Search results for: teaching method
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 8568

Search results for: teaching method

5508 A Holistic Conceptual Measurement Framework for Assessing the Effectiveness and Viability of an Academic Program

Authors: Munir Majdalawieh, Adam Marks

Abstract:

In today’s very competitive higher education industry (HEI), HEIs are faced with the primary concern of developing, deploying, and sustaining high quality academic programs. Today, the HEI has well-established accreditation systems endorsed by a country’s legislation and institutions. The accreditation system is an educational pathway focused on the criteria and processes for evaluating educational programs. Although many aspects of the accreditation process highlight both the past and the present (prove), the “program review” assessment is "forward-looking assessment" (improve) and thus transforms the process into a continuing assessment activity rather than a periodic event. The purpose of this study is to propose a conceptual measurement framework for program review to be used by HEIs to undertake a robust and targeted approach to proactively and continuously review their academic programs to evaluate its practicality and effectiveness as well as to improve the education of the students. The proposed framework consists of two main components: program review principles and the program review measurement matrix.

Keywords: Academic program, program review principles, curriculum development, accreditation, evaluation, assessment, review measurement matrix, program review process, information technologies supporting learning, learning/teaching methodologies and assessment.

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5507 A Hybrid Fuzzy AGC in a Competitive Electricity Environment

Authors: H. Shayeghi, A. Jalili

Abstract:

This paper presents a new Hybrid Fuzzy (HF) PID type controller based on Genetic Algorithms (GA-s) for solution of the Automatic generation Control (AGC) problem in a deregulated electricity environment. In order for a fuzzy rule based control system to perform well, the fuzzy sets must be carefully designed. A major problem plaguing the effective use of this method is the difficulty of accurately constructing the membership functions, because it is a computationally expensive combinatorial optimization problem. On the other hand, GAs is a technique that emulates biological evolutionary theories to solve complex optimization problems by using directed random searches to derive a set of optimal solutions. For this reason, the membership functions are tuned automatically using a modified GA-s based on the hill climbing method. The motivation for using the modified GA-s is to reduce fuzzy system effort and take large parametric uncertainties into account. The global optimum value is guaranteed using the proposed method and the speed of the algorithm-s convergence is extremely improved, too. This newly developed control strategy combines the advantage of GA-s and fuzzy system control techniques and leads to a flexible controller with simple stricture that is easy to implement. The proposed GA based HF (GAHF) controller is tested on a threearea deregulated power system under different operating conditions and contract variations. The results of the proposed GAHF controller are compared with those of Multi Stage Fuzzy (MSF) controller, robust mixed H2/H∞ and classical PID controllers through some performance indices to illustrate its robust performance for a wide range of system parameters and load changes.

Keywords: AGC, Hybrid Fuzzy Controller, Deregulated Power System, Power System Control, GAs.

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5506 Speciation, Preconcentration, and Determination of Iron(II) and (III) Using 1,10-Phenanthroline Immobilized on Alumina-Coated Magnetite Nanoparticles as a Solid Phase Extraction Sorbent in Pharmaceutical Products

Authors: Hossein Tavallali, Mohammad Ali Karimi, Gohar Deilamy-Rad

Abstract:

The proposed method for speciation, preconcentration and determination of Fe(II) and Fe(III) in pharmaceutical products was developed using of alumina-coated magnetite nanoparticles (Fe3O4/Al2O3 NPs) as solid phase extraction (SPE) sorbent in magnetic mixed hemimicell solid phase extraction (MMHSPE) technique followed by flame atomic absorption spectrometry analysis. The procedure is based on complexation of Fe(II) with 1, 10-phenanthroline (OP) as complexing reagent for Fe(II) that immobilized on the modified Fe3O4/Al2O3 NPs. The extraction and concentration process for pharmaceutical sample was carried out in a single step by mixing the extraction solvent, magnetic adsorbents under ultrasonic action. Then, the adsorbents were isolated from the complicated matrix easily with an external magnetic field. Fe(III) ions determined after facility reduced to Fe(II) by added a proper reduction agent to sample solutions. Compared with traditional methods, the MMHSPE method simplified the operation procedure and reduced the analysis time. Various influencing parameters on the speciation and preconcentration of trace iron, such as pH, sample volume, amount of sorbent, type and concentration of eluent, were studied. Under the optimized operating conditions, the preconcentration factor of the modified nano magnetite for Fe(II) 167 sample was obtained. The detection limits and linear range of this method for iron were 1.0 and 9.0 - 175 ng.mL−1, respectively. Also the relative standard deviation for five replicate determinations of 30.00 ng.mL-1 Fe2+ was 2.3%.

Keywords: Alumina-coated magnetite nanoparticles, magnetic mixed hemimicell solid-phase extraction, Fe(ΙΙ) and Fe(ΙΙΙ), pharmaceutical sample.

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5505 Internal Loading Distribution in Statically Loaded Ball Bearings Subjected to a Centric Thrust Load: Alternative Approach

Authors: Mário C. Ricci

Abstract:

An alternative iterative computational procedure is proposed for internal normal ball loads calculation in statically loaded single-row, angular-contact ball bearings, subjected to a known thrust load, which is applied in the inner ring at the geometric bearing center line. An accurate method for curvature radii at contacts with inner and outer raceways in the direction of the motion is used. Numerical aspects of the iterative procedure are discussed. Numerical examples results for a 218 angular-contact ball bearing have been compared with those from the literature. Twenty figures are presented showing the geometrical features, the behavior of the convergence variables and the following parameters as functions of the thrust load: normal ball loads, contact angle, distance between curvature centers, and normal ball and axial deflections.

Keywords: Ball, Bearing, Static, Load, Iterative, Numerical, Method.

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5504 Piezoelectric Transducer Modeling: with System Identification (SI) Method

Authors: Nora Taghavi, Ali Sadr

Abstract:

System identification is the process of creating models of dynamic process from input- output signals. The aim of system identification can be identified as “ to find a model with adjustable parameters and then to adjust them so that the predicted output matches the measured output". This paper presents a method of modeling and simulating with system identification to achieve the maximum fitness for transformation function. First by using optimized KLM equivalent circuit for PVDF piezoelectric transducer and assuming different inputs including: sinuside, step and sum of sinusides, get the outputs, then by using system identification toolbox in MATLAB, we estimate the transformation function from inputs and outputs resulted in last program. Then compare the fitness of transformation function resulted from using ARX,OE(Output- Error) and BJ(Box-Jenkins) models in system identification toolbox and primary transformation function form KLM equivalent circuit.

Keywords: PVDF modeling, ARX, BJ(Box-Jenkins), OE(Output-Error), System Identification.

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5503 Model Updating-Based Approach for Damage Prognosis in Frames via Modal Residual Force

Authors: Gholamreza Ghodrati Amiri, Mojtaba Jafarian Abyaneh, Ali Zare Hosseinzadeh

Abstract:

This paper presents an effective model updating strategy for damage localization and quantification in frames by defining damage detection problem as an optimization issue. A generalized version of the Modal Residual Force (MRF) is employed for presenting a new damage-sensitive cost function. Then, Grey Wolf Optimization (GWO) algorithm is utilized for solving suggested inverse problem and the global extremums are reported as damage detection results. The applicability of the presented method is investigated by studying different damage patterns on the benchmark problem of the IASC-ASCE, as well as a planar shear frame structure. The obtained results emphasize good performance of the method not only in free-noise cases, but also when the input data are contaminated with different levels of noises.

Keywords: Frame, grey wolf optimization algorithm, modal residual force, structural damage detection.

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5502 Hydrogen Storage In Single-Walled Carbon Nanotubes Purified By Microwave Digestion Method

Authors: Neslihan Yuca, Nilgün Karatepe

Abstract:

The aim of this study was to synthesize the single walled carbon nanotubes (SWCNTs) and determine their hydrogen storage capacities. SWCNTs were firstly synthesized by chemical vapor deposition (CVD) of acetylene (C2H2) on a magnesium oxide (MgO) powder impregnated with an iron nitrate (Fe(NO3)3·9H2O) solution. The synthesis parameters were selected as: the synthesis temperature of 800°C, the iron content in the precursor of 5% and the synthesis time of 30 min. Purification process of SWCNTs was fulfilled by microwave digestion at three different temperatures (120, 150 and 200 °C), three different acid concentrations (0.5, 1 and 1.5 M) and for three different time intervals (15, 30 and 60 min). Nitric acid (HNO3) was used in the removal of the metal catalysts. The hydrogen storage capacities of the purified materials were measured using volumetric method at the liquid nitrogen temperature and gas pressure up to 100 bar. The effects of the purification conditions such as temperature, time and acid concentration on hydrogen adsorption were investigated.

Keywords: Carbon nanotubes, purification, microwavedigestion, hydrogen storage

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5501 Closing the Achievement Gap Within Reading and Mathematics Classrooms by Fostering Hispanic Students- Educational Resilience

Authors: Hersh C. Waxman, Yolanda N. Padrón, Jee-Young Shin, Héctor H. Rivera

Abstract:

While many studies have conducted the achievement gap between groups of students in school districts, few studies have utilized resilience research to investigate achievement gaps within classrooms. This paper aims to summarize and discuss some recent studies Waxman, Padr├│n, and their colleagues conducted, in which they examined learning environment differences between resilient and nonresilient students in reading and mathematics classrooms. The classes consist of predominantly Hispanic elementary school students from low-income families. These studies all incorporated learning environment questionnaires and systematic observation methods. Significant differences were found between resilient and nonresilient students on their classroom learning environments and classroom behaviors. The observation results indicate that the amount and quality of teacher and student academic interaction are two of the most influential variables that promote student outcomes. This paper concludes by suggesting the following teacher practices to promote resiliency in schools: (a) using feedback from classroom observation and learning environment measures, (b) employing explicit teaching practices; and (c) understanding students on a social and personal level.

Keywords: achievement gap, classroom learning environments, educational resilience, systematic classroom observation

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5500 Spatial Time Series Models for Rice and Cassava Yields Based On Bayesian Linear Mixed Models

Authors: Panudet Saengseedam, Nanthachai Kantanantha

Abstract:

This paper proposes a linear mixed model (LMM) with spatial effects to forecast rice and cassava yields in Thailand at the same time. A multivariate conditional autoregressive (MCAR) model is assumed to present the spatial effects. A Bayesian method is used for parameter estimation via Gibbs sampling Markov Chain Monte Carlo (MCMC). The model is applied to the rice and cassava yields monthly data which have been extracted from the Office of Agricultural Economics, Ministry of Agriculture and Cooperatives of Thailand. The results show that the proposed model has better performance in most provinces in both fitting part and validation part compared to the simple exponential smoothing and conditional auto regressive models (CAR) from our previous study.

Keywords: Bayesian method, Linear mixed model, Multivariate conditional autoregressive model, Spatial time series.

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5499 Coupled Electromagnetic and Thermal Field Modeling of a Laboratory Busbar System

Authors: Tatyana R. Radeva, Ivan S. Yatchev, Dimitar N. Karastoyanov, Nikolay I. Stoimenov, Stanislav D. Gyoshev

Abstract:

The paper presents coupled electromagnetic and thermal field analysis of busbar system (of rectangular cross-section geometry) submitted to short circuit conditions. The laboratory model was validated against both analytical solution and experimental observations. The considered problem required the computation of the detailed distribution of the power losses and the heat transfer modes. In this electromagnetic and thermal analysis, different definitions of electric busbar heating were considered and compared. The busbar system is a three phase one and consists of aluminum, painted aluminum and copper busbar. The solution to the coupled field problem is obtained using the finite element method and the QuickField™ program. Experiments have been carried out using two different approaches and compared with computed results.

Keywords: Busbar system, coupled problems, finite element method, short-circuit currents.

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5498 A Data Hiding Model with High Security Features Combining Finite State Machines and PMM method

Authors: Souvik Bhattacharyya, Gautam Sanyal

Abstract:

Recent years have witnessed the rapid development of the Internet and telecommunication techniques. Information security is becoming more and more important. Applications such as covert communication, copyright protection, etc, stimulate the research of information hiding techniques. Traditionally, encryption is used to realize the communication security. However, important information is not protected once decoded. Steganography is the art and science of communicating in a way which hides the existence of the communication. Important information is firstly hidden in a host data, such as digital image, video or audio, etc, and then transmitted secretly to the receiver.In this paper a data hiding model with high security features combining both cryptography using finite state sequential machine and image based steganography technique for communicating information more securely between two locations is proposed. The authors incorporated the idea of secret key for authentication at both ends in order to achieve high level of security. Before the embedding operation the secret information has been encrypted with the help of finite-state sequential machine and segmented in different parts. The cover image is also segmented in different objects through normalized cut.Each part of the encoded secret information has been embedded with the help of a novel image steganographic method (PMM) on different cuts of the cover image to form different stego objects. Finally stego image is formed by combining different stego objects and transmit to the receiver side. At the receiving end different opposite processes should run to get the back the original secret message.

Keywords: Cover Image, Finite state sequential machine, Melaymachine, Pixel Mapping Method (PMM), Stego Image, NCUT.

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5497 Analysis of Stress Concentration and Deflectionin Isotropic and Orthotropic Rectangular Plates with Central Circular Hole under Transverse Static Loading

Authors: Nitin Kumar Jain

Abstract:

The distributions of stresses and deflection in rectangular isotropic and orthotropic plates with central circular hole under transverse static loading have been studied using finite element method. The aim of author is to analyze the effect of D/A ratio (where D is hole diameter and A is plate width) upon stress concentration factor (SCF) and deflection in isotropic and orthotropic plates under transverse static loading. The D/A ratio is varied from 0.01 to 0.9. The analysis is done for plates of isotropic and two different orthotropic materials. The results are obtained for three different boundary conditions. The variations of SCF and deflection with respect to D/A ratio are presented in graphical form and discussed. The finite element formulation is carried out in the analysis section of the ANSYS package.

Keywords: Finite Element Method, SCF, Deflection, Plate, Boundary conditions

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5496 A Textual Analysis of Prospective Teachers’ Social Justice Identity Development and LGBTQ Advocacy

Authors: Mi Ok Kang

Abstract:

This study examined the influences of including LGBTQ-related content in a multicultural teacher education course on the development of prospective teachers’ social justice identities. Appling a content analysis to 53 reflection texts written by participating prospective teachers in response to the relevant course content, this study deduced the stages of social justice identity development (naïve, acceptance, resistance, redefinition, and internalization) that participants reached during the course. The analysis demonstrated that the participants reached various stages in the social identity development model and none of the participants remained at the naïve stage during/after class. The majority (53%) of the participants reached the internalization stage during the coursework and became conscious about the heterosexual privileges they have had and aware of possible impacts of such privilege on their future LGBTQ students. Also the participants had begun to develop pedagogic action plans and devised applicable teaching strategies for their future students based on the new understanding of heteronormativity. We expect this study will benefit teacher educators and educational administrators who want to address LGBTQ-related issues in their multicultural education programs and/or revisit the goals, directions, and implications of their approach.

Keywords: LGBTQ, heteronormativity, social justice identity, teacher education, multicultural education, content analysis.

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5495 Evaluating some Feature Selection Methods for an Improved SVM Classifier

Authors: Daniel Morariu, Lucian N. Vintan, Volker Tresp

Abstract:

Text categorization is the problem of classifying text documents into a set of predefined classes. After a preprocessing step the documents are typically represented as large sparse vectors. When training classifiers on large collections of documents, both the time and memory restrictions can be quite prohibitive. This justifies the application of features selection methods to reduce the dimensionality of the document-representation vector. Four feature selection methods are evaluated: Random Selection, Information Gain (IG), Support Vector Machine (called SVM_FS) and Genetic Algorithm with SVM (GA_FS). We showed that the best results were obtained with SVM_FS and GA_FS methods for a relatively small dimension of the features vector comparative with the IG method that involves longer vectors, for quite similar classification accuracies. Also we present a novel method to better correlate SVM kernel-s parameters (Polynomial or Gaussian kernel).

Keywords: Features selection, learning with kernels, support vector machine, genetic algorithms and classification.

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5494 Local Mesh Co-Occurrence Pattern for Content Based Image Retrieval

Authors: C. Yesubai Rubavathi, R. Ravi

Abstract:

This paper presents the local mesh co-occurrence patterns (LMCoP) using HSV color space for image retrieval system. HSV color space is used in this method to utilize color, intensity and brightness of images. Local mesh patterns are applied to define the local information of image and gray level co-occurrence is used to obtain the co-occurrence of LMeP pixels. Local mesh co-occurrence pattern extracts the local directional information from local mesh pattern and converts it into a well-mannered feature vector using gray level co-occurrence matrix. The proposed method is tested on three different databases called MIT VisTex, Corel, and STex. Also, this algorithm is compared with existing methods, and results in terms of precision and recall are shown in this paper.

Keywords: Content-based image retrieval system, HSV color space, gray level co-occurrence matrix, local mesh pattern.

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5493 Calibration Model of %Titratable Acidity (Citric Acid) for Intact Tomato by Transmittance SW-NIR Spectroscopy

Authors: K. Petcharaporn, S. Kumchoo

Abstract:

The acidity (citric acid) is the one of chemical content that can be refer to the internal quality and it’s a maturity index of tomato, The titratable acidity (%TA) can be predicted by a non-destructive method prediction by using the transmittance short wavelength (SW-NIR) spectroscopy in the wavelength range between 665-955 nm. The set of 167 tomato samples divided into groups of 117 tomatoes sample for training set and 50 tomatoes sample for test set were used to establish the calibration model to predict and measure %TA by partial least squares regression (PLSR) technique. The spectra were pretreated with MSC pretreatment and it gave the optimal result for calibration model as (R = 0.92, RMSEC = 0.03%) and this model obtained high accuracy result to use for %TA prediction in test set as (R = 0.81, RMSEP = 0.05%). From the result of prediction in test set shown that the transmittance SW-NIR spectroscopy technique can be used for a non-destructive method for %TA prediction of tomato.

Keywords: Tomato, quality, prediction, transmittance, titratable acidity, citric acid.

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5492 Comparative Study of Fault Identification and Classification on EHV Lines Using Discrete Wavelet Transform and Fourier Transform Based ANN

Authors: K.Gayathri, N. Kumarappan

Abstract:

An appropriate method for fault identification and classification on extra high voltage transmission line using discrete wavelet transform is proposed in this paper. The sharp variations of the generated short circuit transient signals which are recorded at the sending end of the transmission line are adopted to identify the fault. The threshold values involve fault classification and these are done on the basis of the multiresolution analysis. A comparative study of the performance is also presented for Discrete Fourier Transform (DFT) based Artificial Neural Network (ANN) and Discrete Wavelet Transform (DWT). The results prove that the proposed method is an effective and efficient one in obtaining the accurate result within short duration of time by using Daubechies 4 and 9. Simulation of the power system is done using MATLAB.

Keywords: EHV transmission line, Fault identification and classification, Discrete wavelet transform, Multiresolution analysis, Artificial neural network

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5491 New Efficient Method for Coding Color Images

Authors: Walaa M.Abd-Elhafiez, Wajeb Gharibi

Abstract:

In this paper a novel color image compression technique for efficient storage and delivery of data is proposed. The proposed compression technique started by RGB to YCbCr color transformation process. Secondly, the canny edge detection method is used to classify the blocks into the edge and non-edge blocks. Each color component Y, Cb, and Cr compressed by discrete cosine transform (DCT) process, quantizing and coding step by step using adaptive arithmetic coding. Our technique is concerned with the compression ratio, bits per pixel and peak signal to noise ratio, and produce better results than JPEG and more recent published schemes (like CBDCT-CABS and MHC). The provided experimental results illustrate the proposed technique that is efficient and feasible in terms of compression ratio, bits per pixel and peak signal to noise ratio.

Keywords: Image compression, color image, Q-coder, quantization, edge-detection.

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5490 Lattice Boltzmann Method for Turbulent Heat Transfer in Wavy Channel Flows

Authors: H.Y. Lai, S. C. Chang, W. L. Chen

Abstract:

The hydrodynamic and thermal lattice Boltzmann methods are applied to investigate the turbulent convective heat transfer in the wavy channel flows. In this study, the turbulent phenomena are modeling by large-eddy simulations with the Smagorinsky model. As a benchmark, the laminar and turbulent backward-facing step flows are simulated first. The results give good agreement with other numerical and experimental data. For wavy channel flows, the distribution of Nusselt number and the skin-friction coefficients are calculated to evaluate the heat transfer effect and the drag force. It indicates that the vortices at the trough would affect the magnitude of drag and weaken the heat convection effects on the wavy surface. In turbulent cases, if the amplitude of the wavy boundary is large enough, the secondary vortices would be generated at troughs and contribute to the heat convection. Finally, the effects of different Re on the turbulent transport phenomena are discussed.

Keywords: Heat transfer, lattice Boltzmann method, turbulence, wavy channel.

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5489 Generation of Highly Ordered Porous Antimony-Doped Tin Oxide Film by A Simple Coating Method with Colloidal Template

Authors: Asep Bayu Dani Nandiyanto, Asep Suhendi, Yutaka Kisakibaru, Takashi Ogi, Kikuo Okuyama

Abstract:

An ordered porous antimony-doped tin oxide (ATO) film was successfully prepared using a simple coating process with colloidal templates. The facile production was effective when a combination of 16-nm ATO (as a model of an inorganic nanoparticle) and polystyrene (PS) spheres (as a model of the template) weresimply coated to produce a composite ATO/PS film. Heat treatment was then used to remove the PS and produce the porous film. The porous film with a spherical pore shape and a highly ordered porous structure could be obtained. A potential way for the control of pore size could be also achieved by changing initial template size. The theoretical explanation and mechanism of porous formation were also added, which would be important for the scaling-up prediction and estimation.

Keywords: Porous structure film; ATO particle; Ultra-low refractive index; vertical drop method; Low-density material;

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5488 A Robust Method for Hand Tracking Using Mean-shift Algorithm and Kalman Filter in Stereo Color Image Sequences

Authors: Mahmoud Elmezain, Ayoub Al-Hamadi, Robert Niese, Bernd Michaelis

Abstract:

Real-time hand tracking is a challenging task in many computer vision applications such as gesture recognition. This paper proposes a robust method for hand tracking in a complex environment using Mean-shift analysis and Kalman filter in conjunction with 3D depth map. The depth information solve the overlapping problem between hands and face, which is obtained by passive stereo measuring based on cross correlation and the known calibration data of the cameras. Mean-shift analysis uses the gradient of Bhattacharyya coefficient as a similarity function to derive the candidate of the hand that is most similar to a given hand target model. And then, Kalman filter is used to estimate the position of the hand target. The results of hand tracking, tested on various video sequences, are robust to changes in shape as well as partial occlusion.

Keywords: Computer Vision and Image Analysis, Object Tracking, Gesture Recognition.

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5487 A Blind SLM Scheme for Reduction of PAPR in OFDM Systems

Authors: K. Kasiri, M. J. Dehghani

Abstract:

In this paper we propose a blind algorithm for peakto- average power ratio (PAPR) reduction in OFDM systems, based on selected mapping (SLM) algorithm as a distortionless method. The main drawback of the conventional SLM technique is the need for transmission of several side information bits, for each data block, which results in loss in data rate transmission. In the proposed method some special number of carriers in the OFDM frame is reserved to be rotated with one of the possible phases according to the number of phase sequence blocks in SLM algorithm. Reserving some limited number of carriers wont effect the reduction in PAPR of OFDM signal. Simulation results show using ML criteria at the receiver will lead to the same system-performance as the conventional SLM algorithm, while there is no need to send any side information to the receiver.

Keywords: Orthogonal Frequency Division Multiplexing(OFDM), Peak-to-Average Power Ratio (PAPR), Selected Mapping(SLM), Blind SLM (BSLM).

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5486 Parallel Pipelined Conjugate Gradient Algorithm on Heterogeneous Platforms

Authors: Sergey Kopysov, Nikita Nedozhogin, Leonid Tonkov

Abstract:

The article presents a parallel iterative solver for large sparse linear systems which can be used on a heterogeneous platform. Traditionally, the problem of solving linear systems do not scale well on cluster containing multiple Central Processing Units (multi-CPUs cluster) or cluster containing multiple Graphics Processing Units (multi-GPUs cluster). For example, most of the attempts to implement the classical conjugate gradient method were at best counted in the same amount of time as the problem was enlarged. The paper proposes the pipelined variant of the conjugate gradient method (PCG), a formulation that is potentially better suited for hybrid CPU/GPU computing since it requires only one synchronization point per one iteration, instead of two for standard CG (Conjugate Gradient). The standard and pipelined CG methods need the vector entries generated by current GPU and other GPUs for matrix-vector product. So the communication between GPUs becomes a major performance bottleneck on miltiGPU cluster. The article presents an approach to minimize the communications between parallel parts of algorithms. Additionally, computation and communication can be overlapped to reduce the impact of data exchange. Using pipelined version of the CG method with one synchronization point, the possibility of asynchronous calculations and communications, load balancing between the CPU and GPU for solving the large linear systems allows for scalability. The algorithm is implemented with the combined use of technologies: MPI, OpenMP and CUDA. We show that almost optimum speed up on 8-CPU/2GPU may be reached (relatively to a one GPU execution). The parallelized solver achieves a speedup of up to 5.49 times on 16 NVIDIA Tesla GPUs, as compared to one GPU.

Keywords: Conjugate Gradient, GPU, parallel programming, pipelined algorithm.

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5485 An MCDM Approach to Selection Scheduling Rule in Robotic Flexibe Assembly Cells

Authors: Khalid Abd, Kazem Abhary, Romeo Marian

Abstract:

Multiple criteria decision making (MCDM) is an approach to ranking the solutions and finding the best one when two or more solutions are provided. In this study, MCDM approach is proposed to select the most suitable scheduling rule of robotic flexible assembly cells (RFACs). Two MCDM approaches, Analytic Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) are proposed for solving the scheduling rule selection problem. The AHP method is employed to determine the weights of the evaluation criteria, while the TOPSIS method is employed to obtain final ranking order of scheduling rules. Four criteria are used to evaluate the scheduling rules. Also, four scheduling policies of RFAC are examined to choose the most appropriate one for this purpose. A numerical example illustrates applications of the suggested methodology. The results show that the methodology is practical and works in RFAC settings.

Keywords: AHP, TOPSIS, Scheduling rules selection

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5484 Image-Based (RBG) Technique for Estimating Phosphorus Levels of Crops

Authors: M. M. Ali, Ahmed Al-Ani, Derek Eamus, Daniel K. Y. Tan

Abstract:

In this glasshouse study, we developed a new imagebased non-destructive technique for detecting leaf P status of different crops such as cotton, tomato and lettuce. The plants were grown on a nutrient solution containing different P concentrations, e.g. 0%, 50% and 100% of recommended P concentration (P0 = no P, L; P1 = 2.5 mL 10 L-1 of P and P2 = 5 mL 10 L-1 of P). After 7 weeks of treatment, the plants were harvested and data on leaf P contents were collected using the standard destructive laboratory method and at the same time leaf images were collected by a handheld crop image sensor. We calculated leaf area, leaf perimeter and RGB (red, green and blue) values of these images. These data were further used in linear discriminant analysis (LDA) to estimate leaf P contents, which successfully classified these plants on the basis of leaf P contents. The data indicated that P deficiency in crop plants can be predicted using leaf image and morphological data. Our proposed nondestructive imaging method is precise in estimating P requirements of different crop species.

Keywords: Image-based techniques, leaf area, leaf P contents, linear discriminant analysis.

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5483 Convective Heat Transfer of Viscoelastic Flow in a Curved Duct

Authors: M. Norouzi, M. H. Kayhani, M. R. H. Nobari, M. Karimi Demneh

Abstract:

In this paper, fully developed flow and heat transfer of viscoelastic materials in curved ducts with square cross section under constant heat flux have been investigated. Here, staggered mesh is used as computational grids and flow and heat transfer parameters have been allocated in this mesh with marker and cell method. Numerical solution of governing equations has being performed with FTCS finite difference method. Furthermore, Criminale-Eriksen- Filbey (CEF) constitutive equation has being used as viscoelastic model. CEF constitutive equation is a suitable model for studying steady shear flow of viscoelastic materials which is able to model both effects of the first and second normal stress differences. Here, it is shown that the first and second normal stresses differences have noticeable and inverse effect on secondary flows intensity and mean Nusselt number which is the main novelty of current research.

Keywords: Viscoelastic, fluid flow, heat convection, CEF model, curved duct, square cross section.

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5482 3D CAD Models and its Feature Similarity

Authors: Elmi Abu Bakar, Tetsuo Miyake, Zhong Zhang, Takashi Imamura

Abstract:

Knowing the geometrical object pose of products in manufacturing line before robot manipulation is required and less time consuming for overall shape measurement. In order to perform it, the information of shape representation and matching of objects is become required. Objects are compared with its descriptor that conceptually subtracted from each other to form scalar metric. When the metric value is smaller, the object is considered closed to each other. Rotating the object from static pose in some direction introduce the change of value in scalar metric value of boundary information after feature extraction of related object. In this paper, a proposal method for indexing technique for retrieval of 3D geometrical models based on similarity between boundaries shapes in order to measure 3D CAD object pose using object shape feature matching for Computer Aided Testing (CAT) system in production line is proposed. In experimental results shows the effectiveness of proposed method.

Keywords: CAD, rendering, feature extraction, feature classification.

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5481 BLDC Motor Driven for Solar Photo Voltaic Powered Air Cooling System

Authors: D. Shobha Rani, M. Muralidhar

Abstract:

Solar photovoltaic (SPV) power systems can be employed as electrical power sources to meet the daily residential energy needs of rural areas that have no access to grid systems. In view of this, a standalone SPV powered air cooling system is proposed in this paper, which constitutes a dc-dc boost converter, two voltage source inverters (VSI) connected to two brushless dc (BLDC) motors which are coupled to a centrifugal water pump and a fan blower. A simple and efficient Maximum Power Point Tracking (MPPT) technique based on Silver Mean Method (SMM) is utilized in this paper. The air cooling system is developed and simulated using the MATLAB / Simulink environment considering the dynamic and steady state variation in the solar irradiance.

Keywords: Boost converter, solar photovoltaic array, voltage source inverter, brushless DC motor, solar irradiance, Maximum Power Point Tracking, Silver Mean Method.

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5480 Improving University Operations with Data Mining: Predicting Student Performance

Authors: Mladen Dragičević, Mirjana Pejić Bach, Vanja Šimičević

Abstract:

The purpose of this paper is to develop models that would enable predicting student success. These models could improve allocation of students among colleges and optimize the newly introduced model of government subsidies for higher education. For the purpose of collecting data, an anonymous survey was carried out in the last year of undergraduate degree student population using random sampling method. Decision trees were created of which two have been chosen that were most successful in predicting student success based on two criteria: Grade Point Average (GPA) and time that a student needs to finish the undergraduate program (time-to-degree). Decision trees have been shown as a good method of classification student success and they could be even more improved by increasing survey sample and developing specialized decision trees for each type of college. These types of methods have a big potential for use in decision support systems.

Keywords: Data mining, knowledge discovery in databases, prediction models, student success.

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5479 Synchronous Courses Attendance in Distance Higher Education: Case Study of a Computer Science Department

Authors: Thierry Eude

Abstract:

The use of videoconferencing platforms adapted to teaching offers students the opportunity to take distance education courses in much the same way as traditional in-class training. The sessions can be recorded and they allow students the option of following the courses synchronously or asynchronously. Three typical profiles can then be distinguished: students who choose to follow the courses synchronously, students who could attend the course in synchronous mode but choose to follow the session off-line, and students who follow the course asynchronously as they cannot attend the course when it is offered because of professional or personal constraints. Our study consists of observing attendance at all distance education courses offered in the synchronous mode by the Computer Science and Software Engineering Department at Laval University during 10 consecutive semesters. The aim is to identify factors that influence students in their choice of attending the distance courses in synchronous mode. It was found that participation tends to be relatively stable over the years for any one semester (fall, winter summer) and is similar from one course to another, although students may be increasingly familiar with the synchronous distance education courses. Average participation is around 28%. There may be deviations, but they concern only a few courses during certain semesters, suggesting that these deviations would only have occurred because of the composition of particular promotions during specific semesters. Furthermore, course schedules have a great influence on the attendance rate. The highest rates are all for courses which are scheduled outside office hours.

Keywords: Attendance, distance undergraduate education in computer science, student behavior, synchronous e-learning.

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