Search results for: synthetic discriminant function
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 2424

Search results for: synthetic discriminant function

2364 A Utilitarian Approach to Modeling Information Flows in Social Networks

Authors: Usha Sridhar, Sridhar Mandyam

Abstract:

We propose a multi-agent based utilitarian approach to model and understand information flows in social networks that lead to Pareto optimal informational exchanges. We model the individual expected utility function of the agents to reflect the net value of information received. We show how this model, adapted from a theorem by Karl Borch dealing with an actuarial Risk Exchange concept in the Insurance industry, can be used for social network analysis. We develop a utilitarian framework that allows us to interpret Pareto optimal exchanges of value as potential information flows, while achieving a maximization of a sum of expected utilities of information of the group of agents. We examine some interesting conditions on the utility function under which the flows are optimal. We illustrate the promise of this new approach to attach economic value to information in networks with a synthetic example.

Keywords: Borch's Theorem , Economic value of information, Information Exchange, Pareto Optimal Solution, Social Networks, Utility Functions

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2363 New Features for Specific JPEG Steganalysis

Authors: Johann Barbier, Eric Filiol, Kichenakoumar Mayoura

Abstract:

We present in this paper a new approach for specific JPEG steganalysis and propose studying statistics of the compressed DCT coefficients. Traditionally, steganographic algorithms try to preserve statistics of the DCT and of the spatial domain, but they cannot preserve both and also control the alteration of the compressed data. We have noticed a deviation of the entropy of the compressed data after a first embedding. This deviation is greater when the image is a cover medium than when the image is a stego image. To observe this deviation, we pointed out new statistic features and combined them with the Multiple Embedding Method. This approach is motivated by the Avalanche Criterion of the JPEG lossless compression step. This criterion makes possible the design of detectors whose detection rates are independent of the payload. Finally, we designed a Fisher discriminant based classifier for well known steganographic algorithms, Outguess, F5 and Hide and Seek. The experiemental results we obtained show the efficiency of our classifier for these algorithms. Moreover, it is also designed to work with low embedding rates (< 10-5) and according to the avalanche criterion of RLE and Huffman compression step, its efficiency is independent of the quantity of hidden information.

Keywords: Compressed frequency domain, Fisher discriminant, specific JPEG steganalysis.

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2362 Ablation, Mechanical and Thermal Properties of Fiber/Phenolic Matrix Composites

Authors: N. Winya, S. Chankapoe, C. Kiriratnikom

Abstract:

In this study, an ablation, mechanical and thermal properties of a rocket motor insulation from phenolic/ fiber matrix composites forming a laminate with different fiber between fiberglass and locally available synthetic fibers. The phenolic/ fiber matrix composites was mechanics and thermal properties by means of tensile strength, ablation, TGA and DSC. The design of thermal insulation involves several factors.Determined the mechanical properties according to MIL-I-24768: Density >1.3 g/cm3, Tensile strength >103 MPa and Ablation <0.14 mm/s to optimization formulation of phenolic binder, fiber glass reinforcement and other ingredients were conducted after that the insulation prototype was formed and cured. It was found that the density of phenolic/fiberglass composites and phenolic/ synthetic fiber composite was 1.66 and 1.41 g/cm3 respectively. The ablative of phenolic/fiberglass composites and phenolic/ synthetic fiber composite was 0.13 and 0.06 mm/s respectively.

Keywords: Phenolic Resin, Ablation, Rocket Motor, Insulation

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2361 Multinomial Dirichlet Gaussian Process Model for Classification of Multidimensional Data

Authors: Wanhyun Cho, Soonja Kang, Sangkyoon Kim, Soonyoung Park

Abstract:

We present probabilistic multinomial Dirichlet classification model for multidimensional data and Gaussian process priors. Here, we have considered efficient computational method that can be used to obtain the approximate posteriors for latent variables and parameters needed to define the multiclass Gaussian process classification model. We first investigated the process of inducing a posterior distribution for various parameters and latent function by using the variational Bayesian approximations and important sampling method, and next we derived a predictive distribution of latent function needed to classify new samples. The proposed model is applied to classify the synthetic multivariate dataset in order to verify the performance of our model. Experiment result shows that our model is more accurate than the other approximation methods.

Keywords: Multinomial dirichlet classification model, Gaussian process priors, variational Bayesian approximation, Importance sampling, approximate posterior distribution, Marginal likelihood evidence.

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2360 Attribute Analysis of Quick Response Code Payment Users Using Discriminant Non-negative Matrix Factorization

Authors: Hironori Karachi, Haruka Yamashita

Abstract:

Recently, the system of quick response (QR) code is getting popular. Many companies introduce new QR code payment services and the services are competing with each other to increase the number of users. For increasing the number of users, we should grasp the difference of feature of the demographic information, usage information, and value of users between services. In this study, we conduct an analysis of real-world data provided by Nomura Research Institute including the demographic data of users and information of users’ usages of two services; LINE Pay, and PayPay. For analyzing such data and interpret the feature of them, Nonnegative Matrix Factorization (NMF) is widely used; however, in case of the target data, there is a problem of the missing data. EM-algorithm NMF (EMNMF) to complete unknown values for understanding the feature of the given data presented by matrix shape. Moreover, for comparing the result of the NMF analysis of two matrices, there is Discriminant NMF (DNMF) shows the difference of users features between two matrices. In this study, we combine EMNMF and DNMF and also analyze the target data. As the interpretation, we show the difference of the features of users between LINE Pay and Paypay.

Keywords: Data science, non-negative matrix factorization, missing data, quality of services.

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2359 The Core and Shapley Function for Games on Augmenting Systems with a Coalition Structure

Authors: Fan-Yong Meng

Abstract:

In this paper, we first introduce the model of games on augmenting systems with a coalition structure, which can be seen as an extension of games on augmenting systems. The core of games on augmenting systems with a coalition structure is defined, and an equivalent form is discussed. Meantime, the Shapley function for this type of games is given, and two axiomatic systems of the given Shapley function are researched. When the given games are quasi convex, the relationship between the core and the Shapley function is discussed, which does coincide as in classical case. Finally, a numerical example is given.

Keywords: Cooperative game, augmenting system, Shapley function, core.

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2358 The Effect of Ethylene Glycol to Soy Polyurethane Foam Classifications

Authors: Flora Elvistia Firdaus

Abstract:

Soy polyol obtained from hydroxylation of soy epoxide with ethylene glycol were prepared as pre-polyurethane. The two step process method were applied in the polyurethane synthesis. The blending of soy polyol with synthetic polyol then simultaneously carried out to TDI (2,4): MDI (4,4-) (80:20), blowing agent, and surfactant. Ethylene glycol were not taking part in the polyurethane synthesis. The inclusion of ethylene glycol were used as a control. Characterization of polyurethane foam through impact resillience, indentation deflection, and density can visualize the polyurethane classifications.

Keywords: Ethylene glycol, polyurethane foam, soy polyol, synthetic polyol

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2357 Selective Separation of Lead and Mercury Ions from Synthetic Produced Water via a Hollow Fiber Supported Liquid Membrane

Authors: S. Suren, U. Pancharoen

Abstract:

A double module hollow fiber supported liquid membrane (HFSLM) was applied to selectively separate lead and mercury ions from dilute synthetic produced water. The experiments were investigated on several variables: types of extractants (D2EHPA, Cyanex 471, Aliquat 336, and TOA), concentration of the selected extractant and operating time. The results clearly showed that the double module HFSLM could selectively separate Pb(II) and Hg(II) in feed solution at a very low concentration to less than the regulatory discharge limit of 0.2 and 0.005 mg/L issued by the Ministry of Industry and the Ministry of Natural Resource Environment, Thailand. The highest extractions of lead and mercury ions from synthetic produced water were 96% and 100% using 0.03 M D2EHPA and 0.06 M Aliquat 336 as the extractant for the first and second modules.

Keywords: Hollow fiber, Lead ions, Liquid membrane, Mercury ions, Selective separation

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2356 Kalman-s Shrinkage for Wavelet-Based Despeckling of SAR Images

Authors: Mario Mastriani, Alberto E. Giraldez

Abstract:

In this paper, a new probability density function (pdf) is proposed to model the statistics of wavelet coefficients, and a simple Kalman-s filter is derived from the new pdf using Bayesian estimation theory. Specifically, we decompose the speckled image into wavelet subbands, we apply the Kalman-s filter to the high subbands, and reconstruct a despeckled image from the modified detail coefficients. Experimental results demonstrate that our method compares favorably to several other despeckling methods on test synthetic aperture radar (SAR) images.

Keywords: Kalman's filter, shrinkage, speckle, wavelets.

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2355 Calculation of Wave Function at the Origin (WFO) for the Ground State of Doubly Heavy Mesons Based On the Variational Method

Authors: Maryam Momeni Feili, Mahvash Zandy Navgaran

Abstract:

The wave function at the origin is an important quantity in studying many physical problems concerning heavy quarkonia. This is because that it is using for calculating spin state hyperfine splitting and also crucial to evaluating the production and decay amplitude of the heavy quarkonium. In this paper, we present the variational method by using the single-parameter wave function to estimate the WFO for the ground state of heavy mesons.

Keywords: Wave function at the origin, heavy mesons, bound states, variational method, non-relativistic quark model, potential model, trial wave function.

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2354 Predictive Analytics of Student Performance Determinants in Education

Authors: Mahtab Davari, Charles Edward Okon, Somayeh Aghanavesi

Abstract:

Every institute of learning is usually interested in the performance of enrolled students. The level of these performances determines the approach an institute of study may adopt in rendering academic services. The focus of this paper is to evaluate students' academic performance in given courses of study using machine learning methods. This study evaluated various supervised machine learning classification algorithms such as Logistic Regression (LR), Support Vector Machine (SVM), Random Forest, Decision Tree, K-Nearest Neighbors, Linear Discriminant Analysis (LDA), and Quadratic Discriminant Analysis, using selected features to predict study performance. The accuracy, precision, recall, and F1 score obtained from a 5-Fold Cross-Validation were used to determine the best classification algorithm to predict students’ performances. SVM (using a linear kernel), LDA, and LR were identified as the best-performing machine learning methods. Also, using the LR model, this study identified students' educational habits such as reading and paying attention in class as strong determinants for a student to have an above-average performance. Other important features include the academic history of the student and work. Demographic factors such as age, gender, high school graduation, etc., had no significant effect on a student's performance.

Keywords: Student performance, supervised machine learning, prediction, classification, cross-validation.

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2353 A Generalized Sparse Bayesian Learning Algorithm for Near-Field Synthetic Aperture Radar Imaging: By Exploiting Impropriety and Noncircularity

Authors: Pan Long, Bi Dongjie, Li Xifeng, Xie Yongle

Abstract:

The near-field synthetic aperture radar (SAR) imaging is an advanced nondestructive testing and evaluation (NDT&E) technique. This paper investigates the complex-valued signal processing related to the near-field SAR imaging system, where the measurement data turns out to be noncircular and improper, meaning that the complex-valued data is correlated to its complex conjugate. Furthermore, we discover that the degree of impropriety of the measurement data and that of the target image can be highly correlated in near-field SAR imaging. Based on these observations, A modified generalized sparse Bayesian learning algorithm is proposed, taking impropriety and noncircularity into account. Numerical results show that the proposed algorithm provides performance gain, with the help of noncircular assumption on the signals.

Keywords: Complex-valued signal processing, synthetic aperture radar (SAR), 2-D radar imaging, compressive sensing, Sparse Bayesian learning.

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2352 A Transfer Function Representation of Thermo-Acoustic Dynamics for Combustors

Authors: Myunggon Yoon, Jung-Ho Moon

Abstract:

In this paper, we present a transfer function representation of a general one-dimensional combustor. The input of the transfer function is a heat rate perturbation of a burner and the output is a flow velocity perturbation at the burner. This paper considers a general combustor model composed of multiple cans with different cross sectional areas, along with a non-zero flow rate.

Keywords: Thermoacoustics, dynamics, combustor, transfer function.

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2351 Self-Healing Performance of Heavyweight Concrete with Steam Curing

Authors: Hideki Igawa, Yoshinori Kitsutaka, Takashi Yokomuro, Hideo Eguchi

Abstract:

In this study, the crack self-healing performance of the heavyweight concrete used in the walls of containers and structures designed to shield radioactive materials was investigated. A steam curing temperature that preserves self-healing properties and demolding strength was identified. The presented simultaneously mixing method using the expanding material and the fly ash in the process of admixture can maximize the self-curing performance. Also adding synthetic fibers in the heavyweight concrete improved the self-healing performance.

Keywords: Expanding material, heavyweight concrete, self-healing performance, synthetic fiber.

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2350 Predicting Protein Function using Decision Tree

Authors: Manpreet Singh, Parminder Kaur Wadhwa, Surinder Kaur

Abstract:

The drug discovery process starts with protein identification because proteins are responsible for many functions required for maintenance of life. Protein identification further needs determination of protein function. Proposed method develops a classifier for human protein function prediction. The model uses decision tree for classification process. The protein function is predicted on the basis of matched sequence derived features per each protein function. The research work includes the development of a tool which determines sequence derived features by analyzing different parameters. The other sequence derived features are determined using various web based tools.

Keywords: Sequence Derived Features, decision tree.

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2349 Assessing the Function of Light and Colorin Architectural View

Authors: Gholam Hossein Naseri, Manucher Tamizi

Abstract:

Light is one of the most important qualitative and symbolic factors and has a special position in architecture and urban development in regard to practical function. The main function of light, either natural or artificial, is lighting up the environment and the constructional forms which is called lighting. However, light is used to redefine the urban spaces by architectural genius with regard to three aesthetic, conceptual and symbolic factors. In architecture and urban development, light has a function beyond lighting up the environment, and the designers consider it as one of the basic components. The present research aims at studying the function of light and color in architectural view and their effects in buildings.

Keywords: Architectural View , Color , Light

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2348 Electricity Generation from Renewables and Targets: An Application of Multivariate Statistical Techniques

Authors: Filiz Ersoz, Taner Ersoz, Tugrul Bayraktar

Abstract:

Renewable energy is referred to as "clean energy" and common popular support for the use of renewable energy (RE) is to provide electricity with zero carbon dioxide emissions. This study provides useful insight into the European Union (EU) RE, especially, into electricity generation obtained from renewables, and their targets. The objective of this study is to identify groups of European countries, using multivariate statistical analysis and selected indicators. The hierarchical clustering method is used to decide the number of clusters for EU countries. The conducted statistical hierarchical cluster analysis is based on the Ward’s clustering method and squared Euclidean distances. Hierarchical cluster analysis identified eight distinct clusters of European countries. Then, non-hierarchical clustering (k-means) method was applied. Discriminant analysis was used to determine the validity of the results with data normalized by Z score transformation. To explore the relationship between the selected indicators, correlation coefficients were computed. The results of the study reveal the current situation of RE in European Union Member States.

Keywords: Share of electricity generation, CO2 emission, targets, multivariate methods, hierarchical clustering, K-means clustering, discriminant analyzed, correlation, EU member countries.

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2347 Particle Swarm Optimization and Quantum Particle Swarm Optimization to Multidimensional Function Approximation

Authors: Diogo Silva, Fadul Rodor, Carlos Moraes

Abstract:

This work compares the results of multidimensional function approximation using two algorithms: the classical Particle Swarm Optimization (PSO) and the Quantum Particle Swarm Optimization (QPSO). These algorithms were both tested on three functions - The Rosenbrock, the Rastrigin, and the sphere functions - with different characteristics by increasing their number of dimensions. As a result, this study shows that the higher the function space, i.e. the larger the function dimension, the more evident the advantages of using the QPSO method compared to the PSO method in terms of performance and number of necessary iterations to reach the stop criterion.

Keywords: PSO, QPSO, function approximation, AI, optimization, multidimensional functions.

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2346 Synthesis and Characterization of ZnO and Fe3O4 Nanocrystals from Oleat-based Organometallic Compounds

Authors: PoiSim Khiew, WeeSiong Chiu, ThianKhoonTan, Shahidan Radiman, Roslan Abd-Shukor, Muhammad Azmi Abd-Hamid, ChinHua Chia

Abstract:

Magnetic and semiconductor nanomaterials exhibit novel magnetic and optical properties owing to their unique size and shape-dependent effects. With shrinking the size down to nanoscale region, various anomalous properties that normally not present in bulk start to dominate. Ability in harnessing of these anomalous properties for the design of various advance electronic devices is strictly dependent on synthetic strategies. Hence, current research has focused on developing a rational synthetic control to produce high quality nanocrystals by using organometallic approach to tune both size and shape of the nanomaterials. In order to elucidate the growth mechanism, transmission electron microscopy was employed as a powerful tool in performing real time-resolved morphologies and structural characterization of magnetic (Fe3O4) and semiconductor (ZnO) nanocrystals. The current synthetic approach is found able to produce nanostructures with well-defined shapes. We have found that oleic acid is an effective capping ligand in preparing oxide-based nanostructures without any agglomerations, even at high temperature. The oleate-based precursors and capping ligands are fatty acid compounds, which are respectively originated from natural palm oil with low toxicity. In comparison with other synthetic approaches in producing nanostructures, current synthetic method offers an effective route to produce oxide-based nanomaterials with well-defined shapes and good monodispersity. The nanocystals are well-separated with each other without any stacking effect. In addition, the as-synthesized nanopellets are stable in terms of chemically and physically if compared to those nanomaterials that are previous reported. Further development and extension of current synthetic strategy are being pursued to combine both of these materials into nanocomposite form that will be used as “smart magnetic nanophotocatalyst" for industry waste water treatment.

Keywords: Metal oxide nanomaterials, Nanophotocatalyst, Organometallic synthesis, Morphology Control

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2345 Statistical Approach to Basis Function Truncation in Digital Interpolation Filters

Authors: F. Castillo, J. Arellano, S. Sánchez

Abstract:

In this paper an alternative analysis in the time domain is described and the results of the interpolation process are presented by means of functions that are based on the rule of conditional mathematical expectation and the covariance function. A comparison between the interpolation error caused by low order filters and the classic sinc(t) truncated function is also presented. When fewer samples are used, low-order filters have less error. If the number of samples increases, the sinc(t) type functions are a better alternative. Generally speaking there is an optimal filter for each input signal which depends on the filter length and covariance function of the signal. A novel scheme of work for adaptive interpolation filters is also presented.

Keywords: Interpolation, basis function, over-sampling.

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2344 A Case Study to Assess the Validity of Function Points

Authors: Neelam Bawane nee' Singhal, C. V. Srikrishna

Abstract:

Many metrics were proposed to evaluate the characteristics of the analysis and design model of a given product which in turn help to assess the quality of the product. Function point metric is a measure of the 'functionality' delivery by the software. This paper presents an analysis of a set of programs of a project developed in Cµ through Function Points metric. Function points are measured for a Data Flow Diagram (DFD) of the case developed at initial stage. Lines of Codes (LOCs) and possible errors are calculated with the help of measured Function Points (FPs). The calculations are performed using suitable established functions. Calculated LOCs and errors are compared with actual LOCs and errors found at the time of analysis & design review, implementation and testing. It has been observed that actual found errors are more than calculated errors. On the basis of analysis and observations, authors conclude that function point provides useful insight and helps to analyze the drawbacks in the development process.

Keywords: Function Points, Data Flow Diagram, Lines ofCodes.

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2343 Characteristic Function in Estimation of Probability Distribution Moments

Authors: Vladimir S. Timofeev

Abstract:

In this article the problem of distributional moments estimation is considered. The new approach of moments estimation based on usage of the characteristic function is proposed. By statistical simulation technique author shows that new approach has some robust properties. For calculation of the derivatives of characteristic function there is used numerical differentiation. Obtained results confirmed that author’s idea has a certain working efficiency and it can be recommended for any statistical applications.

Keywords: Characteristic function, distributional moments, robustness, outlier, statistical estimation problem, statistical simulation.

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2342 Cash Flow Optimization on Synthetic CDOs

Authors: Timothée Bligny, Clément Codron, Antoine Estruch, Nicolas Girodet, Clément Ginet

Abstract:

Collateralized Debt Obligations are not as widely used nowadays as they were before 2007 Subprime crisis. Nonetheless there remains an enthralling challenge to optimize cash flows associated with synthetic CDOs. A Gaussian-based model is used here in which default correlation and unconditional probabilities of default are highlighted. Then numerous simulations are performed based on this model for different scenarios in order to evaluate the associated cash flows given a specific number of defaults at different periods of time. Cash flows are not solely calculated on a single bought or sold tranche but rather on a combination of bought and sold tranches. With some assumptions, the simplex algorithm gives a way to find the maximum cash flow according to correlation of defaults and maturities. The used Gaussian model is not realistic in crisis situations. Besides present system does not handle buying or selling a portion of a tranche but only the whole tranche. However the work provides the investor with relevant elements on how to know what and when to buy and sell.

Keywords: Synthetic Collateralized Debt Obligation (CDO), Credit Default Swap (CDS), Cash Flow Optimization, Probability of Default, Default Correlation, Strategies, Simulation, Simplex.

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2341 Sophorolipids Production by Candida Bombicola using Synthetic Dairy Wastewater

Authors: A. Daverey, K. Pakshirajan, P. Sangeetha

Abstract:

Sophorolipids (SLs) production by the yeast Candida bombicola was studied in batch shake flasks using synthetic dairy wastewaters (SDWW) with or without any added external carbon and nitrogen sources. A maximum SLs production of 38.76 g/l was observed with the SDWW supplemented with low cost substrate of sugarcane molasses at 50 g/l and soybean oil at 50 g/l. When the SDWW was supplemented with more costly glucose, yeast extract, urea and soybean oil, the production, however, got lowered to only 29.49 g/l, but with a maximum biomass production of 17.38 g/l together with a complete utilization of the carbon sources.

Keywords: Candida bombicola, dairy wastewater, fat and oil, sophorolipids.

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2340 Subclasses of Bi-Univalent Functions Associated with Hohlov Operator

Authors: Rashidah Omar, Suzeini Abdul Halim, Aini Janteng

Abstract:

The coefficients estimate problem for Taylor-Maclaurin series is still an open problem especially for a function in the subclass of bi-univalent functions. A function f ϵ A is said to be bi-univalent in the open unit disk D if both f and f-1 are univalent in D. The symbol A denotes the class of all analytic functions f in D and it is normalized by the conditions f(0) = f’(0) – 1=0. The class of bi-univalent is denoted by  The subordination concept is used in determining second and third Taylor-Maclaurin coefficients. The upper bound for second and third coefficients is estimated for functions in the subclasses of bi-univalent functions which are subordinated to the function φ. An analytic function f is subordinate to an analytic function g if there is an analytic function w defined on D with w(0) = 0 and |w(z)| < 1 satisfying f(z) = g[w(z)]. In this paper, two subclasses of bi-univalent functions associated with Hohlov operator are introduced. The bound for second and third coefficients of functions in these subclasses is determined using subordination. The findings would generalize the previous related works of several earlier authors.

Keywords: Analytic functions, bi-univalent functions, Hohlov operator, subordination.

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2339 Compressive Properties of a Synthetic Bone Substitute for Vertebral Cancellous Bone

Authors: H. N. Mehmanparast, J.M. Mac-Thiong., Y. Petit

Abstract:

Transpedicular screw fixation in spinal fractures, degenerative changes, or deformities is a well-established procedure. However, important rate of fixation failure due to screw bending, loosening, or pullout are still reported particularly in weak bone stock in osteoporosis. To overcome the problem, mechanism of failure has to be fully investigated in vitro. Post-mortem human subjects are less accessible and animal cadavers comprise limitations due to different geometry and mechanical properties. Therefore, the development of a synthetic model mimicking the realistic human vertebra is highly demanded. A bone surrogate, composed of Polyurethane (PU) foam analogous to cancellous bone porous structure, was tested for 3 different densities in this study. The mechanical properties were investigated under uniaxial compression test by minimizing the end artifacts on specimens. The results indicated that PU foam of 0.32 g.cm-3 density has comparable mechanical properties to human cancellous bone in terms of young-s modulus and yield strength. Therefore, the obtained information can be considered as primary step for developing a realistic cancellous bone of human vertebral body. Further evaluations are also recommended for other density groups.

Keywords: Cancellous bone, Pedicle screw, Polyurethane foam, Synthetic bone

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2338 Synthetic Aperture Radar Remote Sensing Classification Using the Bag of Visual Words Model to Land Cover Studies

Authors: Reza Mohammadi, Mahmod R. Sahebi, Mehrnoosh Omati, Milad Vahidi

Abstract:

Classification of high resolution polarimetric Synthetic Aperture Radar (PolSAR) images plays an important role in land cover and land use management. Recently, classification algorithms based on Bag of Visual Words (BOVW) model have attracted significant interest among scholars and researchers in and out of the field of remote sensing. In this paper, BOVW model with pixel based low-level features has been implemented to classify a subset of San Francisco bay PolSAR image, acquired by RADARSAR 2 in C-band. We have used segment-based decision-making strategy and compared the result with the result of traditional Support Vector Machine (SVM) classifier. 90.95% overall accuracy of the classification with the proposed algorithm has shown that the proposed algorithm is comparable with the state-of-the-art methods. In addition to increase in the classification accuracy, the proposed method has decreased undesirable speckle effect of SAR images.

Keywords: Bag of Visual Words, classification, feature extraction, land cover management, Polarimetric Synthetic Aperture Radar.

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2337 Explicit Chain Homotopic Function to Compute Hochschild Homology of the Polynomial Algebra

Authors: Z. Altawallbeh

Abstract:

In this paper, an explicit homotopic function is constructed to compute the Hochschild homology of a finite dimensional free k-module V. Because the polynomial algebra is of course fundamental in the computation of the Hochschild homology HH and the cyclic homology CH of commutative algebras, we concentrate our work to compute HH of the polynomial algebra, by providing certain homotopic function.

Keywords: Exterior algebra, free resolution, free and projective modules, Hochschild homology, homotopic function, symmetric algebra.

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2336 Some Solitary Wave Solutions of Generalized Pochhammer-Chree Equation via Exp-function Method

Authors: Kourosh Parand, Jamal Amani Rad

Abstract:

In this paper, Exp-function method is used for some exact solitary solutions of the generalized Pochhammer-Chree equation. It has been shown that the Exp-function method, with the help of symbolic computation, provides a very effective and powerful mathematical tool for solving nonlinear partial differential equations. As a result, some exact solitary solutions are obtained. It is shown that the Exp-function method is direct, effective, succinct and can be used for many other nonlinear partial differential equations.

Keywords: Exp-function method, generalized Pochhammer- Chree equation, solitary wave solution, ODE's.

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2335 Comparative Studies on Interactions of Synthetic and Natural Compounds with Hen Egg-White Lysozyme

Authors: Seifollah Bahramikia

Abstract:

Amyloid aggregation of polypeptides is related to a growing number of pathologic states known as amyloid disorders. In recent years, blocking or reversing amyloid aggregation via the use of small compounds are considered as two useful approaches in hampering the development of these diseases. In this research, we have compared the ability of several manganese-salen derivatives, as synthetic compounds, and apigenin, as a natural flavonoid, to inhibit of hen egg-white lysozyme (HEWL) aggregation, as an in vitro model system. Different spectroscopic analyses such as Thioflavin T (ThT) and Anilinonaphthalene-8-sulfonic acid (ANS) fluorescence, Congo red (CR) absorbance along with transmission electron microscopy were used in this work to monitor the HEWL aggregation kinetic and inhibition. Our results demonstrated that both type of compounds were capable to prevent the formation of lysozyme amyloid aggregation in vitro. In addition, our data indicated that synthetic compounds had higher activity to inhibit of the β-sheet structures relative to natural compound. Regarding the higher antioxidant activities of the salen derivatives, it can be concluded that in addition to aromatic rings of each of the compounds, the potent antioxidant properties of salen derivatives contributes to lower lysozyme fibril accumulation.

Keywords: Aggregation, anti-amyloidogenic, apigenin, hen egg white lysozyme, salen derivatives.

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