Comparative Study of Virtual Sickness between a Single-screen and Three-screen from Parallax Affect

Virtual environment induces simulator sickness effect for some users. The purpose of this research is to compare the simulation sickness relative with parallax affect in one-screen and three-screen HoloStageTM system, measured by Simulation Sickness Questionnaire (SSQ). The results show the subjects tested in three-screen has less sickness than one-screen and effect from the Oculomotor (O) more than from the Disorientation (D) and more than from the Nausea (N) or represented in O>D>N.

Design of Genetic-Algorithm Based Robust Power System Stabilizer

This paper presents a systematic approach for the design of power system stabilizer using genetic algorithm and investigates the robustness of the GA based PSS. The proposed approach employs GA search for optimal setting of PSS parameters. The performance of the proposed GPSS under small and large disturbances, loading conditions and system parameters is tested. The eigenvalue analysis and nonlinear simulation results show the effectiveness of the GPSS to damp out the system oscillations. It is found tat the dynamic performance with the GPSS shows improved results, over conventionally tuned PSS over a wide range of operating conditions.

Effect of Adaptation Gain on system Performance for Model Reference Adaptive Control Scheme using MIT Rule

Adaptive control involves modifying the control law used by the controller to cope with the fact that the parameters of the system being controlled change drastically due to change in environmental conditions or in system itself. This technique is based on the fundamental characteristic of adaptation of living organism. The adaptive control process is one that continuously and automatically measures the dynamic behavior of plant, compares it with the desired output and uses the difference to vary adjustable system parameters or to generate an actuating signal in such a way so that optimal performance can be maintained regardless of system changes. This paper deals with application of model reference adaptive control scheme in first order system. The rule which is used for this application is MIT rule. This paper also shows the effect of adaptation gain on the system performance. Simulation is done in MATLAB and results are discussed in detail.

Embedded Singly Diagonally Implicit Runge-Kutta –Nystrom Method Order 5(4) for the Integration of Special Second Order ODEs

In this paper a new embedded Singly Diagonally Implicit Runge-Kutta Nystrom fourth order in fifth order method for solving special second order initial value problems is derived. A standard set of test problems are tested upon and comparisons on the numerical results are made when the same set of test problems are reduced to first order systems and solved using the existing embedded diagonally implicit Runge-Kutta method. The results suggests the superiority of the new method.

Investigation of New Method to Achieve Well Dispersed Multiwall Carbon Nanotubes Reinforced Al Matrix Composites

Nanostructured materials have attracted many researchers due to their outstanding mechanical and physical properties. For example, carbon nanotubes (CNTs) or carbon nanofibres (CNFs) are considered to be attractive reinforcement materials for light weight and high strength metal matrix composites. These composites are being projected for use in structural applications for their high specific strength as well as functional materials for their exciting thermal and electrical characteristics. The critical issues of CNT-reinforced MMCs include processing techniques, nanotube dispersion, interface, strengthening mechanisms and mechanical properties. One of the major obstacles to the effective use of carbon nanotubes as reinforcements in metal matrix composites is their agglomeration and poor distribution/dispersion within the metallic matrix. In order to tap into the advantages of the properties of CNTs (or CNFs) in composites, the high dispersion of CNTs (or CNFs) and strong interfacial bonding are the key issues which are still challenging. Processing techniques used for synthesis of the composites have been studied with an objective to achieve homogeneous distribution of carbon nanotubes in the matrix. Modified mechanical alloying (ball milling) techniques have emerged as promising routes for the fabrication of carbon nanotube (CNT) reinforced metal matrix composites. In order to obtain a homogeneous product, good control of the milling process, in particular control of the ball movement, is essential. The control of the ball motion during the milling leads to a reduction in grinding energy and a more homogeneous product. Also, the critical inner diameter of the milling container at a particular rotational speed can be calculated. In the present work, we use conventional and modified mechanical alloying to generate a homogenous distribution of 2 wt. % CNT within Al powders. 99% purity Aluminium powder (Acros, 200mesh) was used along with two different types of multiwall carbon nanotube (MWCNTs) having different aspect ratios to produce Al-CNT composites. The composite powders were processed into bulk material by compaction, and sintering using a cylindrical compaction and tube furnace. Field Emission Scanning electron microscopy (FESEM), X-Ray diffraction (XRD), Raman spectroscopy and Vickers macro hardness tester were used to evaluate CNT dispersion, powder morphology, CNT damage, phase analysis, mechanical properties and crystal size determination. Despite the success of ball milling in dispersing CNTs in Al powder, it is often accompanied with considerable strain hardening of the Al powder, which may have implications on the final properties of the composite. The results show that particle size and morphology vary with milling time. Also, by using the mixing process and sonication before mechanical alloying and modified ball mill, dispersion of the CNTs in Al matrix improves.

Ripper and Sugar Effects on Hydroxymethylfurfural Formation in Gingerbread Biscuits

Hydroxymethylfurfural (HMF) is formed by thermally treating products rich in carbohydrates. HMF and other furan derivatives are toxic. The aim of the research was to establish the content of HMF in gingerbread biscuits with honey and sugar syrup additives by using three leavening agents— ammonium carbonate (NH4HCO3 and (NH4)2CO3), baking powder, and baking soda (NaHCO3). The content of HMF is significantly affected by the leavening agent used. The content of HMF with honey where ammonium carbonate was used as additive range from 5.7 to 27.3mg 100g-1, but when sugar syrup is used the content varies from 2.3 to 7.4mg 100g-1. When baking powder and baking soda are used as leavening agents, the content of HMF exceeds 4mg 100g-1 in the event honey had been added and the baking time had been longer (10 minutes at 180°C or 9 minutes at 200°C).

A NXM Version of 5X5 Playfair Cipher for any Natural Language (Urdu as Special Case)

In this paper a modified version NXM of traditional 5X5 playfair cipher is introduced which enable the user to encrypt message of any Natural language by taking appropriate size of the matrix depending upon the size of the natural language. 5X5 matrix has the capability of storing only 26 characters of English language and unable to store characters of any language having more than 26 characters. To overcome this limitation NXM matrix is introduced which solve this limitation. In this paper a special case of Urdu language is discussed. Where # is used for completing odd pair and * is used for repeating letters.

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

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.

Influence of Ambiguity Cluster on Quality Improvement in Image Compression

Image coding based on clustering provides immediate access to targeted features of interest in a high quality decoded image. This approach is useful for intelligent devices, as well as for multimedia content-based description standards. The result of image clustering cannot be precise in some positions especially on pixels with edge information which produce ambiguity among the clusters. Even with a good enhancement operator based on PDE, the quality of the decoded image will highly depend on the clustering process. In this paper, we introduce an ambiguity cluster in image coding to represent pixels with vagueness properties. The presence of such cluster allows preserving some details inherent to edges as well for uncertain pixels. It will also be very useful during the decoding phase in which an anisotropic diffusion operator, such as Perona-Malik, enhances the quality of the restored image. This work also offers a comparative study to demonstrate the effectiveness of a fuzzy clustering technique in detecting the ambiguity cluster without losing lot of the essential image information. Several experiments have been carried out to demonstrate the usefulness of ambiguity concept in image compression. The coding results and the performance of the proposed algorithms are discussed in terms of the peak signal-tonoise ratio and the quantity of ambiguous pixels.

Concrete Mix Design Using Neural Network

Basic ingredients of concrete are cement, fine aggregate, coarse aggregate and water. To produce a concrete of certain specific properties, optimum proportion of these ingredients are mixed. The important factors which govern the mix design are grade of concrete, type of cement and size, shape and grading of aggregates. Concrete mix design method is based on experimentally evolved empirical relationship between the factors in the choice of mix design. Basic draw backs of this method are that it does not produce desired strength, calculations are cumbersome and a number of tables are to be referred for arriving at trial mix proportion moreover, the variation in attainment of desired strength is uncertain below the target strength and may even fail. To solve this problem, a lot of cubes of standard grades were prepared and attained 28 days strength determined for different combination of cement, fine aggregate, coarse aggregate and water. An artificial neural network (ANN) was prepared using these data. The input of ANN were grade of concrete, type of cement, size, shape and grading of aggregates and output were proportions of various ingredients. With the help of these inputs and outputs, ANN was trained using feed forward back proportion model. Finally trained ANN was validated, it was seen that it gave the result with/ error of maximum 4 to 5%. Hence, specific type of concrete can be prepared from given material properties and proportions of these materials can be quickly evaluated using the proposed ANN.

Life Time Based Analysis of MAC Protocols of Wireless Ad Hoc Networks in WSN Applications

Wireless Sensor Networks (WSN) are emerging because of the developments in wireless communication technology and miniaturization of the hardware. WSN consists of a large number of low-cost, low-power, multifunctional sensor nodes to monitor physical conditions, such as temperature, sound, vibration, pressure, motion, etc. The MAC protocol to be used in the sensor networks must be energy efficient and this should aim at conserving the energy during its operation. In this paper, with the focus of analyzing the MAC protocols used in wireless Adhoc networks to WSN, simulation experiments were conducted in Global Mobile Simulator (GloMoSim) software. Number of packets sent by regular nodes, and received by sink node in different deployment strategies, total energy spent, and the network life time have been chosen as the metric for comparison. From the results of simulation, it is evident that the IEEE 802.11 protocol performs better compared to CSMA and MACA protocols.

Effect of Crystallographic Orientation on the Pitting Corrosion Resistance of Laser Surface Melted AISI 304L Austenitic Stainless Steel

The localized corrosion behavior of laser surface melted 304L austenitic stainless steel was studied by potentiodynamic polarization test. The extent of improvement in corrosion resistance was governed by the preferred orientation and the percentage of delta ferrite present on the surface of the laser melted sample. It was established by orientation imaging microscopy that the highest pitting potential value was obtained when grains were oriented in the most close- packed [101] direction compared to the random distribution of the base metal and other laser surface melted samples oriented in [001] direction. The sample with lower percentage of ferrite had good pitting resistance.

Predicting Bankruptcy using Tabu Search in the Mauritian Context

Throughout this paper, a relatively new technique, the Tabu search variable selection model, is elaborated showing how it can be efficiently applied within the financial world whenever researchers come across the selection of a subset of variables from a whole set of descriptive variables under analysis. In the field of financial prediction, researchers often have to select a subset of variables from a larger set to solve different type of problems such as corporate bankruptcy prediction, personal bankruptcy prediction, mortgage, credit scoring and the Arbitrage Pricing Model (APM). Consequently, to demonstrate how the method operates and to illustrate its usefulness as well as its superiority compared to other commonly used methods, the Tabu search algorithm for variable selection is compared to two main alternative search procedures namely, the stepwise regression and the maximum R 2 improvement method. The Tabu search is then implemented in finance; where it attempts to predict corporate bankruptcy by selecting the most appropriate financial ratios and thus creating its own prediction score equation. In comparison to other methods, mostly the Altman Z-Score model, the Tabu search model produces a higher success rate in predicting correctly the failure of firms or the continuous running of existing entities.

Application of GIS and Statistical Multivariate Techniques for Estimation of Soil Erosion and Sediment Yield

In recent years, most of the regions in the world are exposed to degradation and erosion caused by increasing population and over use of land resources. The understanding of the most important factors on soil erosion and sediment yield are the main keys for decision making and planning. In this study, the sediment yield and soil erosion were estimated and the priority of different soil erosion factors used in the MPSIAC method of soil erosion estimation is evaluated in AliAbad watershed in southwest of Isfahan Province, Iran. Different information layers of the parameters were created using a GIS technique. Then, a multivariate procedure was applied to estimate sediment yield and to find the most important factors of soil erosion in the model. The results showed that land use, geology, land and soil cover are the most important factors describing the soil erosion estimated by MPSIAC model.

Are Asia-Pacific Stock Markets Predictable? Evidence from Wavelet-based Fractional Integration Estimator

This paper examines predictability in stock return in developed and emergingmarkets by testing long memory in stock returns using wavelet approach. Wavelet-based maximum likelihood estimator of the fractional integration estimator is superior to the conventional Hurst exponent and Geweke and Porter-Hudak estimator in terms of asymptotic properties and mean squared error. We use 4-year moving windows to estimate the fractional integration parameter. Evidence suggests that stock return may not be predictable indeveloped countries of the Asia-Pacificregion. However, predictability of stock return insome developing countries in this region such as Indonesia, Malaysia and Philippines may not be ruled out. Stock return in the Thailand stock market appears to be not predictable after the political crisis in 2008.

Adomian Decomposition Method Associated with Boole-s Integration Rule for Goursat Problem

The Goursat partial differential equation arises in linear and non linear partial differential equations with mixed derivatives. This equation is a second order hyperbolic partial differential equation which occurs in various fields of study such as in engineering, physics, and applied mathematics. There are many approaches that have been suggested to approximate the solution of the Goursat partial differential equation. However, all of the suggested methods traditionally focused on numerical differentiation approaches including forward and central differences in deriving the scheme. An innovation has been done in deriving the Goursat partial differential equation scheme which involves numerical integration techniques. In this paper we have developed a new scheme to solve the Goursat partial differential equation based on the Adomian decomposition (ADM) and associated with Boole-s integration rule to approximate the integration terms. The new scheme can easily be applied to many linear and non linear Goursat partial differential equations and is capable to reduce the size of computational work. The accuracy of the results reveals the advantage of this new scheme over existing numerical method.

Robust Fractional-Order PI Controller with Ziegler-Nichols Rules

In process control applications, above 90% of the controllers are of PID type. This paper proposed a robust PI controller with fractional-order integrator. The PI parameters were obtained using classical Ziegler-Nichols rules but enhanced with the application of error filter cascaded to the fractional-order PI. The controller was applied on steam temperature process that was described by FOPDT transfer function. The process can be classified as lag dominating process with very small relative dead-time. The proposed control scheme was compared with other PI controller tuned using Ziegler-Nichols and AMIGO rules. Other PI controller with fractional-order integrator known as F-MIGO was also considered. All the controllers were subjected to set point change and load disturbance tests. The performance was measured using Integral of Squared Error (ISE) and Integral of Control Signal (ICO). The proposed controller produced best performance for all the tests with the least ISE index.

Generational PipeLined Genetic Algorithm (PLGA)using Stochastic Selection

In this paper, a pipelined version of genetic algorithm, called PLGA, and a corresponding hardware platform are described. The basic operations of conventional GA (CGA) are made pipelined using an appropriate selection scheme. The selection operator, used here, is stochastic in nature and is called SA-selection. This helps maintaining the basic generational nature of the proposed pipelined GA (PLGA). A number of benchmark problems are used to compare the performances of conventional roulette-wheel selection and the SA-selection. These include unimodal and multimodal functions with dimensionality varying from very small to very large. It is seen that the SA-selection scheme is giving comparable performances with respect to the classical roulette-wheel selection scheme, for all the instances, when quality of solutions and rate of convergence are considered. The speedups obtained by PLGA for different benchmarks are found to be significant. It is shown that a complete hardware pipeline can be developed using the proposed scheme, if parallel evaluation of the fitness expression is possible. In this connection a low-cost but very fast hardware evaluation unit is described. Results of simulation experiments show that in a pipelined hardware environment, PLGA will be much faster than CGA. In terms of efficiency, PLGA is found to outperform parallel GA (PGA) also.

Impact Assessment of Air Pollution Stress on Plant Species through Biochemical Estimations

The present study was conducted to investigate the response of plants exposed to lignite-based thermal power plant emission. For this purpose, five plant species were collected from 1.0 km distance (polluted site) and control plants were collected from 20.0 km distance (control site) to thermal power plant. The common tree species Cassia siamea Lamk., Polyalthia longifolia. Sonn, Acacia longifolia (Andrews) Wild., Azadirachta indica A.Juss, Ficus religiosa L. were selected as test plants. Photosynthetic pigments changes (chlorophyll a, chlorophyll b and carotenoids) and rubisco enzyme modifications were studied. Reduction was observed in the photosynthetic pigments of plants growing in polluted site and also large sub unit of the rubisco enzyme was degraded in Azadirachta indica A. Juss collected from polluted site.

Solar Photo-Fenton Induced Degradation of Combined Chlorpyrifos, Cypermethrin and Chlorothalonil Pesticides in Aqueous Solution

The feasibility of employing solar radiation for enhanced Fenton process in degradation of combined chlorpyrifos, cypermethrin and chlorothalonil pesticides was examined. The effect of various operating conditions of the process on biodegradability improvement and mineralization of the pesticides were also evaluated. The optimum operating conditions for treatment of aqueous solution containing 100, 50 and 250 mg L-1 chlorpyrifos cypermethrin and chlorothalonil, respectively were observed to be H2O2/COD molar ratio 2, H2O2/Fe2+ molar ratio 25 and pH 3. Under the optimum operating conditions, complete degradation of the pesticides occurred in 1 min. Biodegradability (BOD5/COD) increased from zero to 0.36 in 60 min, and COD and TOC removal were 74.19 and 58.32%, respectively in 60 min. Due to mineralization of organic carbon, decrease in ammonia-nitrogen from 22 to 4.3 mg L-1 and increase in nitrate from 0.7 to 18.1 mg L-1 in 60 min were recorded. The study indicated that solar photo-Fenton process can be used for pretreatment of chlorpyrifos, cypermethrin and chlorothalonil pesticides in aqueous solution for further biological treatment.