving Positive Solutions to a Class of Semilinear Elliptic Equations and Stability Analysis of Solutions

Semilinear elliptic equations are ubiquitous in natural sciences. They give rise to a variety of important phenomena in quantum mechanics, nonlinear optics, astrophysics, etc because they have rich multiple solutions. But the nontrivial solutions of semilinear equations are hard to be solved for the lack of stabilities, such as Lane-Emden equation, Henon equation and Chandrasekhar equation. In this paper, bifurcation method is applied to solving semilinear elliptic equations which are with homogeneous Dirichlet boundary conditions in 2D. Using this method, nontrivial numerical solutions will be computed and visualized in many different domains (such as square, disk, annulus, dumbbell, etc).

Preliminary Chaos Analyses of Explosion Earthquakes Followed by Harmonic Tremors at Semeru Volcano, East Java, Indonesia

Successive event of explosion earthquake and harmonic tremor recorded at Semeru volcano were analyzed to investigate the dynamical system regarding to their eruptive mechanism. The eruptive activity at Semeru volcano East Java, Indonesia is intermittent emission of ash and bombs with Strombolian style which occurred at interval of 15 to 45 minutes. The explosive eruptions accompanied by explosion earthquakes and followed by volcanic tremor which generated by continuous emission of volcanic ash. The spectral and Lyapunov exponent of successive event of explosion and harmonic tremor were analyzed. Peak frequencies of explosion earthquakes range 1.2 to 1.9 Hz and those of the harmonic tremor have peak frequency range 1.5 — 2.2 Hz. The phase space is reconstructed and evaluated based on the Lyapunov exponents. Harmonic tremors have smaller Lyapunov exponent than explosion earthquakes. It can be considerably as correlated complexity of the mechanism from the variance of spectral and fractal dimension and can be concluded that the successive event of harmonic tremor and explosions are chaotic.

Delay Preserving Substructures in Wireless Networks Using Edge Difference between a Graph and its Square Graph

In practice, wireless networks has the property that the signal strength attenuates with respect to the distance from the base station, it could be better if the nodes at two hop away are considered for better quality of service. In this paper, we propose a procedure to identify delay preserving substructures for a given wireless ad-hoc network using a new graph operation G 2 – E (G) = G* (Edge difference of square graph of a given graph and the original graph). This operation helps to analyze some induced substructures, which preserve delay in communication among them. This operation G* on a given graph will induce a graph, in which 1- hop neighbors of any node are at 2-hop distance in the original network. In this paper, we also identify some delay preserving substructures in G*, which are (i) set of all nodes, which are mutually at 2-hop distance in G that will form a clique in G*, (ii) set of nodes which forms an odd cycle C2k+1 in G, will form an odd cycle in G* and the set of nodes which form a even cycle C2k in G that will form two disjoint companion cycles ( of same parity odd/even) of length k in G*, (iii) every path of length 2k+1 or 2k in G will induce two disjoint paths of length k in G*, and (iv) set of nodes in G*, which induces a maximal connected sub graph with radius 1 (which identifies a substructure with radius equal 2 and diameter at most 4 in G). The above delay preserving sub structures will behave as good clusters in the original network.