Search results for: Conventional
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1449

Search results for: Conventional

429 Novel NMR-Technology to Assess Food Quality and Safety

Authors: Markus Link, Manfred Spraul, Hartmut Schaefer, Fang Fang, Birk Schuetz

Abstract:

High Resolution NMR Spectroscopy offers unique screening capabilities for food quality and safety by combining non-targeted and targeted screening in one analysis.

The objective is to demonstrate, that due to its extreme reproducibility NMR can detect smallest changes in concentrations of many components in a mixture, which is best monitored by statistical evaluation however also delivers reliable quantification results.

The methodology typically uses a 400 MHz high resolution instrument under full automation after minimized sample preparation.

For example one fruit juice analysis in a push button operation takes at maximum 15 minutes and delivers a multitude of results, which are automatically summarized in a PDF report.

The method has been proven on fruit juices, where so far unknown frauds could be detected. In addition conventional targeted parameters are obtained in the same analysis. This technology has the advantage that NMR is completely quantitative and concentration calibration only has to be done once for all compounds. Since NMR is so reproducible, it is also transferable between different instruments (with same field strength) and laboratories. Based on strict SOP`s, statistical models developed once can be used on multiple instruments and strategies for compound identification and quantification are applicable as well across labs.

Keywords: Automated solution, NMR, non-targeted screening, targeted screening.

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428 Towards Model-Driven Communications

Authors: Antonio Natali, Ambra Molesini

Abstract:

In modern distributed software systems, the issue of communication among composing parts represents a critical point, but the idea of extending conventional programming languages with general purpose communication constructs seems difficult to realize. As a consequence, there is a (growing) gap between the abstraction level required by distributed applications and the concepts provided by platforms that enable communication. This work intends to discuss how the Model Driven Software Development approach can be considered as a mature technology to generate in automatic way the schematic part of applications related to communication, by providing at the same time high level specialized languages useful in all the phases of software production. To achieve the goal, a stack of languages (meta-meta¬models) has been introduced in order to describe – at different levels of abstraction – the collaborative behavior of generic entities in terms of communication actions related to a taxonomy of messages. Finally, the generation of platforms for communication is viewed as a form of specification of language semantics, that provides executable models of applications together with model-checking supports and effective runtime environments.

Keywords: Interactions, specific languages, meta-models, model driven development.

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427 Perceptual JPEG Compliant Coding by Using DCT-Based Visibility Thresholds of Color Images

Authors: Kuo-Cheng Liu

Abstract:

Effective estimation of just noticeable distortion (JND) for images is helpful to increase the efficiency of a compression algorithm in which both the statistical redundancy and the perceptual redundancy should be accurately removed. In this paper, we design a DCT-based model for estimating JND profiles of color images. Based on a mathematical model of measuring the base detection threshold for each DCT coefficient in the color component of color images, the luminance masking adjustment, the contrast masking adjustment, and the cross masking adjustment are utilized for luminance component, and the variance-based masking adjustment based on the coefficient variation in the block is proposed for chrominance components. In order to verify the proposed model, the JND estimator is incorporated into the conventional JPEG coder to improve the compression performance. A subjective and fair viewing test is designed to evaluate the visual quality of the coding image under the specified viewing condition. The simulation results show that the JPEG coder integrated with the proposed DCT-based JND model gives better coding bit rates at visually lossless quality for a variety of color images.

Keywords: Just-noticeable distortion (JND), discrete cosine transform (DCT), JPEG.

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426 A Low Power SRAM Base on Novel Word-Line Decoding

Authors: Arash Azizi Mazreah, Mohammad T. Manzuri Shalmani, Hamid Barati, Ali Barati, Ali Sarchami

Abstract:

This paper proposes a low power SRAM based on five transistor SRAM cell. Proposed SRAM uses novel word-line decoding such that, during read/write operation, only selected cell connected to bit-line whereas, in conventional SRAM (CV-SRAM), all cells in selected row connected to their bit-lines, which in turn develops differential voltages across all bit-lines, and this makes energy consumption on unselected bit-lines. In proposed SRAM memory array divided into two halves and this causes data-line capacitance to reduce. Also proposed SRAM uses one bit-line and thus has lower bit-line leakage compared to CV-SRAM. Furthermore, the proposed SRAM incurs no area overhead, and has comparable read/write performance versus the CV-SRAM. Simulation results in standard 0.25μm CMOS technology shows in worst case proposed SRAM has 80% smaller dynamic energy consumption in each cycle compared to CV-SRAM. Besides, energy consumption in each cycle of proposed SRAM and CV-SRAM investigated analytically, the results of which are in good agreement with the simulation results.

Keywords: SRAM, write Operation, read Operation, capacitances, dynamic energy consumption.

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425 Cost Analysis of Hybrid Wind Energy Generating System Considering CO2 Emissions

Authors: M. A. Badr, M.N. El Kordy, A. N. Mohib, M. M. Ibrahim

Abstract:

The basic objective of the research is to study the effect of hybrid wind energy on the cost of generated electricity considering the cost of reduction CO2 emissions. The system consists of small wind turbine(s), storage battery bank and a diesel generator (W/D/B). Using an optimization software package, different system configurations are investigated to reach optimum configuration based on the net present cost (NPC) and cost of energy (COE) as economic optimization criteria. The cost of avoided CO2 is taken into consideration. The system is intended to supply the electrical load of a small community (gathering six families) in a remote Egyptian area. The investigated system is not connected to the electricity grid and may replace an existing conventional diesel powered electric supply system to reduce fuel consumption and CO2 emissions. The simulation results showed that W/D energy system is more economic than diesel alone. The estimated COE is 0.308$/kWh and extracting the cost of avoided CO2, the COE reached 0.226 $/kWh which is an external benefit of wind turbine, as there are no pollutant emissions through operational phase.

Keywords: Hybrid wind turbine systems, remote areas electrification, simulation of hybrid energy systems, techno-economic study.

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424 Optical 3D-Surface Reconstruction of Weak Textured Objects Based on an Approach of Disparity Stereo Inspection

Authors: Thomas Kerstein, Martin Laurowski, Philipp Klein, Michael Weyrich, Hubert Roth, Jürgen Wahrburg

Abstract:

Optical 3D measurement of objects is meaningful in numerous industrial applications. In various cases shape acquisition of weak textured objects is essential. Examples are repetition parts made of plastic or ceramic such as housing parts or ceramic bottles as well as agricultural products like tubers. These parts are often conveyed in a wobbling way during the automated optical inspection. Thus, conventional 3D shape acquisition methods like laser scanning might fail. In this paper, a novel approach for acquiring 3D shape of weak textured and moving objects is presented. To facilitate such measurements an active stereo vision system with structured light is proposed. The system consists of multiple camera pairs and auxiliary laser pattern generators. It performs the shape acquisition within one shot and is beneficial for rapid inspection tasks. An experimental setup including hardware and software has been developed and implemented.

Keywords: automated optical inspection, depth from structured light, stereo vision, surface reconstruction

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423 Bandwidth Efficient Diversity Scheme Using STTC Concatenated With STBC: MIMO Systems

Authors: Sameru Sharma, Sanjay Sharma, Derick Engles

Abstract:

Multiple-input multiple-output (MIMO) systems are widely in use to improve quality, reliability of wireless transmission and increase the spectral efficiency. However in MIMO systems, multiple copies of data are received after experiencing various channel effects. The limitations on account of complexity due to number of antennas in case of conventional decoding techniques have been looked into. Accordingly we propose a modified sphere decoder (MSD-1) algorithm with lower complexity and give rise to system with high spectral efficiency. With the aim to increase signal diversity we apply rotated quadrature amplitude modulation (QAM) constellation in multi dimensional space. Finally, we propose a new architecture involving space time trellis code (STTC) concatenated with space time block code (STBC) using MSD-1 at the receiver for improving system performance. The system gains have been verified with channel state information (CSI) errors.

Keywords: Channel State Information , Diversity, Multi-Antenna, Rotated Constellation, Space Time Codes.

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422 Dynamic Power Reduction in Sequential Circuits Using Look Ahead Clock Gating Technique

Authors: R. Manjith, C. Muthukumari

Abstract:

In this paper, a novel Linear Feedback Shift Register (LFSR) with Look Ahead Clock Gating (LACG) technique is presented to reduce the power consumption in modern processors and System-on-Chip. Clock gating is a predominant technique used to reduce unwanted switching of clock signals. Several clock gating techniques to reduce the dynamic power have been developed, of which LACG is predominant. LACG computes the clock enabling signals of each flip-flop (FF) one cycle ahead of time, based on the present cycle data of the flip-flops on which it depends. It overcomes the timing problems in the existing clock gating methods like datadriven clock gating and Auto-Gated flip-flops (AGFF) by allotting a full clock cycle for the determination of the clock enabling signals. Further to reduce the power consumption in LACG technique, FFs can be grouped so that they share a common clock enabling signal. Simulation results show that the novel grouped LFSR with LACG achieves 15.03% power savings than conventional LFSR with LACG and 44.87% than data-driven clock gating.

Keywords: AGFF, data-driven, LACG, LFSR.

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421 Thermodynamic Analysis of a Vapor Absorption System Using Modified Gouy-Stodola Equation

Authors: Gulshan Sachdeva, Ram Bilash

Abstract:

In this paper, the exergy analysis of vapor absorption refrigeration system using LiBr-H2O as working fluid is carried out with the modified Gouy-Stodola approach rather than the classical Gouy-Stodola equation and effect of varying input parameters is also studied on the performance of the system. As the modified approach uses the concept of effective temperature, the mathematical expressions for effective temperature have been formulated and calculated for each component of the system. Various constraints and equations are used to develop program in EES to solve these equations. The main aim of this analysis is to determine the performance of the system and the components having major irreversible loss. Results show that exergy destruction rate is considerable in absorber and generator followed by evaporator and condenser. There is an increase in exergy destruction in generator, absorber and condenser and decrease in the evaporator by the modified approach as compared to the conventional approach. The value of exergy determined by the modified Gouy-Stodola equation deviates maximum i.e. 26% in the generator as compared to the exergy calculated by the classical Gouy-Stodola method.

Keywords: Exergy analysis, Gouy-Stodola, refrigeration, vapor absorption.

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420 An Improved Fast Video Clip Search Algorithm for Copy Detection using Histogram-based Features

Authors: Feifei Lee, Qiu Chen, Koji Kotani, Tadahiro Ohmi

Abstract:

In this paper, we present an improved fast and robust search algorithm for copy detection using histogram-based features for short MPEG video clips from large video database. There are two types of histogram features used to generate more robust features. The first one is based on the adjacent pixel intensity difference quantization (APIDQ) algorithm, which had been reliably applied to human face recognition previously. An APIDQ histogram is utilized as the feature vector of the frame image. Another one is ordinal histogram feature which is robust to color distortion. Furthermore, by Combining with a temporal division method, the spatial and temporal features of the video sequence are integrated to realize fast and robust video search for copy detection. Experimental results show the proposed algorithm can detect the similar video clip more accurately and robust than conventional fast video search algorithm.

Keywords: Fast search, Copy detection, Adjacent pixel intensity difference quantization (APIDQ), DC image, Histogram feature.

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419 Detection of Actuator Faults for an Attitude Control System using Neural Network

Authors: S. Montenegro, W. Hu

Abstract:

The objective of this paper is to develop a neural network-based residual generator to detect the fault in the actuators for a specific communication satellite in its attitude control system (ACS). First, a dynamic multilayer perceptron network with dynamic neurons is used, those neurons correspond a second order linear Infinite Impulse Response (IIR) filter and a nonlinear activation function with adjustable parameters. Second, the parameters from the network are adjusted to minimize a performance index specified by the output estimated error, with the given input-output data collected from the specific ACS. Then, the proposed dynamic neural network is trained and applied for detecting the faults injected to the wheel, which is the main actuator in the normal mode for the communication satellite. Then the performance and capabilities of the proposed network were tested and compared with a conventional model-based observer residual, showing the differences between these two methods, and indicating the benefit of the proposed algorithm to know the real status of the momentum wheel. Finally, the application of the methods in a satellite ground station is discussed.

Keywords: Satellite, Attitude Control, Momentum Wheel, Neural Network, Fault Detection.

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418 A Modified Cross Correlation in the Frequency Domain for Fast Pattern Detection Using Neural Networks

Authors: Hazem M. El-Bakry, Qiangfu Zhao

Abstract:

Recently, neural networks have shown good results for detection of a certain pattern in a given image. In our previous papers [1-5], a fast algorithm for pattern detection using neural networks was presented. Such algorithm was designed based on cross correlation in the frequency domain between the input image and the weights of neural networks. Image conversion into symmetric shape was established so that fast neural networks can give the same results as conventional neural networks. Another configuration of symmetry was suggested in [3,4] to improve the speed up ratio. In this paper, our previous algorithm for fast neural networks is developed. The frequency domain cross correlation is modified in order to compensate for the symmetric condition which is required by the input image. Two new ideas are introduced to modify the cross correlation algorithm. Both methods accelerate the speed of the fast neural networks as there is no need for converting the input image into symmetric one as previous. Theoretical and practical results show that both approaches provide faster speed up ratio than the previous algorithm.

Keywords: Fast Pattern Detection, Neural Networks, Modified Cross Correlation

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417 Optimal Supplementary Damping Controller Design for TCSC Employing RCGA

Authors: S. Panda, S. C. Swain, A. K. Baliarsingh, C. Ardil

Abstract:

Optimal supplementary damping controller design for Thyristor Controlled Series Compensator (TCSC) is presented in this paper. For the proposed controller design, a multi-objective fitness function consisting of both damping factors and real part of system electromachanical eigenvalue is used and Real- Coded Genetic Algorithm (RCGA) is employed for the optimal supplementary controller parameters. The performance of the designed supplementary TCSC-based damping controller is tested on a weakly connected power system with different disturbances and loading conditions with parameter variations. Simulation results are presented and compared with a conventional power system stabilizer and also with the TCSC-based supplementary controller when the controller parameters are not optimized to show the effectiveness and robustness of the proposed approach over a wide range of loading conditions and disturbances.

Keywords: Power System Oscillations, Real-Coded Genetic Algorithm (RCGA), Thyristor Controlled Series Compensator (TCSC), Damping Controller, Power System Stabilizer.

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416 Performance Evaluation of Minimum Quantity Lubrication on EN3 Mild Steel Turning

Authors: Swapnil Rajan Jadhav, Ajay Vasantrao Kashikar

Abstract:

Lubrication, cooling and chip removal are the desired functions of any cutting fluid. Conventional or flood lubrication requires high volume flow rate and cost associated with this is higher. In addition, flood lubrication possesses health risks to machine operator. To avoid these consequences, dry machining and minimum quantity are two alternatives. Dry machining cannot be a suited alternative as it can generate greater heat and poor surface finish. Here, turning work is carried out on a Lathe machine using EN3 Mild steel. Variable cutting speeds and depth of cuts are provided and corresponding temperatures and surface roughness values were recorded. Experimental results are analyzed by Minitab software. Regression analysis, main effect plot, and interaction plot conclusion are drawn by using ANOVA. There is a 95.83% reduction in the use of cutting fluid. MQL gives a 9.88% reduction in tool temperature, this will improve tool life. MQL produced a 17.64% improved surface finish. MQL appears to be an economical and environmentally compatible lubrication technique for sustainable manufacturing.

Keywords: ANOVA, MQL, regression analysis, surface roughness

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415 Performance Evaluation of Minimum Quantity Lubrication on EN3 Mild Steel Turning

Authors: Swapnil Rajan Jadhav, Ajay Vasantrao Kashikar

Abstract:

Lubrication, cooling and chip removal are the desired functions of any cutting fluid. Conventional or flood lubrication requires high volume flow rate and cost associated with this is higher. In addition, flood lubrication possesses health risks to machine operator. To avoid these consequences, dry machining and minimum quantity are two alternatives. Dry machining cannot be a suited alternative as it can generate greater heat and poor surface finish. Here, turning work is carried out on a Lathe machine using EN3 Mild steel. Variable cutting speeds and depth of cuts are provided and corresponding temperatures and surface roughness values were recorded. Experimental results are analyzed by Minitab software. Regression analysis, main effect plot, and interaction plot conclusion are drawn by using ANOVA. There is a 95.83% reduction in the use of cutting fluid. MQL gives a 9.88% reduction in tool temperature, this will improve tool life. MQL produced a 17.64% improved surface finish. MQL appears to be an economical and environmentally compatible lubrication technique for sustainable manufacturing.

Keywords: ANOVA, MQL, regression analysis, surface roughness

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414 Data Envelopment Analysis with Partially Perfect Objects

Authors: Alexander Y. Vaninsky

Abstract:

This paper presents a simplified version of Data Envelopment Analysis (DEA) - a conventional approach to evaluating the performance and ranking of competitive objects characterized by two groups of factors acting in opposite directions: inputs and outputs. DEA with a Perfect Object (DEA PO) augments the group of actual objects with a virtual Perfect Object - the one having greatest outputs and smallest inputs. It allows for obtaining an explicit analytical solution and making a step to an absolute efficiency. This paper develops this approach further and introduces a DEA model with Partially Perfect Objects. DEA PPO consecutively eliminates the smallest relative inputs or greatest relative outputs, and applies DEA PO to the reduced collections of indicators. The partial efficiency scores are combined to get the weighted efficiency score. The computational scheme remains simple, like that of DEA PO, but the advantage of the DEA PPO is taking into account all of the inputs and outputs for each actual object. Firm evaluation is considered as an example.

Keywords: Data Envelopment Analysis, Perfect object, Partially perfect object, Partial efficiency, Explicit solution, Simplified algorithm.

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413 Interactive Planning of Suburban Apartment Buildings

Authors: J. Koiso-Kanttila, A. Soikkeli, A. Aapaoja

Abstract:

Construction in Finland is focusing increasingly on renovation instead of conventional new construction, and this trend will continue to grow in the coming years and decades. Renovation of the large number of suburban residential apartment buildings built in the 1960s and 1970s poses a particular challenge. However, renovation projects are demanding for the residents of these buildings, since they usually are uninitiated in construction issues. On the other hand, renovation projects generally apply the operating models of new construction. Nevertheless, the residents of an existing residential apartment building are some of the best experts on the site. Thus, in this research project we applied a relational model in developing and testing at case sites a planning process that employs interactive planning methods. Current residents, housing company managers, the city zoning manager, the contractor’s and prefab element supplier’s representatives, professional designers and researchers all took part in the planning. The entire interactive planning process progressed phase by phase as the participants’ and designers’ concerted discussion and ideation process, so that the end result was a renovation plan desired by the residents.

Keywords: Apartment building renovation, interactive planning, project alliance, user-orientedness.

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412 Novel Design and Analysis of a Brake Rotor

Authors: Sharath Kumar T., S.Vinodh

Abstract:

Over the course of the past century, the global automotive industry-s stance towards safety has evolved from one of contempt to one nearing reverence. A suspension system that provides safe handling and cornering capabilities can, with the help of an efficient braking system, improve safety to a large extent. The aim of this research is to propose a new automotive brake rotor design and to compare it with automotive vented disk rotor. Static structural and transient thermal analysis have been carried out on the vented disk rotor and proposed rotor designs to evaluate and compare their performance. Finite element analysis was employed for both static structural and transient thermal analysis. Structural analysis was carried out to study the stress and deformation pattern of the rotors under extreme loads. Time varying temperature load was applied on the rotors and the temperature distribution was analysed considering cooling parameters (convection and radiation). This dissertation illustrates the use of Finite Element Methods to examine models, concluding with a comparative study of the proposed rotor design and the conventional vented disk rotor for structural stability and thermal efficiency.

Keywords: Disk brakes, CAD model, rotor design, structural and thermal analysis

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411 Factors Influence Depositors- Withdrawal Behavior in Islamic Banks: A Theory of Reasoned Action

Authors: Muhamad Abduh, Jarita Duasa, Mohd. Azmi Omar

Abstract:

Unlike its conventional counterpart, Islamic principles forbid Islamic banks to take any interest-related income and thus makes deposits from depositors as an important source of fund for its operational and financing. Consequently, the risk of deposit withdrawal by depositors is an important aspect that should be wellmanaged in Islamic banking. This paper aims to investigate factors that influence depositors- withdrawal behavior in Islamic banks, particularly in Malaysia, using the framework of theory of reasoned action. A total of 368 respondents from Klang valley are involved in the analysis. The paper finds that all the constructs variable i.e. normative beliefs, subjective norms, behavioral beliefs, and attitude towards behavior are perceived to be distinct by the respondents. In addition, the structural equation model is able to verify the structural relationships between subjective norms, attitude towards behavior and behavioral intention. Subjective norms gives more influence to depositors- decision on deposit withdrawal compared to attitude towards behavior.

Keywords: Islamic bank, structural equation model, theory of reasoned action, withdrawal behavior

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410 Design of Robust Fuzzy Logic Power System Stabilizer

Authors: S. A. Taher, A. Shemshadi

Abstract:

Power system stabilizers (PSS) must be capable of providing appropriate stabilization signals over a broad range of operating conditions and disturbance. Traditional PSS rely on robust linear design method in an attempt to cover a wider range of operating condition. Expert or rule-based controllers have also been proposed. Recently fuzzy logic (FL) as a novel robust control design method has shown promising results. The emphasis in fuzzy control design center is around uncertainties in the system parameters & operating conditions. In this paper a novel Robust Fuzzy Logic Power System Stabilizer (RFLPSS) design is proposed The RFLPSS basically utilizes only one measurable Δω signal as input (generator shaft speed). The speed signal is discretized resulting in three inputs to the RFLPSS. There are six rules for the fuzzification and two rules for defuzzification. To provide robustness, additional signal namely, speed are used as inputs to RFLPSS enabling appropriate gain adjustments for the three RFLPSS inputs. Simulation studies show the superior performance of the RFLPSS compared with an optimally designed conventional PSS and discrete mode FLPSS.

Keywords: Controller design, Fuzzy Logic, PID, Power SystemStabilizer, Robust control.

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409 Assessment of the Adaptive Pushover Analysis Using Displacement-based Loading in Prediction the Seismic Behaviour of the Unsymmetric-Plan Buildings

Authors: M.O. Makhmalbaf, F. Mohajeri Nav, M. Zabihi Samani

Abstract:

The recent drive for use of performance-based methodologies in design and assessment of structures in seismic areas has significantly increased the demand for the development of reliable nonlinear inelastic static pushover analysis tools. As a result, the adaptive pushover methods have been developed during the last decade, which unlike their conventional pushover counterparts, feature the ability to account for the effect that higher modes of vibration and progressive stiffness degradation might have on the distribution of seismic storey forces. Even in advanced pushover methods, little attention has been paid to the Unsymmetric structures. This study evaluates the seismic demands for three dimensional Unsymmetric-Plan buildings determined by the Displacement-based Adaptive Pushover (DAP) analysis, which has been introduced by Antoniou and Pinho [2004]. The capability of DAP procedure in capturing the torsional effects due to the irregularities of the structures, is investigated by comparing its estimates to the exact results, obtained from Incremental Dynamic Analysis (IDA). Also the capability of the procedure in prediction the seismic behaviour of the structure is discussed.

Keywords: Nonlinear static procedures, Unsymmetric-PlanBuildings, Torsional effects, IDA.

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408 Counterpropagation Neural Network for Solving Power Flow Problem

Authors: Jayendra Krishna, Laxmi Srivastava

Abstract:

Power flow (PF) study, which is performed to determine the power system static states (voltage magnitudes and voltage angles) at each bus to find the steady state operating condition of a system, is very important and is the most frequently carried out study by power utilities for power system planning, operation and control. In this paper, a counterpropagation neural network (CPNN) is proposed to solve power flow problem under different loading/contingency conditions for computing bus voltage magnitudes and angles of the power system. The counterpropagation network uses a different mapping strategy namely counterpropagation and provides a practical approach for implementing a pattern mapping task, since learning is fast in this network. The composition of the input variables for the proposed neural network has been selected to emulate the solution process of a conventional power flow program. The effectiveness of the proposed CPNN based approach for solving power flow is demonstrated by computation of bus voltage magnitudes and voltage angles for different loading conditions and single line-outage contingencies in IEEE 14-bus system.

Keywords: Admittance matrix, counterpropagation neural network, line outage contingency, power flow

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407 Plastic Waste Utilization as Asphalt Binder Modifier in Asphalt Concrete Pavement

Authors: H. Naghawi, R. Al-Ajarmeh, R. Allouzi, A. AlKlub, K. Masarwah, A. AL-Quraini, M. Abu-Sarhan

Abstract:

The main objective of this paper is to evaluate the use of plastic waste as a low cost asphalt binder modifier. For this purpose Marshall mix design procedure was used. Marshall mix design procedure seeks to select the Optimum Binder Content (OBC) to be added to a specific aggregate blend resulting in a mixture that satisfies the desired properties of strength and durability. In order to evaluate the plastic waste modified (PWM) asphalt mixtures, the OBC for the conventional asphalt mix was first identified, and then different percentages of crushed plastic waste by weight of the identified OBC were tested. Marshall test results for the modified asphalt mixtures were analyzed to find the optimum PWM content. Finally, the static indirect tensile strength (IDT) was determined for all mixtures using the splitting tensile test. It was found that PWM content of 7.43% by weight of OBC is recommended as the optimum PWM content needed for enhancing the performance of asphalt mixtures. It enhanced stability by 42.56%, flow by 89.91% and strength by 13.54%. This would lead to a more durable pavement by improving the pavement resistance to fatigue cracking and rutting.

Keywords: Binder content modifier, Marshall test, plastic waste, polyethylene terephthalate.

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406 Meta-Learning for Hierarchical Classification and Applications in Bioinformatics

Authors: Fabio Fabris, Alex A. Freitas

Abstract:

Hierarchical classification is a special type of classification task where the class labels are organised into a hierarchy, with more generic class labels being ancestors of more specific ones. Meta-learning for classification-algorithm recommendation consists of recommending to the user a classification algorithm, from a pool of candidate algorithms, for a dataset, based on the past performance of the candidate algorithms in other datasets. Meta-learning is normally used in conventional, non-hierarchical classification. By contrast, this paper proposes a meta-learning approach for more challenging task of hierarchical classification, and evaluates it in a large number of bioinformatics datasets. Hierarchical classification is especially relevant for bioinformatics problems, as protein and gene functions tend to be organised into a hierarchy of class labels. This work proposes meta-learning approach for recommending the best hierarchical classification algorithm to a hierarchical classification dataset. This work’s contributions are: 1) proposing an algorithm for splitting hierarchical datasets into new datasets to increase the number of meta-instances, 2) proposing meta-features for hierarchical classification, and 3) interpreting decision-tree meta-models for hierarchical classification algorithm recommendation.

Keywords: Algorithm recommendation, meta-learning, bioinformatics, hierarchical classification.

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405 Medical Image Fusion Based On Redundant Wavelet Transform and Morphological Processing

Authors: P. S. Gomathi, B. Kalaavathi

Abstract:

The process in which the complementary information from multiple images is integrated to provide composite image that contains more information than the original input images is called image fusion. Medical image fusion provides useful information from multimodality medical images that provides additional information to the doctor for diagnosis of diseases in a better way. This paper represents the wavelet based medical image fusion algorithm on different multimodality medical images. In order to fuse the medical images, images are decomposed using Redundant Wavelet Transform (RWT). The high frequency coefficients are convolved with morphological operator followed by the maximum-selection (MS) rule. The low frequency coefficients are processed by MS rule. The reconstructed image is obtained by inverse RWT. The quantitative measures which includes Mean, Standard Deviation, Average Gradient, Spatial frequency, Edge based Similarity Measures are considered for evaluating the fused images. The performance of this proposed method is compared with Pixel averaging, PCA, and DWT fusion methods. When compared with conventional methods, the proposed framework provides better performance for analysis of multimodality medical images.

Keywords: Discrete Wavelet Transform (DWT), Image Fusion, Morphological Processing, Redundant Wavelet Transform (RWT).

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404 The Use of Seashell by-Products in Pervious Concrete Pavers

Authors: Dang Hanh Nguyen, Nassim Sebaibi, Mohamed Boutouil, Lydia Leleyter, Fabienne Baraud

Abstract:

Pervious concrete is a green alternative to conventional pavements with minimal fine aggregate and a high void content. Pervious concrete allows water to infiltrate through the pavement, thereby reducing the runoff and the requirement for stormwater management systems.

Seashell By-Products (SBP) are produced in an important quantity in France and are considered as waste. This work investigated to use SBP in pervious concrete and produce an even more environmentally friendly product, Pervious Concrete Pavers.

The research methodology involved substituting the coarse aggregate in the previous concrete mix design with 20%, 40% and 60% SBP. The testing showed that pervious concrete containing less than 40% SBP had strengths, permeability and void content which are comparable to the pervious concrete containing with only natural aggregate. The samples that contained 40% SBP or higher had a significant loss in strength and an increase in permeability and a void content from the control mix pervious concrete. On the basis of the results in this research, it was found that the natural aggregate can be substituted by SBP without affecting the delicate balance of a pervious concrete mix. Additional, it is recommended that the optimum replacement percentage for SBP in pervious concrete is 40 % direct replacement of natural coarse aggregate while maintaining the structural performance and drainage capabilities of the pervious concrete.

Keywords: Seashell by-products, pervious concrete pavers, permeability and mechanical strength.

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403 Environmentally Adaptive Acoustic Echo Suppression for Barge-in Speech Recognition

Authors: Jong Han Joo, Jeong Hun Lee, Young Sun Kim, Jae Young Kang, Seung Ho Choi

Abstract:

In this study, we propose a novel technique for acoustic echo suppression (AES) during speech recognition under barge-in conditions. Conventional AES methods based on spectral subtraction apply fixed weights to the estimated echo path transfer function (EPTF) at the current signal segment and to the EPTF estimated until the previous time interval. However, the effects of echo path changes should be considered for eliminating the undesired echoes. We describe a new approach that adaptively updates weight parameters in response to abrupt changes in the acoustic environment due to background noises or double-talk. Furthermore, we devised a voice activity detector and an initial time-delay estimator for barge-in speech recognition in communication networks. The initial time delay is estimated using log-spectral distance measure, as well as cross-correlation coefficients. The experimental results show that the developed techniques can be successfully applied in barge-in speech recognition systems.

Keywords: Acoustic echo suppression, barge-in, speech recognition, echo path transfer function, initial delay estimator, voice activity detector.

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402 Artificial Neural Networks Modeling in Water Resources Engineering: Infrastructure and Applications

Authors: M. R. Mustafa, M. H. Isa, R. B. Rezaur

Abstract:

The use of artificial neural network (ANN) modeling for prediction and forecasting variables in water resources engineering are being increasing rapidly. Infrastructural applications of ANN in terms of selection of inputs, architecture of networks, training algorithms, and selection of training parameters in different types of neural networks used in water resources engineering have been reported. ANN modeling conducted for water resources engineering variables (river sediment and discharge) published in high impact journals since 2002 to 2011 have been examined and presented in this review. ANN is a vigorous technique to develop immense relationship between the input and output variables, and able to extract complex behavior between the water resources variables such as river sediment and discharge. It can produce robust prediction results for many of the water resources engineering problems by appropriate learning from a set of examples. It is important to have a good understanding of the input and output variables from a statistical analysis of the data before network modeling, which can facilitate to design an efficient network. An appropriate training based ANN model is able to adopt the physical understanding between the variables and may generate more effective results than conventional prediction techniques.

Keywords: ANN, discharge, modeling, prediction, sediment,

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401 Alignment of a Combined Groin for Flow through a Straight Open Channel

Authors: M. Alauddin, M. A. Ullah, M. Alom, M. N. Islam

Abstract:

The rivers in Bangladesh are highly unstable having loose boundaries, mild slope of water surface and bed, irregular siltation of huge sediment coming from upstream, among others. The groins are installed in the river bank to deflect the flowing water away from the vulnerable zones. The conventional groins are found to be unstable and ineffective. The combined groin having both impermeable and permeable components in the same structure improves the flow field to function better over others. The main goal of this study is to analyze the hydraulic characteristics induced by the combined groins of different alignments by using a 2D numerical model, iRIC Nays2DH. In this numerical simulation, the K-ε model for turbulence and Cubic Interpolation Pseudo-particle (CIP) method for advective terms are utilized. A particular flow condition is applied in the channel for all sets of groins with different alignments. The simulation results reveal that the combined groins alter the flow patterns considerably, with no significant recirculation of flow in the groin field. The effect of different alignments of groins is found somewhat different. Based on hydraulic features caused by the groins, the combined groin that aligns the permeable component towards slightly downstream performs better over others.

Keywords: Combined groin, alignment, hydraulic characteristics, numerical model.

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400 Computational Analysis of the Scaling Effects on the Performance of an Axial Compressor

Authors: Junting Xiang, Jörg Uwe Schlüter, Fei Duan

Abstract:

The miniaturization of gas turbines promises many advantages. Miniature gas turbines can be used for local power generation or the propulsion of small aircraft, such as UAV and MAV. However, experience shows that the miniaturization of conventional gas turbines, which are optimized at their current large size, leads to a substantial loss of efficiency and performance at smaller scales. This may be due to a number of factors, such as the Reynolds-number effect, the increased heat transfer, and manufacturing tolerances. In the present work, we focus on computational investigations of the Reynolds number effect and the wall heat transfer on the performance of axial compressor during its size change. The NASA stage 35 compressor is selected as the configuration in this study and computational fluid dynamics (CFD) is used to carry out the miniaturization process and simulations. We perform parameter studies on the effect of Reynolds number and wall thermal conditions. Our results indicate a decrease of efficiency, if the compressor is miniaturized based on its original geometry due to the increase of viscous effects. The increased heat transfer through wall has only a small effect and will actually benefit compressor performance based on our study.

Keywords: Axial compressor, CFD, heat transfer, miniature gas turbines, Reynolds number.

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