Search results for: Gaussian mixture

Authors: Morteza Farahani, Ahmad Seif, Asadallah Boshra, Hossein Aghaie

Abstract:

Density functional theory (DFT) calculations were performed to calculate aluminum-27, boron-11, and nitrogen-14 quadrupole coupling constant (CQ) in the representative considered model of (6, 0) boron nitride-aluminum nitride nanotube junction (BN-AlNNT) for the first time. To this aim, 1.3 nm length of BNAlN consisting of 18 Al, 18 B, and 36 N atoms was selected where the end atoms capped by hydrogen atoms. The calculated CQ values for optimized BN-AlNNT system reveal different electrostatic environment in the mentioned system. The calculations were performed using the Gaussian 98 package of program.

Keywords: Nanotube Junction, Density functional, Nuclear Quadrupole Resonance.

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Authors: Ahmad M. Sarhan, Omar I. Al Helalat

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In this paper, an Arabic letter recognition system based on Artificial Neural Networks (ANNs) and statistical analysis for feature extraction is presented. The ANN is trained using the Least Mean Squares (LMS) algorithm. In the proposed system, each typed Arabic letter is represented by a matrix of binary numbers that are used as input to a simple feature extraction system whose output, in addition to the input matrix, are fed to an ANN. Simulation results are provided and show that the proposed system always produces a lower Mean Squared Error (MSE) and higher success rates than the current ANN solutions.

Keywords: ANN, Backpropagation, Gaussian, LMS, MSE, Neuron, standard deviation, Widrow-Hoff rule.

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Authors: K. V. Pagalthivarthi, R. J. Visintainer

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Two-dimensional Eulerian (volume-averaged) continuity and momentum equations governing multi-size slurry flow through pump casings are solved by applying a penalty finite element formulation. The computational strategy validated for multi-phase flow through rectangular channels is adapted to the present study.   The flow fields of the carrier, mixture and each solids species, and the concentration field of each species are determined sequentially in an iterative manner. The eddy viscosity field computed using Spalart-Allmaras model for the pure carrier phase is modified for the presence of particles. Streamline upwind Petrov-Galerkin formulation is used for all the momentum equations for the carrier, mixture and each solids species and the concentration field for each species. After ensuring mesh-independence of solutions, results of multi-size particulate flow simulation are presented to bring out the effect of bulk flow rate, average inlet concentration, and inlet particle size distribution. Mono-size computations using (1) the concentration-weighted mean diameter of the slurry and (2) the D50 size of the slurry are also presented for comparison with multi-size results.

Keywords: Eulerian-Eulerian model, Multi-size particulate flow, Penalty finite elements, Pump casing, Spalart-Allmaras.

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

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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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Authors: Ε. Giovanis

Abstract:

In this paper we present, propose and examine additional membership functions for the Smoothing Transition Autoregressive (STAR) models. More specifically, we present the tangent hyperbolic, Gaussian and Generalized bell functions. Because Smoothing Transition Autoregressive (STAR) models follow fuzzy logic approach, more fuzzy membership functions should be tested. Furthermore, fuzzy rules can be incorporated or other training or computational methods can be applied as the error backpropagation or genetic algorithm instead to nonlinear squares. We examine two macroeconomic variables of US economy, the inflation rate and the 6-monthly treasury bills interest rates.

Keywords: Forecast , Fuzzy membership functions, Smoothingtransition, Time-series

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Authors: Mohamed Boulouird, Moha M'Rabet Hassani

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In this paper, many techniques for blind identification of moving average (MA) process are presented. These methods utilize third- and fourth-order cumulants of the noisy observations of the system output. The system is driven by an independent and identically distributed (i.i.d) non-Gaussian sequence that is not observed. Two nonlinear optimization algorithms, namely the Gradient Descent and the Gauss-Newton algorithms are exposed. An algorithm based on the joint-diagonalization of the fourth-order cumulant matrices (FOSI) is also considered, as well as an improved version of the classical C(q, 0, k) algorithm based on the choice of the Best 1-D Slice of fourth-order cumulants. To illustrate the effectiveness of our methods, various simulation examples are presented.

Keywords: Cumulants, Identification, MA models, Parameter estimation

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Authors: U. Rubins, Z. Marcinkevics, K.Volceka

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The cardiovascular system has become the most important subject of clinical research, particularly measurement of arterial blood flow. Therefore correct determination of arterial diameter is crucial. We propose a novel, semi-automatic method for artery lumen detection. The method is based on Gaussian probability function. Usability of our proposed method was assessed by analyzing ultrasound B-mode CFA video sequences acquired from eleven healthy volunteers. The correlation coefficient between the manual and semi-automatic measurement of arterial diameter was 0.996. Our proposed method for detecting artery boundary is novel and accurate enough for the measurement of artery diameter.

Keywords: Ultrasound, boundary detection, artery diameter, curve fitting.

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Authors: R. Fan, Q. Wan, H. Chen, Y.L. Liu, Y.P. Liu

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In the paper, a fast high-resolution range profile synthetic algorithm called orthogonal matching pursuit with sensing dictionary (OMP-SD) is proposed. It formulates the traditional HRRP synthetic to be a sparse approximation problem over redundant dictionary. As it employs a priori that the synthetic range profile (SRP) of targets are sparse, SRP can be accomplished even in presence of data lost. Besides, the computation complexity decreases from O(MNDK) flops for OMP to O(M(N + D)K) flops for OMP-SD by introducing sensing dictionary (SD). Simulation experiments illustrate its advantages both in additive white Gaussian noise (AWGN) and noiseless situation, respectively.

Keywords: GTD-based model, HRRP, orthogonal matching pursuit, sensing dictionary.

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Authors: Ε. Giovanis

Abstract:

In this paper we propose and examine an Adaptive Neuro-Fuzzy Inference System (ANFIS) in Smoothing Transition Autoregressive (STAR) modeling. Because STAR models follow fuzzy logic approach, in the non-linear part fuzzy rules can be incorporated or other training or computational methods can be applied as the error backpropagation algorithm instead to nonlinear squares. Furthermore, additional fuzzy membership functions can be examined, beside the logistic and exponential, like the triangle, Gaussian and Generalized Bell functions among others. We examine two macroeconomic variables of US economy, the inflation rate and the 6-monthly treasury bills interest rates.

Keywords: Forecasting, Neuro-Fuzzy, Smoothing transition, Time-series

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Authors: M. Tridi, N. Nacereddine, N. Oucief

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This paper describes a novel method for automatic estimation of the contours of weld defect in radiography images. Generally, the contour detection is the first operation which we apply in the visual recognition system. Our approach can be described as a region based maximum likelihood formulation of parametric deformable contours. This formulation provides robustness against the poor image quality, and allows simultaneous estimation of the contour parameters together with other parameters of the model. Implementation is performed by a deterministic iterative algorithm with minimal user intervention. Results testify for the very good performance of the approach especially in synthetic weld defect images.

Keywords: Contour, gaussian, likelihood, rayleigh.

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Authors: F. Esmaeilzadeh, Y. Fayazi, J. Fathikaljahi

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Gas hydrates form when a number of factors co-exist: free water, hydrocarbon gas, cold temperatures and high pressures are typical of the near mud-line conditions in a deepwater drilling operation. Subsequently, when drilling with water based muds, particularly on exploration wells, the risk of hydrate formation associated with a gas influx is high. The consequences of gas hydrate formation while drilling are severe, and as such, every effort should be made to ensure the risk of hydrate formation is either eliminated or significantly reduced. Thermodynamic inhibitors are used to reduce the free water content of a drilling mud, and thus suppress the hydrate formation temperature. Very little experimental work has been performed by oil and gas research companies on the evaluation of gas hydrate formation in a water-based drilling mud. The main objective of this paper is to investigate the experimental gas hydrate formation for a mixture of methane, carbon dioxide & nitrogen in a water-based drilling mud with or without presence of different concentrations of thermodynamic inhibitors including pure salt and a combination of salt with methanol or ethylene glycol at different concentrations in a static loop apparatus. The experiments were performed using a static loop apparatus consisting of a 2.4307 cm inside diameter and 800 cm long pipe. All experiments were conducted at 2200 psia. The temperature in the loop was decreased at a rate of 3.33 °F/h from initial temperature of 80 °F.

Keywords: Hydrate formation, thermodynamic inhibitor, waterbaseddrilling mud, salt, static loop apparatus.

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Authors: Khosrow Maleknejad, Asyieh Ebrahimzadeh

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In this paper, the numerical solution of optimal control problem (OCP) for systems governed by Volterra integro-differential (VID) equation is considered. The method is developed by means of the Legendre wavelet approximation and collocation method. The properties of Legendre wavelet together with Gaussian integration method are utilized to reduce the problem to the solution of nonlinear programming one. Some numerical examples are given to confirm the accuracy and ease of implementation of the method.

Keywords: Collocation method, Legendre wavelet, optimal control, Volterra integro-differential equation.

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Authors: M. Ghazikhani, M. R. Kalateh, Y. K. Toroghi, M. Dehnavi

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In this study, effects of EGR on CO and HC emissions of a dual fuel HCCI-DI engine are investigated. Tests were conducted on a single-cylinder variable compression ratio (VCR) diesel engine with compression ratio of 17.5. Premixed gasoline is provided by a carburetor connected to intake manifold and equipped with a screw to adjust premixed air-fuel ratio, and diesel fuel is injected directly into the cylinder through an injector at pressure of 250 bars. A heater placed at inlet manifold is used to control the intake charge temperature. Optimal intake charge temperature was 110-115ºC due to better formation of a homogeneous mixture causing HCCI combustion. Timing of diesel fuel injection has a great effect on stratification of in-cylinder charge in HCCI combustion. Experiments indicated 35 BTDC as the optimum injection timing. Coolant temperature was maintained 50ºC during the tests. Results show that increasing engine speed at a constant EGR rate leads to increase in CO and UHC emissions due to the incomplete combustion caused by shorter combustion duration and less homogeneous mixture. Results also show that increasing EGR reduces the amount of oxygen and leads to incomplete combustion and therefore increases CO emission due to lower combustion temperature. HC emission also increases as a result of lower combustion temperatures.

Keywords: Dual fuel HCCI engine, EGR, engine speed, CO andUHC emissions.

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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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Authors: T. M. Agbede, A. O. Adekiya

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Field experiments were conducted during 2013, 2014 and 2015 cropping seasons at Rufus Giwa Polytechnic, Owo, Ondo State, southwest Nigeria. The objective of the investigation was to determine the effect of Cocoa Pod Ash (CPA) and Poultry Manure (PM) applied solely and their combined form, as sources of fertilizers on soil properties, leaf nutrient composition, growth and yield of yam. Three soil amendments: CPA, PM (sole forms), CPA and PM (mixture), were applied at 20 t ha^-1 with an inorganic fertilizer (NPK 15-15-15) at 400 kg ha^-1 as a reference and a natural soil fertility, NSF (control). The five treatments were arranged in a randomized complete block design with three replications. The test soil was slightly acidic, low in organic carbon (OC), N, P, K, Ca and Mg. Results showed that soil amendments significantly increased (p = 0.05) tuber weights and growth of yam, soil and leaf N, P, K, Ca and Mg, soil pH and OC concentrations compared with the NSF (control). The mixture of CPA+PM treatment increased tuber weights of yam by 36%, compared with inorganic fertilizer (NPK) and 19%, compared with PM alone. Sole PM increased tuber weight of yam by 15%, compared with NPK. Sole or mixed forms of soil amendments showed remarkable improvement in soil physical properties, nutrient availability, compared with NPK and the NSF (control). Integrated application of CPA at 10 t ha^-1 + PM at 10 t ha^-1 was the most effective treatment in improving soil physical properties, increasing nutrient availability and yam performance than sole application of any of the fertilizer materials.

Keywords: Cocoa pod ash, leaf nutrient composition, poultry manure, soil properties, yam.

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Authors: Chi Kyu Ahn, Young Mi Kim, Seung Han Woo, Jong Moon Park

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Soil washing process with a surfactant solution is a potential technology for the rapid removal of hydrophobic organic compound (HOC) from soil. However, large amount of washed water would be produced during operation and this should be treated effectively by proper methods. The soil washed water for complex contaminated site with HOC and heavy metals might contain high amount of pollutants such as HOC and heavy metals as well as used surfactant. The heavy metals in the soil washed water have toxic effects on microbial activities thus these should be removed from the washed water before proceeding to a biological waste-water treatment system. Moreover, the used surfactant solutions are necessary to be recovered for reducing the soil washing operation cost. In order to simultaneously remove the heavy metals and HOC from soil-washed water, activated carbon (AC) was used in the present study. In an anionic-nonionic surfactant mixed solution, the Cd(II) and phenanthrene (PHE) were effectively removed by adsorption on activated carbon. The removal efficiency for Cd(II) was increased from 0.027 mmol-Cd/g-AC to 0.142 mmol-Cd/g-AC as the mole ratio of SDS increased in the presence of PHE. The adsorptive capacity of PHE was also increased according to the SDS mole ratio due to the decrement of molar solubilization ratios (MSR) for PHE in an anionic-nonionic surfactant mixture. The simultaneous adsorption of HOC and cationic heavy metals using activated carbon could be a useful method for surfactant recovery and the reduction of heavy metal toxicity in a surfactant-enhanced soil washing process.

Keywords: Activated carbon, Anionic-nonionic surfactant mixture, Cationic heavy metal, HOC, Soil washing

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Authors: S. Safi, A. Zeroual

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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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Authors: M. Mohamadi, M. Mostamand, M. Moosavi, M. Soltanolkotabi

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The output beam quality of multi transverse modes of laser, are relatively poor. In order to obtain better beam quality, one may use an aperture inside the laser resonator. In this case, various transverse modes can be selected. We have selected various transverse modes both by simulation and doing experiment. By inserting a circular aperture inside the diode end-pumped Nd:YAG pulsed laser resonator, we have obtained 00 TEM , 01 TEM , 20 TEM and have studied which parameters, can change the mode shape. Then, we have determined the beam quality factor of TEM00 gaussian mode.

Keywords: Beam shape, Transverse mode , Beam quality factor

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Authors: Aly Farag, Ayman El-Baz, Refaat Mohamed

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In this paper we present a novel approach for density estimation. The proposed approach is based on using the logistic regression model to get initial density estimation for the given empirical density. The empirical data does not exactly follow the logistic regression model, so, there will be a deviation between the empirical density and the density estimated using logistic regression model. This deviation may be positive and/or negative. In this paper we use a linear combination of Gaussian (LCG) with positive and negative components as a model for this deviation. Also, we will use the expectation maximization (EM) algorithm to estimate the parameters of LCG. Experiments on real images demonstrate the accuracy of our approach.

Keywords: Logistic regression model, Expectationmaximization, Segmentation.

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Authors: Reinhold Decker, Christian Holsing, Sascha Lerke

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This paper presents a new growing neural network for cluster analysis and market segmentation, which optimizes the size and structure of clusters by iteratively checking them for multivariate normality. We combine the recently published SGNN approach [8] with the basic principle underlying the Gaussian-means algorithm [13] and the Mardia test for multivariate normality [18, 19]. The new approach distinguishes from existing ones by its holistic design and its great autonomy regarding the clustering process as a whole. Its performance is demonstrated by means of synthetic 2D data and by real lifestyle survey data usable for market segmentation.

Keywords: Artificial neural network, clustering, multivariatenormality, market segmentation, self-organization

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Authors: Gela Gelashvili, David Gelenidze, Sulkhan Nanobashvili, Irakli Nanobashvili, George Tavkhelidze, Tsiuri Sitchinava

Abstract:

Development of new highly efficient plasma arc combustion system of pulverized coal is presented. As it is well-known, coal is one of the main energy carriers by means of which electric and heat energy is produced in thermal power stations. The quality of the extracted coal decreases very rapidly. Therefore, the difficulties associated with its firing and complete combustion arise and thermo-chemical preparation of pulverized coal becomes necessary. Usually, other organic fuels (mazut-fuel oil or natural gas) are added to low-quality coal for this purpose. The fraction of additional organic fuels varies within 35-40% range. This decreases dramatically the economic efficiency of such systems. At the same time, emission of noxious substances in the environment increases. Because of all these, intense development of plasma combustion systems of pulverized coal takes place in whole world. These systems are equipped with Non-Transferred Plasma Arc Torches. They allow practically complete combustion of pulverized coal (without organic additives) in boilers, increase of energetic and financial efficiency. At the same time, emission of noxious substances in the environment decreases dramatically. But, the non-transferred plasma torches have numerous drawbacks, e.g. complicated construction, low service life (especially in the case of high power), instability of plasma arc and most important – up to 30% of energy loss due to anode cooling. Due to these reasons, intense development of new plasma technologies that are free from these shortcomings takes place. In our proposed system, pulverized coal-air mixture passes through plasma arc area that burns between to carbon electrodes directly in pulverized coal muffler burner. Consumption of the carbon electrodes is low and does not need a cooling system, but the main advantage of this method is that radiation of plasma arc directly impacts on coal-air mixture that accelerates the process of thermo-chemical preparation of coal to burn. To ensure the stability of the plasma arc in such difficult conditions, we have developed a power source that provides fixed current during fluctuations in the arc resistance automatically compensated by the voltage change as well as regulation of plasma arc length over a wide range. Our combustion system where plasma arc acts directly on pulverized coal-air mixture is simple. This should allow a significant improvement of pulverized coal combustion (especially low-quality coal) and its economic efficiency. Preliminary experiments demonstrated the successful functioning of the system.

Keywords: Coal combustion, plasma arc, plasma torches, pulverized coal.

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Authors: Asadollah Boshra, Ahmad Seif, Mehran Aghaei

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A model of (4, 4) single-walled boron-nitride nanotube as a representative of armchair boron-nitride nanotubes studied. At first the structure optimization performed and then Nuclear Magnetic Resonance parameters (NMR) by Density Functional Theory (DFT) method at 11B and 15N nuclei calculated. Resulted parameters evaluation presents electrostatic environment heterogeneity along the nanotube and especially at the ends but the nuclei in a layer feel the same electrostatic environment. All of calculations carried out using Gaussian 98 Software package.

Keywords: Boron-nitride nanotube, Density Functional Theory, Nuclear Magnetic Resonance (NMR).

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Authors: Nidal F. Shilbayeh, Belal AbuHaija, Zainab N. Al-Qudsy

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In this paper, we propose a new robust and secure system that is based on the combination between two different transforms Discrete wavelet Transform (DWT) and Contourlet Transform (CT). The combined transforms will compensate the drawback of using each transform separately. The proposed algorithm has been designed, implemented and tested successfully. The experimental results showed that selecting the best sub-band for embedding from both transforms will improve the imperceptibility and robustness of the new combined algorithm. The evaluated imperceptibility of the combined DWT-CT algorithm which gave a PSNR value 88.11 and the combination DWT-CT algorithm improves robustness since it produced better robust against Gaussian noise attack. In addition to that, the implemented system shored a successful extraction method to extract watermark efficiently.

Keywords: DWT, CT, Digital Image Watermarking, Copyright Protection.

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Authors: Francis Chinweuba Eboh, Peter Ahlström, Tobias Richards

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Entropy, as an outcome of the second law of thermodynamics, measures the level of irreversibility associated with any process. The identification and reduction of irreversibility in the energy conversion process helps to improve the efficiency of the system. The entropy of pure substances known as absolute entropy is determined at an absolute reference point and is useful in the thermodynamic analysis of chemical reactions; however, municipal solid waste (MSW) is a structurally complicated material with unknown absolute entropy. In this work, an empirical model to calculate the absolute entropy of MSW based on the content of carbon, hydrogen, oxygen, nitrogen, sulphur, and chlorine on a dry ash free basis (daf) is presented. The proposed model was derived from 117 relevant organic substances which represent the main constituents in MSW with known standard entropies using statistical analysis. The substances were divided into different waste fractions; namely, food, wood/paper, textiles/rubber and plastics waste and the standard entropies of each waste fraction and for the complete mixture were calculated. The correlation of the standard entropy of the complete waste mixture derived was found to be s^o_msw= 0.0101C + 0.0630H + 0.0106O + 0.0108N + 0.0155S + 0.0084Cl (kJ.K^-1.kg) and the present correlation can be used for estimating the absolute entropy of MSW by using the elemental compositions of the fuel within the range of 10.3% ≤ C ≤ 95.1%, 0.0% ≤ H ≤ 14.3%, 0.0% ≤ O ≤ 71.1%, 0.0 ≤ N ≤ 66.7%, 0.0% ≤ S ≤ 42.1%, 0.0% ≤ Cl ≤ 89.7%. The model is also applicable for the efficient modelling of a combustion system in a waste-to-energy plant.

Keywords: Absolute entropy, irreversibility, municipal solid waste, waste-to-energy.

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Authors: Praveen Kumar, Nitin Kumar, Hemant Kumar

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The modernization of computer technology and commercial computational fluid dynamic (CFD) simulation has given better detailed results as compared to experimental investigation techniques. CFD techniques are widely used in different field due to its flexibility and performance. Evaluation of pipeline erosion is complex phenomenon to solve by numerical arithmetic technique, whereas CFD simulation is an easy tool to resolve that type of problem. Erosion wear behaviour due to solid–liquid mixture in the slurry pipeline has been investigated using commercial CFD code in FLUENT. Multi-phase Euler-Lagrange model was adopted to predict the solid particle erosion wear in 22.5° pipe bend for the flow of bottom ash-water suspension. The present study addresses erosion prediction in three dimensional 22.5° pipe bend for two-phase (solid and liquid) flow using finite volume method with standard k-ε turbulence, discrete phase model and evaluation of erosion wear rate with varying velocity 2-4 m/s. The result shows that velocity of solid-liquid mixture found to be highly dominating parameter as compared to solid concentration, density, and particle size. At low velocity, settling takes place in the pipe bend due to low inertia and gravitational effect on solid particulate which leads to high erosion at bottom side of pipeline.

Keywords: Computational fluid dynamics, erosion, slurry transportation, k-ε Model.

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Authors: Chee-Ming Chan

Abstract:

In spite of the advent of new materials, clay bricks remain, arguably, the most popular construction materials today. Nevertheless the low cost and versatility of clay bricks cannot always be associated with high environmental and sustainable values, especially in terms of raw material sources and manufacturing processes. At the same time, the worldwide agricultural footprint is fast growing, with vast agricultural land cultivation and active expansion of the agro-based industry. The resulting large quantities of agricultural wastes, unfortunately, are not always well managed or utilised. These wastes can be recycled, such as by retrieving fibres from disposed leaves and fruit bunches, and then incorporated in brick-making. This way the clay bricks are made a 'greener' building material and the discarded natural wastes can be reutilised, avoiding otherwise wasteful landfill and harmful open incineration. This study examined the physical and mechanical properties of clay bricks made by adding two natural fibres to a clay-water mixture, with baked and non-baked conditions. The fibres were sourced from pineapple leaves (PF) and oil palm fruit bunch (OF), and added within the range of 0.25-0.75 %. Cement was added as a binder to the mixture at 5-15 %. Although the two fibres had different effects on the bricks produced, cement appeared to dominate the compressive strength. The non-baked bricks disintegrated when submerged in water, while the baked ones displayed cement-dependent characteristics in water-absorption and density changes. Interestingly, further increase in fibre content did not cause significant density decrease in both the baked and non-baked bricks.

Keywords: natural fibres, clay bricks, strength, water absorption, density.

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Authors: Ml. López-Moreno, Le. Lugo Avilés, Fr. Román, J. Lugo Rosas, Ja. Hernández-Viezcas, Jr. Peralta-Videa, Jl. Gardea-Torresdey

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Degradation of agricultural soils has increased rapidly during the last 20 years due to the indiscriminate use of pesticides and other anthropogenic activities. Currently, there is an urgent need of soil restoration to increase agricultural production. Utilization of sewage sludge or municipal solid waste is an important way to recycle nutrient elements and improve soil quality. With these amendments, nutrient availability in the aqueous phase might be increased and production of healthier crops can be accomplished. This research project aimed to achieve sustainable management of tropical agricultural soils, specifically in Puerto Rico, through the amendment of water treatment plant sludge’s. This practice avoids landfill disposal of sewage sludge and at the same time results costeffective practice for recycling solid waste residues. Coriander sativum was cultivated in a compost-soil-sludge mixture at different proportions. Results showed that Coriander grown in a mixture of 25% compost+50% Voladora soi+25% sludge had the best growth and development. High chlorophyll content (33.01 ± 0.8) was observed in Coriander plants cultivated in 25% compost+62.5% Coloso soil+ 12.5% sludge compared to plants grown with no sludge (32.59 ± 0.7). ICP-OES analysis showed variations in mineral element contents (macro and micronutrients) in coriander plant grown I soil amended with sludge and compost.

Keywords: Compost, Coriandrum sativum, nutrients, waste sludge.

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Authors: Antonella Hadzich, Santiago Flores

Abstract:

Alkyds have become essential raw materials in the coating and paint industry, due to their low cost, good application properties and lower environmental impact in comparison with petroleum-based polymers. The properties of these oil-modified materials depend on the type of polyunsaturated vegetable oil used for its manufacturing, since a higher degree of unsaturation provides a better crosslinking of the cured paint. Linum usitatissimum L. (flax) oil is widely used to develop alkyd resins due to its high degree of unsaturation. Although it is intended to find non-traditional sources and increase their commercial value, to authors’ best knowledge a natural source that can replace flaxseed oil has not yet been found. However, Plukenetia volubilis L. oil, of Peruvian origin, contains a similar fatty acid polyunsaturated content to the one reported for Linum usitatissimum L. oil. In this perspective, medium alkyd resins were prepared with a mixture of 50% of Linum usitatissimum L. oil and 50% of Plukenetia volubilis L. oil. Pure Linum usitatissimum L. oil was also used for comparison purposes. Three different resins were obtained by varying the amount of glycerol and pentaerythritol. The synthesized alkyd resins were characterized by FT-IR, and physicochemical properties like acid value, colour, viscosity, density and drying time were evaluated by standard methods. The pencil hardness and chemical resistance behaviour of the cured resins were also studied. Overall, it can be concluded that medium alkyd resins containing Plukenetia volubilis L. oil have an equivalent behaviour compared to those prepared purely with Linum usitatissimum L. oil. Both Plukenetia volubilis L. oil and pentaerythritol have a remarkable influence on certain physicochemical properties of medium alkyd resins.

Keywords: Alkyd resins, flaxseed oil, pentaerythritol, Plukenetia volubilis L. oil, protective coating.

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Authors: Mohammad H. Fattahi

Abstract:

Chaotic analysis has been performed on the river flow time series before and after applying the wavelet based de-noising techniques in order to investigate the noise content effects on chaotic nature of flow series. In this study, 38 years of monthly runoff data of three gauging stations were used. Gauging stations were located in Ghar-e-Aghaj river basin, Fars province, Iran. Noise level of time series was estimated with the aid of Gaussian kernel algorithm. This step was found to be crucial in preventing removal of the vital data such as memory, correlation and trend from the time series in addition to the noise during de-noising process.

Keywords: Chaotic behavior, wavelet, noise reduction, river flow.

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Authors: Daniel Morariu, Lucian N. Vintan, Volker Tresp

Abstract:

Text categorization is the problem of classifying text documents into a set of predefined classes. After a preprocessing step, the documents are typically represented as large sparse vectors. When training classifiers on large collections of documents, both the time and memory restrictions can be quite prohibitive. This justifies the application of feature selection methods to reduce the dimensionality of the document-representation vector. In this paper, three feature selection methods are evaluated: Random Selection, Information Gain (IG) and Support Vector Machine feature selection (called SVM_FS). We show that the best results were obtained with SVM_FS method for a relatively small dimension of the feature vector. Also we present a novel method to better correlate SVM kernel-s parameters (Polynomial or Gaussian kernel).

Keywords: Feature Selection, Learning with Kernels, SupportVector Machine, and Classification.

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