Search results for: methanol decomposition
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 447

Search results for: methanol decomposition

357 A Linearization and Decomposition Based Approach to Minimize the Non-Productive Time in Transfer Lines

Authors: Hany Osman, M. F. Baki

Abstract:

We address the balancing problem of transfer lines in this paper to find the optimal line balancing that minimizes the nonproductive time. We focus on the tool change time and face orientation change time both of which influence the makespane. We consider machine capacity limitations and technological constraints associated with the manufacturing process of auto cylinder heads. The problem is represented by a mixed integer programming model that aims at distributing the design features to workstations and sequencing the machining processes at a minimum non-productive time. The proposed model is solved by an algorithm established using linearization schemes and Benders- decomposition approach. The experiments show the efficiency of the algorithm in reaching the exact solution of small and medium problem instances at reasonable time.

Keywords: Transfer line balancing, Benders' decomposition, Linearization.

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356 An Experimental Design Approach to Determine Effects of The Operating Parameters on The Rate of Ru promoted Ir Carbonylation of Methanol

Authors: Vahid Hosseinpour, Mohammad Kazemini, Alireza Mohammadrezaee

Abstract:

carbonylation of methanol in homogenous phase is one of the major routesfor production of acetic acid. Amongst group VIII metal catalysts used in this process iridium has displayed the best capabilities. To investigate effect of operating parameters like: temperature, pressure, methyl iodide, methyl acetate, iridium, ruthenium, and water concentrations on the reaction rate, experimental design for this system based upon central composite design (CCD) was utilized. Statistical rate equation developed by this method contained individual, interactions and curvature effects of parameters on the reaction rate. The model with p-value less than 0.0001 and R2 values greater than 0.9; confirmeda satisfactory fitness of the experimental and theoretical studies. In other words, the developed model and experimental data obtained passed all diagnostic tests establishing this model as a statistically significant.

Keywords: Acetic Acid, Carbonylation of Methanol, Central Composite Design, Experimental Design, Iridium/Ruthenium

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355 Electrical Properties of Roystonea regia Fruit Extract as Dye Sensitized Solar Cells

Authors: Adenike Boyo, Olasunkanmi Kesinro, Henry Boyo, Surukite Oluwole

Abstract:

Utilizing solar energy in producing electricity can minimize environmental pollution generated by fossil fuel in producing electricity. Our research was base on the extraction of dye from Roystonea regia fruit by using methanol as solvent. The dye extracts were used as sensitizers in Dye-sensitized solar cell (DSSCs). Study was done on the electrical properties from the extracts of Roystonea regia fruit as Dye-sensitized solar cell (DSSCs). The absorptions of the extracts and extracts with dye were determined at different wavelengths (350-1000nm). Absorption peak was observed at 1.339 at wavelength 400nm. The obtained values for methanol extract Roystonea regia extract are, Imp = 0.015mA, Vmp = 12.0mV, fill factor = 0.763, Isc= 0.018 mA and Voc = 13.1 mV and efficiency of 0.32%. .The phytochemical screening was taken and it was observed that Roystonea regia extract contained less of anthocyanin compared to flavonoids. The nanostructured dye sensitized solar cell (DSSC) will provide economically credible alternative to present day silicon p–n junction photovoltaic.

Keywords: Methanol, Ethanol, Titanium dioxide, Roystonea regia fruit, Dye-sensitized solar cell.

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354 Robust Stability Criteria for Uncertain Genetic Regulatory Networks with Time-Varying Delays

Authors: Wenqin Wang, Shouming Zhong

Abstract:

This paper presents the robust stability criteria for uncertain genetic regulatory networks with time-varying delays. One key point of the criterion is that the decomposition of the matrix ˜D into ˜D = ˜D1 + ˜D2. This decomposition corresponds to a decomposition of the delayed terms into two groups: the stabilizing ones and the destabilizing ones. This technique enables one to take the stabilizing effect of part of the delayed terms into account. Meanwhile, by choosing an appropriate new Lyapunov functional, a new delay-dependent stability criteria is obtained and formulated in terms of linear matrix inequalities (LMIs). Finally, numerical examples are presented to illustrate the effectiveness of the theoretical results.

Keywords: Genetic regulatory network, Time-varying delay, Uncertain system, Lyapunov-Krasovskii functional

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353 Empirical Mode Decomposition with Wavelet Transform Based Analytic Signal for Power Quality Assessment

Authors: Sudipta Majumdar, Amarendra Kumar Mishra

Abstract:

This paper proposes empirical mode decomposition (EMD) together with wavelet transform (WT) based analytic signal for power quality (PQ) events assessment. EMD decomposes the complex signals into several intrinsic mode functions (IMF). As the PQ events are non stationary, instantaneous parameters have been calculated from these IMFs using analytic signal obtained form WT. We obtained three parameters from IMFs and then used KNN classifier for classification of PQ disturbance. We compared the classification of proposed method for PQ events by obtaining the features using Hilbert transform (HT) method. The classification efficiency using WT based analytic method is 97.5% and using HT based analytic signal is 95.5%.

Keywords: Empirical mode decomposition, Hilbert transform, wavelet transform.

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352 Oil Extraction from Microalgae Dunalliela sp. by Polar and Non-Polar Solvents

Authors: A. Zonouzi, M. Auli, M. Javanmard Dakheli, M. A. Hejazi

Abstract:

Microalgae are tiny photosynthetic plants. Nowadays, microalgae are being used as nutrient-dense foods and sources of fine chemicals. They have significant amounts of lipid, carotenoids, vitamins, protein, minerals, chlorophyll, and pigments. Oil extraction from algae is a hotly debated topic currently because introducing an efficient method could decrease the process cost. This can determine the sustainability of algae-based foods. Scientific research works show that solvent extraction using chloroform/methanol (2:1) mixture is one of the efficient methods for oil extraction from algal cells, but both methanol and chloroform are toxic solvents, and therefore, the extracted oil will not be suitable for food application. In this paper, the effect of two food grade solvents (hexane and hexane/ isopropanol) on oil extraction yield from microalgae Dunaliella sp. was investigated and the results were compared with chloroform/methanol (2:1) extraction yield. It was observed that the oil extraction yield using hexane, hexane/isopropanol (3:2) and chloroform/methanol (2:1) mixture were 5.4, 13.93, and 17.5 (% w/w, dry basis), respectively. The fatty acid profile derived from GC illustrated that the palmitic (36.62%), oleic (18.62%), and stearic acids (19.08%) form the main portion of fatty acid composition of microalgae Dunalliela sp. oil. It was concluded that, the addition of isopropanol as polar solvent could increase the extraction yield significantly. Isopropanol solves cell wall phospholipids and enhances the release of intercellular lipids, which improves accessing of hexane to fatty acids.

Keywords: Fatty acid profile, Microalgae, Oil extraction, Polar solvent.

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351 A Simple Adaptive Atomic Decomposition Voice Activity Detector Implemented by Matching Pursuit

Authors: Thomas Bryan, Veton Kepuska, Ivica Kostanic

Abstract:

A simple adaptive voice activity detector (VAD) is implemented using Gabor and gammatone atomic decomposition of speech for high Gaussian noise environments. Matching pursuit is used for atomic decomposition, and is shown to achieve optimal speech detection capability at high data compression rates for low signal to noise ratios. The most active dictionary elements found by matching pursuit are used for the signal reconstruction so that the algorithm adapts to the individual speakers dominant time-frequency characteristics. Speech has a high peak to average ratio enabling matching pursuit greedy heuristic of highest inner products to isolate high energy speech components in high noise environments. Gabor and gammatone atoms are both investigated with identical logarithmically spaced center frequencies, and similar bandwidths. The algorithm performs equally well for both Gabor and gammatone atoms with no significant statistical differences. The algorithm achieves 70% accuracy at a 0 dB SNR, 90% accuracy at a 5 dB SNR and 98% accuracy at a 20dB SNR using 30d B SNR as a reference for voice activity.

Keywords: Atomic Decomposition, Gabor, Gammatone, Matching Pursuit, Voice Activity Detection.

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350 Carbon Supported Cu and TiO2 Catalysts Applied for Ozone Decomposition

Authors: Katya Milenova, Penko Nikolov, Irina Stambolova, Plamen Nikolov, Vladimir Blaskov

Abstract:

In this article a comparison was made between Cu and TiO2 supported catalysts on activated carbon for ozone decomposition reaction. The activated carbon support in the case of TiO2/AC sample was prepared by physicochemical pyrolysis and for Cu/AC samples the supports are chemically modified carbons. The prepared catalysts were synthesized by impregnation method. The samples were annealed in two different regimes- in air and under vacuum. To examine adsorption efficiency of the samples BET method was used. All investigated catalysts supported on chemically modified carbons have higher specific surface area compared to the specific surface area of TiO2 supported catalysts, varying in the range 590÷620 m2/g. The method of synthesis of the precursors had influenced catalytic activity.

Keywords: Activated carbon, adsorption, copper, ozone decomposition, TiO2.

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349 Enhancement of Low Contrast Satellite Images using Discrete Cosine Transform and Singular Value Decomposition

Authors: A. K. Bhandari, A. Kumar, P. K. Padhy

Abstract:

In this paper, a novel contrast enhancement technique for contrast enhancement of a low-contrast satellite image has been proposed based on the singular value decomposition (SVD) and discrete cosine transform (DCT). The singular value matrix represents the intensity information of the given image and any change on the singular values change the intensity of the input image. The proposed technique converts the image into the SVD-DCT domain and after normalizing the singular value matrix; the enhanced image is reconstructed by using inverse DCT. The visual and quantitative results suggest that the proposed SVD-DCT method clearly shows the increased efficiency and flexibility of the proposed method over the exiting methods such as Linear Contrast Stretching technique, GHE technique, DWT-SVD technique, DWT technique, Decorrelation Stretching technique, Gamma Correction method based techniques.

Keywords: Singular Value Decomposition (SVD), discretecosine transforms (DCT), image equalization and satellite imagecontrast enhancement.

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348 Bisymmetric, Persymmetric Matrices and Its Applications in Eigen-decomposition of Adjacency and Laplacian Matrices

Authors: Mahdi Nouri

Abstract:

In this paper we introduce an efficient solution method for the Eigen-decomposition of bisymmetric and per symmetric matrices of symmetric structures. Here we decompose adjacency and Laplacian matrices of symmetric structures to submatrices with low dimension for fast and easy calculation of eigenvalues and eigenvectors. Examples are included to show the efficiency of the method.

Keywords: Graphs theory, Eigensolution, adjacency and Laplacian matrix, Canonical forms, bisymmetric, per symmetric.

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347 Effect of Catalyst Preparation on the Performance of CaO-ZnO Catalysts for Transesterification

Authors: Pathravut Klinklom, Apanee Luengnaruemitchai, Samai Jai-In

Abstract:

In this research, CaO-ZnO catalysts (with various Ca:Zn atomic ratios of 1:5, 1:3, 1:1, and 3:1) prepared by incipientwetness impregnation (IWI) and co-precipitation (CP) methods were used as a catalyst in the transesterification of palm oil with methanol for biodiesel production. The catalysts were characterized by several techniques, including BET method, CO2-TPD, and Hemmett Indicator. The effects of precursor concentration, and calcination temperature on the catalytic performance were studied under reaction conditions of a 15:1 methanol to oil molar ratio, 6 wt% catalyst, reaction temperature of 60°C, and reaction time of 8 h. At Ca:Zn atomic ratio of 1:3 gave the highest FAME value owing to a basic properties and surface area of the prepared catalyst.

Keywords: CaO, ZnO, Biodiesel, Impregnation, Coprecipitation.

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346 Sub-Image Detection Using Fast Neural Processors and Image Decomposition

Authors: Hazem M. El-Bakry, Qiangfu Zhao

Abstract:

In this paper, an approach to reduce the computation steps required by fast neural networksfor the searching process is presented. The principle ofdivide and conquer strategy is applied through imagedecomposition. Each image is divided into small in sizesub-images and then each one is tested separately usinga fast neural network. The operation of fast neuralnetworks based on applying cross correlation in thefrequency domain between the input image and theweights of the hidden neurons. Compared toconventional and fast neural networks, experimentalresults show that a speed up ratio is achieved whenapplying this technique to locate human facesautomatically in cluttered scenes. Furthermore, fasterface detection is obtained by using parallel processingtechniques to test the resulting sub-images at the sametime using the same number of fast neural networks. Incontrast to using only fast neural networks, the speed upratio is increased with the size of the input image whenusing fast neural networks and image decomposition.

Keywords: Fast Neural Networks, 2D-FFT, CrossCorrelation, Image decomposition, Parallel Processing.

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345 A Nonoblivious Image Watermarking System Based on Singular Value Decomposition and Texture Segmentation

Authors: Soroosh Rezazadeh, Mehran Yazdi

Abstract:

In this paper, a robust digital image watermarking scheme for copyright protection applications using the singular value decomposition (SVD) is proposed. In this scheme, an entropy masking model has been applied on the host image for the texture segmentation. Moreover, the local luminance and textures of the host image are considered for watermark embedding procedure to increase the robustness of the watermarking scheme. In contrast to all existing SVD-based watermarking systems that have been designed to embed visual watermarks, our system uses a pseudo-random sequence as a watermark. We have tested the performance of our method using a wide variety of image processing attacks on different test images. A comparison is made between the results of our proposed algorithm with those of a wavelet-based method to demonstrate the superior performance of our algorithm.

Keywords: Watermarking, copyright protection, singular value decomposition, entropy masking, texture segmentation.

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344 Solving Fully Fuzzy Linear Systems by use of a Certain Decomposition of the Coefficient Matrix

Authors: S. H. Nasseri, M. Sohrabi, E. Ardil

Abstract:

In this paper, we give a certain decomposition of the coefficient matrix of the fully fuzzy linear system (FFLS) to obtain a simple algorithm for solving these systems. The new algorithm can solve FFLS in a smaller computing process. We will illustrate our method by solving some examples.

Keywords: Fully fuzzy linear system, Fuzzy number, LUdecomposition.

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343 Application of Computational Methods Mm2 and Gussian for Studing Unimolecular Decomposition of Vinil Ethers based on the Mechanism of Hydrogen Bonding

Authors: Behnaz Shahrokh, Garnik N. Sargsyan, Arkadi B. Harutyunyan

Abstract:

Investigations of the unimolecular decomposition of vinyl ethyl ether (VEE), vinyl propyl ether (VPE) and vinyl butyl ether (VBE) have shown that activation of the molecule of a ether results in formation of a cyclic construction - the transition state (TS), which may lead to the displacement of the thermodynamic equilibrium towards the reaction products. The TS is obtained by applying energy minimization relative to the ground state of an ether under the program MM2 when taking into account the hydrogen bond formation between a hydrogen atom of alkyl residue and the extreme atom of carbon of the vinyl group. The dissociation of TS up to the products is studied by energy minimization procedure using the mathematical program Gaussian. The obtained calculation data for VEE testify that the decomposition of this ether may be conditioned by hydrogen bond formation for two possible versions: when α- or β- hydrogen atoms of the ethyl group are bound to carbon atom of the vinyl group. Applying the same calculation methods to other ethers (VPE and VBE) it is shown that only in the case of hydrogen bonding between α-hydrogen atom of the alkyl residue and the extreme atom of carbon of the vinyl group (αH---C) results in decay of theses ethers.

Keywords: Gaussian, MM2, ethers, TS, decomposition

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342 Functional Decomposition Based Effort Estimation Model for Software-Intensive Systems

Authors: Nermin Sökmen

Abstract:

An effort estimation model is needed for softwareintensive projects that consist of hardware, embedded software or some combination of the two, as well as high level software solutions. This paper first focuses on functional decomposition techniques to measure functional complexity of a computer system and investigates its impact on system development effort. Later, it examines effects of technical difficulty and design team capability factors in order to construct the best effort estimation model. With using traditional regression analysis technique, the study develops a system development effort estimation model which takes functional complexity, technical difficulty and design team capability factors as input parameters. Finally, the assumptions of the model are tested.

Keywords: Functional complexity, functional decomposition, development effort, technical difficulty, design team capability, regression analysis.

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341 An Improved Algorithm for Calculation of the Third-order Orthogonal Tensor Product Expansion by Using Singular Value Decomposition

Authors: Chiharu Okuma, Naoki Yamamoto, Jun Murakami

Abstract:

As a method of expanding a higher-order tensor data to tensor products of vectors we have proposed the Third-order Orthogonal Tensor Product Expansion (3OTPE) that did similar expansion as Higher-Order Singular Value Decomposition (HOSVD). In this paper we provide a computation algorithm to improve our previous method, in which SVD is applied to the matrix that constituted by the contraction of original tensor data and one of the expansion vector obtained. The residual of the improved method is smaller than the previous method, truncating the expanding tensor products to the same number of terms. Moreover, the residual is smaller than HOSVD when applying to color image data. It is able to be confirmed that the computing time of improved method is the same as the previous method and considerably better than HOSVD.

Keywords: Singular value decomposition (SVD), higher-orderSVD (HOSVD), outer product expansion, power method.

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340 Global Kinetics of Direct Dimethyl Ether Synthesis Process from Syngas in Slurry Reactor over a Novel Cu-Zn-Al-Zr Slurry Catalyst

Authors: Zhen Chen, Haitao Zhang, Weiyong Ying, Dingye Fang

Abstract:

The direct synthesis process of dimethyl ether (DME) from syngas in slurry reactors is considered to be promising because of its advantages in caloric transfer. In this paper, the influences of operating conditions (temperature, pressure and weight hourly space velocity) on the conversion of CO, selectivity of DME and methanol were studied in a stirred autoclave over Cu-Zn-Al-Zr slurry catalyst, which is far more suitable to liquid phase dimethyl ether synthesis process than bifunctional catalyst commercially. A Langmuir- Hinshelwood mechanism type global kinetics model for liquid phase DME direct synthesis based on methanol synthesis models and a methanol dehydration model has been investigated by fitting our experimental data. The model parameters were estimated with MATLAB program based on general Genetic Algorithms and Levenberg-Marquardt method, which is suitably fitting experimental data and its reliability was verified by statistical test and residual error analysis.

Keywords: alcohol/ether fuel, Cu-Zn-Al-Zr slurry catalyst, global kinetics, slurry reactor

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339 The Utility of Wavelet Transform in Surface Electromyography Feature Extraction -A Comparative Study of Different Mother Wavelets

Authors: Farzaneh Akhavan Mahdavi, Siti Anom Ahmad, Mohd Hamiruce Marhaban, Mohammad-R. Akbarzadeh-T

Abstract:

Electromyography (EMG) signal processing has been investigated remarkably regarding various applications such as in rehabilitation systems. Specifically, wavelet transform has served as a powerful technique to scrutinize EMG signals since wavelet transform is consistent with the nature of EMG as a non-stationary signal. In this paper, the efficiency of wavelet transform in surface EMG feature extraction is investigated from four levels of wavelet decomposition and a comparative study between different mother wavelets had been done. To recognize the best function and level of wavelet analysis, two evaluation criteria, scatter plot and RES index are recruited. Hereupon, four wavelet families, namely, Daubechies, Coiflets, Symlets and Biorthogonal are studied in wavelet decomposition stage. Consequently, the results show that only features from first and second level of wavelet decomposition yields good performance and some functions of various wavelet families can lead to an improvement in separability class of different hand movements.

Keywords: Electromyography signal, feature extraction, wavelettransform, means absolute value.

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338 Production Process for Diesel Fuel Components Polyoxymethylene Dimethyl Ethers from Methanol and Formaldehyde Solution

Authors: Xiangjun Li, Huaiyuan Tian, Wujie Zhang, Dianhua Liu

Abstract:

Polyoxymethylene dimethyl ethers (PODEn) as clean diesel additive can improve the combustion efficiency and quality of diesel fuel and alleviate the problem of atmospheric pollution. Considering synthetic routes, PODE production from methanol and formaldehyde is regarded as the most economical and promising synthetic route. However, methanol used for synthesizing PODE can produce water, which causes the loss of active center of catalyst and hydrolysis of PODEn in the production process. Macroporous strong acidic cation exchange resin catalyst was prepared, which has comparative advantages over other common solid acid catalysts in terms of stability and catalytic efficiency for synthesizing PODE. Catalytic reactions were carried out under 353 K, 1 MPa and 3mL·gcat-1·h-1 in a fixed bed reactor. Methanol conversion and PODE3-6 selectivity reached 49.91% and 23.43%, respectively. Catalyst lifetime evaluation showed that resin catalyst retained its catalytic activity for 20 days without significant changes and catalytic activity of completely deactivated resin catalyst can basically return to previous level by simple acid regeneration. The acid exchange capacities of original and deactivated catalyst were 2.5191 and 0.0979 mmol·g-1, respectively, while regenerated catalyst reached 2.0430 mmol·g-1, indicating that the main reason for resin catalyst deactivation is that Brønsted acid sites of original resin catalyst were temporarily replaced by non-hydrogen ion cations. A separation process consisting of extraction and distillation for PODE3-6 product was designed for separation of water and unreacted formaldehyde from reactive mixture and purification of PODE3-6, respectively. The concentration of PODE3-6 in final product can reach up to 97%. These results indicate that the scale-up production of PODE3-6 from methanol and formaldehyde solution is feasible.

Keywords: Inactivation, polyoxymethylene dimethyl ethers, separation process, sulfonic cation exchange resin.

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337 Used Frying Oil for Biodiesel Production Over Kaolinite as Catalyst

Authors: Jorge Ramírez-Ortiz, Jorge Medina-Valtierra, Merced Martínez Rosales

Abstract:

Biodiesel production with used frying by transesterification reaction with methanol, using a commercial kaolinite thermally-activated solid acid catalyst was investigated. The surface area, the average pore diameter and pore volume of the kaolinite catalyst were 10 m2/g, 13.0 nm and 30 mm3/g, respectively. The optimal conditions for the transesterification reaction were determined to be oil/methanol, in a molar ratio 1:31, temperature 160 ºC and catalyst concentration of 3% (w/w). The yield of fatty acids methyl esters (FAME) was 92.4% after 2 h of reaction. This method of preparation of biodiesel can be a positive alternative for utilizing used frying corn oil for feedstock of biodiesel combined with the inexpensive catalyst.

Keywords: Biodiesel, frying corn oil, kaolinite, transesterification

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336 Oil Debris Signal Detection Based on Integral Transform and Empirical Mode Decomposition

Authors: Chuan Li, Ming Liang

Abstract:

Oil debris signal generated from the inductive oil debris monitor (ODM) is useful information for machine condition monitoring but is often spoiled by background noise. To improve the reliability in machine condition monitoring, the high-fidelity signal has to be recovered from the noisy raw data. Considering that the noise components with large amplitude often have higher frequency than that of the oil debris signal, the integral transform is proposed to enhance the detectability of the oil debris signal. To cancel out the baseline wander resulting from the integral transform, the empirical mode decomposition (EMD) method is employed to identify the trend components. An optimal reconstruction strategy including both de-trending and de-noising is presented to detect the oil debris signal with less distortion. The proposed approach is applied to detect the oil debris signal in the raw data collected from an experimental setup. The result demonstrates that this approach is able to detect the weak oil debris signal with acceptable distortion from noisy raw data.

Keywords: Integral transform, empirical mode decomposition, oil debris, signal processing, detection.

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335 Preparation and Characterization of Pectin Based Proton Exchange Membranes Derived by Solution Casting Method for Direct Methanol Fuel Cells

Authors: Mohanapriya Subramanian, V. Raj

Abstract:

Direct methanol fuel cells (DMFCs) are considered to be one of the most promising candidates for portable and stationary applications in the view of their advantages such as high energy density, easy manipulation, high efficiency and they operate with liquid fuel which could be used without requiring any fuel-processing units. Electrolyte membrane of DMFC plays a key role as a proton conductor as well as a separator between electrodes. Increasing concern over environmental protection, biopolymers gain tremendous interest owing to their eco-friendly bio-degradable nature. Pectin is a natural anionic polysaccharide which plays an essential part in regulating mechanical behavior of plant cell wall and it is extracted from outer cells of most of the plants. The aim of this study is to develop and demonstrate pectin based polymer composite membranes as methanol impermeable polymer electrolyte membranes for DMFCs. Pectin based nanocomposites membranes are prepared by solution-casting technique wherein pectin is blended with chitosan followed by the addition of optimal amount of sulphonic acid modified Titanium dioxide nanoparticle (S-TiO2). Nanocomposite membranes are characterized by Fourier Transform-Infra Red spectroscopy, Scanning electron microscopy, and Energy dispersive spectroscopy analyses. Proton conductivity and methanol permeability are determined into order to evaluate their suitability for DMFC application. Pectin-chitosan blends endow with a flexible polymeric network which is appropriate to disperse rigid S-TiO2 nanoparticles. Resulting nanocomposite membranes possess adequate thermo-mechanical stabilities as well as high charge-density per unit volume. Pectin-chitosan natural polymeric nanocomposite comprising optimal S-TiO2 exhibits good electrochemical selectivity and therefore desirable for DMFC application.

Keywords: Biopolymers, fuel cells, nanocomposite, methanol crossover.

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334 Feature Extraction of Dorsal Hand Vein Pattern Using a Fast Modified PCA Algorithm Based On Cholesky Decomposition and Lanczos Technique

Authors: Maleika Heenaye- Mamode Khan , Naushad Mamode Khan, Raja K.Subramanian

Abstract:

Dorsal hand vein pattern is an emerging biometric which is attracting the attention of researchers, of late. Research is being carried out on existing techniques in the hope of improving them or finding more efficient ones. In this work, Principle Component Analysis (PCA) , which is a successful method, originally applied on face biometric is being modified using Cholesky decomposition and Lanczos algorithm to extract the dorsal hand vein features. This modified technique decreases the number of computation and hence decreases the processing time. The eigenveins were successfully computed and projected onto the vein space. The system was tested on a database of 200 images and using a threshold value of 0.9 to obtain the False Acceptance Rate (FAR) and False Rejection Rate (FRR). This modified algorithm is desirable when developing biometric security system since it significantly decreases the matching time.

Keywords: Dorsal hand vein pattern, PCA, Cholesky decomposition, Lanczos algorithm.

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333 Industry Openness, Human Capital and Wage Inequality: Evidence from Chinese Manufacturing Firms

Authors: Qiong Huang, Satish Chand

Abstract:

This paper uses a primary data from 670 Chinese manufacturing firms, together with the newly introduced regressionbased inequality decomposition method, to study the effect of openness on wage inequality. We find that openness leads to a positive industry wage premium, but its contribution to firm-level wage inequality is relatively small, only 4.69%. The major contributor to wage inequality is human capital, which could explain 14.3% of wage inequality across sample firms.  

Keywords: Openness, human capital, wage inequality, decomposition; China.

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332 Simulation of a Multi-Component Transport Model for the Chemical Reaction of a CVD-Process

Authors: J. Geiser, R. Röhle

Abstract:

In this paper we present discretization and decomposition methods for a multi-component transport model of a chemical vapor deposition (CVD) process. CVD processes are used to manufacture deposition layers or bulk materials. In our transport model we simulate the deposition of thin layers. The microscopic model is based on the heavy particles, which are derived by approximately solving a linearized multicomponent Boltzmann equation. For the drift-process of the particles we propose diffusionreaction equations as well as for the effects of heat conduction. We concentrate on solving the diffusion-reaction equation with analytical and numerical methods. For the chemical processes, modelled with reaction equations, we propose decomposition methods and decouple the multi-component models to simpler systems of differential equations. In the numerical experiments we present the computational results of our proposed models.

Keywords: Chemical reactions, chemical vapor deposition, convection-diffusion-reaction equations, decomposition methods, multi-component transport.

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331 Progressive Loading Effect of Co over SiO2/Al2O3 Catalyst for Cox Free Hydrogen and Carbon Nanotubes Production via Catalytic Decomposition of Methane

Authors: Sushil Kumar Saraswat, K. K. Pant

Abstract:

Co metal supported on SiO2 and Al2O3 catalysts with a metal loading varied from 30 of 70 wt.% were evaluated for decomposition of methane to COx free hydrogen and carbon nanomaterials. The catalytic runs were carried out from 550-800oC under atmospheric pressure using fixed bed vertical flow reactor. The fresh and spent catalysts were characterized by BET surface area analyzer, XRD, SEM, TEM and TG analysis. The data showed that 50% Co/Al2O3 catalyst exhibited remarkable higher activity at 800oC with respect to H2 production compared to rest of the catalysts. However, the catalytic activity and durability was greatly declined at higher temperature. The main reason for the catalytic inhibition of Co containing SiO2 catalysts is the higher reduction temperature of Co2SiO4. TEM images illustrate that the carbon materials with various morphologies, carbon nanofibers (CNFs), helical-shaped CNFs and branched CNFs depending on the catalyst composition and reaction temperature were obtained.

Keywords: Carbon nanotubes, Cobalt, Hydrogen Production, Methane decomposition.

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330 Numerical Algorithms for Solving a Type of Nonlinear Integro-Differential Equations

Authors: Shishen Xie

Abstract:

In this article two algorithms, one based on variation iteration method and the other on Adomian's decomposition method, are developed to find the numerical solution of an initial value problem involving the non linear integro differantial equation where R is a nonlinear operator that contains partial derivatives with respect to x. Special cases of the integro-differential equation are solved using the algorithms. The numerical solutions are compared with analytical solutions. The results show that these two methods are efficient and accurate with only two or three iterations

Keywords: variation iteration method, decomposition method, nonlinear integro-differential equations

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329 Optimization of Quercus cerris Bark Liquefaction

Authors: Luísa P. Cruz-Lopes, Hugo Costa e Silva, Idalina Domingos, José Ferreira, Luís Teixeira de Lemos, Bruno Esteves

Abstract:

The liquefaction process of cork based tree barks has led to an increase of interest due to its potential innovation in the lumber and wood industries. In this particular study the bark of Quercus cerris (Turkish oak) is used due to its appreciable amount of cork tissue, although of inferior quality when compared to the cork provided by other Quercus trees. This study aims to optimize alkaline catalysis liquefaction conditions, regarding several parameters. To better comprehend the possible chemical characteristics of the bark of Quercus cerris, a complete chemical analysis was performed. The liquefaction process was performed in a double-jacket reactor heated with oil, using glycerol and a mixture of glycerol/ethylene glycol as solvents, potassium hydroxide as a catalyst, and varying the temperature, liquefaction time and granulometry. Due to low liquefaction efficiency resulting from the first experimental procedures a study was made regarding different washing techniques after the filtration process using methanol and methanol/water. The chemical analysis stated that the bark of Quercus cerris is mostly composed by suberin (ca. 30%) and lignin (ca. 24%) as well as insolvent hemicelluloses in hot water (ca. 23%). On the liquefaction stage, the results that led to higher yields were: using a mixture of methanol/ethylene glycol as reagents and a time and temperature of 120 minutes and 200 ºC, respectively. It is concluded that using a granulometry of <80 mesh leads to better results, even if this parameter barely influences the liquefaction efficiency. Regarding the filtration stage, washing the residue with methanol and then distilled water leads to a considerable increase on final liquefaction percentages, which proves that this procedure is effective at liquefying suberin content and lignocellulose fraction.

Keywords: Liquefaction, alkaline catalysis, optimization, Quercus cerris bark.

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328 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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