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.

Robust Position Control of an Electromechanical Actuator for Automotive Applications

In this paper, the position control of an electronic throttle actuator is outlined. The dynamic behavior of the actuator is described with the help of an uncertain plant model. This motivates the controller design based on the ideas of higher-order slidingmodes. As a consequence anti-chattering techniques can be omitted. It is shown that the same concept is applicable to estimate unmeasureable signals. The control law and the observer are implemented on an electronic control unit. Results achieved by numerical simulations and real world experiments are presented and discussed.

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.

A Clock Skew Minimization Technique Considering Temperature Gradient

The trend of growing density on chips has increases not only the temperature in chips but also the gradient of the temperature depending on locations. In this paper, we propose the balanced skew tree generation technique for minimizing the clock skew that is affected by the temperature gradients on chips. We calculate the interconnect delay using Elmore delay equation, and find out the optimal balanced clock tree by modifying the clock trees generated through the Deferred Merge Embedding(DME) algorithm. The experimental results show that the distance variance of clock insertion points with and without considering the temperature gradient can be lowered below 54% and we confirm that the skew is remarkably decreased after applying the proposed technique.

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.

Approximate Frequent Pattern Discovery Over Data Stream

Frequent pattern discovery over data stream is a hard problem because a continuously generated nature of stream does not allow a revisit on each data element. Furthermore, pattern discovery process must be fast to produce timely results. Based on these requirements, we propose an approximate approach to tackle the problem of discovering frequent patterns over continuous stream. Our approximation algorithm is intended to be applied to process a stream prior to the pattern discovery process. The results of approximate frequent pattern discovery have been reported in the paper.

Algorithm for Reconstructing 3D-Binary Matrix with Periodicity Constraints from Two Projections

We study the problem of reconstructing a three dimensional binary matrices whose interiors are only accessible through few projections. Such question is prominently motivated by the demand in material science for developing tool for reconstruction of crystalline structures from their images obtained by high-resolution transmission electron microscopy. Various approaches have been suggested to reconstruct 3D-object (crystalline structure) by reconstructing slice of the 3D-object. To handle the ill-posedness of the problem, a priori information such as convexity, connectivity and periodicity are used to limit the number of possible solutions. Formally, 3Dobject (crystalline structure) having a priory information is modeled by a class of 3D-binary matrices satisfying a priori information. We consider 3D-binary matrices with periodicity constraints, and we propose a polynomial time algorithm to reconstruct 3D-binary matrices with periodicity constraints from two orthogonal projections.

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.

The Recession as an Opportunity for Curbing Transport Emissions

The effects of the transport sector on the environment are a well-recognized issue in the European Union and around the world. This area is a subject of much discussion as to how these negative effects could be minimized, especially with regards to impacts contributing to climate change. This paper aims to investigate the results of the economic crisis and how its consequences could be exploited to combat air pollution.

Visual Study on Flow Patterns and Heat Transfer during Convective Boiling Inside Horizontal Smooth and Microfin Tubes

Evaporator is an important and widely used heat exchanger in air conditioning and refrigeration industries. Different methods have been used by investigators to increase the heat transfer rates in evaporators. One of the passive techniques to enhance heat transfer coefficient is the application of microfin tubes. The mechanism of heat transfer augmentation in microfin tubes is dependent on the flow regime of two-phase flow. Therefore many investigations of the flow patterns for in-tube evaporation have been reported in literatures. The gravitational force, surface tension and the vapor-liquid interfacial shear stress are known as three dominant factors controlling the vapor and liquid distribution inside the tube. A review of the existing literature reveals that the previous investigations were concerned with the two-phase flow pattern for flow boiling in horizontal tubes [12], [9]. Therefore, the objective of the present investigation is to obtain information about the two-phase flow patterns for evaporation of R-134a inside horizontal smooth and microfin tubes. Also Investigation of heat transfer during flow boiling of R-134a inside horizontal microfin and smooth tube have been carried out experimentally The heat transfer coefficients for annular flow in the smooth tube is shown to agree well with Gungor and Winterton-s correlation [4]. All the flow patterns occurred in the test can be divided into three dominant regimes, i.e., stratified-wavy flow, wavy-annular flow and annular flow. Experimental data are plotted in two kinds of flow maps, i.e., Weber number for the vapor versus weber number for the liquid flow map and mass flux versus vapor quality flow map. The transition from wavy-annular flow to annular or stratified-wavy flow is identified in the flow maps.

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).

Operation Stability Enhancement in Once-Through Micro Evaporators

Equipment miniaturisation offers several opportunities such as an increased surface-to-volume ratio and higher heat transfer coefficients. However, moving towards small-diameter channels demands extra attention to fouling, reliability and stable operation of the system. The present investigation explores possibilities to enhance the stability of the once-through micro evaporator by reducing its flow boiling induced pressure fluctuations. Experimental comparison shows that the measured reduction factor approaches a theoretically derived value. Pressure fluctuations are reduced by a factor of ten in the solid conical channel and a factor of 15 in the porous conical channel. This presumably leads to less backflow and therefore to a better flow control.

An Example of Post-Harvest Thermotherapy as a Non-Chemical Method of Pathogen Control on Apples of Topaz Cultivar in Storage

Huge losses in apple production are caused by pathogens that cannot be seen shortly after harvest. After-harvest thermotherapy treatments can considerably improve control of storage diseases on apples and become an alternative to chemical pesticides. In the years 2010-2012 carried out research in this area. Apples of 'Topaz' cultivar were harvested at optimal maturity time for long storage and subject to water bath treatment at 45, 50, 52, 55°C for 60, 120, 180 and 240 seconds. The control was untreated fruits. After 12 and 24 weeks and during so called simulated trade turnover the fruits were checked for their condition and the originators of diseases were determined by using the standard phytopathological methods. The most common originator of 'Topaz' apple infection during storage were the fungi of genus Gloeosporium. In this paper it was proven that for effective protection of 'Topaz' apples against diseases, thermotherapy by using water treatments at temperature range of 50-52°C is quite sufficient.

Robot Path Planning in 3D Space Using Binary Integer Programming

This paper presents a novel algorithm for path planning of mobile robots in known 3D environments using Binary Integer Programming (BIP). In this approach the problem of path planning is formulated as a BIP with variables taken from 3D Delaunay Triangulation of the Free Configuration Space and solved to obtain an optimal channel made of connected tetrahedrons. The 3D channel is then partitioned into convex fragments which are used to build safe and short paths within from Start to Goal. The algorithm is simple, complete, does not suffer from local minima, and is applicable to different workspaces with convex and concave polyhedral obstacles. The noticeable feature of this algorithm is that it is simply extendable to n-D Configuration spaces.