Search results for: modified discretecosine transformation (MDCT).
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1509

Search results for: modified discretecosine transformation (MDCT).

969 An Improved Algorithm of SPIHT based on the Human Visual Characteristics

Authors: Meng Wang, Qi-rui Han

Abstract:

Because of excellent properties, people has paid more attention to SPIHI algorithm, which is based on the traditional wavelet transformation theory, but it also has its shortcomings. Combined the progress in the present wavelet domain and the human's visual characteristics, we propose an improved algorithm based on human visual characteristics of SPIHT in the base of analysis of SPIHI algorithm. The experiment indicated that the coding speed and quality has been enhanced well compared to the original SPIHT algorithm, moreover improved the quality of the transmission cut off.

Keywords: Lifted wavelet transform, SPIHT, Human Visual Characteristics.

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968 Efficient Preparation and Characterization of Carbohydrate Based Monomers. D-mannose Derivatives

Authors: L. M. Stefan, A. M. Pana, M. Silion, M. Balan, G. Bandur, L. M. Rusnac

Abstract:

The field of polymeric biomaterials is very important from the socio-economical viewpoint. Synthetic carbohydrate polymers are being increasingly investigated as biodegradable, biocompatible and biorenewable materials. The aim of this study was to synthesize and characterize some derivatives based on D-mannose. D-mannose was chemically modified to obtain 1-O-allyl-2,3:5,6-di- O-isopropylidene-D-mannofuranose and 1-O-(2-,3--epoxy-propyl)- 2,3:5,6-di-O-isopropylidene-D-mannofuranose. The chemical structure of the resulting compounds was characterized by FT-IR and NMR spectroscopy, and by HPLC-MS.

Keywords: D-mannose, biopolymers , spectroscopy, synthesis.

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967 A New Approach to Optimal Control Problem Constrained by Canonical Form

Authors: B. Farhadinia

Abstract:

In this article, it is considered a class of optimal control problems constrained by differential and integral constraints are called canonical form. A modified measure theoretical approach is introduced to solve this class of optimal control problems.

Keywords: control problem, Canonical form, Measure theory.

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966 Analysis of Short Bearing in Turbulent Regime Considering Micropolar Lubrication

Authors: S. S. Gautam, S. Samanta

Abstract:

The aim of the paper work is to investigate and predict the static performance of journal bearing in turbulent flow condition considering micropolar lubrication. The Reynolds equation has been modified considering turbulent micropolar lubrication and is solved for steady state operations. The Constantinescu-s turbulence model is adopted using the coefficients. The analysis has been done for a parallel and inertia less flow. Load capacity and friction factor have been evaluated for various operating parameters.

Keywords: hydrodynamic bearing, micropolar lubrication, coupling number, characteristic length, perturbation analysis

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965 An Improved Preprocessing for Biosonar Target Classification

Authors: Turgay Temel, John Hallam

Abstract:

An improved processing description to be employed in biosonar signal processing in a cochlea model is proposed and examined. It is compared to conventional models using a modified discrimination analysis and both are tested. Their performances are evaluated with echo data captured from natural targets (trees).Results indicate that the phase characteristics of low-pass filters employed in the echo processing have a significant effect on class separability for this data.

Keywords: Cochlea model, discriminant analysis, neurospikecoding, classification.

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964 Statistical Modeling of Constituents in Ash Evolved From Pulverized Coal Combustion

Authors: Esam Jassim

Abstract:

Industries using conventional fossil fuels have an  interest in better understanding the mechanism of particulate  formation during combustion since such is responsible for emission  of undesired inorganic elements that directly impact the atmospheric  pollution level. Fine and ultrafine particulates have tendency to  escape the flue gas cleaning devices to the atmosphere. They also  preferentially collect on surfaces in power systems resulting in  ascending in corrosion inclination, descending in the heat transfer  thermal unit, and severe impact on human health. This adverseness  manifests particularly in the regions of world where coal is the  dominated source of energy for consumption.  This study highlights the behavior of calcium transformation as  mineral grains verses organically associated inorganic components  during pulverized coal combustion. The influence of existing type of  calcium on the coarse, fine and ultrafine mode formation mechanisms  is also presented. The impact of two sub-bituminous coals on particle  size and calcium composition evolution during combustion is to be  assessed. Three mixed blends named Blends 1, 2, and 3 are selected  according to the ration of coal A to coal B by weight. Calcium  percentage in original coal increases as going from Blend 1 to 3.  A mathematical model and a new approach of describing  constituent distribution are proposed. Analysis of experiments of  calcium distribution in ash is also modeled using Poisson distribution.  A novel parameter, called elemental index λ, is introduced as a  measuring factor of element distribution.  Results show that calcium in ash that originally in coal as mineral  grains has index of 17, whereas organically associated calcium  transformed to fly ash shown to be best described when elemental  index λ is 7.  As an alkaline-earth element, calcium is considered the  fundamental element responsible for boiler deficiency since it is the  major player in the mechanism of ash slagging process. The  mechanism of particle size distribution and mineral species of ash  particles are presented using CCSEM and size-segregated ash  characteristics. Conclusions are drawn from the analysis of  pulverized coal ash generated from a utility-scale boiler.

 

Keywords: Calcium transformation, Coal Combustion, Inorganic Element, Poisson distribution.

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963 Data Preprocessing for Supervised Leaning

Authors: S. B. Kotsiantis, D. Kanellopoulos, P. E. Pintelas

Abstract:

Many factors affect the success of Machine Learning (ML) on a given task. The representation and quality of the instance data is first and foremost. If there is much irrelevant and redundant information present or noisy and unreliable data, then knowledge discovery during the training phase is more difficult. It is well known that data preparation and filtering steps take considerable amount of processing time in ML problems. Data pre-processing includes data cleaning, normalization, transformation, feature extraction and selection, etc. The product of data pre-processing is the final training set. It would be nice if a single sequence of data pre-processing algorithms had the best performance for each data set but this is not happened. Thus, we present the most well know algorithms for each step of data pre-processing so that one achieves the best performance for their data set.

Keywords: Data mining, feature selection, data cleaning.

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962 Gas Sensing Properties of SnO2 Thin Films Modified by Ag Nanoclusters Synthesized by SILD Method

Authors: G. Korotcenkov, B. K. Cho, L. B. Gulina, V. P. Tolstoy

Abstract:

The effect of SnO2 surface modification by Ag nanoclusters, synthesized by SILD method, on the operating characteristics of thin film gas sensors was studied and models for the promotional role of Ag additives were discussed. It was found that mentioned above approach can be used for improvement both the sensitivity and the rate of response of the SnO2-based gas sensors to CO and H2. At the same time, the presence of the Ag clusters on the surface of SnO2 depressed the sensor response to ozone.

Keywords: Ag nanoparticles, deposition, characterization, gas sensors, optimization.

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961 Modified Levenberg-Marquardt Method for Neural Networks Training

Authors: Amir Abolfazl Suratgar, Mohammad Bagher Tavakoli, Abbas Hoseinabadi

Abstract:

In this paper a modification on Levenberg-Marquardt algorithm for MLP neural network learning is proposed. The proposed algorithm has good convergence. This method reduces the amount of oscillation in learning procedure. An example is given to show usefulness of this method. Finally a simulation verifies the results of proposed method.

Keywords: Levenberg-Marquardt, modification, neural network, variable learning rate.

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960 2-D Realization of WiMAX Channel Interleaver for Efficient Hardware Implementation

Authors: Rizwan Asghar, Dake Liu

Abstract:

The direct implementation of interleaver functions in WiMAX is not hardware efficient due to presence of complex functions. Also the conventional method i.e. using memories for storing the permutation tables is silicon consuming. This work presents a 2-D transformation for WiMAX channel interleaver functions which reduces the overall hardware complexity to compute the interleaver addresses on the fly. A fully reconfigurable architecture for address generation in WiMAX channel interleaver is presented, which consume 1.1 k-gates in total. It can be configured for any block size and any modulation scheme in WiMAX. The presented architecture can run at a frequency of 200 MHz, thus fully supporting high bandwidth requirements for WiMAX.

Keywords: Interleaver, deinterleaver, WiMAX, 802.16e.

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959 Mathematical Reconstruction of an Object Image Using X-Ray Interferometric Fourier Holography Method

Authors: M. K. Balyan

Abstract:

The main principles of X-ray Fourier interferometric holography method are discussed. The object image is reconstructed by the mathematical method of Fourier transformation. The three methods are presented – method of approximation, iteration method and step by step method. As an example the complex amplitude transmission coefficient reconstruction of a beryllium wire is considered. The results reconstructed by three presented methods are compared. The best results are obtained by means of step by step method.

Keywords: Dynamical diffraction, hologram, object image, X-ray holography.

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958 Continuous Text Translation Using Text Modeling in the Thetos System

Authors: Nina Suszczanska, Przemyslaw Szmal, Slawomir Kulikow

Abstract:

In the paper a method of modeling text for Polish is discussed. The method is aimed at transforming continuous input text into a text consisting of sentences in so called canonical form, whose characteristic is, among others, a complete structure as well as no anaphora or ellipses. The transformation is lossless as to the content of text being transformed. The modeling method has been worked out for the needs of the Thetos system, which translates Polish written texts into the Polish sign language. We believe that the method can be also used in various applications that deal with the natural language, e.g. in a text summary generator for Polish.

Keywords: anaphora, machine translation, NLP, sign language, text syntax.

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957 A Method for Quality Inspection of Motors by Detecting Abnormal Sound

Authors: Tadatsugu Kitamoto

Abstract:

Recently, a quality of motors is inspected by human ears. In this paper, I propose two systems using a method of speech recognition for automation of the inspection. The first system is based on a method of linear processing which uses K-means and Nearest Neighbor method, and the second is based on a method of non-linear processing which uses neural networks. I used motor sounds in these systems, and I successfully recognize 86.67% of motor sounds in the linear processing system and 97.78% in the non-linear processing system.

Keywords: Acoustical diagnosis, Neural networks, K-means, Short-time Fourier transformation

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956 Non-Rigid Registration of Medical Images Using an Automated Method

Authors: Panos Kotsas

Abstract:

This paper presents the application of a signal intensity independent registration criterion for non-rigid body registration of medical images. The criterion is defined as the weighted ratio image of two images. The ratio is computed on a voxel per voxel basis and weighting is performed by setting the ratios between signal and background voxels to a standard high value. The mean squared value of the weighted ratio is computed over the union of the signal areas of the two images and it is minimized using the Chebyshev polynomial approximation. The geometric transformation model adopted is a local cubic B-splines based model.

Keywords: Medical image, non-rigid, registration.

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955 BER Performance of UWB Modulations through S-V Channel Model

Authors: Risanuri Hidayat

Abstract:

BER analysis of Impulse Radio Ultra Wideband (IRUWB) pulse modulations over S-V channel model is proposed in this paper. The UWB pulse is Gaussian monocycle pulse modulated using Pulse Amplitude Modulation (PAM) and Pulse Position Modulation (PPM). The channel model is generated from a modified S-V model. Bit-error rate (BER) is measured over several of bit rates. The result shows that all modulation are appropriate for both LOS and NLOS channel, but PAM gives better performance in bit rates and SNR. Moreover, as standard of speed has been given for UWB, the communication is appropriate with high bit rates in LOS channel.

Keywords: IR-UWB, S-V Channel Model, LOS NLOS, PAM, PPM

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954 Supervisory Control for Induction Machine with a Modified Star/Delta Switch in Fluid Transportation

Authors: O. S. Ebrahim, K. O. Shawky, M. A. Badr, P. K. Jain

Abstract:

This paper proposes an intelligent, supervisory, hysteresis liquid-level control with three-state energy saving mode (ESM) for induction motor (IM) in fluid transportation system (FTS) including storage tank. The IM pump drive comprises a modified star/delta switch and hydromantic coupler. Three-state ESM is defined, along with the normal running, and named analog to the computer’s ESMs as follows: Sleeping mode in which the motor runs at no load with delta stator connection, hibernate mode in which the motor runs at no load with a star connection, and motor shutdown is the third energy saver mode. Considering the motor’s thermal capacity used (TCU) and grid-compatible tariff structure, a logic flow-chart is synthesized to select the motor state at no-load for best energetic cost reduction. Fuzzy-logic (FL) based availability assessment is designed and deployed on cloud, in order to provide mobilized service for the star/delta switch and highly reliable contactors. Moreover, an artificial neural network (ANN) state estimator, based on the recurrent architecture, is constructed and learned in order to provide fault-tolerant capability for the supervisory controller. Sequential test of Wald is used for sensor fault detection. Theoretical analysis, preliminary experimental testing and computer simulations are performed to demonstrate the validity and effectiveness of the proposed control system in terms of reliability, power quality and operational cost reduction with a motivation of power factor correction.

Keywords: Artificial Neural Network, ANN, Contactor Health Assessment, Energy Saving Mode, Induction Machine, IM, Supervisory Control, Fluid Transportation, Fuzzy Logic, FL, cloud computing, pumped storage.

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953 Mathematical Modelling of Venturi Scrubber for Ammonia Absorption

Authors: S.Mousavian, D.Ashouri, M.abdolahi, M.H.Vakili, Y.Rahnama

Abstract:

In this study, the dispersed model is used to predict gas phase concentration, liquid drop concentration. The venturi scrubber efficiency is calculated by gas phase concentration. The modified model has been validated with available experimental data of Johnstone, Field and Tasler for a range of throat gas velocities, liquid to gas ratios and particle diameters and is used to study the effect of some design parameters on collection efficiency.

Keywords: Ammonia, Modelling, Purge gas, Removal efficiency, Venturi scrubber

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952 Stability Analysis of Neural Networks with Leakage, Discrete and Distributed Delays

Authors: Qingqing Wang, Baocheng Chen, Shouming Zhong

Abstract:

This paper deals with the problem of stability of neural networks with leakage, discrete and distributed delays. A new Lyapunov functional which contains some new double integral terms are introduced. By using appropriate model transformation that shifts the considered systems into the neutral-type time-delay system, and by making use of some inequality techniques, delay-dependent criteria are developed to guarantee the stability of the considered system. Finally, numerical examples are provided to illustrate the usefulness of the proposed main results.

Keywords: Neural networks, Stability, Time-varying delays, Linear matrix inequality.

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951 Analytical Camera Model Supplemented with Influence of Temperature Variations

Authors: Peter Podbreznik, Božidar Potocnik

Abstract:

A camera in the building site is exposed to different weather conditions. Differences between images of the same scene captured with the same camera arise also due to temperature variations. The influence of temperature changes on camera parameters were modelled and integrated into existing analytical camera model. Modified camera model enables quantitatively assessing the influence of temperature variations.

Keywords: camera calibration, analytical model, intrinsic parameters, extrinsic parameters, temperature variations.

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950 The Relationship of Eigenvalues between Backward MPSD and Jacobi Iterative Matrices

Authors: Zhuan-de Wang, Hou-biao Li, Zhong-xi Gao

Abstract:

In this paper, the backward MPSD (Modified Preconditioned Simultaneous Displacement) iterative matrix is firstly proposed. The relationship of eigenvalues between the backward MPSD iterative matrix and backward Jacobi iterative matrix for block p-cyclic case is obtained, which improves and refines the results in the corresponding references.

Keywords: Backward MPSD iterative matrix, Jacobi iterative matrix, eigenvalue, p-cyclic matrix.

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949 Ottoman Script Recognition Using Hidden Markov Model

Authors: Ayşe Onat, Ferruh Yildiz, Mesut Gündüz

Abstract:

In this study, an OCR system for segmentation, feature extraction and recognition of Ottoman Scripts has been developed using handwritten characters. Detection of handwritten characters written by humans is a difficult process. Segmentation and feature extraction stages are based on geometrical feature analysis, followed by the chain code transformation of the main strokes of each character. The output of segmentation is well-defined segments that can be fed into any classification approach. The classes of main strokes are identified through left-right Hidden Markov Model (HMM).

Keywords: Chain Code, HMM, Ottoman Script Recognition, OCR

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948 TACS : Thermo Acoustic Cooling System

Authors: Z. Zarid, C. Gamba, A. Brusseaux, C. Laborie, K. Briens

Abstract:

Cooling with sound is a physical phenomenon allowed by Thermo-Acoustics in which acoustic energy is transformed into a negative heat transfer, in other words: into cooling! Without needing any harmful gas, the transformation is environmentally friendly and can respond to many needs in terms of air conditioning, food refrigeration for domestic use, and cooling medical samples for example. To explore the possibilities of this cooling solution on a small scale, the TACS prototype has been designed, consisting of a low cost thermoacoustic refrigerant “pipe” able to lower the temperature by a few degrees. The obtained results are providing an interesting element for possible future of thermo-acoustic refrigeration.

Keywords: Domestic Scale Cooling System, Thermoacoustic, Environmental Friendly Refrigeration.

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947 Analysis of Combustion, Performance and Emission Characteristics of Turbocharged LHR Extended Expansion DI Diesel Engine

Authors: Mohd.F.Shabir, P. Tamilporai, B. Rajendra Prasath

Abstract:

The fundamental aim of extended expansion concept is to achieve higher work done which in turn leads to higher thermal efficiency. This concept is compatible with the application of turbocharger and LHR engine. The Low Heat Rejection engine was developed by coating the piston crown, cylinder head inside with valves and cylinder liner with partially stabilized zirconia coating of 0.5 mm thickness. Extended expansion in diesel engines is termed as Miller cycle in which the expansion ratio is increased by reducing the compression ratio by modifying the inlet cam for late inlet valve closing. The specific fuel consumption reduces to an appreciable level and the thermal efficiency of the extended expansion turbocharged LHR engine is improved. In this work, a thermodynamic model was formulated and developed to simulate the LHR based extended expansion turbocharged direct injection diesel engine. It includes a gas flow model, a heat transfer model, and a two zone combustion model. Gas exchange model is modified by incorporating the Miller cycle, by delaying inlet valve closing timing which had resulted in considerable improvement in thermal efficiency of turbocharged LHR engines. The heat transfer model, calculates the convective and radiative heat transfer between the gas and wall by taking into account of the combustion chamber surface temperature swings. Using the two-zone combustion model, the combustion parameters and the chemical equilibrium compositions were determined. The chemical equilibrium compositions were used to calculate the Nitric oxide formation rate by assuming a modified Zeldovich mechanism. The accuracy of this model is scrutinized against actual test results from the engine. The factors which affect thermal efficiency and exhaust emissions were deduced and their influences were discussed. In the final analysis it is seen that there is an excellent agreement in all of these evaluations.

Keywords: Low Heat Rejection, Miller cycle.

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946 Parallel Image Compression and Analysis with Wavelets

Authors: M. Kutila, J. Viitanen

Abstract:

This paper presents image compression with wavelet based method. The wavelet transformation divides image to low- and high pass filtered parts. The traditional JPEG compression technique requires lower computation power with feasible losses, when only compression is needed. However, there is obvious need for wavelet based methods in certain circumstances. The methods are intended to the applications in which the image analyzing is done parallel with compression. Furthermore, high frequency bands can be used to detect changes or edges. Wavelets enable hierarchical analysis for low pass filtered sub-images. The first analysis can be done for a small image, and only if any interesting is found, the whole image is processed or reconstructed.

Keywords: image compression, jpeg, wavelet, vlc

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945 Variational Iteration Method for Solving Systems of Linear Delay Differential Equations

Authors: Sara Barati, Karim Ivaz

Abstract:

In this paper, using a model transformation approach a system of linear delay differential equations (DDEs) with multiple delays is converted to a non-delayed initial value problem. The variational iteration method (VIM) is then applied to obtain the approximate analytical solutions. Numerical results are given for several examples involving scalar and second order systems. Comparisons with the classical fourth-order Runge-Kutta method (RK4) verify that this method is very effective and convenient.

Keywords: Variational iteration method, delay differential equations, multiple delays, Runge-Kutta method.

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944 Robust Probabilistic Online Change Detection Algorithm Based On the Continuous Wavelet Transform

Authors: Sergei Yendiyarov, Sergei Petrushenko

Abstract:

In this article we present a change point detection algorithm based on the continuous wavelet transform. At the beginning of the article we describe a necessary transformation of a signal which has to be made for the purpose of change detection. Then case study related to iron ore sinter production which can be solved using our proposed technique is discussed. After that we describe a probabilistic algorithm which can be used to find changes using our transformed signal. It is shown that our algorithm works well with the presence of some noise and abnormal random bursts.

Keywords: Change detection, sinter production, wavelet transform.

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943 Classification Influence Index and its Application for k-Nearest Neighbor Classifier

Authors: Sejong Oh

Abstract:

Classification is an important topic in machine learning and bioinformatics. Many datasets have been introduced for classification tasks. A dataset contains multiple features, and the quality of features influences the classification accuracy of the dataset. The power of classification for each feature differs. In this study, we suggest the Classification Influence Index (CII) as an indicator of classification power for each feature. CII enables evaluation of the features in a dataset and improved classification accuracy by transformation of the dataset. By conducting experiments using CII and the k-nearest neighbor classifier to analyze real datasets, we confirmed that the proposed index provided meaningful improvement of the classification accuracy.

Keywords: accuracy, classification, dataset, data preprocessing

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942 An Exploratory Approach of the Latin American Migrants’ Urban Space Transformation of Antofagasta City, Chile

Authors: Carolina Arriagada, Yasna Contreras

Abstract:

Since mid-2000, the migratory flows of Latin American migrants to Chile have been increasing constantly. There are two reasons that would explain why Chile is presented as an attractive country for the migrants. On the one hand, traditional centres of migrants’ attraction such as the United States and Europe have begun to close their borders. On the other hand, Chile exhibits relative economic and political stability, which offers greater job opportunities and better standard of living when compared to the migrants’ origin country. At the same time, the neoliberal economic model of Chile, developed under an extractive production of the natural resources, has privatized the urban space. The market regulates the growth of the fragmented and segregated cities. Then, the vulnerable population, most of the time, is located in the periphery and in the marginal areas of the urban space. In this aspect, the migrants have begun to occupy those degraded and depressed areas of the city. The problem raised is that the increase of the social spatial segregation could be also attributed to the migrants´ occupation of the marginal urban places of the city. The aim of this investigation is to carry out an analysis of the migrants’ housing strategies, which are transforming the marginal areas of the city. The methodology focused on the urban experience of the migrants, through the observation of spatial practices, ways of living and networks configuration in order to transform the marginal territory. The techniques applied in this study are semi–structured interviews in-depth interviews. The study reveals that the migrants housing strategies for living in the marginal areas of the city are built on a paradox way. On the one hand, the migrants choose proximity to their place of origin, maintaining their identity and customs. On the other hand, the migrants choose proximity to their social and familiar places, generating sense of belonging. In conclusion, the migration as international displacements under a globalized economic model increasing socio spatial segregation in cities is evidenced, but the transformation of the marginal areas is a fundamental resource of their integration migratory process. The importance of this research is that it is everybody´s responsibility not only the right to live in a city without any discrimination but also to integrate the citizens within the social urban space of a city.

Keywords: Inhabit, migrations, social spatial segregation.

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941 Performance of Block Codes Using the Eigenstructure of the Code Correlation Matrixand Soft-Decision Decoding of BPSK

Authors: Vitalice K. Oduol, C. Ardil

Abstract:

A method is presented for obtaining the error probability for block codes. The method is based on the eigenvalueeigenvector properties of the code correlation matrix. It is found that under a unary transformation and for an additive white Gaussian noise environment, the performance evaluation of a block code becomes a one-dimensional problem in which only one eigenvalue and its corresponding eigenvector are needed in the computation. The obtained error rate results show remarkable agreement between simulations and analysis.

Keywords: bit error rate, block codes, code correlation matrix, eigenstructure, soft-decision decoding, weight vector.

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940 Lagrangian Method for Solving Unsteady Gas Equation

Authors: Amir Taghavi, kourosh Parand, Hosein Fani

Abstract:

In this paper we propose, a Lagrangian method to solve unsteady gas equation which is a nonlinear ordinary differential equation on semi-infnite interval. This approach is based on Modified generalized Laguerre functions. This method reduces the solution of this problem to the solution of a system of algebraic equations. We also compare this work with some other numerical results. The findings show that the present solution is highly accurate.

Keywords: Unsteady gas equation, Generalized Laguerre functions, Lagrangian method, Nonlinear ODE.

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