Search results for: experimental hysteresis loops
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 3517

Search results for: experimental hysteresis loops

937 Bearing Capacity of Sheet Hanger Connection to the Trapezoidal Metal Sheet

Authors: Kateřina Jurdová

Abstract:

Hanging to the trapezoidal sheet by decking hanger is a very widespread solution used in civil engineering to lead the distribution of energy, sanitary, air distribution system etc. under the roof or floor structure. The trapezoidal decking hanger is usually a part of the whole installation system for specific distribution medium. The leading companies offer installation systems for each specific distribution e.g. pipe rings, sprinkler systems, installation channels etc. Every specific part is connected to the base connector which is decking hanger. The own connection has three main components: decking hanger, threaded bar with nuts and web of trapezoidal sheet. The aim of this contribution is determinate the failure mechanism of each component in connection. Load bearing capacity of most components in connection could be calculated by formulas in European codes. This contribution is focused on problematic of bearing resistance of threaded bar in web of trapezoidal sheet. This issue is studied by experimental research and numerical modelling. This contribution presented the initial results of experiment which is compared with numerical model of specimen.

Keywords: Decking hanger, concentrated load, connection, load bearing capacity, trapezoidal metal sheet.

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936 Influence of the Paint Coating Thickness in Digital Image Correlation Experiments

Authors: Jesús A. Pérez, Sam Coppieters, Dimitri Debruyne

Abstract:

In the past decade, the use of digital image correlation (DIC) techniques has increased significantly in the area of experimental mechanics, especially for materials behavior characterization. This non-contact tool enables full field displacement and strain measurements over a complete region of interest. The DIC algorithm requires a random contrast pattern on the surface of the specimen in order to perform properly. To create this pattern, the specimen is usually first coated using a white matt paint. Next, a black random speckle pattern is applied using any suitable method. If the applied paint coating is too thick, its top surface may not be able to exactly follow the deformation of the specimen, and consequently, the strain measurement might be underestimated. In the present article, a study of the influence of the paint thickness on the strain underestimation is performed for different strain levels. The results are then compared to typical paint coating thicknesses applied by experienced DIC users. A slight strain underestimation was observed for paint coatings thicker than about 30μm. On the other hand, this value was found to be uncommonly high compared to coating thicknesses applied by DIC users.

Keywords: Digital Image Correlation, paint coating thickness, strain.

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935 Bioethanol: Indonesian Macro-Algae as a Renewable Feedstock for Liquid Fuel

Authors: T. Poespowati, E. Marsyahyo, R. Kartika-Dewi

Abstract:

This experimental study aims at studying the conversion of macro-algae into bioethanol under several steps of procedure: preparation, pre-treatment, fermentation, and distillation. The main objective of this work was to investigate the role of buffer’s type as a stabiliser of pH level and fermentation time on the yield of ethanol. For this purpose, experiments were carried out on biomass macro-algae to de-couple the pre-treatment and fermentation processes from those associated with distillation process. β- glucosidase was used as cellulose decomposer during hydrolysis step and yeast was used during fermentation process. The species of macro-algae utilised as energy feedstock was Ulva lactuca and it was harvested from southern coast of Central of Java Island – Indonesia. Experiments were conducted in a simple fermenter over a different buffer: citrate buffer and acetic buffer, and over a range of fermentation times between 5 to 20 days. The ethanol production was found to be significantly affected by both variables. The optimum time of fermentation was 10 days with citrate buffer; result in 0.88458% of ethanol, and the ethanol content after distillation process was shown 0.985015%.

Keywords: Fermentation, ulva-lactuca, buffer, β-glucosidase, bioethanol.

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934 Estimation of Buffer Size of Internet Gateway Server via G/M/1 Queuing Model

Authors: Dr. L.K. Singh, Dr. R. M. L, Riktesh Srivastava

Abstract:

How to efficiently assign system resource to route the Client demand by Gateway servers is a tricky predicament. In this paper, we tender an enhanced proposal for autonomous recital of Gateway servers under highly vibrant traffic loads. We devise a methodology to calculate Queue Length and Waiting Time utilizing Gateway Server information to reduce response time variance in presence of bursty traffic. The most widespread contemplation is performance, because Gateway Servers must offer cost-effective and high-availability services in the elongated period, thus they have to be scaled to meet the expected load. Performance measurements can be the base for performance modeling and prediction. With the help of performance models, the performance metrics (like buffer estimation, waiting time) can be determined at the development process. This paper describes the possible queue models those can be applied in the estimation of queue length to estimate the final value of the memory size. Both simulation and experimental studies using synthesized workloads and analysis of real-world Gateway Servers demonstrate the effectiveness of the proposed system.

Keywords: Gateway Server, G/M/1 Queuing Model.

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933 Experimental Implementation of Model Predictive Control for Permanent Magnet Synchronous Motor

Authors: Abdelsalam A. Ahmed

Abstract:

Fast speed drives for Permanent Magnet Synchronous Motor (PMSM) is a crucial performance for the electric traction systems. In this paper, PMSM is derived with a Model-based Predictive Control (MPC) technique. Fast speed tracking is achieved through optimization of the DC source utilization using MPC. The technique is based on predicting the optimum voltage vector applied to the driver. Control technique is investigated by comparing to the cascaded PI control based on Space Vector Pulse Width Modulation (SVPWM). MPC and SVPWM-based FOC are implemented with the TMS320F2812 DSP and its power driver circuits. The designed MPC for a PMSM drive is experimentally validated on a laboratory test bench. The performances are compared with those obtained by a conventional PI-based system in order to highlight the improvements, especially regarding speed tracking response.

Keywords: Permanent magnet synchronous motor, mode predictive control, optimization of DC source utilization, cascaded PI control, space vector pulse width modulation, TMS320F2812 DSP.

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932 3D Frictionless Contact Case between the Structure of E-Bike and the Ground

Authors: Lele Zhang, HuiLeng Choo, Alexander Konyukhov, Shuguang Li

Abstract:

China is currently the world's largest producer and distributor of electric bicycle (e-bike). The increasing number of e-bikes on the road is accompanied by rising injuries and even deaths of e-bike drivers. Therefore, there is a growing need to improve the safety structure of e-bikes. This 3D frictionless contact analysis is a preliminary, but necessary work for further structural design improvement of an e-bike. The contact analysis between e-bike and the ground was carried out as follows: firstly, the Penalty method was illustrated and derived from the simplest spring-mass system. This is one of the most common methods to satisfy the frictionless contact case; secondly, ANSYS static analysis was carried out to verify finite element (FE) models with contact pair (without friction) between e-bike and the ground; finally, ANSYS transient analysis was used to obtain the data of the penetration p(u) of e-bike with respect to the ground. Results obtained from the simulation are as estimated by comparing with that from theoretical method. In the future, protective shell will be designed following the stability criteria and added to the frame of e-bike. Simulation of side falling of the improvedsafety structure of e-bike will be confirmed with experimental data.

Keywords: Frictionless contact, penalty method, e-bike, finite element.

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931 Experimental Analysis on Electrical and Photometric Performances of Commercially Available Integrated Compact Fluorescent Lamp

Authors: Hu-Hsiao Hsu, Po-Ren Chung, Ming-Chin Ho, Chieh-Feng Tsai, Che-Ming Chiang, Shin-Ku Lee

Abstract:

Lighting upgrades involve relatively lower costs which allow the benefits to be spread more widely than is possible with any other energy efficiency measure. In order to popularize the adoption of CFL in Taiwan, the authority proposes to implement a new energy efficient lamp comparative label system. The current study was accordingly undertaken to investigate the factors affecting the performance and the deviation of actual and labeled performance of commercially available integrated CFLs. In this paper, standard test methods to determine the electrical and photometric performances of CFL were developed based on CIE 84-1989 and CIE 60901-1987, then 55 selected CFLs from market were tested. The results show that with higher color temperature of CFLs lower efficacy are achieved. It was noticed that the most packaging of CFL often lack the information of Color Rendering Index. Also, there was no correlation between price and performance of the CFLs was indicated in this work. The results of this paper might help consumers to make more informed CFL-purchasing decisions.

Keywords: Compact fluorescent lamp (CFL), Efficacy, Color Rendering Index (CRI), Energy saving.

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930 A Fast Replica Placement Methodology for Large-scale Distributed Computing Systems

Authors: Samee Ullah Khan, C. Ardil

Abstract:

Fine-grained data replication over the Internet allows duplication of frequently accessed data objects, as opposed to entire sites, to certain locations so as to improve the performance of largescale content distribution systems. In a distributed system, agents representing their sites try to maximize their own benefit since they are driven by different goals such as to minimize their communication costs, latency, etc. In this paper, we will use game theoretical techniques and in particular auctions to identify a bidding mechanism that encapsulates the selfishness of the agents, while having a controlling hand over them. In essence, the proposed game theory based mechanism is the study of what happens when independent agents act selfishly and how to control them to maximize the overall performance. A bidding mechanism asks how one can design systems so that agents- selfish behavior results in the desired system-wide goals. Experimental results reveal that this mechanism provides excellent solution quality, while maintaining fast execution time. The comparisons are recorded against some well known techniques such as greedy, branch and bound, game theoretical auctions and genetic algorithms.

Keywords: Data replication, auctions, static allocation, pricing.

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929 A Hybrid Classification Method using Artificial Neural Network Based Decision Tree for Automatic Sleep Scoring

Authors: Haoyu Ma, Bin Hu, Mike Jackson, Jingzhi Yan, Wen Zhao

Abstract:

In this paper we propose a new classification method for automatic sleep scoring using an artificial neural network based decision tree. It attempts to treat sleep scoring progress as a series of two-class problems and solves them with a decision tree made up of a group of neural network classifiers, each of which uses a special feature set and is aimed at only one specific sleep stage in order to maximize the classification effect. A single electroencephalogram (EEG) signal is used for our analysis rather than depending on multiple biological signals, which makes greatly simplifies the data acquisition process. Experimental results demonstrate that the average epoch by epoch agreement between the visual and the proposed method in separating 30s wakefulness+S1, REM, S2 and SWS epochs was 88.83%. This study shows that the proposed method performed well in all the four stages, and can effectively limit error propagation at the same time. It could, therefore, be an efficient method for automatic sleep scoring. Additionally, since it requires only a small volume of data it could be suited to pervasive applications.

Keywords: Sleep, Sleep stage, Automatic sleep scoring, Electroencephalography, Decision tree, Artificial neural network

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928 A Study on Manufacturing of Head-Part of Pipes Using a Rotating Manufacturing Process

Authors: J. H. Park, S. K. Lee, Y. W. Kim, D. C. Ko

Abstract:

A large variety of pipe flange is required in marine and construction industry. Pipe flanges are usually welded or screwed to the pipe end and are connected with bolts. This approach is very simple and widely used for a long time; however, it results in high development cost and low productivity, and the productions made by this approach usually have safety problem at the welding area. In this research, a new approach of forming pipe flange based on cold forging and floating die concept is presented. This innovative approach increases the effectiveness of the material usage and save the time cost compared with conventional welding method. To ensure the dimensional accuracy of the final product, the finite element analysis (FEA) was carried out to simulate the process of cold forging, and the orthogonal experiment methods were used to investigate the influence of four manufacturing factors (pin die angle, pipe flange angle, rpm, pin die distance from clamp jig) and predicted the best combination of them. The manufacturing factors were obtained by numerical and experimental studies and it shows that the approach is very useful and effective for the forming of pipe flange, and can be widely used later.

Keywords: Cold forging, FEA, finite element analysis, Forge- 3D, rotating forming, tubes.

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927 A Learning-Community Recommendation Approach for Web-Based Cooperative Learning

Authors: Jian-Wei Li, Yao-Tien Wang, Yi-Chun Chang

Abstract:

Cooperative learning has been defined as learners working together as a team to solve a problem to complete a task or to accomplish a common goal, which emphasizes the importance of interactions among members to promote the whole learning performance. With the popularity of society networks, cooperative learning is no longer limited to traditional classroom teaching activities. Since society networks facilitate to organize online learners, to establish common shared visions, and to advance learning interaction, the online community and online learning community have triggered the establishment of web-based societies. Numerous research literatures have indicated that the collaborative learning community is a critical issue to enhance learning performance. Hence, this paper proposes a learning community recommendation approach to facilitate that a learner joins the appropriate learning communities, which is based on k-nearest neighbor (kNN) classification. To demonstrate the viability of the proposed approach, the proposed approach is implemented for 117 students to recommend learning communities. The experimental results indicate that the proposed approach can effectively recommend appropriate learning communities for learners.

Keywords: k-nearest neighbor classification, learning community, Cooperative/Collaborative Learning and Environments.

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926 Visual Thing Recognition with Binary Scale-Invariant Feature Transform and Support Vector Machine Classifiers Using Color Information

Authors: Wei-Jong Yang, Wei-Hau Du, Pau-Choo Chang, Jar-Ferr Yang, Pi-Hsia Hung

Abstract:

The demands of smart visual thing recognition in various devices have been increased rapidly for daily smart production, living and learning systems in recent years. This paper proposed a visual thing recognition system, which combines binary scale-invariant feature transform (SIFT), bag of words model (BoW), and support vector machine (SVM) by using color information. Since the traditional SIFT features and SVM classifiers only use the gray information, color information is still an important feature for visual thing recognition. With color-based SIFT features and SVM, we can discard unreliable matching pairs and increase the robustness of matching tasks. The experimental results show that the proposed object recognition system with color-assistant SIFT SVM classifier achieves higher recognition rate than that with the traditional gray SIFT and SVM classification in various situations.

Keywords: Color moments, visual thing recognition system, SIFT, color SIFT.

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925 Modeling, Analysis and Control of a Smart Composite Structure

Authors: Nader H. Ghareeb, Mohamed S. Gaith, Sayed M. Soleimani

Abstract:

In modern engineering, weight optimization has a priority during the design of structures. However, optimizing the weight can result in lower stiffness and less internal damping, causing the structure to become excessively prone to vibration. To overcome this problem, active or smart materials are implemented. The coupled electromechanical properties of smart materials, used in the form of piezoelectric ceramics in this work, make these materials well-suited for being implemented as distributed sensors and actuators to control the structural response. The smart structure proposed in this paper is composed of a cantilevered steel beam, an adhesive or bonding layer, and a piezoelectric actuator. The static deflection of the structure is derived as function of the piezoelectric voltage, and the outcome is compared to theoretical and experimental results from literature. The relation between the voltage and the piezoelectric moment at both ends of the actuator is also investigated and a reduced finite element model of the smart structure is created and verified. Finally, a linear controller is implemented and its ability to attenuate the vibration due to the first natural frequency is demonstrated.

Keywords: Active linear control, Lyapunov stability theorem, piezoelectricity, smart structure, static deflection.

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924 Optimum Design of Alkali Activated Slag Concretes for Low Chloride Ion Permeability and Water Absorption Capacity

Authors: Müzeyyen Balçikanli, Erdoğan Özbay, Hakan Tacettin Türker, Okan Karahan, Cengiz Duran Atiş

Abstract:

In this research, effect of curing time (TC), curing temperature (CT), sodium concentration (SC) and silicate modules (SM) on the compressive strength, chloride ion permeability, and water absorption capacity of alkali activated slag (AAS) concretes were investigated. For maximization of compressive strength while for minimization of chloride ion permeability and water absorption capacity of AAS concretes, best possible combination of CT, CTime, SC and SM were determined. An experimental program was conducted by using the central composite design method. Alkali solution-slag ratio was kept constant at 0.53 in all mixture. The effects of the independent parameters were characterized and analyzed by using statistically significant quadratic regression models on the measured properties (dependent parameters). The proposed regression models are valid for AAS concretes with the SC from 0.1% to 7.5%, SM from 0.4 to 3.2, CT from 20 °C to 94 °C and TC from 1.2 hours to 25 hours. The results of test and analysis indicate that the most effective parameter for the compressive strength, chloride ion permeability and water absorption capacity is the sodium concentration.

Keywords: Alkali activation, slag, rapid chloride permeability, water absorption capacity.

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923 Advanced Neural Network Learning Applied to Pulping Modeling

Authors: Z. Zainuddin, W. D. Wan Rosli, R. Lanouette, S. Sathasivam

Abstract:

This paper reports work done to improve the modeling of complex processes when only small experimental data sets are available. Neural networks are used to capture the nonlinear underlying phenomena contained in the data set and to partly eliminate the burden of having to specify completely the structure of the model. Two different types of neural networks were used for the application of pulping problem. A three layer feed forward neural networks, using the Preconditioned Conjugate Gradient (PCG) methods were used in this investigation. Preconditioning is a method to improve convergence by lowering the condition number and increasing the eigenvalues clustering. The idea is to solve the modified odified problem M-1 Ax= M-1b where M is a positive-definite preconditioner that is closely related to A. We mainly focused on Preconditioned Conjugate Gradient- based training methods which originated from optimization theory, namely Preconditioned Conjugate Gradient with Fletcher-Reeves Update (PCGF), Preconditioned Conjugate Gradient with Polak-Ribiere Update (PCGP) and Preconditioned Conjugate Gradient with Powell-Beale Restarts (PCGB). The behavior of the PCG methods in the simulations proved to be robust against phenomenon such as oscillations due to large step size.

Keywords: Convergence, pulping modeling, neural networks, preconditioned conjugate gradient.

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922 Geometric and Material Nonlinear Analysis of Reinforced Concrete Structure Considering Soil-Structure Interaction

Authors: Mohamed M. El-Gendy, Ibrahim A. El-Arabi, Rafik W. Abdel-Missih, Omar A. Kandil

Abstract:

In the present research, a finite element model is presented to study the geometrical and material nonlinear behavior of reinforced concrete plane frames considering soil-structure interaction. The nonlinear behaviors of concrete and reinforcing steel are considered both in compression and tension up to failure. The model takes account also for the number, diameter, and distribution of rebar along every cross section. Soil behavior is taken into consideration using four different models; namely: linear-, nonlinear Winkler's model, and linear-, nonlinear continuum model. A computer program (NARC) is specially developed in order to perform the analysis. The results achieved by the present model show good agreement with both theoretical and experimental published literature. The nonlinear behavior of a rectangular frame resting on soft soil up to failure using the proposed model is introduced for demonstration.

Keywords: Nonlinear analysis, Geometric nonlinearity, Material nonlinearity, Reinforced concrete, Finite element method, Soilstructure interaction, Winkler's soil model, Continuum soil model

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921 Quick Sequential Search Algorithm Used to Decode High-Frequency Matrices

Authors: Mohammed M. Siddeq, Mohammed H. Rasheed, Omar M. Salih, Marcos A. Rodrigues

Abstract:

This research proposes a data encoding and decoding method based on the Matrix Minimization algorithm. This algorithm is applied to high-frequency coefficients for compression/encoding. The algorithm starts by converting every three coefficients to a single value; this is accomplished based on three different keys. The decoding/decompression uses a search method called QSS (Quick Sequential Search) Decoding Algorithm presented in this research based on the sequential search to recover the exact coefficients. In the next step, the decoded data are saved in an auxiliary array. The basic idea behind the auxiliary array is to save all possible decoded coefficients; this is because another algorithm, such as conventional sequential search, could retrieve encoded/compressed data independently from the proposed algorithm. The experimental results showed that our proposed decoding algorithm retrieves original data faster than conventional sequential search algorithms.

Keywords: Matrix Minimization Algorithm, Decoding Sequential Search Algorithm, image compression, Discrete Cosine Transform, Discrete Wavelet Transform.

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920 Hydrogen from Waste Tyres

Authors: Ibrahim F. Elbaba, Paul T. Williams

Abstract:

Hydrogen is regarded to play an important role in future energy systems because it can be produced from abundant resources and its combustion only generates water. The disposal of waste tyres is a major problem in environmental management throughout the world. The use of waste materials as a source of hydrogen is particularly of interest in that it would also solve a waste treatment problem. There is much interest in the use of alternative feedstocks for the production of hydrogen since more than 95% of current production is from fossil fuels. The pyrolysis of waste tyres for the production of liquid fuels, activated carbons and gases has been extensively researched. However, combining pyrolysis with gasification is a novel process that can gasify the gaseous products from pyrolysis. In this paper, an experimental investigation into the production of hydrogen and other gases from the bench scale pyrolysis-gasification of tyres has been investigated. Experiments were carried using a two stage system consisting of pyrolysis of the waste tyres followed by catalytic steam gasification of the evolved gases and vapours in a second reactor. Experiments were conducted at a pyrolysis temperature of 500 °C using Ni/Al2O3 as a catalyst. The results showed that there was a dramatic increase in gas yield and the potential H2 production when the gasification temperature was increased from 600 to 900 oC. Overall, the process showed that high yields of hydrogen can be produced from waste tyres.

Keywords: Catalyst, Hydrogen, Pyrolysis, Gasification, Tyre, Waste

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919 A Hidden Markov Model-Based Isolated and Meaningful Hand Gesture Recognition

Authors: Mahmoud Elmezain, Ayoub Al-Hamadi, Jörg Appenrodt, Bernd Michaelis

Abstract:

Gesture recognition is a challenging task for extracting meaningful gesture from continuous hand motion. In this paper, we propose an automatic system that recognizes isolated gesture, in addition meaningful gesture from continuous hand motion for Arabic numbers from 0 to 9 in real-time based on Hidden Markov Models (HMM). In order to handle isolated gesture, HMM using Ergodic, Left-Right (LR) and Left-Right Banded (LRB) topologies is applied over the discrete vector feature that is extracted from stereo color image sequences. These topologies are considered to different number of states ranging from 3 to 10. A new system is developed to recognize the meaningful gesture based on zero-codeword detection with static velocity motion for continuous gesture. Therefore, the LRB topology in conjunction with Baum-Welch (BW) algorithm for training and forward algorithm with Viterbi path for testing presents the best performance. Experimental results show that the proposed system can successfully recognize isolated and meaningful gesture and achieve average rate recognition 98.6% and 94.29% respectively.

Keywords: Computer Vision & Image Processing, Gesture Recognition, Pattern Recognition, Application

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918 Fracture Toughness Properties and FTIR Analysis of Corn Fiber Green Composites

Authors: Ahmed Mudhafar Hashim, Aseel Mahmood Abdullah

Abstract:

The present work introduced a green composite consisting of corn natural fiber of constant concentration of 10% by weight incorporation with poly methyl methacrylate matrix biomaterial prepared by hand lay-up technique. Corn natural fibers were treated with two concentrations of sodium hydroxide solution (3% and 5%) with different immersed time (1.5 and 3 hours) at room temperature. The fracture toughness test of untreated and alkali treated corn fiber composites were performed. The effect of chemically treated on fracture properties of composites has been analyzed using Fourier transform infrared (FTIR) spectroscopy. The experimental results showed that the alkali treatment improved the fracture properties in terms of plane strain fracture toughness KIC. It was found that the plane strain fracture toughness KIC increased by up to 62% compared to untreated fiber composites. On the other hand, increases in both concentrations of alkali solution and time of soaking to 5% NaOH and 3 hours, respectively reduced the values of KIC lower than the value of the unfilled material.

Keywords: green composites, fracture toughness, corn natural fiber, Bio-PMMA

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917 Physiological and Biochemical Responses to Drought Stress of Chickpea Genotypes

Authors: E. Ceyhan, A. Kahraman, M. Önder, M.K. Ateş, S. Karadaş, R. Topak, M.A. Avcı

Abstract:

The experimental design was 4 x 5 factorial with three replications in fully controlled research greenhouse in Department of Soil Sciences and Plant Nutrition, Faculty of Agriculture, University of Selcuk in the year of 2009. Determination of tolerant chickpea genotypes to drought was made in the research. Additionally, sophisticated effects of drought on plant growth and development, biochemical and physical properties or physical defense mechanisms were presented. According to the results, the primary genotypes were Ilgın YP (0.0063 g/gh) for leaf water capacity, 22235 70.44(%) for relative water content, 22159 (82.47%) for real water content, 22159 (5.03 mg/l) for chlorophyll a+b, Ilgın YP (125.89 nmol H2O2.dak-1/ mg protein-1) for peroxidase, Yunak YP (769.67 unit/ mg protein-1) for superoxide dismutase, Seydişehir YP (16.74 μg.TA-1) for proline, Gökçe (80.01 nmol H2O2.dak-1/ mg protein-1) for catalase. Consequently, all the genotypes increased their enzyme activity depending on the increasing of drought stress consider with the effects of drought stress on leaf enzyme activity. Chickpea genotypes are increasing enzyme activity against to drought stress.

Keywords: Chickpea, drought, enzyme, tolerance to drought

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916 A Procedure for Post-Earthquake Damage Estimation Based on Detection of High-Frequency Transients

Authors: Aleksandar Zhelyazkov, Daniele Zonta, Helmut Wenzel, Peter Furtner

Abstract:

In the current research structural health monitoring is considered for addressing the critical issue of post-earthquake damage detection. A non-standard approach for damage detection via acoustic emission is presented - acoustic emissions are monitored in the low frequency range (up to 120 Hz). Such emissions are termed high-frequency transients. Further a damage indicator defined as the Time-Ratio Damage Indicator is introduced. The indicator relies on time-instance measurements of damage initiation and deformation peaks. Based on the time-instance measurements a procedure for estimation of the maximum drift ratio is proposed. Monitoring data is used from a shaking-table test of a full-scale reinforced concrete bridge pier. Damage of the experimental column is successfully detected and the proposed damage indicator is calculated.

Keywords: Acoustic emission, Damage detection, Shaking table test, Structural health monitoring, High-frequency transients.

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915 Effect of Cooling Coherent Nozzle Orientation on the Machinability of Ti-6Al-4V in Step Shoulder Milling

Authors: Salah Gariani, Islam Shyha, Osama Elgadi, Khaled Jegandi

Abstract:

In this work, a cooling coherent round nozzle was developed and the impact of nozzle placement (i.e. nozzle angle and stand-off/impinging distance) on the machinability of Ti-6Al-4V was evaluated. Key process measures were cutting force, workpiece temperature, tool wear, burr formation and average surface roughness (Ra). Experimental results showed that nozzle position at a 15° angle in the feed direction and 45°/60° against feed direction assisted in minimising workpiece temperature. A stand-off distance of 55 and 75 mm is also necessary to control burr formation, workpiece temperature and Ra, but coherent nozzle orientation has no statistically significant impact on the mean values of cutting force and tool wear. It can be concluded that stand-off distance is more substantially significant than nozzle angles when step shoulder milling Ti-6Al- 4V using vegetable oil-based cutting fluid.

Keywords: Coherent round nozzle, step shoulder milling, Ti-6Al-4V, vegetable oil-based cutting fluid.

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914 Bidirectional Discriminant Supervised Locality Preserving Projection for Face Recognition

Authors: Yiqin Lin, Wenbo Li

Abstract:

Dimensionality reduction and feature extraction are of crucial importance for achieving high efficiency in manipulating the high dimensional data. Two-dimensional discriminant locality preserving projection (2D-DLPP) and two-dimensional discriminant supervised LPP (2D-DSLPP) are two effective two-dimensional projection methods for dimensionality reduction and feature extraction of face image matrices. Since 2D-DLPP and 2D-DSLPP preserve the local structure information of the original data and exploit the discriminant information, they usually have good recognition performance. However, 2D-DLPP and 2D-DSLPP only employ single-sided projection, and thus the generated low dimensional data matrices have still many features. In this paper, by combining the discriminant supervised LPP with the bidirectional projection, we propose the bidirectional discriminant supervised LPP (BDSLPP). The left and right projection matrices for BDSLPP can be computed iteratively. Experimental results show that the proposed BDSLPP achieves higher recognition accuracy than 2D-DLPP, 2D-DSLPP, and bidirectional discriminant LPP (BDLPP).

Keywords: Face recognition, dimension reduction, locality preserving projection, discriminant information, bidirectional projection.

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913 A Spatial Point Pattern Analysis to Recognize Fail Bit Patterns in Semiconductor Manufacturing

Authors: Youngji Yoo, Seung Hwan Park, Daewoong An, Sung-Shick Kim, Jun-Geol Baek

Abstract:

The yield management system is very important to produce high-quality semiconductor chips in the semiconductor manufacturing process. In order to improve quality of semiconductors, various tests are conducted in the post fabrication (FAB) process. During the test process, large amount of data are collected and the data includes a lot of information about defect. In general, the defect on the wafer is the main causes of yield loss. Therefore, analyzing the defect data is necessary to improve performance of yield prediction. The wafer bin map (WBM) is one of the data collected in the test process and includes defect information such as the fail bit patterns. The fail bit has characteristics of spatial point patterns. Therefore, this paper proposes the feature extraction method using the spatial point pattern analysis. Actual data obtained from the semiconductor process is used for experiments and the experimental result shows that the proposed method is more accurately recognize the fail bit patterns.

Keywords: Semiconductor, wafer bin map (WBM), feature extraction, spatial point patterns, contour map.

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912 Adaptive Motion Estimator Based on Variable Block Size Scheme

Authors: S. Dhahri, A. Zitouni, H. Chaouch, R. Tourki

Abstract:

This paper presents an adaptive motion estimator that can be dynamically reconfigured by the best algorithm depending on the variation of the video nature during the lifetime of an application under running. The 4 Step Search (4SS) and the Gradient Search (GS) algorithms are integrated in the estimator in order to be used in the case of rapid and slow video sequences respectively. The Full Search Block Matching (FSBM) algorithm has been also integrated in order to be used in the case of the video sequences which are not real time oriented. In order to efficiently reduce the computational cost while achieving better visual quality with low cost power, the proposed motion estimator is based on a Variable Block Size (VBS) scheme that uses only the 16x16, 16x8, 8x16 and 8x8 modes. Experimental results show that the adaptive motion estimator allows better results in term of Peak Signal to Noise Ratio (PSNR), computational cost, FPGA occupied area, and dissipated power relatively to the most popular variable block size schemes presented in the literature.

Keywords: H264, Configurable Motion Estimator, VariableBlock Size, PSNR, Dissipated power.

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911 Assessment of Time-Lapse in Visible and Thermal Face Recognition

Authors: Sajad Farokhi, Siti Mariyam Shamsuddin, Jan Flusser, Usman Ullah Sheikh

Abstract:

Although face recognition seems as an easy task for human, automatic face recognition is a much more challenging task due to variations in time, illumination and pose. In this paper, the influence of time-lapse on visible and thermal images is examined. Orthogonal moment invariants are used as a feature extractor to analyze the effect of time-lapse on thermal and visible images and the results are compared with conventional Principal Component Analysis (PCA). A new triangle square ratio criterion is employed instead of Euclidean distance to enhance the performance of nearest neighbor classifier. The results of this study indicate that the ideal feature vectors can be represented with high discrimination power due to the global characteristic of orthogonal moment invariants. Moreover, the effect of time-lapse has been decreasing and enhancing the accuracy of face recognition considerably in comparison with PCA. Furthermore, our experimental results based on moment invariant and triangle square ratio criterion show that the proposed approach achieves on average 13.6% higher in recognition rate than PCA.

Keywords: Infrared Face recognition, Time-lapse, Zernike moment invariants

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910 A Study on Remote On-Line Diagnostic System for Vehicles by Integrating the Technology of OBD, GPS, and 3G

Authors: Jyong Lin, Shih-Chang Chen, Yu-Tsen Shih, Shi-Huang Chen

Abstract:

This paper presents a remote on-line diagnostic system for vehicles via the use of On-Board Diagnostic (OBD), GPS, and 3G techniques. The main parts of the proposed system are on-board computer, vehicle monitor server, and vehicle status browser. First, the on-board computer can obtain the location of deriver and vehicle status from GPS receiver and OBD interface, respectively. Then on-board computer will connect with the vehicle monitor server through 3G network to transmit the real time vehicle system status. Finally, vehicle status browser could show the remote vehicle status including vehicle speed, engine rpm, battery voltage, engine coolant temperature, and diagnostic trouble codes. According to the experimental results, the proposed system can help fleet managers and car knockers to understand the remote vehicle status. Therefore this system can decrease the time of fleet management and vehicle repair due to the fleet managers and car knockers who find the diagnostic trouble messages in time.

Keywords: Diagnostic Trouble Code (DTC), Electronic Control Unit (ECU), Global Position System (GPS), On-Board Diagnostic (OBD).

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909 Binary Decision Diagrams: An Improved Variable Ordering using Graph Representation of Boolean Functions

Authors: P.W. C. Prasad, A. Assi, A. Harb, V.C. Prasad

Abstract:

This paper presents an improved variable ordering method to obtain the minimum number of nodes in Reduced Ordered Binary Decision Diagrams (ROBDD). The proposed method uses the graph topology to find the best variable ordering. Therefore the input Boolean function is converted to a unidirectional graph. Three levels of graph parameters are used to increase the probability of having a good variable ordering. The initial level uses the total number of nodes (NN) in all the paths, the total number of paths (NP) and the maximum number of nodes among all paths (MNNAP). The second and third levels use two extra parameters: The shortest path among two variables (SP) and the sum of shortest path from one variable to all the other variables (SSP). A permutation of the graph parameters is performed at each level for each variable order and the number of nodes is recorded. Experimental results are promising; the proposed method is found to be more effective in finding the variable ordering for the majority of benchmark circuits.

Keywords: Binary decision diagrams, graph representation, Boolean functions representation, variable ordering.

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908 Investigation of Anti-Inflammatory, Antipyretic and Analgesic Effect of Yemeni Sidr Honey

Authors: Aman Ahmed Alzubier, Patrick Nwabueze Okechukwu

Abstract:

Traditionally, Yemini Sidr honey has been reported to cure liver problems, stomach ulcers, and respiratory disorders. In this experiment, we evaluated Yemeni Sidr honey for its ability to protect inflammations caused by acetic acid and formalin -induced writhing, carrageenan and histamine-induced paw oedema in experimental rat model. Hyperpyrexia, membrane stabilizing activity, and phytochemical screening of the honey was also examined. Yemini Sidr Honey at (100, 200 and 500 mg/kg) exhibited a concentration dependant inhibition of acetic acid induced and formalin induced writhing, paw oedema induced by carrageenan & histamine, and hyperpyrexia induced by brewer's yeast, it also inhibited membrane stabilizing activity. Phytochemical screenings of the honey reveal the presence of flavonoids, steroid, alkaloids, saponins and tannins. This study suggested that Yemeni Sidr honey possess very strong antiinflammatory, analgesic and antipyretic effects and these effects would be a result of the phytochemicals present.

Keywords: Anti-inflammatory, Analgesic, Carrageenan, Aceticacid, Histamine, Yemini Sidr Honey

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