Search results for: range estimation
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2851

Search results for: range estimation

1561 Shock Induced Damage onto Free-Standing Objects in an Earthquake

Authors: Haider AlAbadi, Joe Petrolito, Nelson Lam, Emad Gad

Abstract:

In areas of low to moderate seismicity many building contents and equipment are not positively fixed to the floor or tied to adjacent walls. Under seismic induced horizontal vibration, such contents and equipment can suffer from damage by either overturning or impact associated with rocking. This paper focuses on the estimation of shock on typical contents and equipment due to rocking. A simplified analytical model is outlined that can be used to estimate the maximum acceleration on a rocking object given its basic geometric and mechanical properties. The developed model was validated against experimental results. The experimental results revealed that the maximum shock acceleration can be underestimated if the static stiffness of the materials at the interface between the rocking object and floor is used rather than the dynamic stiffness. Excellent agreement between the model and experimental results was found when the dynamic stiffness for the interface material was used, which was found to be generally much higher than corresponding static stiffness under different investigated boundary conditions of the cushion. The proposed model can be a beneficial tool in performing a rapid assessment of shock sensitive components considered for possible seismic rectification. 

Keywords: Impact, shock, earthquakes, rocking, building contents, overturning.

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1560 Fast Wavelet Image Denoising Based on Local Variance and Edge Analysis

Authors: Gaoyong Luo

Abstract:

The approach based on the wavelet transform has been widely used for image denoising due to its multi-resolution nature, its ability to produce high levels of noise reduction and the low level of distortion introduced. However, by removing noise, high frequency components belonging to edges are also removed, which leads to blurring the signal features. This paper proposes a new method of image noise reduction based on local variance and edge analysis. The analysis is performed by dividing an image into 32 x 32 pixel blocks, and transforming the data into wavelet domain. Fast lifting wavelet spatial-frequency decomposition and reconstruction is developed with the advantages of being computationally efficient and boundary effects minimized. The adaptive thresholding by local variance estimation and edge strength measurement can effectively reduce image noise while preserve the features of the original image corresponding to the boundaries of the objects. Experimental results demonstrate that the method performs well for images contaminated by natural and artificial noise, and is suitable to be adapted for different class of images and type of noises. The proposed algorithm provides a potential solution with parallel computation for real time or embedded system application.

Keywords: Edge strength, Fast lifting wavelet, Image denoising, Local variance.

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1559 Genetic Mining: Using Genetic Algorithm for Topic based on Concept Distribution

Authors: S. M. Khalessizadeh, R. Zaefarian, S.H. Nasseri, E. Ardil

Abstract:

Today, Genetic Algorithm has been used to solve wide range of optimization problems. Some researches conduct on applying Genetic Algorithm to text classification, summarization and information retrieval system in text mining process. This researches show a better performance due to the nature of Genetic Algorithm. In this paper a new algorithm for using Genetic Algorithm in concept weighting and topic identification, based on concept standard deviation will be explored.

Keywords: Genetic Algorithm, Text Mining, Term Weighting, Concept Extraction, Concept Distribution.

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1558 Comparison of Artificial Neural Network and Multivariate Regression Methods in Prediction of Soil Cation Exchange Capacity

Authors: Ali Keshavarzi, Fereydoon Sarmadian

Abstract:

Investigation of soil properties like Cation Exchange Capacity (CEC) plays important roles in study of environmental reaserches as the spatial and temporal variability of this property have been led to development of indirect methods in estimation of this soil characteristic. Pedotransfer functions (PTFs) provide an alternative by estimating soil parameters from more readily available soil data. 70 soil samples were collected from different horizons of 15 soil profiles located in the Ziaran region, Qazvin province, Iran. Then, multivariate regression and neural network model (feedforward back propagation network) were employed to develop a pedotransfer function for predicting soil parameter using easily measurable characteristics of clay and organic carbon. The performance of the multivariate regression and neural network model was evaluated using a test data set. In order to evaluate the models, root mean square error (RMSE) was used. The value of RMSE and R2 derived by ANN model for CEC were 0.47 and 0.94 respectively, while these parameters for multivariate regression model were 0.65 and 0.88 respectively. Results showed that artificial neural network with seven neurons in hidden layer had better performance in predicting soil cation exchange capacity than multivariate regression.

Keywords: Easily measurable characteristics, Feed-forwardback propagation, Pedotransfer functions, CEC.

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1557 Inhibition Kinetic Determination of Trace Amounts of Ruthenium(III) by the Spectrophotometric method with Rhodamine B in Micellar Medium

Authors: Mohsen Keyvanfard

Abstract:

A new, simple and highly sensitive kinetic spectrophotometric method was developed for the determination of trace amounts of Ru(III) in the range of 0.06-20 ng/ml .The method is based on the inhibitory effect of ruthenium(III) on the oxidation of Rhodamine B by bromate in acidic and micellar medium. The reaction was monitored spectrophotometrically by measuring the decreasing in absorbance of Rhodamine B at 554 nm with a fixedtime method..The limit of detection is 0.04 ng/ml Ru(III).The relative standard deviation of 5 and 10 ng/ml Ru(III) was 2.3 and 2.7 %, respectively. The method was applied to the determination of ruthenium in real water samples

Keywords: Ruthenium ;Inhibitory; Rhodamine B; bromate

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1556 The Link between Financial and Overall Corporate Strategies

Authors: Jaroslav Pavlíček

Abstract:

Company strategy expresses a basic idea of how to reach company objectives. A whole range of models of strategic management are used in practice. The concept of strategic management should fulfill some basic requirements to make it applicable for both the typical, but also more specific company environment. The financial strategy plays an important role in corporate strategy. The paper develops a methodology of strategic model implementing into the category of micro, small and medium-sized enterprises (SMEs). Furthermore, the methodology recommends procedures while solving an up-to-date worldwide task of the definition of the company strategy and its financial strategy.

Keywords: corporate strategy, financial strategy, corporate planning

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1555 Development of Prediction Models of Day-Ahead Hourly Building Electricity Consumption and Peak Power Demand Using the Machine Learning Method

Authors: Dalin Si, Azizan Aziz, Bertrand Lasternas

Abstract:

To encourage building owners to purchase electricity at the wholesale market and reduce building peak demand, this study aims to develop models that predict day-ahead hourly electricity consumption and demand using artificial neural network (ANN) and support vector machine (SVM). All prediction models are built in Python, with tool Scikit-learn and Pybrain. The input data for both consumption and demand prediction are time stamp, outdoor dry bulb temperature, relative humidity, air handling unit (AHU), supply air temperature and solar radiation. Solar radiation, which is unavailable a day-ahead, is predicted at first, and then this estimation is used as an input to predict consumption and demand. Models to predict consumption and demand are trained in both SVM and ANN, and depend on cooling or heating, weekdays or weekends. The results show that ANN is the better option for both consumption and demand prediction. It can achieve 15.50% to 20.03% coefficient of variance of root mean square error (CVRMSE) for consumption prediction and 22.89% to 32.42% CVRMSE for demand prediction, respectively. To conclude, the presented models have potential to help building owners to purchase electricity at the wholesale market, but they are not robust when used in demand response control.

Keywords: Building energy prediction, data mining, demand response, electricity market.

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1554 Modeling of a UAV Longitudinal Dynamics through System Identification Technique

Authors: Asadullah I. Qazi, Mansoor Ahsan, Zahir Ashraf, Uzair Ahmad

Abstract:

System identification of an Unmanned Aerial Vehicle (UAV), to acquire its mathematical model, is a significant step in the process of aircraft flight automation. The need for reliable mathematical model is an established requirement for autopilot design, flight simulator development, aircraft performance appraisal, analysis of aircraft modifications, preflight testing of prototype aircraft and investigation of fatigue life and stress distribution etc.  This research is aimed at system identification of a fixed wing UAV by means of specifically designed flight experiment. The purposely designed flight maneuvers were performed on the UAV and aircraft states were recorded during these flights. Acquired data were preprocessed for noise filtering and bias removal followed by parameter estimation of longitudinal dynamics transfer functions using MATLAB system identification toolbox. Black box identification based transfer function models, in response to elevator and throttle inputs, were estimated using least square error   technique. The identification results show a high confidence level and goodness of fit between the estimated model and actual aircraft response.

Keywords: Black box modeling, fixed wing aircraft, least square error, longitudinal dynamics, system identification.

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1553 Design of a Novel CPW Fed Fractal Antenna for UWB

Authors: A. El Hamdouni, J. Zbitou, A. Tajmouati, L. El Abdellaoui, A. Errkik, A. Tribak, M. Latrach

Abstract:

This paper presents a novel fractal antenna structure proposed for UWB (Ultra – Wideband) applications. The frequency band 3.1-10.6GHz released by FCC (Federal Communication Commission) as the commercial operation of UWB has been chosen as frequency range for this antenna based on coplanar waveguide (CPW) feed and circular shapes fulfilled according to fractal geometry. The proposed antenna is validated and designed by using an FR4 substrate with overall area of 34x43 mm2. The simulated results performed by CST-Microwave Studio and compared by ADS (Advanced Design System) show good matching input impedance with return loss less than -10dB between 2.9 GHz and 11 GHz.

Keywords: Fractal antenna, Fractal Geometry, CPW Feed, UWB, FCC.

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1552 Heat Transfer from Two Cam Shaped Cylinders in Side-by-Side Arrangement

Authors: Arash Mir Abdolah Lavasani, Hamidreza Bayat

Abstract:

Heat transfer from two cam shape cylinder in side-byside arrangement had been studied numerically. The transverse gap between the centers of cylinders (T) is allowed to vary to change the pitch ratio (T/Deq). The equivalent diameter of the cylinder (Deq) is 27.6 mm and pitch ratio varies in range of 1≤T/Deq≤3. The Reynolds numbers based on equivalent circular cylinder are within 50≤ Reeq≤150. Results show that Nusselt number of cylinders increases about 1 to 36 percent when pitch ratio increases from 1 to 3.

Keywords: Cam shaped, side-by-side cylinders, numerical, heat Transfer.

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1551 A TISM Model for Structuring the Productivity Elements of Flexible Manufacturing System

Authors: Sandhya Dixit, Tilak Raj

Abstract:

Flexible Manufacturing System (FMS) is seen as an option for industries which want to boost productivity as well as respond quickly to an increasingly changing marketplace. FMS produces in mid variety, mid volume range and can meet the changing market demands very quickly. But still the impact of adoption of FMS on the productivity of any industry is not very clear. In this paper an attempt has been made to model the various factors affecting the productivity of FMS installation using Total Interpretive Structural Modelling (TISM) Technique.

Keywords: Flexible manufacturing system, productivity, total interpretive structural modelling.

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1550 Earthquake Vulnerability and Repair Cost Estimation of Masonry Buildings in the Old City Center of Annaba, Algeria

Authors: Allaeddine Athmani, Abdelhacine Gouasmia, Tiago Ferreira, Romeu Vicente

Abstract:

The seismic risk mitigation from the perspective of the old buildings stock is truly essential in Algerian urban areas, particularly those located in seismic prone regions, such as Annaba city, and which the old buildings present high levels of degradation associated with no seismic strengthening and/or rehabilitation concerns. In this sense, the present paper approaches the issue of the seismic vulnerability assessment of old masonry building stocks through the adaptation of a simplified methodology developed for a European context area similar to that of Annaba city, Algeria. Therefore, this method is used for the first level of seismic vulnerability assessment of the masonry buildings stock of the old city center of Annaba. This methodology is based on a vulnerability index that is suitable for the evaluation of damage and for the creation of large-scale loss scenarios. Over 380 buildings were evaluated in accordance with the referred methodology and the results obtained were then integrated into a Geographical Information System (GIS) tool. Such results can be used by the Annaba city council for supporting management decisions, based on a global view of the site under analysis, which led to more accurate and faster decisions for the risk mitigation strategies and rehabilitation plans.

Keywords: Damage scenarios, masonry buildings, old city center, seismic vulnerability, vulnerability index.

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1549 Diagnosing the Cause and its Timing of Changes in Multivariate Process Mean Vector from Quality Control Charts using Artificial Neural Network

Authors: Farzaneh Ahmadzadeh

Abstract:

Quality control charts are very effective in detecting out of control signals but when a control chart signals an out of control condition of the process mean, searching for a special cause in the vicinity of the signal time would not always lead to prompt identification of the source(s) of the out of control condition as the change point in the process parameter(s) is usually different from the signal time. It is very important to manufacturer to determine at what point and which parameters in the past caused the signal. Early warning of process change would expedite the search for the special causes and enhance quality at lower cost. In this paper the quality variables under investigation are assumed to follow a multivariate normal distribution with known means and variance-covariance matrix and the process means after one step change remain at the new level until the special cause is being identified and removed, also it is supposed that only one variable could be changed at the same time. This research applies artificial neural network (ANN) to identify the time the change occurred and the parameter which caused the change or shift. The performance of the approach was assessed through a computer simulation experiment. The results show that neural network performs effectively and equally well for the whole shift magnitude which has been considered.

Keywords: Artificial neural network, change point estimation, monte carlo simulation, multivariate exponentially weighted movingaverage

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1548 High Accuracy ESPRIT-TLS Technique for Wind Turbine Fault Discrimination

Authors: Saad Chakkor, Mostafa Baghouri, Abderrahmane Hajraoui

Abstract:

ESPRIT-TLS method appears a good choice for high resolution fault detection in induction machines. It has a very high effectiveness in the frequency and amplitude identification. Contrariwise, it presents a high computation complexity which affects its implementation in real time fault diagnosis. To avoid this problem, a Fast-ESPRIT algorithm that combined the IIR band-pass filtering technique, the decimation technique and the original ESPRIT-TLS method was employed to enhance extracting accurately frequencies and their magnitudes from the wind stator current with less computation cost. The proposed algorithm has been applied to verify the wind turbine machine need in the implementation of an online, fast, and proactive condition monitoring. This type of remote and periodic maintenance provides an acceptable machine lifetime, minimize its downtimes and maximize its productivity. The developed technique has evaluated by computer simulations under many fault scenarios. Study results prove the performance of Fast- ESPRIT offering rapid and high resolution harmonics recognizing with minimum computation time and less memory cost.

Keywords: Spectral Estimation, ESPRIT-TLS, Real Time, Diagnosis, Wind Turbine Faults, Band-Pass Filtering, Decimation.

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1547 Well-Being Inequality Using Superimposing Satisfaction Waves: Heisenberg Uncertainty in Behavioural Economics and Econometrics

Authors: Okay Gunes

Abstract:

In this article, a new method is proposed for the measuring of well-being inequality through a model composed of superimposing satisfaction waves. The displacement of households’ satisfactory state (i.e. satisfaction) is defined in a satisfaction string. The duration of the satisfactory state for a given period is measured in order to determine the relationship between utility and total satisfactory time, itself dependent on the density and tension of each satisfaction string. Thus, individual cardinal total satisfaction values are computed by way of a one-dimensional form for scalar sinusoidal (harmonic) moving wave function, using satisfaction waves with varying amplitudes and frequencies which allow us to measure wellbeing inequality. One advantage to using satisfaction waves is the ability to show that individual utility and consumption amounts would probably not commute; hence, it is impossible to measure or to know simultaneously the values of these observables from the dataset. Thus, we crystallize the problem by using a Heisenberg-type uncertainty resolution for self-adjoint economic operators. We propose to eliminate any estimation bias by correlating the standard deviations of selected economic operators; this is achieved by replacing the aforementioned observed uncertainties with households’ perceived uncertainties (i.e. corrected standard deviations) obtained through the logarithmic psychophysical law proposed by Weber and Fechner.

Keywords: Heisenberg Uncertainty Principle, superimposing satisfaction waves, Weber–Fechner law, well-being inequality.

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1546 Performance Analysis of 5G for Low Latency Transmission Based on Universal Filtered Multi-Carrier Technique and Interleave Division Multiple Access

Authors: A. Asgharzadeh, M. Maroufi

Abstract:

5G mobile communication system has drawn more and more attention. The 5G system needs to provide three different types of services, including enhanced Mobile BroadBand (eMBB), massive machine-type communication (mMTC), and ultra-reliable and low-latency communication (URLLC). Universal Filtered Multi-Carrier (UFMC), Filter Bank Multicarrier (FBMC), and Filtered Orthogonal Frequency Division Multiplexing (f-OFDM) are suggested as a well-known candidate waveform for the coming 5G system. Themachine-to-machine (M2M) communications are one of the essential applications in 5G, and it involves exchanging of concise messages with a very short latency. However, in UFMC systems, the subcarriers are grouped into subbands but f-OFDM only one subband covers the entire band. Furthermore, in FBMC, a subband includes only one subcarrier, and the number of subbands is the same as the number of subcarriers. This paper mainly discusses the performance of UFMC with different parameters for the UFMC system. Also, paper shows that UFMC is the best choice outperforming OFDM in any case and FBMC in case of very short packets while performing similarly for long sequences with channel estimation techniques for Interleave Division Multiple Access (IDMA) systems.

Keywords: UFMC, IDMA, 5G, subband.

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1545 Dynamic Clustering Estimation of Tool Flank Wear in Turning Process using SVD Models of the Emitted Sound Signals

Authors: A. Samraj, S. Sayeed, J. E. Raja., J. Hossen, A. Rahman

Abstract:

Monitoring the tool flank wear without affecting the throughput is considered as the prudent method in production technology. The examination has to be done without affecting the machining process. In this paper we proposed a novel work that is used to determine tool flank wear by observing the sound signals emitted during the turning process. The work-piece material we used here is steel and aluminum and the cutting insert was carbide material. Two different cutting speeds were used in this work. The feed rate and the cutting depth were constant whereas the flank wear was a variable. The emitted sound signal of a fresh tool (0 mm flank wear) a slightly worn tool (0.2 -0.25 mm flank wear) and a severely worn tool (0.4mm and above flank wear) during turning process were recorded separately using a high sensitive microphone. Analysis using Singular Value Decomposition was done on these sound signals to extract the feature sound components. Observation of the results showed that an increase in tool flank wear correlates with an increase in the values of SVD features produced out of the sound signals for both the materials. Hence it can be concluded that wear monitoring of tool flank during turning process using SVD features with the Fuzzy C means classification on the emitted sound signal is a potential and relatively simple method.

Keywords: Fuzzy c means, Microphone, Singular ValueDecomposition, Tool Flank Wear.

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1544 Coherent and Incoherent Scattering Cross Sections for Elements with 13

Authors: Panakkada Latha, K. K. Abdullah, M. P. Unnikrishnan, K. M. Varier, B. R. S. Babu

Abstract:

Coherent and incoherent scattering cross section measurements have been carried out using a HPGe detector on elements in the range of Z = 13 - 50 using 241Am gamma rays. The cross sections have been derived by comparing the net count rate obtained from the Compton peak of aluminium with the corresponding peak of the target. The measured cross sections for the coherent and incoherent processes are compared with theoretical values and earlier reported values. Our results are in agreement with the theoretical values.

Keywords: Cross section, coherent scattering, incoherent scattering, 241Am.

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1543 Optically Active Material Based on Bi2O3@Yb3+, Nd3+ with High Intensity of Upconversion Luminescence in the Red and Green Region

Authors: D. Artamonov, A. Tsibulnikova, I. Samusev, V. Bryukhanov, A. Kozhevnikov

Abstract:

The synthesis and luminescent properties of Yb2O3,Nd2O3@Bi2O3 complex with upconversion generation are discussed in this work. The obtained samples were measured in the visible region of the spectrum under excitation with a wavelength of 980 nm. The studies showed that the obtained complexes have a high degree of stability and intense luminescence in the wavelength range of 400-750 nm. Consideration of the time dependence of the intensity of the upconversion luminescence allowed us to conclude that the enhancement of the intensity occurs in the time interval from 5 to 30 min, followed by the appearance of a stationary mode.

Keywords: Lasers, luminescence, upconversion photonics, rare earth metals.

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1542 Transform-Domain Rate-Distortion Optimization Accelerator for H.264/AVC Video Encoding

Authors: Mohammed Golam Sarwer, Lai Man Po, Kai Guo, Q.M. Jonathan Wu

Abstract:

In H.264/AVC video encoding, rate-distortion optimization for mode selection plays a significant role to achieve outstanding performance in compression efficiency and video quality. However, this mode selection process also makes the encoding process extremely complex, especially in the computation of the ratedistortion cost function, which includes the computations of the sum of squared difference (SSD) between the original and reconstructed image blocks and context-based entropy coding of the block. In this paper, a transform-domain rate-distortion optimization accelerator based on fast SSD (FSSD) and VLC-based rate estimation algorithm is proposed. This algorithm could significantly simplify the hardware architecture for the rate-distortion cost computation with only ignorable performance degradation. An efficient hardware structure for implementing the proposed transform-domain rate-distortion optimization accelerator is also proposed. Simulation results demonstrated that the proposed algorithm reduces about 47% of total encoding time with negligible degradation of coding performance. The proposed method can be easily applied to many mobile video application areas such as a digital camera and a DMB (Digital Multimedia Broadcasting) phone.

Keywords: Context-adaptive variable length coding (CAVLC), H.264/AVC, rate-distortion optimization (RDO), sum of squareddifference (SSD).

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1541 Steady State Thermal Analysis and Design of a Cooling System in an AFPM Motor

Authors: K. Sarrafan, A. Darabi

Abstract:

In this paper, the steady-state temperature of a sample 500 KW two rotor one stator Non-slotted axial flux permanent magnet motor is calculated using the finite element simulator software package. Due to the high temperature in various parts of the machine, especially at stator winding, a cooling system is designed for the motor and the temperature is recalculated. The results show that the temperature obtained for the parts is within the permissible range.

Keywords: Axial Flux, Cooling System, Permanent Magnet, Thermal Analysis.

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1540 Use of Gaussian-Euclidean Hybrid Function Based Artificial Immune System for Breast Cancer Diagnosis

Authors: Cuneyt Yucelbas, Seral Ozsen, Sule Yucelbas, Gulay Tezel

Abstract:

Due to the fact that there exist only a small number of complex systems in artificial immune system (AIS) that work out nonlinear problems, nonlinear AIS approaches, among the well-known solution techniques, need to be developed. Gaussian function is usually used as similarity estimation in classification problems and pattern recognition. In this study, diagnosis of breast cancer, the second type of the most widespread cancer in women, was performed with different distance calculation functions that euclidean, gaussian and gaussian-euclidean hybrid function in the clonal selection model of classical AIS on Wisconsin Breast Cancer Dataset (WBCD), which was taken from the University of California, Irvine Machine-Learning Repository. We used 3-fold cross validation method to train and test the dataset. According to the results, the maximum test classification accuracy was reported as 97.35% by using of gaussian-euclidean hybrid function for fold-3. Also, mean of test classification accuracies for all of functions were obtained as 94.78%, 94.45% and 95.31% with use of euclidean, gaussian and gaussian-euclidean, respectively. With these results, gaussian-euclidean hybrid function seems to be a potential distance calculation method, and it may be considered as an alternative distance calculation method for hard nonlinear classification problems.

Keywords: Artificial Immune System, Breast Cancer Diagnosis, Euclidean Function, Gaussian Function.

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1539 Effect of L/D Ratio on the Performance of a Four-Lobe Pressure Dam Bearing

Authors: G. Bhushan, S. S. Rattan, N. P. Mehta

Abstract:

A four-lobe pressure dam bearing which is produced by cutting two pressure dams on the upper two lobes and two relief-tracks on the lower two lobes of an ordinary four-lobe bearing is found to be more stable than a conventional four-lobe bearing. In this paper a four-lobe pressure dam bearing supporting rigid and flexible rotors is analytically investigated to determine its performance when L/D ratio is varied in the range 0.75 to 1.5. The static and dynamic characteristics are studied at various L/D ratios. The results show that the stability of a four-lobe pressure dam bearing increases with decrease in L/D ratios both for rigid as well as flexible rotors.

Keywords: Four-lobe pressure dam bearing, finite-elementmethod, L/D ratio.

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1538 Modeling of CO2 Removal from Gas Mixtureby 2-amino-2-methyl-1-propanol (AMP) Using the Modified Kent Eisenberg Model

Authors: H. Pahlavanzadeh, A.R.Jahangiri, I. Noshadi

Abstract:

In this paper, the solubility of CO2 in AMP solution have been measured at temperature range of ( 293, 303 ,313,323) K.The amine concentration ranges studied are (2.0, 2.8, and 3.4) M. A solubility apparatus was used to measure the solubility of CO2 in AMP solution on samples of flue gases from Thermal and Central Power Plants of Esfahan Steel Company. The modified Kent Eisenberg model was used to correlate and predict the vapor-liquid equilibria of the (CO2 + AMP + H2O) system. The model predicted results are in good agreement with the experimental vapor-liquid equilibrium measurements.

Keywords: AMP, Carbon dioxide; loading, Flue gases, Modified Kent Eisenberg model

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1537 Towards an Enhanced Stochastic Simulation Model for Risk Analysis in Highway Construction

Authors: Anshu Manik, William G. Buttlar, Kasthurirangan Gopalakrishnan

Abstract:

Over the years, there is a growing trend towards quality-based specifications in highway construction. In many Quality Control/Quality Assurance (QC/QA) specifications, the contractor is primarily responsible for quality control of the process, whereas the highway agency is responsible for testing the acceptance of the product. A cooperative investigation was conducted in Illinois over several years to develop a prototype End-Result Specification (ERS) for asphalt pavement construction. The final characteristics of the product are stipulated in the ERS and the contractor is given considerable freedom in achieving those characteristics. The risk for the contractor or agency depends on how the acceptance limits and processes are specified. Stochastic simulation models are very useful in estimating and analyzing payment risk in ERS systems and these form an integral part of the Illinois-s prototype ERS system. This paper describes the development of an innovative methodology to estimate the variability components in in-situ density, air voids and asphalt content data from ERS projects. The information gained from this would be crucial in simulating these ERS projects for estimation and analysis of payment risks associated with asphalt pavement construction. However, these methods require at least two parties to conduct tests on all the split samples obtained according to the sampling scheme prescribed in present ERS implemented in Illinois.

Keywords: Asphalt Pavement, Risk Analysis, StochasticSimulation, QC/QA.

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1536 X-ray Pulse Profiles of PSR J0538+2817

Authors: Kun Tao Zhao, Na Wang, Jian Ping Yuan

Abstract:

This paper reports our analysis of 163 ks observations of PSR J0538+2817 with the Rossi X-Ray Timing Explorer (RXTE).The pulse profiles, detected up to 60 keV, show a single peak asin the case for radio frequency. The profile is well described by one Gaussians function with full width at half maximum (FWHM) 0.04794. We compared the difference of arrival time between radio and X-ray pulse profiles for the first time. It turns out that the phase of radio emits precede the X-ray by 8.7 ± 4.5 ms. Furthermore we obtained the pulse profiles in the energy ranges of 2.29-6.18 keV, 6.18-12.63 keV and 12.63-17.36 keV. The intensity of pulses decreases with the increasing energy range. We discuss the emission geometry in our work.

Keywords: RXTE, X-ray pulsars, PSR J0538+2817.

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1535 Jamun Juice Extraction Using Commercial Enzymes and Optimization of the Treatment with the Help of Physicochemical, Nutritional and Sensory Properties

Authors: Payel Ghosh, Rama Chandra Pradhan, Sabyasachi Mishra

Abstract:

Jamun (Syzygium cuminii L.) is one of the important indigenous minor fruit with high medicinal value. The jamun cultivation is unorganized and there is huge loss of this fruit every year. The perishable nature of the fruit makes its postharvest management further difficult. Due to the strong cell wall structure of pectin-protein bonds and hard seeds, extraction of juice becomes difficult. Enzymatic treatment has been commercially used for improvement of juice quality with high yield. The objective of the study was to optimize the best treatment method for juice extraction. Enzymes (Pectinase and Tannase) from different stains had been used and for each enzyme, best result obtained by using response surface methodology. Optimization had been done on the basis of physicochemical property, nutritional property, sensory quality and cost estimation. According to quality aspect, cost analysis and sensory evaluation, the optimizing enzymatic treatment was obtained by Pectinase from Aspergillus aculeatus strain. The optimum condition for the treatment was 44 oC with 80 minute with a concentration of 0.05% (w/w). At these conditions, 75% of yield with turbidity of 32.21NTU, clarity of 74.39%T, polyphenol content of 115.31 mg GAE/g, protein content of 102.43 mg/g have been obtained with a significant difference in overall acceptability.

Keywords: Jamun, enzymatic treatment, physicochemical property, sensory analysis, optimization.

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1534 Gas Detection via Machine Learning

Authors: Walaa Khalaf, Calogero Pace, Manlio Gaudioso

Abstract:

We present an Electronic Nose (ENose), which is aimed at identifying the presence of one out of two gases, possibly detecting the presence of a mixture of the two. Estimation of the concentrations of the components is also performed for a volatile organic compound (VOC) constituted by methanol and acetone, for the ranges 40-400 and 22-220 ppm (parts-per-million), respectively. Our system contains 8 sensors, 5 of them being gas sensors (of the class TGS from FIGARO USA, INC., whose sensing element is a tin dioxide (SnO2) semiconductor), the remaining being a temperature sensor (LM35 from National Semiconductor Corporation), a humidity sensor (HIH–3610 from Honeywell), and a pressure sensor (XFAM from Fujikura Ltd.). Our integrated hardware–software system uses some machine learning principles and least square regression principle to identify at first a new gas sample, or a mixture, and then to estimate the concentrations. In particular we adopt a training model using the Support Vector Machine (SVM) approach with linear kernel to teach the system how discriminate among different gases. Then we apply another training model using the least square regression, to predict the concentrations. The experimental results demonstrate that the proposed multiclassification and regression scheme is effective in the identification of the tested VOCs of methanol and acetone with 96.61% correctness. The concentration prediction is obtained with 0.979 and 0.964 correlation coefficient for the predicted versus real concentrations of methanol and acetone, respectively.

Keywords: Electronic nose, Least square regression, Mixture ofgases, Support Vector Machine.

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1533 Studying the Effects of Economic and Financial Development as well as Institutional Quality on Environmental Destruction in the Upper-Middle Income Countries

Authors: Morteza Raei Dehaghi, Seyed Mohammad Mirhashemi

Abstract:

The current study explored the effect of economic development, financial development and institutional quality on environmental destruction in upper-middle income countries during the time period of 1999-2011. The dependent variable is logarithm of carbon dioxide emissions that can be considered as an index for destruction or quality of the environment given to its effects on the environment. Financial development and institutional development variables as well as some control variables were considered. In order to study cross-sectional correlation among the countries under study, Pesaran and Friz test was used. Since the results of both tests show cross-sectional correlation in the countries under study, seemingly unrelated regression method was utilized for model estimation. The results disclosed that Kuznets’ environmental curve hypothesis is confirmed in upper-middle income countries and also, financial development and institutional quality have a significant effect on environmental quality. The results of this study can be considered by policy makers in countries with different income groups to have access to a growth accompanied by improved environmental quality.

Keywords: Economic Development, Environmental Destruction, Financial Development, Institutional Development, Seemingly Unrelated Regression.

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1532 Temporal Signal Processing by Inference Bayesian Approach for Detection of Abrupt Variation of Statistical Characteristics of Noisy Signals

Authors: Farhad Asadi, Hossein Sadati

Abstract:

In fields such as neuroscience and especially in cognition modeling of mental processes, uncertainty processing in temporal zone of signal is vital. In this paper, Bayesian online inferences in estimation of change-points location in signal are constructed. This method separated the observed signal into independent series and studies the change and variation of the regime of data locally with related statistical characteristics. We give conditions on simulations of the method when the data characteristics of signals vary, and provide empirical evidence to show the performance of method. It is verified that correlation between series around the change point location and its characteristics such as Signal to Noise Ratios and mean value of signal has important factor on fluctuating in finding proper location of change point. And one of the main contributions of this study is related to representing of these influences of signal statistical characteristics for finding abrupt variation in signal. There are two different structures for simulations which in first case one abrupt change in temporal section of signal is considered with variable position and secondly multiple variations are considered. Finally, influence of statistical characteristic for changing the location of change point is explained in details in simulation results with different artificial signals.

Keywords: Time series, fluctuation in statistical characteristics, optimal learning.

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