Search results for: particle interaction.

Authors: Gyo Woo Lee

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In this study, the phase transition characteristics of flame-synthesized γ-Al₂O₃ nanoparticles to α-Al₂O₃ have been investigated. The nanoparticles were synthesized by using a coflow hydrogen diffusion flame. The phase transition and particle characteristics of the Al₂O₃ nanoparticles were determined by examining the crystalline structure and the shape of the collected nanoparticles before and after the heat treatment. The morphology and crystal structure of the Al₂O₃ nanoparticles were determined from SEM images and XRD analyses, respectively. The measured specific surface area and averaged particle size were 63.44m²/g and 23.94nm, respectively. Based on the scanning electron microscope images and x-ray diffraction patterns, it is believed that the onset temperature of the phase transition to α-Al₂O₃ was existed near 1200^oC. The averaged diameters of the sintered particles heat treated at 1,260^oC were approximately 80nm.

Keywords: BET Specific Surface Area, Gamma-Al2O3 Nanoparticles, Flame Synthesis, Phase Transition, X-ray Diffraction.

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Authors: S. Panda, S. K. Tomar, R. Prasad, C. Ardil

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Reduction of Single Input Single Output (SISO) continuous systems into Reduced Order Model (ROM), using a conventional and an evolutionary technique is presented in this paper. In the conventional technique, the mixed advantages of Mihailov stability criterion and continued fraction expansions (CFE) technique is employed where the reduced denominator polynomial is derived using Mihailov stability criterion and the numerator is obtained by matching the quotients of the Cauer second form of Continued fraction expansions. In the evolutionary technique method Particle Swarm Optimization (PSO) is employed to reduce the higher order model. PSO method is based on the minimization of the Integral Squared Error (ISE) between the transient responses of original higher order model and the reduced order model pertaining to a unit step input. Both the methods are illustrated through numerical example.

Keywords: Reduced Order Modeling, Stability, Continued Fraction Expansions, Mihailov Stability Criterion, Particle Swarm Optimization, Integral Squared Error.

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Authors: R. Hanuma Naik, D. V. Ashok Kumar, K. S. R. Anjaneyulu

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Several of the practical industrial control processes are multivariable processes. Due to the relation amid the variables (interaction), delay in the loops, it is very intricate to design a controller directly for these processes. So first, the interaction of the variables is analyzed using Relative Normalized Gain Array (RNGA), which considers the time constant, static gain and delay time of the processes. Based on the effect of RNGA, relative gain array (RGA) and NI, the pair (control configuration) of variables to be controlled by decentralized control is selected. The equivalent transfer function (ETF) of the process model is estimated as first order process with delay using the corresponding elements in the Relative gain array and Relative average residence time array (RARTA) of the processes. Secondly, a decentralized Proportional- Integral (PI) controller is designed for each ETF simply using frequency response specifications. Finally, the performance and robustness of the algorithm is comparing with existing related approaches to validate the effectiveness of the projected algorithm.

Keywords: Decentralized control, interaction, Multivariable processes, relative normalized gain array, relative average residence time array, steady state gain.

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Authors: R. Ramaprabha

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This paper presents an extraction of maximum energy from Solar Photovoltaic Array (SPVA) under partial shaded conditions by optimum selection of array size using Particle Swarm Optimization (PSO) technique. In this paper a detailed study on the output reduction of different SPVA configurations under partial shaded conditions have been carried out. A generalized MATLAB M-code based software model has been used for any required array size, configuration, shading patterns and number of bypass diodes. Comparative study has been carried out on different configurations by testing several shading scenarios. While the number of shading patterns and the rate of change are very low for stationary SPVA but these may be quite large for SPVA mounted on a mobile platforms. This paper presents the suitability of PSO technique to select optimum configuration for mobile arrays by calculating the global peak (GP) of different configurations and to transfer maximum power to the load.

Keywords: Global peak, Mobile PV arrays, Partial shading, optimization, PSO.

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Authors: Moses C. Siame, Kazutoshi Haga, Atsushi Shibayama

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This study investigates the removal of silica, alumina and phosphorus as impurities from Sanje iron ore using wet high-intensity magnetic separation (WHIMS). Sanje iron ore contains low-grade hematite ore found in Nampundwe area of Zambia from which iron is to be used as the feed in the steelmaking process. The chemical composition analysis using X-ray Florence spectrometer showed that Sanje low-grade ore contains 48.90 mass% of hematite (Fe₂O₃) with 34.18 mass% as an iron grade. The ore also contains silica (SiO₂) and alumina (Al₂O₃) of 31.10 mass% and 7.65 mass% respectively. The mineralogical analysis using X-ray diffraction spectrometer showed hematite and silica as the major mineral components of the ore while magnetite and alumina exist as minor mineral components. Mineral particle distribution analysis was done using scanning electron microscope with an X-ray energy dispersion spectrometry (SEM-EDS) and images showed that the average mineral size distribution of alumina-silicate gangue particles is in order of 100 μm and exists as iron-bearing interlocked particles. Magnetic separation was done using series L model 4 Magnetic Separator. The effect of various magnetic separation parameters such as magnetic flux density, particle size, and pulp density of the feed was studied during magnetic separation experiments. The ore with average particle size of 25 µm and pulp density of 2.5% was concentrated using pulp flow of 7 L/min. The results showed that 10 T was optimal magnetic flux density which enhanced the recovery of 93.08% of iron with 53.22 mass% grade. The gangue mineral particles containing 12 mass% silica and 3.94 mass% alumna remained in the concentrate, therefore the concentrate was further treated in the second stage WHIMS using the same parameters from the first stage. The second stage process recovered 83.41% of iron with 67.07 mass% grade. Silica was reduced to 2.14 mass% and alumina to 1.30 mass%. Accordingly, phosphorus was also reduced to 0.02 mass%. Therefore, the two stage magnetic separation process was established using these results.

Keywords: Sanje iron ore, magnetic separation, silica, alumina, recovery.

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Authors: Omid Alizadeh, Ali Parsaeimehr, Barmak.jaefary Hagheghy

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An experiment was conducted in October 2008 due the ability replacement plant associate biofertilizers by chemical fertilizers and the qualifying rate of chemical N fertilizers at the moment of using this biofertilizers and the interaction of this biofertilizer on each other. This field experiment has been done in Persepolis (Throne of Jamshid) and arrange by using factorial with the basis of randomized complete block design, in three replication Azespirilium SP bacteria has been admixed with consistence 108 cfu/g and inoculated with seeds of wheat, The streptomyces SP has been used in amount of 550 gr/ha and concatenated on clay and for the qualifying range of chemical fertilizer 4 level of N chemical fertilizer from the source of urea (N0=0, N1=60, N2=120, N3=180) has been used in this experiment. The results indicated there were Significant differences between levels of Nitrogen fertilizer in the entire characteristic which has been measured in this experiment. The admixed Azespirilium SP showed significant differences between their levels in the characteristics such as No. of fertile ear, No. of grain per ear, grain yield, grain protein percentage, leaf area index and the agronomic fertilizer use efficiency. Due the interaction streptomyses with Azespirilium SP bacteria this actinomycet didn-t show any statistically significant differences between it levels.

Keywords: AzetobacterSP, AzespiriliumSP, StreptomycesSP

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Authors: R. Balamurugan, A. M. Natarajan, K. Premalatha

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Microarray gene expression data play a vital in biological processes, gene regulation and disease mechanism. Biclustering in gene expression data is a subset of the genes indicating consistent patterns under the subset of the conditions. Finding a biclustering is an optimization problem. In recent years, swarm intelligence techniques are popular due to the fact that many real-world problems are increasingly large, complex and dynamic. By reasons of the size and complexity of the problems, it is necessary to find an optimization technique whose efficiency is measured by finding the near optimal solution within a reasonable amount of time. In this paper, the algorithmic concepts of the Particle Swarm Optimization (PSO), Shuffled Frog Leaping (SFL) and Cuckoo Search (CS) algorithms have been analyzed for the four benchmark gene expression dataset. The experiment results show that CS outperforms PSO and SFL for 3 datasets and SFL give better performance in one dataset. Also this work determines the biological relevance of the biclusters with Gene Ontology in terms of function, process and component.

Keywords: Particle swarm optimization, Shuffled frog leaping, Cuckoo search, biclustering, gene expression data.

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Authors: Brahim Belattar, Abdelhabib Bourouis

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This paper describes important features of JAPROSIM, a free and open source simulation library implemented in Java programming language. It provides a framework for building discrete event simulation models. The process interaction world view adopted by JAPROSIM is discussed. We present the architecture and major components of the simulation library. A pedagogical example is given in order to illustrate how to use JAPROSIM for building discrete event simulation models. Further motivations are discussed and suggestions for improving our work are given.

Keywords: Discrete Event Simulation, Object-Oriented Simulation, JAPROSIM, Process Interaction Worldview, Java-based modeling and simulation.

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Authors: Anuj K. Sharma, Amit Sharma, Kulbhushan Agnihotri

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In this work, we propose and analyze a model of Phytoplankton-Zooplankton interaction with harvesting considering that some species are exploited commercially for food. Criteria for local stability, instability and global stability are derived and some threshold harvesting levels are explored to maintain the population at an appropriate equilibrium level even if the species are exploited continuously.Further,biological and bionomic equilibria of the system are obtained and an optimal harvesting policy is also analysed using the Pantryagin’s Maximum Principle.Finally analytical findings are also supported by some numerical simulations.

Keywords: Phytoplankton-Zooplankton, Global stability, Bionomic Equilibrium, Pontrying-Maximum Principal.

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Authors: Ching Louis Liu, Edmund Kazmierczak, Tim Miller

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Safety analysis for multi-agent systems is complicated by the, potentially nonlinear, interactions between agents. This paper proposes a method for analyzing the safety of multi-agent systems by explicitly focusing on interactions and the accident data of systems that are similar in structure and function to the system being analyzed. The method creates a Bayesian network using the accident data from similar systems. A feature of our method is that the events in accident data are labeled with HAZOP guide words. Our method uses an Ontology to abstract away from the details of a multi-agent implementation. Using the ontology, our methods then constructs an “Interaction Map,” a graphical representation of the patterns of interactions between agents and other artifacts. Interaction maps combined with statistical data from accidents and the HAZOP classifications of events can be converted into a Bayesian Network. Bayesian networks allow designers to explore “what it” scenarios and make design trade-offs that maintain safety. We show how to use the Bayesian networks, and the interaction maps to improve multi-agent system designs.

Keywords: Multi-agent system, safety analysis, safety model.

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Authors: Chan-Sik Kim, Jong-Seong Kim, Se Won Lee, Hoo-Gon Choi

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In rapidly changing market environment, firms are investing a lot of time and resources into new product development (NPD) projects to make profit and to obtain competitive advantage. However, failure rate of NPD projects is becoming high due to various internal and external risks which hinder successful NPD projects. To reduce the failure rate, it is critical that risks have to be managed effectively and efficiently through good strategy, and treated by optimal responses to minimize risk cost. Four strategies are adopted to handle the risks in this study. The optimal responses are characterized by high reduction of risk costs with high efficiency. This study suggests a framework to decide the optimal responses considering the core risks, risk costs, response efficiency and response costs for successful NPD projects. Both binary particles warm optimization (BPSO) and multi-objective particle swarm optimization (MOPSO) methods are mainly used in the framework. Although several limitations exist in use for real industries, the frame work shows good strength for handling the risks with highly scientific ways through an example.

Keywords: NPD projects, risk cost, strategy, optimal responses, Particle Swarm Optimization.

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Authors: Bao Thach Nguyen, Abbas Mohajerani

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A typical flexible pavement structure consists of the surface, base, sub-base and subgrade soil. The loading traffic is transferred from the top layer with higher stiffness to the layer below with less stiffness. Under normal traffic loading, the behaviour of flexible pavement is very complex and can be predicted by using the repeated load triaxial test equipment in the laboratory. However, the nature of the repeated load triaxial testing procedure is considered time-consuming, complicated and expensive, and it is a challenge to carry out as a routine test in the laboratory. Therefore, the current paper proposes a numerical approach to simulate the repeated load triaxial test by employing the discrete element method. A sample with particle size ranging from 2.36mm to 19.0mm was constructed. Material properties, which included normal stiffness, shear stiffness, coefficient of friction, maximum dry density and particle density, were used as the input for the simulation. The sample was then subjected to a combination of deviator and confining stress and it was found that the discrete element method is able to simulate the repeated load triaxial test in the laboratory.

Keywords: Discrete element method, repeated load triaxial, pavement materials.

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Authors: B. Murali Krishna, J. M. Mallikarjuna

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This paper deals with the experimental investigations of the in-cylinder tumble flows in an unfired internal combustion engine with a flat piston at the engine speeds ranging from 400 to 1000 rev/min., and also with the dome and dome-cavity pistons at an engine speed of 1000 rev/min., using particle image velocimetry. From the two-dimensional in-cylinder flow measurements, tumble flow analysis is carried out in the combustion space on a vertical plane passing through cylinder axis. To analyze the tumble flows, ensemble average velocity vectors are used and to characterize it, tumble ratio is estimated. From the results, generally, we have found that tumble ratio varies mainly with crank angle position. Also, at the end of compression stroke, average turbulent kinetic energy is more at higher engine speeds. We have also found that, at 330 crank angle position, flat piston shows an improvement of about 85 and 23% in tumble ratio, and about 24 and 2.5% in average turbulent kinetic energy compared to dome and dome-cavity pistons respectively

Keywords: In-cylinder flow, Dome piston, Cavity, Tumble, PIV

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Authors: Ashwini V. Chavan, Sukhanand S. Bhosale

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Challenges of weak soil subgrade are often resolved either by stabilization or reinforcing it. However, it is also practiced to reinforce the granular fill to improve the load-settlement behavior of it over weak soil strata. The inclusion of reinforcement in the engineered granular fill provided a new impetus for the development of enhanced Soil-Structure Interaction (SSI) models, also known as mechanical foundation models or lumped parameter models. Several researchers have been working in this direction to understand the mechanism of granular fill-reinforcement interaction and the response of weak soil under the application of load. These models have been developed by extending available SSI models such as the Winkler Model, Pasternak Model, Hetenyi Model, Kerr Model etc., and are helpful to visualize the load-settlement behavior of a physical system through 1-D and 2-D analysis considering beam and plate resting on the foundation, respectively. Based on the literature survey, these models are categorized as ‘Reinforced Pasternak Model,’ ‘Double Beam Model,’ ‘Reinforced Timoshenko Beam Model,’ and ‘Reinforced Kerr Model’. The present work reviews the past 30+ years of research in the field of SSI models for reinforced foundation systems, presenting the conceptual development of these models systematically and discussing their limitations. A flow-chart showing procedure for compution of deformation and mobilized tension is also incorporated in the paper. Special efforts are taken to tabulate the parameters and their significance in the load-settlement analysis, which may be helpful in future studies for the comparison and enhancement of results and findings of physical models. 

Keywords: geosynthetics, mathematical modeling, reinforced foundation, soil-structure interaction, ground improvement, soft soil

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Authors: M. R. Alrashidi, M. E. El-Hawary

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Environmental awareness and the recent environmental policies have forced many electric utilities to restructure their operational practices to account for their emission impacts. One way to accomplish this is by reformulating the traditional economic dispatch problem such that emission effects are included in the mathematical model. This paper presents a Particle Swarm Optimization (PSO) algorithm to solve the Economic- Emission Dispatch problem (EED) which gained recent attention due to the deregulation of the power industry and strict environmental regulations. The problem is formulated as a multi-objective one with two competing functions, namely economic cost and emission functions, subject to different constraints. The inequality constraints considered are the generating unit capacity limits while the equality constraint is generation-demand balance. A novel equality constraint handling mechanism is proposed in this paper. PSO algorithm is tested on a 30-bus standard test system. Results obtained show that PSO algorithm has a great potential in handling multi-objective optimization problems and is capable of capturing Pareto optimal solution set under different loading conditions.

Keywords: Economic emission dispatch, economic cost dispatch, particle swarm, multi-objective optimization.

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Authors: K. Thangavel, R. Rathipriya

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For the past one decade, biclustering has become popular data mining technique not only in the field of biological data analysis but also in other applications like text mining, market data analysis with high-dimensional two-way datasets. Biclustering clusters both rows and columns of a dataset simultaneously, as opposed to traditional clustering which clusters either rows or columns of a dataset. It retrieves subgroups of objects that are similar in one subgroup of variables and different in the remaining variables. Firefly Algorithm (FA) is a recently-proposed metaheuristic inspired by the collective behavior of fireflies. This paper provides a preliminary assessment of discrete version of FA (DFA) while coping with the task of mining coherent and large volume bicluster from web usage dataset. The experiments were conducted on two web usage datasets from public dataset repository whereby the performance of FA was compared with that exhibited by other population-based metaheuristic called binary Particle Swarm Optimization (PSO). The results achieved demonstrate the usefulness of DFA while tackling the biclustering problem.

Keywords: Biclustering, Binary Particle Swarm Optimization, Discrete Firefly Algorithm, Firefly Algorithm, Usage profile Web usage mining.

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Authors: Varun Singh, Mainak Bandyopadhyay, Maharana Pratap Singh

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The shortest path (SP) problem concerns with finding the shortest path from a specific origin to a specified destination in a given network while minimizing the total cost associated with the path. This problem has widespread applications. Important applications of the SP problem include vehicle routing in transportation systems particularly in the field of in-vehicle Route Guidance System (RGS) and traffic assignment problem (in transportation planning). Well known applications of evolutionary methods like Genetic Algorithms (GA), Ant Colony Optimization, Particle Swarm Optimization (PSO) have come up to solve complex optimization problems to overcome the shortcomings of existing shortest path analysis methods. It has been reported by various researchers that PSO performs better than other evolutionary optimization algorithms in terms of success rate and solution quality. Further Geographic Information Systems (GIS) have emerged as key information systems for geospatial data analysis and visualization. This research paper is focused towards the application of PSO for solving the shortest path problem between multiple points of interest (POI) based on spatial data of Allahabad City and traffic speed data collected using GPS. Geovisualization of results of analysis is carried out in GIS.

Keywords: GIS, Outliers, PSO, Traffic Data.

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Authors: Andreas Ahrens, Ojaras Purvinis Jelena Zāšcerinska

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A successful shopping experience without overcrowded shops and long waiting times undoubtedly leads to the release of happiness hormones and is generally considered as the goal of any optimization. Factors influencing the shopping experience can be divided into internal and external ones. External factors are related e. g. to the arrival of the customers to the shop whereas internal factors are linked with the service process itself when checking out (waiting in the queue to the cash register and the scanning of the goods as well as the payment process itself) or any other non-expected delay when changing the status from a visitor to a buyer by choosing goods or items. This paper divides the customer-server interaction in five phases starting with the customer arrival at the shop, the selection of goods, the buyer waiting in the queue to the cash register, the payment process and ending with the customer or buyer departure. Our simulation results show how five phases are intertwined and influence the overall shopping experience. Parameters for measuring the shopping experience based on a burstiness level in each of the five phases of the customer-server interaction are estimated.

Keywords: Customers’ burstiness, cash register, customers’ waiting time, gap distribution function.

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Authors: Faghihnia Torshizi Mostafa, Saitoh Masato

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An efficient method is developed for the response of a group of vertical, cylindrical fixed-head, finite length piles embedded in a homogeneous elastic stratum, subjected to harmonic force atop the pile group cap. Pile to pile interaction is represented through simplified beam-on-dynamic-Winkler-foundation (BDWF) with realistic frequency-dependent springs and dashpots. Pile group effect is considered through interaction factors. New closed-form expressions for interaction factors and curvature ratios atop the pile are extended by considering different boundary conditions at the tip of the piles (fixed, hinged). In order to investigate the fundamental characteristics of inertial bending strains in pile groups, inertial bending strains at the head of each pile are expressed in terms of slenderness ratio. The results of parametric study give valuable insight in understanding the behavior of fixed head pile groups in fundamental natural frequency of soil stratum.

Keywords: Winkler-foundation, fundamental frequency of soil stratum, normalized inertial bending strain, harmonic excitation.

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Authors: R. Sarathi, G. Koperundevi

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Design of Converter transformer insulation is a major challenge. The insulation of these transformers is stressed by both AC and DC voltages. Particle contamination is one of the major problems in insulation structures, as they generate partial discharges leading it to major failure of insulation. Similarly corona discharges occur in transformer insulation. This partial discharge due to particle movement / corona formation in insulation structure under different voltage wave shapes, are different. In the present study, UHF technique is adopted to understand the discharge activity and could be realized that the characteristics of UHF signal generated under low and high fields are different. In the case of corona generated signal, the frequency content of the UHF sensor output lies in the range 0.3-1.2 GHz and is not much varied except for its increase in magnitude of discharge with the increase in applied voltage. It is realized that the current signal injected due to partial discharges/corona is about 4ns duration measured for first one half cycle. Wavelet technique is adopted in the present study. It allows one to identify the frequency content present in the signal at different instant of time. The STD-MRA analysis helps one to identify the frequency band in which the energy content of the UHF signal is maximum.

Keywords: Contamination, Insulation, Partial Discharges, Transformer oil, UHF sensors.

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Authors: Haibo Hu, Dan Yang, Chunxiao Ye, Chunlei Fu, Ren Li

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High quality requirements analysis is one of the most crucial activities to ensure the success of a software project, so that requirements verification for software system becomes more and more important in Requirements Engineering (RE) and it is one of the most helpful strategies for improving the quality of software system. Related works show that requirement elicitation and analysis can be facilitated by ontological approaches and semantic web technologies. In this paper, we proposed a hybrid method which aims to verify requirements with structural and formal semantics to detect interactions. The proposed method is twofold: one is for modeling requirements with the semantic web language OWL, to construct a semantic context; the other is a set of interaction detection rules which are derived from scenario-based analysis and represented with semantic web rule language (SWRL). SWRL based rules are working with rule engines like Jess to reason in semantic context for requirements thus to detect interactions. The benefits of the proposed method lie in three aspects: the method (i) provides systematic steps for modeling requirements with an ontological approach, (ii) offers synergy of requirements elicitation and domain engineering for knowledge sharing, and (3)the proposed rules can systematically assist in requirements interaction detection.

Keywords: Requirements Engineering, Semantic Web, OWL, Requirements Interaction Detection, SWRL.

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Authors: S. Joseph Antony, Z. K. Jahanger

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Soils are subjected to cyclic loading in situ in situations such as during earthquakes and in the compaction of pavements. Investigations on the local scale measurement of the displacements of the grain and failure patterns within the soil bed under the cyclic loading conditions are rather limited. In this paper, using the digital particle image velocimetry (DPIV), local scale displacement fields of a dense sand medium interacting with a rigid footing are measured under the plane-strain condition for two commonly used types of cyclic loading, and the quasi-static loading condition for the purposes of comparison. From the displacement measurements of the grains, the failure envelopes of the sand media are also presented. The results show that, the ultimate cyclic bearing capacity (qultcyc) occurred corresponding to a relatively higher settlement value when compared with that of under the quasi-static loading. For the sand media under the cyclic loading conditions considered here, the displacement fields in the soil media occurred more widely in the horizontal direction and less deeper along the vertical direction when compared with that of under the quasi-static loading. The 'dead zone' in the sand grains beneath the footing is identified for all types of the loading conditions studied here. These grain-scale characteristics have implications on the resulting bulk bearing capacity of the sand media in footing-sand interaction problems.

Keywords: Cyclic loading, DPIV, settlement, soil-structure interactions, strip footing.

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Authors: Anuchita Moongngarm, John E. Bronlund, Nigel Grigg, Naruemon Sriwai

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The study aimed to investigate the effect of rice types on chewing behaviours (chewing time, number of chews, and portion size) and bolus properties (bolus moisture content, solid loss, and particle size distribution (PSD)) in human subjects. Five cooked rice types including brown rice (BR), white rice (WR), parboiled white rice (PR), high amylose white rice (HR) and waxy white rice (WXR) were chewed by six subjects. The chewing behaviours were recorded and the food boluses were collected during mastication. Rice typeswere found to significantly influence all chewing parameters evaluated. The WXR and BR showed the most pronounced differences compared with other rice types. The initial moisture content of un-chewed WXR was lowest (43.39%) whereas those of other rice types were ranged from 66.86 to 70.33%. The bolus obtained from chewing the WXR contained lowest moisture content (56.43%) whilst its solid loss (22.03%) was not significant different from those of all rice types. In PSD evaluation using Mastersizer S, the diameter of particles measured was ranged between 4 to 3500 μm. The particle size of food bolus from BR, HR, and WXR contained much finer particles than those of WR and PR.

Keywords: Chewing behavior, Mastication, Rice, Rice types, Bolus properties

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Authors: Ibtissem Gammoudi, Ndeye Rokhaya Faye, Fabien Moroté, Daniel Moynet, Christine Grauby-Heywang, Touria Cohen-Bouhacina

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The objective of the present investigation was to evaluate the morphology of Escherchia coli bacteria in interaction with SiO2 nanoparticles. This study was made by atomic force microscopy and quartz crystal microbalance using SiO2 nanoparticles with 10nm, 50nm and 100nm diameter and bacteria immobilized on polyelectrolyte multilayer films obtained by spin coating or by “layer by layer” (LbL) method.

Keywords: Atomic Force Microscopy, Escherichia coli, Quartz Crystal Microbalance, polyelectrolyte, silica nanoparticle.

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Authors: Hema C. R., Paulraj M. P., S. Yaacob, A. H. Adom, R. Nagarajan

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Motor imagery classification provides an important basis for designing Brain Machine Interfaces [BMI]. A BMI captures and decodes brain EEG signals and transforms human thought into actions. The ability of an individual to control his EEG through imaginary mental tasks enables him to control devices through the BMI. This paper presents a method to design a four state BMI using EEG signals recorded from the C3 and C4 locations. Principle features extracted through principle component analysis of the segmented EEG are analyzed using two novel classification algorithms using Elman recurrent neural network and functional link neural network. Performance of both classifiers is evaluated using a particle swarm optimization training algorithm; results are also compared with the conventional back propagation training algorithm. EEG motor imagery recorded from two subjects is used in the offline analysis. From overall classification performance it is observed that the BP algorithm has higher average classification of 93.5%, while the PSO algorithm has better training time and maximum classification. The proposed methods promises to provide a useful alternative general procedure for motor imagery classification

Keywords: Motor Imagery, Brain Machine Interfaces, Neural Networks, Particle Swarm Optimization, EEG signal processing.

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Authors: D. Mondal, A. Chakrabarti, A. Sengupta

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This paper aims to select the optimal location and setting parameters of TCSC (Thyristor Controlled Series Compensator) controller using Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) to mitigate small signal oscillations in a multimachine power system. Though Power System Stabilizers (PSSs) are prime choice in this issue, installation of FACTS device has been suggested here in order to achieve appreciable damping of system oscillations. However, performance of any FACTS devices highly depends upon its parameters and suitable location in the power network. In this paper PSO as well as GA based techniques are used separately and compared their performances to investigate this problem. The results of small signal stability analysis have been represented employing eigenvalue as well as time domain response in face of two common power system disturbances e.g., varying load and transmission line outage. It has been revealed that the PSO based TCSC controller is more effective than GA based controller even during critical loading condition.

Keywords: Genetic Algorithm, Particle Swarm Optimization, Small Signal Stability, Thyristor Controlled Series Compensator.

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Authors: Baljit Singh Khehra, Amar Partap Singh Pharwaha

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Clusters of Microcalcifications (MCCs) are most frequent symptoms of Ductal Carcinoma in Situ (DCIS) recognized by mammography. Least-Square Support Vector Machine (LS-SVM) is a variant of the standard SVM. In the paper, LS-SVM is proposed as a classifier for classifying MCCs as benign or malignant based on relevant extracted features from enhanced mammogram. To establish the credibility of LS-SVM classifier for classifying MCCs, a comparative evaluation of the relative performance of LS-SVM classifier for different kernel functions is made. For comparative evaluation, confusion matrix and ROC analysis are used. Experiments are performed on data extracted from mammogram images of DDSM database. A total of 380 suspicious areas are collected, which contain 235 malignant and 145 benign samples, from mammogram images of DDSM database. A set of 50 features is calculated for each suspicious area. After this, an optimal subset of 23 most suitable features is selected from 50 features by Particle Swarm Optimization (PSO). The results of proposed study are quite promising.

Keywords: Clusters of Microcalcifications, Ductal Carcinoma in Situ, Least-Square Support Vector Machine, Particle Swarm Optimization.

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Authors: Perumal, V., Hassan, H., Bolong, J., Osman, M. N.

Abstract:

Film, as an art form playing a vital role and is a powerful tool in documenting, influencing and shaping the society. Films are the collective creation of a large number of separate individuals, each contributing with creative input, unique talents, and technical expertise to the project. Recently, the Malaysian Independent (or “Indie") filmmakers have made their presence felt by winning awards at various international film festivals. Working in the digital video (DV) format, a number of independent filmmakers really hit their stride with a range of remarkably strong titles and international recognition has been quick in coming and their works are now regularly in exhibition or in competition, winning many top prizes at prestigious festivals around the world. The interaction factors among crewmembers are emphasized as imperative for group success. An in-depth interview is conducted to analyze the social interactions and exchanges between filmmakers through Social Exchanges Theory (SET). Certainly the new millennium that was marked as the digital technology revolution has changed the face of filmmaking in Malaysia. There is a clear need to study the Malaysian independent cinema especially from the perspective of understanding what causes the independent filmmakers to work so well given all of the difficulties and constraints.

Keywords: Digital filmmaking, technology, interaction, crewmembers, cinema, independent filmmaker.

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Authors: Samy M. El-Behery, W. A. El-Askary, K. A. Ibrahim, Mofreh H. Hamed

Abstract:

A steady two-phase flow model has been developed to simulate the drying process of porous particle in a pneumatic conveying dryer. The model takes into account the momentum, heat and mass transfer between the continuous phase and the dispersed phase. A single particle model was employed to calculate the evaporation rate. In this model the pore structure is simplified to allow the dominant evaporation mechanism to be readily identified at all points within the duct. The predominant mechanism at any time depends upon the pressure, temperature and the diameter of pore from which evaporating is occurring. The model was validated against experimental studies of pneumatic transport at low and high speeds as well as pneumatic drying. The effects of operating conditions on the dryer parameters are studied numerically. The present results show that the drying rate is enhanced as the inlet gas temperature and the gas flow rate increase and as the solid mass flow rate deceases. The present results also demonstrate the necessity of measuring the inlet gas velocity or the solid concentration in any experimental analysis.

Keywords: Two-phase, gas-solid, pneumatic drying, pneumatic conveying, heat and mass transfer

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Authors: Zhang Tianci, Ding Meng, Zuo Hongfu, Zeng Lina, Sun Zejun

Abstract:

Automation of airport operations can greatly improve ground movement efficiency. In this paper, we study the speed profile design problem for advanced airport ground movement control and guidance. The problem is constrained by the surface four-dimensional trajectory generated in taxi planning. A decomposed approach of two stages is presented to solve this problem efficiently. In the first stage, speeds are allocated at control points, which ensure smooth speed profiles can be found later. In the second stage, detailed speed profiles of each taxi interval are generated according to the allocated control point speeds with the objective of minimizing the overall fuel consumption. We present a swarm intelligence based algorithm for the first-stage problem and a discrete variable driven enumeration method for the second-stage problem, since it only has a small set of discrete variables. Experimental results demonstrate the presented methodology performs well on real world speed profile design problems.

Keywords: Airport ground movement, fuel consumption, particle swarm optimization, smoothness, speed profile design.

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