Search results for: Finite element method

Authors: D.J. Brink, N.G. van der Berg, L.C. Prinsloo, A. Botha

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In this work we study the reflection of circularly polarised light from a nano-structured biological material found in the exocuticle of scarabus beetles. This material is made of a stack of ultra-thin (~5 nm) uniaxial layers arranged in a left-handed helicoidal stack, which resonantly reflects circularly polarized light. A chirp in the layer thickness combined with a finite absorption coefficient produce a broad smooth reflectance spectrum. By comparing model calculations and electron microscopy with measured spectra we can explain our observations and quantify most relevant structural parameters.

Keywords: Chiral reflectors, circularly polarised light, helicoidal structures, nano photonics.

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Authors: Autcha Araveeporn

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This paper is to compare the parameter estimation of the mean in normal distribution by Maximum Likelihood (ML), Bayes, and Markov Chain Monte Carlo (MCMC) methods. The ML estimator is estimated by the average of data, the Bayes method is considered from the prior distribution to estimate Bayes estimator, and MCMC estimator is approximated by Gibbs sampling from posterior distribution. These methods are also to estimate a parameter then the hypothesis testing is used to check a robustness of the estimators. Data are simulated from normal distribution with the true parameter of mean 2, and variance 4, 9, and 16 when the sample sizes is set as 10, 20, 30, and 50. From the results, it can be seen that the estimation of MLE, and MCMC are perceivably different from the true parameter when the sample size is 10 and 20 with variance 16. Furthermore, the Bayes estimator is estimated from the prior distribution when mean is 1, and variance is 12 which showed the significant difference in mean with variance 9 at the sample size 10 and 20.

Keywords: Bayes method, Markov Chain Monte Carlo method, Maximum Likelihood method, normal distribution.

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Authors: Nursyarizal Mohd Nor, Ramiah Jegatheesan, Perumal Nallagownden

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Newton-Raphson State Estimation method using bus admittance matrix remains as an efficient and most popular method to estimate the state variables. Elements of Jacobian matrix are computed from standard expressions which lack physical significance. In this paper, elements of the state estimation Jacobian matrix are obtained considering the power flow measurements in the network elements. These elements are processed one-by-one and the Jacobian matrix H is updated suitably in a simple manner. The constructed Jacobian matrix H is integrated with Weight Least Square method to estimate the state variables. The suggested procedure is successfully tested on IEEE standard systems.

Keywords: State Estimation (SE), Weight Least Square (WLS), Newton-Raphson State Estimation (NRSE), Jacobian matrix H.

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Authors: Takuya Sumi, Syoko Nukaya, Takashi Kaburagi, Hiroshi Tanaka, Kajiro Watanabe, Yosuke Kurihara

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We propose an unconstrained measurement system for scratching motion based on mathematical model of unconstrained bed sensing method which could measure the bed vibrations due to the motion of the person on the bed. In this paper, we construct mathematical model of the unconstrained bed monitoring system; and we apply the unconstrained bed sensing method to the system for detecting scratching motion. The proposed sensors are placed under the three bed feet. When the person is lying on the bed, the output signals from the sensors are proportional to the magnitude of the vibration due to the scratching motion. Hence, we could detect the subject’s scratching motion from the output signals from ceramic sensors. We evaluated two scratching motions using the proposed system in the validity experiment as follows: 1st experiment is the subject’s scratching the right side cheek with his right hand, and; 2nd experiment is the subject’s scratching the shin with another foot. As the results of the experiment, we recognized the scratching signals that enable the determination when the scratching occurred. Furthermore, the difference among the amplitudes of the output signals enabled us to estimate where the subject scratched.

Keywords: Unconstrained bed sensing method, scratching, body movement, itchy, piezoceramics.

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Authors: Mohammadreza Vafaei, Amirali Moradi, Sophia C. Alih

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The method selected for the design of structures not only can affect their seismic vulnerability but also can affect their construction cost. For the design of steel structures, two distinct methods have been introduced by existing codes, namely allowable stress design (ASD) and load resistant factor design (LRFD). This study investigates the effect of using the aforementioned design methods on the seismic vulnerability and construction cost of steel structures. Specifically, a 20-story building equipped with special moment resisting frame and an eccentrically braced system was selected for this study. The building was designed for three different intensities of peak ground acceleration including 0.2 g, 0.25 g, and 0.3 g using the ASD and LRFD methods. The required sizes of beams, columns, and braces were obtained using response spectrum analysis. Then, the designed frames were subjected to nine natural earthquake records which were scaled to the designed response spectrum. For each frame, the base shear, story shears, and inter-story drifts were calculated and then were compared. Results indicated that the LRFD method led to a more economical design for the frames. In addition, the LRFD method resulted in lower base shears and larger inter-story drifts when compared with the ASD method. It was concluded that the application of the LRFD method not only reduced the weights of structural elements but also provided a higher safety margin against seismic actions when compared with the ASD method.

Keywords: Allowable stress design, load resistant factor design, nonlinear time history analysis, seismic vulnerability, steel structures.

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Authors: Mahanijah Md Kamal., Dingli Yu

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This paper presents a new method of fault detection and isolation (FDI) for polymer electrolyte membrane (PEM) fuel cell (FC) dynamic systems under an open-loop scheme. This method uses a radial basis function (RBF) neural network to perform fault identification, classification and isolation. The novelty is that the RBF model of independent mode is used to predict the future outputs of the FC stack. One actuator fault, one component fault and three sensor faults have been introduced to the PEMFC systems experience faults between -7% to +10% of fault size in real-time operation. To validate the results, a benchmark model developed by Michigan University is used in the simulation to investigate the effect of these five faults. The developed independent RBF model is tested on MATLAB R2009a/Simulink environment. The simulation results confirm the effectiveness of the proposed method for FDI under an open-loop condition. By using this method, the RBF networks able to detect and isolate all five faults accordingly and accurately.

Keywords: Polymer electrolyte membrane fuel cell, radial basis function neural networks, fault detection, fault isolation.

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Authors: Nicolae Bold, Daniel Nijloveanu

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The idea of cropping-system is a method used by farmers. It is an environmentally-friendly method, protecting the natural resources (soil, water, air, nutritive substances) and increase the production at the same time, taking into account some crop particularities. The combination of this powerful method with the concepts of genetic algorithms results into a possibility of generating sequences of crops in order to form a rotation. The usage of this type of algorithms has been efficient in solving problems related to optimization and their polynomial complexity allows them to be used at solving more difficult and various problems. In our case, the optimization consists in finding the most profitable rotation of cultures. One of the expected results is to optimize the usage of the resources, in order to minimize the costs and maximize the profit. In order to achieve these goals, a genetic algorithm was designed. This algorithm ensures the finding of several optimized solutions of cropping-systems possibilities which have the highest profit and, thus, which minimize the costs. The algorithm uses genetic-based methods (mutation, crossover) and structures (genes, chromosomes). A cropping-system possibility will be considered a chromosome and a crop within the rotation is a gene within a chromosome. Results about the efficiency of this method will be presented in a special section. The implementation of this method would bring benefits into the activity of the farmers by giving them hints and helping them to use the resources efficiently.

Keywords: Genetic algorithm, chromosomes, genes, cropping, agriculture.

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Authors: Ahcene Habbi, Yassine Boudouaoui

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This paper deals with the problem of automatic rule generation for fuzzy systems design. The proposed approach is based on hybrid artificial bee colony (ABC) optimization and weighted least squares (LS) method and aims to find the structure and parameters of fuzzy systems simultaneously. More precisely, two ABC based fuzzy modeling strategies are presented and compared. The first strategy uses global optimization to learn fuzzy models, the second one hybridizes ABC and weighted least squares estimate method. The performances of the proposed ABC and ABC-LS fuzzy modeling strategies are evaluated on complex modeling problems and compared to other advanced modeling methods.

Keywords: Automatic design, learning, fuzzy rules, hybrid, swarm optimization.

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Authors: Katsumi Hirata

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To develop the useful acoustic environmental recognition system, the method of estimating 3D-position of a stationary random acoustic source using bispectral analysis of 4-point detected signals is proposed. The method uses information about amplitude attenuation and propagation delay extracted from amplitude ratios and angles of auto- and cross-bispectra of the detected signals. It is expected that using bispectral analysis affects less influence of Gaussian noises than using conventional power spectral one. In this paper, the basic principle of the method is mentioned first, and its validity and features are considered from results of the fundamental experiments assumed ideal circumstances.

Keywords: 4-point detection, a stationary random acoustic source, auto- and cross-bispectra, estimation of 3D-position.

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Authors: Sajith Sajeev, Brenton McLaury, Siamack Shirazi

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In the petroleum industry, solid particles are often present along with the produced fluids. It is imperative to keep particles from accumulating in flow lines. In this study, various experiments are conducted to study sand particle transport, where critical velocity is defined as the average fluid velocity to keep particles continuously moving. Many parameters related to the fluid, particles and pipe affect the transport process. Experimental results are presented varying the particle concentration. Additionally, CFD simulations using a discrete element modeling (DEM) approach are presented to compare with experimental result.

Keywords: Particle transport, critical velocity, CFD, DEM.

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Authors: Salam Khalifa, Naveed Ahmed

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We present a new method to reconstruct a temporally coherent 3D animation from single or multi-view RGB-D video data using unbiased feature point sampling. Given RGB-D video data, in form of a 3D point cloud sequence, our method first extracts feature points using both color and depth information. In the subsequent steps, these feature points are used to match two 3D point clouds in consecutive frames independent of their resolution. Our new motion vectors based dynamic alignement method then fully reconstruct a spatio-temporally coherent 3D animation. We perform extensive quantitative validation using novel error functions to analyze the results. We show that despite the limiting factors of temporal and spatial noise associated to RGB-D data, it is possible to extract temporal coherence to faithfully reconstruct a temporally coherent 3D animation from RGB-D video data.

Keywords: 3D video, 3D animation, RGB-D video, Temporally Coherent 3D Animation.

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Authors: M. Tahmasebi, R.A. Rahman, M. Mailah, M. Gohari

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The control of sprayer boom undesired vibrations pose a great challenge to investigators due to various disturbances and conditions. Sprayer boom movements lead to reduce of spread efficiency and crop yield. This paper describes the design of a novel control method for an active suspension system applying proportional-integral-derivative (PID) controller with an active force control (AFC) scheme integration of an iterative learning algorithm employed to a sprayer boom. The iterative learning as an intelligent method is principally used as a method to calculate the best value of the estimated inertia of the sprayer boom needed for the AFC loop. Results show that the proposed AFC-based scheme performs much better than the standard PID control technique. Also, this shows that the system is more robust and accurate.

Keywords: Active force control, sprayer boom, active suspension, iterative learning.

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Authors: Xu Zhao

Abstract:

Text categorization techniques are widely used to many Information Retrieval (IR) applications. In this paper, we proposed a simple but efficient method that can automatically find the relationship between any pair of terms and documents, also an indexing matrix is established for text categorization. We call this method Indexing Matrix Categorization Machine (IMCM). Several experiments are conducted to show the efficiency and robust of our algorithm.

Keywords: Text categorization, Sub-space learning, Latent Semantic Space

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Authors: M. Behbahani-Nejad, Y. Shekari

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A reduced order modeling approach for natural gas transient flow in pipelines is presented. The Euler equations are considered as the governing equations and solved numerically using the implicit Steger-Warming flux vector splitting method. Next, the linearized form of the equations is derived and the corresponding eigensystem is obtained. Then, a few dominant flow eigenmodes are used to construct an efficient reduced-order model. A well-known test case is presented to demonstrate the accuracy and the computational efficiency of the proposed method. The results obtained are in good agreement with those of the direct numerical method and field data. Moreover, it is shown that the present reduced-order model is more efficient than the conventional numerical techniques for transient flow analysis of natural gas in pipelines.

Keywords: Eigenmode, Natural Gas, Reduced Order Modeling, Transient Flow.

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Authors: Matías Micheletto, Rodrigo Santos, Sergio F. Ochoa

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In developing countries, most roads in rural areas are dirt road. They require frequent maintenance since they are affected by erosive events, such as rain or wind, and the transit of heavy-weight trucks and machinery. Early detection of damages on the road condition is a key aspect, since it allows to reduce the maintenance time and cost, and also the limitations for other vehicles to travel through. Most proposals that help address this problem require the explicit participation of drivers, a permanent internet connection, or important instrumentation in vehicles or roads. These constraints limit the suitability of these proposals when applied into developing regions, like Latin America. This paper proposes an alternative method, based on unattended crowdsensing, to determine the quality of dirt roads in rural areas. This method involves the use of a mobile application that complements the road condition surveys carried out by organizations in charge of the road network maintenance, giving them early warnings about road areas that could be requiring maintenance. Drivers can also take advantage of the early warnings while they move through these roads. The method was evaluated using information from a public dataset. Although they are preliminary, the results indicate the proposal is potentially suitable to provide awareness about dirt roads condition to drivers, transportation authority and road maintenance companies.

Keywords: Dirt roads automatic quality assessment, collaborative system, unattended crowdsensing method, roads quality awareness provision.

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Authors: H. Sajjadi, M. Gorji, GH.R. Kefayati, D. D. Ganji, M. Shayan nia

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In this paper effects of inclination angle on natural convection flow in an open cavity has been analyzed with Lattice Boltzmann Method (LBM).The angle of inclination varied from θ= - 45° to 45° with 15° intervals. Study has been conducted for Rayleigh numbers (Ra) 104 to 106. The comparisons show that the average Nusselt number increases with growth of Rayleigh number and the average Nusselt number increase as inclination angles increases at Ra=104.At Ra=105 and Ra=106 the average Nusselt number enhance as inclination angels varied from θ= -45° to θ= 0° and decrease as inclination angels increase in θ= 0° to θ= 45°.

Keywords: Lattice Boltzmann Method, Inclination angle, Opencavity, Natural convection

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Authors: Behnaz Zohouri, Mahdi Zowghiand, Mohsen haghighi

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In this paper, a method for decision making in fuzzy environment is presented.A new subjective and objective integrated approach is introduced that used to assign weight attributes in fuzzy multiple attribute decision making (FMADM) problems and alternatives and fmally ranked by proposed method.

Keywords: Multiple Attribute Decision Making, Triangular fuzzy numbers, ranking index, Fuzzy Entropy.

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Authors: A. O. Oladele

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The purpose of this study was to find out the effectiveness of neurological impress method and repeated reading technique on reading fluency of children with learning disabilities. Thirty primary four pupils in three public primary schools participated in the study. There were two experimental groups and a control. This research employed a 3 by 2 factorial matrix and the participants were taught for one session. Two hypotheses were formulated to guide the research. T-test was used to analyse the data gathered, and data analysis revealed that pupils exposed to the two treatment strategies had improvement in their reading fluency. It was recommended that the two strategies used in the study can be used to intervene in reading fluency problems in children with learning disabilities.

Keywords: Learning disabilities, neurological impress method, repeated reading, reading fluency.

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Authors: Maliheh Raji, Hossein Abolghasemi, Jaber Safdari, Ali Kargari

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Samarium as a rare-earth element is playing a growing important role in high technology. Traditional methods for extraction of rare earth metals such as ion exchange and solvent extraction have disadvantages of high investment and high energy consumption. Emulsion liquid membrane (ELM) as an improved solvent extraction technique is an effective transport method for separation of various compounds from aqueous solutions. In this work, the extraction of samarium from aqueous solutions by ELM was investigated using response surface methodology (RSM). The organic membrane phase of the ELM was a nanofluid consisted of multiwalled carbon nanotubes (MWCNT), Span80 as surfactant, Cyanex 272 as mobile carrier, and kerosene as base fluid. 1 M nitric acid solution was used as internal aqueous phase. The effects of the important process parameters on samarium extraction were investigated, and the values of these parameters were optimized using the Central Composition Design (CCD) of RSM. These parameters were the concentration of MWCNT in nanofluid, the carrier concentration, and the volume ratio of organic membrane phase to internal phase (Roi). The three-dimensional (3D) response surfaces of samarium extraction efficiency were obtained to visualize the individual and interactive effects of the process variables. A regression model for % extraction was developed, and its adequacy was evaluated. The result shows that % extraction improves by using MWCNT nanofluid in organic membrane phase and extraction efficiency of 98.92% can be achieved under the optimum conditions. In addition, demulsification was successfully performed and the recycled membrane phase was proved to be effective in the optimum condition.

Keywords: Cyanex 272, emulsion liquid membrane, multiwalled carbon nanotubes, nanofluid, response surface methodology, Samarium.

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Authors: S. Jeyarajan

Abstract:

Concept of knowledge is discovered from conducted study for successive Competition in Sri Lankan Non-State Higher Educational Institutes. The Concept discovered out of collected Knowledge Management Practices from Emerald inside likewise reputed literatures and of Non-State Higher Educational sector. A test is conducted to reveal existences and its reason behind of these collected practices in Sri Lankan Non-State Higher Education Institutes. Further, unavailability of such study and uncertain on number of participants for data collection in the Sri Lankan context contributed selection of research method as qualitative method, which used attributes of Delphi Method to manage those likewise uncertainty. Data are collected under Dramaturgical Method, which contributes efficient usage of the Delphi method. Grounded theory is selected as data analysis techniques, which is conducted in intermixed discourse to manage different perspectives of data that are collected systematically through perspective and modified snowball sampling techniques. Data are then analysed using Grounded Theory Development Techniques in Intermix discourses to manage differences in Data. Consequently, Agreement in the results of Grounded theories and of finding in the Foreign Study is discovered in the analysis whereas present study conducted as Qualitative Research and The Foreign Study conducted as Quantitative Research. As such, the Present study widens the discovery in the Foreign Study. Further, having discovered reason behind of the existences, the Present result shows Concept for Knowledge from Sri Lankan Non-State sector to manage higher educational Institutes in successful manner.

Keywords: Adherence of snowball sampling into perspective sampling, Delphi method in qualitative method, grounded theory development in intermix discourses of analysis, knowledge management for success of higher educational institutes.

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Authors: K. Abuzayan, H. Alabed, J. Ezarrugh, M. Agila

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Static and dynamic balance are essential in daily and sports life. Many factors have been identified as influencing static balance control. Therefore, the aim of this study was to apply the (XCoM) method and other relevant variables (CoP, CoM, F_h, KE, P, Q, and, AI) to investigate sport related activities such as hopping and jumping. Many studies have represented the CoP data without mentioning its accuracy so several experiments were done to establish the agreement between the CoP and the projected CoM in a static condition. 5 healthy male were participated in this study (Mean ± SD:- age 24.6 years ±4.5, height 177cm ± 6.3, body mass 72.8kg ± 6.6).Results found that the implementation of the XCoM method was found to be practical for evaluating both static and dynamic balance. The general findings were that the CoP, the CoM, the XCoM, F_h, and Q were more informative than the other variables (e.g. KE, P, and AI) during static and dynamic balance. The XCoM method was found to be applicable to dynamic balance as well as static balance.

Keywords: Centre of Mass, static balance, Dynamic balance, extrapolated Centre of Mass

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Authors: Ahmad Javid Habib, Tetsuo Kidokoro

Abstract:

There is an increasing demand for developing urban land to provide better living conditions for all citizens in Afghanistan. Most of the development will involve the acquisition of land. And the current land acquisition method practiced by central government is expropriation, which is a cash-based transaction method that imposes heavy fiscal burden on local municipalities and central government, and it does not protect ownership rights and social equity of landowners besides it relocates the urban poor to remote areas with limited access to jobs and public services. The questionnaire analysis, backed by observations of different case studies in countries where land readjustment is used as a collaborative land development tool indicates that the method plays a key role in valuing landowners’ rights, giving other community members and stakeholders the opportunity to collaboratively implement urban development projects. The practice of the method is reducing the heavy fiscal burden on the local and central governments and is a better option to deal with the current development challenges in Afghanistan.

Keywords: Collaboration, land readjustment, master plan, expropriation.

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Authors: C. R. Ríos-Soberanis, V. M. Moo-Huchin, R. J. Estrada-Leon, E. Perez-Pacheco

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Polymers from renewable resources have attracted an increasing amount of attention over the last two decades, predominantly due to two major reasons: firstly environmental concerns, and secondly the realization that our petroleum resources are finite. Finding new uses for agricultural commodities is also an important area of research. Therefore, it is crucial to get new sources of natural materials that can be used in different applications. Ramon tree (Brosimum alicastrum) is a tropical plant that grows freely in Yucatan countryside. This paper focuses on the seeds recollection, processing and starch extraction and characterization in order to find out about its suitability as biomaterial. Results demonstrated that it has a high content of qualities to be used not only as comestible but also as an important component in polymeric blends.

Keywords: Biomaterials, biopolymer, starch, characterization techniques.

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Authors: A. Borji, M. Hamidi

Abstract:

A new method for color image segmentation using fuzzy logic is proposed in this paper. Our aim here is to automatically produce a fuzzy system for color classification and image segmentation with least number of rules and minimum error rate. Particle swarm optimization is a sub class of evolutionary algorithms that has been inspired from social behavior of fishes, bees, birds, etc, that live together in colonies. We use comprehensive learning particle swarm optimization (CLPSO) technique to find optimal fuzzy rules and membership functions because it discourages premature convergence. Here each particle of the swarm codes a set of fuzzy rules. During evolution, a population member tries to maximize a fitness criterion which is here high classification rate and small number of rules. Finally, particle with the highest fitness value is selected as the best set of fuzzy rules for image segmentation. Our results, using this method for soccer field image segmentation in Robocop contests shows 89% performance. Less computational load is needed when using this method compared with other methods like ANFIS, because it generates a smaller number of fuzzy rules. Large train dataset and its variety, makes the proposed method invariant to illumination noise

Keywords: Comprehensive learning Particle Swarmoptimization, fuzzy classification.

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Authors: J. Sliseris, K. Rocens

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The new optimization method for fiber orientation angle optimization of symmetrical multilayer plates like plywood is proposed. Optimization method consists of seeking for minimal compliance by choosing appropriate fiber orientation angle in outer layers of flexural plate. The discrete values of fiber orientation angles are used in method. Optimization results of simply supported plate and multispan plate with uniformly distributed load are provided. Results show that stiffness could be increased up to 20% by changing wood fiber orientation angle in one or two outer layers.

Keywords: Minimal compliance, flexural plate, plywood, discrete fiber angle optimization.

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Authors: José M. Merigó, Montserrat Casanovas

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We analyze the problem of decision making under ignorance with regrets. Recently, Yager has developed a new method for decision making where instead of using regrets he uses another type of transformation called negrets. Basically, the negret is considered as the dual of the regret. We study this problem in detail and we suggest the use of geometric aggregation operators in this method. For doing this, we develop a different method for constructing the negret matrix where all the values are positive. The main result obtained is that now the model is able to deal with negative numbers because of the transformation done in the negret matrix. We further extent these results to another model developed also by Yager about mixing valuations and negrets. Unfortunately, in this case we are not able to deal with negative numbers because the valuations can be either positive or negative.

Keywords: Decision Making, Aggregation operators, Negret, OWA operator, OWG operator.

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Authors: K. Shiba, T. Kaburagi, Y. Kurihara

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With global aging, people who require care, such as people with dementia (PwD), are increasing within many developed countries. And PwDs may wander and unconsciously set foot outdoors, it may lead serious accidents, such as, traffic accidents. Here, round-the-clock monitoring by caregivers is necessary, which can be a burden for the caregivers. Therefore, an automatic wandering detection system is required when an elderly person wanders outdoors, in which case the detection system transmits a ‘moving’ followed by an ‘absence’ state. In this paper, we focus on the transition from the ‘resting’ to the ‘absence’ state, via the ‘moving’ state as one of the wandering transitions. To capture the transition of the three states, our method based on the hidden Markov model (HMM) is built. Using our method, the restraint where the ‘resting’ state and ‘absence’ state cannot be transmitted to each other is applied. To validate our method, we conducted the experiment with 10 subjects. Our results show that the method can classify three states with 0.92 accuracy.

Keywords: Wander, microwave Doppler sensor, respiratory frequency band, the state transition, hidden Markov model.

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Authors: Hossein Morshedlou, Ahmad Abdollahzade Barforoush

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Recent developments in storage technology and networking architectures have made it possible for broad areas of applications to rely on data streams for quick response and accurate decision making. Data streams are generated from events of real world so existence of associations, which are among the occurrence of these events in real world, among concepts of data streams is logical. Extraction of these hidden associations can be useful for prediction of subsequent concepts in concept shifting data streams. In this paper we present a new method for learning association among concepts of data stream and prediction of what the next concept will be. Knowing the next concept, an informed update of data model will be possible. The results of conducted experiments show that the proposed method is proper for classification of concept shifting data streams.

Keywords: Data Stream, Classification, Concept Shift, History.

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Authors: J. Ruiz-Pinales, J. J. Acosta-Reyes, A. Salazar-Garibay, R. Jaime-Rivas

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In this paper, we present a new method for incorporating global shift invariance in support vector machines. Unlike other approaches which incorporate a feature extraction stage, we first scale the image and then classify it by using the modified support vector machines classifier. Shift invariance is achieved by replacing dot products between patterns used by the SVM classifier with the maximum cross-correlation value between them. Unlike the normal approach, in which the patterns are treated as vectors, in our approach the patterns are treated as matrices (or images). Crosscorrelation is computed by using computationally efficient techniques such as the fast Fourier transform. The method has been tested on the ORL face database. The tests indicate that this method can improve the recognition rate of an SVM classifier.

Keywords: Face recognition, support vector machines, shiftinvariance, image registration.

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Authors: K.Tavzarashvili, G.Ghvedashili

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A semi-analytic boundary discretization method, the Method of Auxiliary Sources (MAS) is used to analyze Optical Antennas consisting of metallic parts. In addition to standard dipoletype antennas, consisting of two pieces of metal, a new structure consisting of a single metal piece with a tiny groove in the center is analyzed. It is demonstrated that difficult numerical problems are caused because optical antennas exhibit strong material dispersion, loss, and plasmon-polariton effects that require a very accurate numerical simulation. This structure takes advantage of the Channel Plasmon-Polariton (CPP) effect and exhibits a strong enhancement of the electric field in the groove. Also primitive 3D antenna model with spherical nano particles is analyzed.

Keywords: optical antenna, channel plasmon-polariton, computational physics, Method of Auxiliary Sources

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