Search results for: stiffness estimation.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1364

Search results for: stiffness estimation.

584 An Expectation of the Rate of Inflation According to Inflation-Unemployment Interaction in Croatia

Authors: Zdravka Aljinović, Snježana Pivac, Boško Šego

Abstract:

According to the interaction of inflation and unemployment, expectation of the rate of inflation in Croatia is estimated. The interaction between inflation and unemployment is shown by model based on three first-order differential i.e. difference equations: Phillips relation, adaptive expectations equation and monetary-policy equation. The resulting equation is second order differential i.e. difference equation which describes the time path of inflation. The data of the rate of inflation and the rate of unemployment are used for parameters estimation. On the basis of the estimated time paths, the stability and convergence analysis is done for the rate of inflation.

Keywords: Differencing, inflation, time path, unemployment.

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583 Predicting Residence Time of Pollutants in Transient Storage Zones of Rivers by Genetic Programming

Authors: Rajeev R. Sahay

Abstract:

Rivers have transient storage or dead zones where injected pollutants or solutes are entrapped for considerable period of time, known as residence time, before being released into the main flowing zones of rivers. In this study, a new empirical expression for residence time, implementing genetic programming on published dispersion data, has been derived. The proposed expression uses few hydraulic and geometric characteristics of rivers which are normally known to the authorities. When compared with some reported expressions, based on various statistical indices, it can be concluded that the proposed expression predicts the residence time of pollutants in natural rivers more accurately.

Keywords: Parameter estimation, pollutant transport, residence time, rivers, transient storage.

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582 Failure Modes and Bearing Capacity Estimation for Strip Foundations in C-ɸ Soils: A Numerical Study

Authors: Paul Akagwu, Aaron Aboshio

Abstract:

In this study, typical c-ɸ soils subjected to loadings were assessed with a view to understand the general stress distribution and settlement behaviour of the soils under drained conditions. Numerical estimations of the non-dimensional bearing capacity factors, Nq and Nγ for varied angles of friction in the soil mass were obtained using PLAXIS. Ultimate bearing capacity values over a Ф range of 0-30 degrees were also computed and compared with analytical results obtained from the traditional simplified uncoupled approach of Terzaghi and Meyerhof. Results from the numerical study agree well with theoretical findings.

Keywords: Bearing capacity factors, finite element method, safe bearing pressure, structure-soil interaction.

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581 Voltage Stability Proximity Index Determined by LES Algorithm

Authors: Benalia Nadia, Bensiali Nadia, Mekki Mounira

Abstract:

In this paper, we propose an easily computable proximity index for predicting voltage collapse of a load bus using only measured values of the bus voltage and power; Using these measurements a polynomial of fourth order is obtained by using LES estimation algorithms. The sum of the absolute values of the polynomial coefficient gives an idea of the critical bus. We demonstrate the applicability of our proposed method on 6 bus test system. The results obtained verify its applicability, as well as its accuracy and the simplicity. From this indicator, it is allowed to predict the voltage instability or the proximity of a collapse. Results obtained by the PV curve are compared with corresponding values by QV curves and are observed to be in close agreement.

Keywords: least square method, Voltage Collapse, Voltage Stability, PV curve

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580 Fuzzy Based Visual Texture Feature for Psoriasis Image Analysis

Authors: G. Murugeswari, A. Suruliandi

Abstract:

This paper proposes a rotational invariant texture feature based on the roughness property of the image for psoriasis image analysis. In this work, we have applied this feature for image classification and segmentation. The fuzzy concept is employed to overcome the imprecision of roughness. Since the psoriasis lesion is modeled by a rough surface, the feature is extended for calculating the Psoriasis Area Severity Index value. For classification and segmentation, the Nearest Neighbor algorithm is applied. We have obtained promising results for identifying affected lesions by using the roughness index and severity level estimation.

Keywords: Fuzzy texture feature, psoriasis, roughness feature, skin disease.

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579 Physical Parameter Based Compact Expression for Propagation Constant of SWCNT Interconnects

Authors: Kollarama Subramanyam, Nisha Kuruvilla, J. P. Raina

Abstract:

Novel compact expressions for propagation constant (γ) of SWCNT and bundled SWCNTs interconnect, in terms of physical parameters such as length, operating frequency and diameter of CNTs is proposed in this work. These simplified expressions enable physical insight and accurate estimation of signal attenuation level and its phase change at any length for a particular frequency. The proposed expressions are validated against SPICE simulated results of lumped as well as distributed equivalent electrical RLC nets of CNT interconnect. These expressions also help us to evaluate the cut off frequencies of SWCNTs for different interconnect lengths.

Keywords: Attenuation constant, Bundled SWCNT, CNT interconnects, Propagation Constant.

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578 Monitoring Blood Pressure Using Regression Techniques

Authors: Qasem Qananwah, Ahmad Dagamseh, Hiam AlQuran, Khalid Shaker Ibrahim

Abstract:

Blood pressure helps the physicians greatly to have a deep insight into the cardiovascular system. The determination of individual blood pressure is a standard clinical procedure considered for cardiovascular system problems. The conventional techniques to measure blood pressure (e.g. cuff method) allows a limited number of readings for a certain period (e.g. every 5-10 minutes). Additionally, these systems cause turbulence to blood flow; impeding continuous blood pressure monitoring, especially in emergency cases or critically ill persons. In this paper, the most important statistical features in the photoplethysmogram (PPG) signals were extracted to estimate the blood pressure noninvasively. PPG signals from more than 40 subjects were measured and analyzed and 12 features were extracted. The features were fed to principal component analysis (PCA) to find the most important independent features that have the highest correlation with blood pressure. The results show that the stiffness index means and standard deviation for the beat-to-beat heart rate were the most important features. A model representing both features for Systolic Blood Pressure (SBP) and Diastolic Blood Pressure (DBP) was obtained using a statistical regression technique. Surface fitting is used to best fit the series of data and the results show that the error value in estimating the SBP is 4.95% and in estimating the DBP is 3.99%.

Keywords: Blood pressure, noninvasive optical system, PCA, continuous monitoring.

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577 On Fault Diagnosis of Asynchronous Sequential Machines with Parallel Composition

Authors: Jung-Min Yang

Abstract:

Fault diagnosis of composite asynchronous sequential machines with parallel composition is addressed in this paper. An adversarial input can infiltrate one of two submachines comprising the composite asynchronous machine, causing an unauthorized state transition. The objective is to characterize the condition under which the controller can diagnose any fault occurrence. Two control configurations, state feedback and output feedback, are considered in this paper. In the case of output feedback, the exact estimation of the state is impossible since the current state is inaccessible and the output feedback is given as the form of burst. A simple example is provided to demonstrate the proposed methodology.

Keywords: Asynchronous sequential machines, parallel composition, fault diagnosis.

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576 Estimation of Broadcast Probability in Wireless Adhoc Networks

Authors: Bharadwaj Kadiyala, Sunitha V

Abstract:

Most routing protocols (DSR, AODV etc.) that have been designed for wireless adhoc networks incorporate the broadcasting operation in their route discovery scheme. Probabilistic broadcasting techniques have been developed to optimize the broadcast operation which is otherwise very expensive in terms of the redundancy and the traffic it generates. In this paper we have explored percolation theory to gain a different perspective on probabilistic broadcasting schemes which have been actively researched in the recent years. This theory has helped us estimate the value of broadcast probability in a wireless adhoc network as a function of the size of the network. We also show that, operating at those optimal values of broadcast probability there is at least 25-30% reduction in packet regeneration during successful broadcasting.

Keywords: Crossover length, Percolation, Probabilistic broadcast, Wireless adhoc networks

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575 Self-tuned LMS Algorithm for Sinusoidal Time Delay Tracking

Authors: Jonah Gamba

Abstract:

In this paper the problem of estimating the time delay between two spatially separated noisy sinusoidal signals by system identification modeling is addressed. The system is assumed to be perturbed by both input and output additive white Gaussian noise. The presence of input noise introduces bias in the time delay estimates. Normally the solution requires a priori knowledge of the input-output noise variance ratio. We utilize the cascade of a self-tuned filter with the time delay estimator, thus making the delay estimates robust to input noise. Simulation results are presented to confirm the superiority of the proposed approach at low input signal-to-noise ratios.

Keywords: LMS algorithm, Self-tuned filter, Systemidentification, Time delay estimation, .

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574 Categorization and Estimation of Relative Connectivity of Genes from Meta-OFTEN Network

Authors: U. Kairov, T. Karpenyuk, E. Ramanculov, A. Zinovyev

Abstract:

The most common result of analysis of highthroughput data in molecular biology represents a global list of genes, ranked accordingly to a certain score. The score can be a measure of differential expression. Recent work proposed a new method for selecting a number of genes in a ranked gene list from microarray gene expression data such that this set forms the Optimally Functionally Enriched Network (OFTEN), formed by known physical interactions between genes or their products. Here we present calculation results of relative connectivity of genes from META-OFTEN network and tentative biological interpretation of the most reproducible signal. The relative connectivity and inbetweenness values of genes from META-OFTEN network were estimated.

Keywords: Microarray, META-OFTEN, gene network.

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573 Comparison of MODIS-Based Rice Extent Map and Landsat-Based Rice Classification Map in Determining Biomass Energy Potential of Rice Hull in Nueva Ecija, Philippines

Authors: Klathea Sevilla, Marjorie Remolador, Bryan Baltazar, Imee Saladaga, Loureal Camille Inocencio, Ma. Rosario Concepcion Ang

Abstract:

The underutilization of biomass resources in the Philippines, combined with its growing population and the rise in fossil fuel prices confirms demand for alternative energy sources. The goal of this paper is to provide a comparison of MODIS-based and Landsat-based agricultural land cover maps when used in the estimation of rice hull’s available energy potential. Biomass resource assessment was done using mathematical models and remote sensing techniques employed in a GIS platform.

Keywords: Biomass, geographic information system, GIS, renewable energy.

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572 Trial Development the Evaluation Method of Quantification the Feeling of Preventing Visibility by Front A Pillar

Authors: T. Arakawa, H. Sato

Abstract:

There are many drivers who feel right A pillar of Japanese right-hand-drive car preventing visibility on turning right or left at intersection. On the other hand, there is a report that almost pedestrian accident is caused by the delay of finding pedestrian by drivers and this is found by drivers’ eye movement. Thus, we developed the evaluation method of quantification using drivers’ eye movement data by least squares estimation and we applied this method to commercial vehicle and evaluation the visibility. It is suggested that visibility of vehicle can be quantified and estimated by linear model obtained from experimental eye fixation data and information of vehicle dimensions.

Keywords: Eye fixation, modeling, obstacle feeling, right A pillar.

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571 Residual Life Prediction for a System Subject to Condition Monitoring and Two Failure Modes

Authors: Akram Khaleghei Ghosheh Balagh, Viliam Makis

Abstract:

In this paper, we investigate the residual life prediction problem for a partially observable system subject to two failure modes, namely a catastrophic failure and a failure due to the system degradation. The system is subject to condition monitoring and the degradation process is described by a hidden Markov model with unknown parameters. The parameter estimation procedure based on an EM algorithm is developed and the formulas for the conditional reliability function and the mean residual life are derived, illustrated by a numerical example.

Keywords: Partially observable system, hidden Markov model, competing risks, residual life prediction.

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570 Blind Non-Minimum Phase Channel Identification Using 3rd and 4th Order Cumulants

Authors: S. Safi, A. Zeroual

Abstract:

In this paper we propose a family of algorithms based on 3rd and 4th order cumulants for blind single-input single-output (SISO) Non-Minimum Phase (NMP) Finite Impulse Response (FIR) channel estimation driven by non-Gaussian signal. The input signal represents the signal used in 10GBASE-T (or IEEE 802.3an-2006) as a Tomlinson-Harashima Precoded (THP) version of random Pulse-Amplitude Modulation with 16 discrete levels (PAM-16). The proposed algorithms are tested using three non-minimum phase channel for different Signal-to-Noise Ratios (SNR) and for different data input length. Numerical simulation results are presented to illustrate the performance of the proposed algorithms.

Keywords: Higher Order Cumulants, Channel identification, Ethernet communication.

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569 Assessment of Multiscale Information for Short Physiological Time Series

Authors: Young-Seok Choi

Abstract:

This paper presents a multiscale information measure of Electroencephalogram (EEG) for analysis with a short data length. A multiscale extension of permutation entropy (MPE) is capable of fully reflecting the dynamical characteristics of EEG across different temporal scales. However, MPE yields an imprecise estimation due to coarse-grained procedure at large scales. We present an improved MPE measure to estimate entropy more accurately with a short time series. By computing entropies of all coarse-grained time series and averaging those at each scale, it leads to the modified MPE (MMPE) which provides an enhanced accuracy as compared to MPE. Simulation and experimental studies confirmed that MMPE has proved its capability over MPE in terms of accuracy.

Keywords: Multiscale entropy, permutation entropy, EEG, seizure.

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568 Prediction of Basic Wind Speed for Ayeyarwady

Authors: Chaw Su Mon

Abstract:

Abstract— The paper presents a preliminary study on modeling and estimation of basic wind speed ( extreme wind gusts ) for the consideration of vulnerability and design of building in Ayeyarwady Region. The establishment of appropriate design wind speeds is a critical step towards the calculation of design wind loads for structures. In this paper the extreme value analysis of this prediction work is based on the anemometer data (1970-2009) maintained by the department of meteorology and hydrology of Pathein. Statistical and probabilistic approaches are used to derive formulas for estimating 3-second gusts from recorded data (10-minute sustained mean wind speeds).

Keywords: Basic Wind Speed, Building, Gusts, Statistical and probabilistic approaches

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567 An Estimation of the Performance of HRLS Algorithm

Authors: Shazia Javed, Noor Atinah Ahmad

Abstract:

The householder RLS (HRLS) algorithm is an O(N2) algorithm which recursively updates an arbitrary square-root of the input data correlation matrix and naturally provides the LS weight vector. A data dependent householder matrix is applied for such an update. In this paper a recursive estimate of the eigenvalue spread and misalignment of the algorithm is presented at a very low computational cost. Misalignment is found to be highly sensitive to the eigenvalue spread of input signals, output noise of the system and exponential window. Simulation results show noticeable degradation in the misalignment by increase in eigenvalue spread as well as system-s output noise, while exponential window was kept constant.

Keywords: HRLS algorithm, eigenvalue spread, misalignment.

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566 Currency Exchange Rate Forecasts Using Quantile Regression

Authors: Yuzhi Cai

Abstract:

In this paper, we discuss a Bayesian approach to quantile autoregressive (QAR) time series model estimation and forecasting. Together with a combining forecasts technique, we then predict USD to GBP currency exchange rates. Combined forecasts contain all the information captured by the fitted QAR models at different quantile levels and are therefore better than those obtained from individual models. Our results show that an unequally weighted combining method performs better than other forecasting methodology. We found that a median AR model can perform well in point forecasting when the predictive density functions are symmetric. However, in practice, using the median AR model alone may involve the loss of information about the data captured by other QAR models. We recommend that combined forecasts should be used whenever possible.

Keywords: Exchange rate, quantile regression, combining forecasts.

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565 New Corneal Reflection Removal Method Used In Iris Recognition System

Authors: Walid Aydi, Nouri Masmoudi, Lotfi Kamoun

Abstract:

Images of human iris contain specular highlights due to the reflective properties of the cornea. This corneal reflection causes many errors not only in iris and pupil center estimation but also to locate iris and pupil boundaries especially for methods that use active contour. Each iris recognition system has four steps: Segmentation, Normalization, Encoding and Matching. In order to address the corneal reflection, a novel reflection removal method is proposed in this paper. Comparative experiments of two existing methods for reflection removal method are evaluated on CASIA iris image databases V3. The experimental results reveal that the proposed algorithm provides higher performance in reflection removal.

Keywords: iris, pupil, specular highlights, reflection removal

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564 Low-Cost and Highly Accurate Motion Models for Three-Dimensional Local Landmark-based Autonomous Navigation

Authors: Gheorghe Galben, Daniel N. Aloi

Abstract:

Recently, the Spherical Motion Models (SMM-s) have been introduced [1]. These new models have been developed for 3D local landmark-base Autonomous Navigation (AN). This paper is revealing new arguments and experimental results to support the SMM-s characteristics. The accuracy and the robustness in performing a specific task are the main concerns of the new investigations. To analyze their performances of the SMM-s, the most powerful tools of estimation theory, the extended Kalman filter (EKF) and unscented Kalman filter (UKF), which give the best estimations in noisy environments, have been employed. The Monte Carlo validation implementations used to test the stability and robustness of the models have been employed as well.

Keywords: Autonomous navigation, extended kalman filter, unscented kalman filter, localization algorithms.

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563 GMDH Modeling Based on Polynomial Spline Estimation and Its Applications

Authors: LI qiu-min, TIAN yi-xiang, ZHANG gao-xun

Abstract:

GMDH algorithm can well describe the internal structure of objects. In the process of modeling, automatic screening of model structure and variables ensure the convergence rate.This paper studied a new GMDH model based on polynomial spline  stimation. The polynomial spline function was used to instead of the transfer function of GMDH to characterize the relationship between the input variables and output variables. It has proved that the algorithm has the optimal convergence rate under some conditions. The empirical results show that the algorithm can well forecast Consumer Price Index (CPI).

Keywords: spline, GMDH, nonparametric, bias, forecast.

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562 Interval Type-2 Fuzzy Vibration Control of an ERF Embedded Smart Structure

Authors: Chih-Jer Lin, Chun-Ying Lee, Ying Liu, Chiang-Ho Cheng

Abstract:

The main objective of this article is to present the semi-active vibration control using an electro-rheological fluid embedded sandwich structure for a cantilever beam. ER fluid is a smart material, which cause the suspended particles polarize and connect each other to form chain. The stiffness and damping coefficients of the ER fluid can be changed in 10 micro seconds; therefore, ERF is suitable to become the material embedded in the tunable vibration absorber to become a smart absorber. For the ERF smart material embedded structure, the fuzzy control law depends on the experimental expert database and the proposed self-tuning strategy. The electric field is controlled by a CRIO embedded system to implement the real application. This study investigates the different performances using the Type-1 fuzzy and interval Type-2 fuzzy controllers. The Interval type-2 fuzzy control is used to improve the modeling uncertainties for this ERF embedded shock absorber. The self-tuning vibration controllers using Type-1 and Interval Type-2 fuzzy law are implemented to the shock absorber system. Based on the resulting performance, Internal Type-2 fuzzy is better than the traditional Type-1 fuzzy control for this vibration control system.

 

Keywords: Electro-Rheological Fluid, Semi-active vibration control, shock absorber, type 2 fuzzy control.

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561 On the outlier Detection in Nonlinear Regression

Authors: Hossein Riazoshams, Midi Habshah, Jr., Mohamad Bakri Adam

Abstract:

The detection of outliers is very essential because of their responsibility for producing huge interpretative problem in linear as well as in nonlinear regression analysis. Much work has been accomplished on the identification of outlier in linear regression, but not in nonlinear regression. In this article we propose several outlier detection techniques for nonlinear regression. The main idea is to use the linear approximation of a nonlinear model and consider the gradient as the design matrix. Subsequently, the detection techniques are formulated. Six detection measures are developed that combined with three estimation techniques such as the Least-Squares, M and MM-estimators. The study shows that among the six measures, only the studentized residual and Cook Distance which combined with the MM estimator, consistently capable of identifying the correct outliers.

Keywords: Nonlinear Regression, outliers, Gradient, LeastSquare, M-estimate, MM-estimate.

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560 Modelling of a Stress-Strain State of Screws of Transpedicular Spine Fixation System

Authors: Oleksandr Poliakov, Genadiy Olinichenko, Yevgen Pashkov, Vadym Kramar, Mykhaylo Kalinin

Abstract:

For maintenance of a spine stability during the postoperative period a transpedicular fixing of its elements is often used. Usually the transpedicular systems are formed of rods which as a result form a design of the frame type, fastening by screws to vertebras. Such design should be rigid and perceive loadings operating from the spine without essential deformations. From the perfection point of view of known designs their stress whole, and each of elements, in particular is of interest. In this study the modeling of the transpedicular screw is performed and estimation of its deformations taking into account interaction with a vertebra body having variable structure is made.

Keywords: Spine, screw, stress-strain state, transpedicular fixation system, vertebra

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559 Experimental and Theoretical Study on Hygrothermal Aging Effect on Mechanical Behavior of Fiber Reinforced Plastic Laminates

Authors: S. Larbi, R. Bensaada, S. Djebali, A. Bilek

Abstract:

The manufacture of composite parts is a major issue in many industrial domains. Polymer composite materials are ideal for structural applications where high strength-to-weight and stiffness-to-weight ratios are required. However, exposition to extreme environment conditions (temperature, humidity) affects mechanical properties of organic composite materials and lead to an undesirable degradation. Aging mechanisms in organic matrix are very diverse and vary according to the polymer and the aging conditions such as temperature, humidity etc. This paper studies the hygrothermal aging effect on the mechanical properties of fiber reinforced plastics laminates at 40 °C in different environment exposure. Two composite materials are used to conduct the study (carbon fiber/epoxy and glass fiber/vinyl ester with two stratifications for both the materials [904/04] and [454/04]). The experimental procedure includes a mechanical characterization of the materials in a virgin state and exposition of specimens to two environments (seawater and demineralized water). Absorption kinetics for the two materials and both the stratifications are determined. Three-point bending test is performed on the aged materials in order to determine the hygrothermal effect on the mechanical properties of the materials.

Keywords: FRP laminates, hygrothermal aging, mechanical properties, theory of laminates.

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558 Local Error Control in the RK5GL3 Method

Authors: J.S.C. Prentice

Abstract:

The RK5GL3 method is a numerical method for solving initial value problems in ordinary differential equations, and is based on a combination of a fifth-order Runge-Kutta method and 3-point Gauss-Legendre quadrature. In this paper we describe an effective local error control algorithm for RK5GL3, which uses local extrapolation with an eighth-order Runge-Kutta method in tandem with RK5GL3, and a Hermite interpolating polynomial for solution estimation at the Gauss-Legendre quadrature nodes.

Keywords: RK5GL3, RKrGLm, Runge-Kutta, Gauss-Legendre, Hermite interpolating polynomial, initial value problem, local error.

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557 Comparison of Rheological Properties for Polymer Modified Asphalt Produced in Riyadh

Authors: Ali M. Babalghaith, Hamad A. Alsoliman, Abdulrahman S. Al-Suhaibani

Abstract:

Flexible pavement made with neat asphalt binder is not enough to resist heavy traffic loads as well as harsh environmental condition found in Riyadh region. Therefore, there is a need to modify asphalt binder with polymers to satisfy such conditions. There are several types of polymers that are used to modify asphalt binder. The objective of this paper is to compare the rheological properties of six polymer modified asphalt binders (Lucolast7010, Anglomak2144, Paveflex140, SBS KTR401, EE-2 and Crumb rubber) obtained from asphalt manufacturer plants. The rheological properties of polymer modified asphalt binders were tested using conventional tests such as penetration, softening point and viscosity; and SHRP tests such as dynamic shear rheometer and bending beam rheometer. The results have indicated that the polymer modified asphalt binders have lower penetration and higher softening point than neat asphalt indicating an improvement in stiffness of asphalt binder, and as a result, more resistant to rutting. Moreover, the dynamic shear rheometer results have shown that all modifiers used in this study improved the binder properties and satisfied the Superpave specifications except SBS KTR401 which failed to satisfy the rutting parameter (G*/sinδ).

Keywords: Polymer modified asphalt, rheological properties, SBS, crumb rubber, EE-2.

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556 Component-based Segmentation of Words from Handwritten Arabic Text

Authors: Jawad H AlKhateeb, Jianmin Jiang, Jinchang Ren, Stan S Ipson

Abstract:

Efficient preprocessing is very essential for automatic recognition of handwritten documents. In this paper, techniques on segmenting words in handwritten Arabic text are presented. Firstly, connected components (ccs) are extracted, and distances among different components are analyzed. The statistical distribution of this distance is then obtained to determine an optimal threshold for words segmentation. Meanwhile, an improved projection based method is also employed for baseline detection. The proposed method has been successfully tested on IFN/ENIT database consisting of 26459 Arabic words handwritten by 411 different writers, and the results were promising and very encouraging in more accurate detection of the baseline and segmentation of words for further recognition.

Keywords: Arabic OCR, off-line recognition, Baseline estimation, Word segmentation.

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555 Estimation of Reconnaissance Drought Index (RDI) for Bhavnagar District, Gujarat, India

Authors: Ravi Shah, V. L. Manekar, R. A. Christian, N. J. Mistry

Abstract:

There are two types of drought as conceptual drought and operational drought. The three parameters as the beginning, the end and the degree of severity of the drought can be identifying in operational drought by average precipitation in the whole region. One of the methods classified to measure drought is Reconnaissance Drought Index (RDI). Evapotranspiration is calculated using Penman-Monteith method by analyzing thirty nine years prolong climatic data. The evapotranspiration is then utilized in RDI to classify normalized and standardized RDI. These RDI classifications led to what kind of drought faced in Bhavnagar region on 12 month time scale basis. The comparison between actual drought conditions and RDI method used to find out drought are also illustrated. It can be concluded that the index results of drought in a particular year are same in both methods but having different index values where as severity remain same.

Keywords: Drought, Drought index, Reconnaissance Drought Index (RDI), Precipitation.

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