Search results for: fractional dimension
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 484

Search results for: fractional dimension

244 Preparation and Characterization of Newly Developed Trabecular Structures in Titanium Alloy to Optimize Osteointegration

Authors: M. Regis, E. Marin, S. Fusi, M. Pressacco, L. Fedrizzi

Abstract:

Electron Beam Melting (EBM) process was used to prepare porous scaffolds with controlled porosity to ensure optimal levels of osteointegration for different trabeculae sizes. Morphological characterization by means of SEM analyses was carried out to assess pore dimensions; tensile, compression and adhesion tests have been carried out to determine the mechanical behavior. The results indicate that EBM process allows the creation of regular and repeatable porous scaffolds. Mechanical properties greatly depend on pore dimension and on bulk-pore ratio. Adhesion resistance meets the normative requirements, and the overall performance of the produced structures is compatible with potential orthopaedic applications.

Keywords: Additive manufacturing, orthopaedic implants, osteointegration, trabecular structures

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243 The Impact of Corporate Governance on Risk Taking in European Insurance Industry

Authors: Francesco Venuti, Simona Alfiero

Abstract:

The aim of this paper is to develop an empirical research on the nature and consequences of corporate governance on Eurozone Insurance Industry risk taking attitude. More particularly, we analyzed the effect of public ownership on risk taking with respect to privately held Insurance Companies. We also analyzed the effects on risk taking attitude of different degrees of ownership concentration, directors compensation, and the dimension/diversity of the Board of Directors. Our results provide quite strong evidence that, coherently with the Agency Theory, publicly traded insurance companies with more concentrated ownership are less risky than the corresponding privately held.

Keywords: Agency theory, corporate governance, insurance companies, risk taking.

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242 Gradual Shot Boundary Detection and Classification Based on Fractal Analysis

Authors: Zeinab Zeinalpour-Tabrizi, Faeze Asdaghi, Mahmooh Fathy, Mohammad Reza Jahed-Motlagh

Abstract:

Shot boundary detection is a fundamental step for the organization of large video data. In this paper, we propose a new method for video gradual shots detection and classification, using advantages of fractal analysis and AIS-based classifier. Proposed features are “vertical intercept" and “fractal dimension" of each frame of videos which are computed using Fourier transform coefficients. We also used a classifier based on Clonal Selection Algorithm. We have carried out our solution and assessed it according to the TRECVID2006 benchmark dataset.

Keywords: shot boundary detection, gradual shots, fractal analysis, artificial immune system, choose Clooney.

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241 Surface Defects Detection for Ceramic Tiles UsingImage Processing and Morphological Techniques

Authors: H. Elbehiery, A. Hefnawy, M. Elewa

Abstract:

Quality control in ceramic tile manufacturing is hard, labor intensive and it is performed in a harsh industrial environment with noise, extreme temperature and humidity. It can be divided into color analysis, dimension verification, and surface defect detection, which is the main purpose of our work. Defects detection is still based on the judgment of human operators while most of the other manufacturing activities are automated so, our work is a quality control enhancement by integrating a visual control stage using image processing and morphological operation techniques before the packing operation to improve the homogeneity of batches received by final users.

Keywords: Quality control, Defects detection, Visual control, Image processing, Morphological operation

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240 A New Face Recognition Method using PCA, LDA and Neural Network

Authors: A. Hossein Sahoolizadeh, B. Zargham Heidari, C. Hamid Dehghani

Abstract:

In this paper, a new face recognition method based on PCA (principal Component Analysis), LDA (Linear Discriminant Analysis) and neural networks is proposed. This method consists of four steps: i) Preprocessing, ii) Dimension reduction using PCA, iii) feature extraction using LDA and iv) classification using neural network. Combination of PCA and LDA is used for improving the capability of LDA when a few samples of images are available and neural classifier is used to reduce number misclassification caused by not-linearly separable classes. The proposed method was tested on Yale face database. Experimental results on this database demonstrated the effectiveness of the proposed method for face recognition with less misclassification in comparison with previous methods.

Keywords: Face recognition Principal component analysis, Linear discriminant analysis, Neural networks.

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239 Evolutionary Feature Selection for Text Documents using the SVM

Authors: Daniel I. 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, we present three feature selection methods: Information Gain, Support Vector Machine feature selection called (SVM_FS) and Genetic Algorithm with SVM (called GA_SVM). We show that the best results were obtained with GA_SVM method for a relatively small dimension of the feature vector.

Keywords: Feature Selection, Learning with Kernels, Support Vector Machine, Genetic Algorithm, and Classification.

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238 Feature Selection Methods for an Improved SVM Classifier

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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237 Discovering the Dimension of Abstractness: Structure-Based Model that Learns New Categories and Categorizes on Different Levels of Abstraction

Authors: Georgi I. Petkov, Ivan I. Vankov, Yolina A. Petrova

Abstract:

A structure-based model of category learning and categorization at different levels of abstraction is presented. The model compares different structures and expresses their similarity implicitly in the forms of mappings. Based on this similarity, the model can categorize different targets either as members of categories that it already has or creates new categories. The model is novel using two threshold parameters to evaluate the structural correspondence. If the similarity between two structures exceeds the higher threshold, a new sub-ordinate category is created. Vice versa, if the similarity does not exceed the higher threshold but does the lower one, the model creates a new category on higher level of abstraction.

Keywords: Analogy-making, categorization, learning of categories, abstraction, hierarchical structure.

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236 Characteristics of Corporate Social Responsibility Indicators

Authors: Grigoris Giannarakis, Nikolaos Litinas, Ioannis Theotokas

Abstract:

The aim of the study is to investigate a number of characteristics of Corporate Social Responsibility (CSR) indicators that should be adopted by CSR assessment methodologies. For the purpose of this paper, a survey among the Greek companies that belong to FTSE 20 in Athens Exchange (FTSE/Athex-20) has been conducted, as these companies are expected to pioneer in the field of CSR. The results show consensus as regards the characteristics of indicators such as the need for the adoption of general and specific sector indicators, financial and non-financial indicators, the origin and the weight rate. However, the results are contradictory concerning the appropriate number of indicators for the assessment of CSR and the unit of measurement. Finally, the company-s sector is a more important dimension of CSR than the size and the country where the company operates. The purpose of this paper is to standardize the main characteristics of CSR indicators.

Keywords: Corporate social responsibility, Greece, Indicators

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235 Analysis on Urban Form and Evolution Mechanism of High-Density City: Case Study of Hong Kong

Authors: Yuan Zhang

Abstract:

Along with large population and great demands for urban development, Hong Kong serves as a typical high-density city with multiple altitudes, advanced three-dimensional traffic system, rich city open space, etc. This paper contributes to analyzing its complex urban form and evolution mechanism from three aspects of view, separately as time, space and buildings. Taking both horizontal and vertical dimension into consideration, this paper provides a perspective to explore the fascinating process of growing and space folding in the urban form of high-density city, also as a research reference for related high-density urban design.

Keywords: Evolution mechanism, high-density city, Hong Kong, urban form.

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234 Normalization Discriminant Independent Component Analysis

Authors: Liew Yee Ping, Pang Ying Han, Lau Siong Hoe, Ooi Shih Yin, Housam Khalifa Bashier Babiker

Abstract:

In face recognition, feature extraction techniques attempts to search for appropriate representation of the data. However, when the feature dimension is larger than the samples size, it brings performance degradation. Hence, we propose a method called Normalization Discriminant Independent Component Analysis (NDICA). The input data will be regularized to obtain the most reliable features from the data and processed using Independent Component Analysis (ICA). The proposed method is evaluated on three face databases, Olivetti Research Ltd (ORL), Face Recognition Technology (FERET) and Face Recognition Grand Challenge (FRGC). NDICA showed it effectiveness compared with other unsupervised and supervised techniques.

Keywords: Face recognition, small sample size, regularization, independent component analysis.

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233 Efficient Hardware Architecture of the Direct 2- D Transform for the HEVC Standard

Authors: Fatma Belghith, Hassen Loukil, Nouri Masmoudi

Abstract:

This paper presents the hardware design of a unified architecture to compute the 4x4, 8x8 and 16x16 efficient twodimensional (2-D) transform for the HEVC standard. This architecture is based on fast integer transform algorithms. It is designed only with adders and shifts in order to reduce the hardware cost significantly. The goal is to ensure the maximum circuit reuse during the computing while saving 40% for the number of operations. The architecture is developed using FIFOs to compute the second dimension. The proposed hardware was implemented in VHDL. The VHDL RTL code works at 240 MHZ in an Altera Stratix III FPGA. The number of cycles in this architecture varies from 33 in 4-point- 2D-DCT to 172 when the 16-point-2D-DCT is computed. Results show frequency improvements reaching 96% when compared to an architecture described as the direct transcription of the algorithm.

Keywords: HEVC, Modified Integer Transform, FPGA.

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232 A Neural Approach for Color-Textured Images Segmentation

Authors: Khalid Salhi, El Miloud Jaara, Mohammed Talibi Alaoui

Abstract:

In this paper, we present a neural approach for unsupervised natural color-texture image segmentation, which is based on both Kohonen maps and mathematical morphology, using a combination of the texture and the image color information of the image, namely, the fractal features based on fractal dimension are selected to present the information texture, and the color features presented in RGB color space. These features are then used to train the network Kohonen, which will be represented by the underlying probability density function, the segmentation of this map is made by morphological watershed transformation. The performance of our color-texture segmentation approach is compared first, to color-based methods or texture-based methods only, and then to k-means method.

Keywords: Segmentation, color-texture, neural networks, fractal, watershed.

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231 Organizational Socialization Levels in Nurses

Authors: M. Aslan, A. Karaaslan, S. Selcuk

Abstract:

The research was conducted in order to determine the organizational socialization levels of nurses working in hospitals in the form of a descriptive study. The research population was composed of nurses employed in public and private sector hospitals in the province of Konya with 0-3 years of professional experience in the hospitals (N=1200); and the sample was composed of 495 nurses that accepted to take part in the study voluntarily. Statistical evaluation of data was conducted in SPSS.16 software. The results of the study revealed that the total score taken by nurses at the organizational socialization scale was 262.95; and this was close to the maximum score. Particularly the departmental socialization sub-dimension proved to be higher in comparison to the other two dimensions (organization socialization and task socialization). Statistically meaningful differences were found in the levels of organization socialization in relation to the status of organizational orientation training, level of education and age group.

Keywords: Nurses, Newcomers, Organizational Socialization.

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230 Grid-based Supervised Clustering - GBSC

Authors: Pornpimol Bungkomkhun, Surapong Auwatanamongkol

Abstract:

This paper presents a supervised clustering algorithm, namely Grid-Based Supervised Clustering (GBSC), which is able to identify clusters of any shapes and sizes without presuming any canonical form for data distribution. The GBSC needs no prespecified number of clusters, is insensitive to the order of the input data objects, and is capable of handling outliers. Built on the combination of grid-based clustering and density-based clustering, under the assistance of the downward closure property of density used in bottom-up subspace clustering, the GBSC can notably reduce its search space to avoid the memory confinement situation during its execution. On two-dimension synthetic datasets, the GBSC can identify clusters with different shapes and sizes correctly. The GBSC also outperforms other five supervised clustering algorithms when the experiments are performed on some UCI datasets.

Keywords: supervised clustering, grid-based clustering, subspace clustering

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229 Application and Limitation of Parallel Modelingin Multidimensional Sequential Pattern

Authors: Mahdi Esmaeili, Mansour Tarafdar

Abstract:

The goal of data mining algorithms is to discover useful information embedded in large databases. One of the most important data mining problems is discovery of frequently occurring patterns in sequential data. In a multidimensional sequence each event depends on more than one dimension. The search space is quite large and the serial algorithms are not scalable for very large datasets. To address this, it is necessary to study scalable parallel implementations of sequence mining algorithms. In this paper, we present a model for multidimensional sequence and describe a parallel algorithm based on data parallelism. Simulation experiments show good load balancing and scalable and acceptable speedup over different processors and problem sizes and demonstrate that our approach can works efficiently in a real parallel computing environment.

Keywords: Sequential Patterns, Data Mining, ParallelAlgorithm, Multidimensional Sequence Data

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228 Internationalization and Multilingualism in Brazil: Possibilities of Content and Language Integrated Learning and Intercomprehension Approaches

Authors: Kyria Rebeca Finardi

Abstract:

The study discusses the role of foreign languages in general and of English in particular in the process of internationalization of higher education (IHE), defined as the intentional integration of an international, intercultural or global dimension in the purpose, function or offer of higher education. The study is bibliographical and offers a brief outline of the current political, economic and educational scenarios in Brazil, before discussing some possibilities and challenges for the development of multilingualism and IHE there. The theoretical background includes a review of Brazilian language and internationalization policies. The review and discussion concludes that the use of the Content and Language Integrated Learning (CLIL) approach and the Intercomprehension approach to foreign language teaching/learning are relevant alternatives to foster multilingualism in that context.

Keywords: Brazil, higher education, internationalization, multilingualism.

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227 Supporting QoS-aware Multicasting in Differentiated Service Networks

Authors: Manas Ranjan Kabat, Rajib Mall, Chita Ranjan Tripathy

Abstract:

A scalable QoS aware multicast deployment in DiffServ networks has become an important research dimension in recent years. Although multicasting and differentiated services are two complementary technologies, the integration of the two technologies is a non-trivial task due to architectural conflicts between them. A popular solution proposed is to extend the functionality of the DiffServ components to support multicasting. In this paper, we propose an algorithm to construct an efficient QoSdriven multicast tree, taking into account the available bandwidth per service class. We also present an efficient way to provision the limited available bandwidth for supporting heterogeneous users. The proposed mechanism is evaluated using simulated tests. The simulated result reveals that our algorithm can effectively minimize the bandwidth use and transmission cost

Keywords: Differentiated Services, multicasting, QoSheterogeneity, DSCP

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226 Characterization of Carbon Based Nanometer Scale Coil Growth

Authors: C. C. Su, S. H. Chang

Abstract:

The carbon based coils with the nanometer scale have the 3 dimension helix geometry. We synthesized the carbon nano-coils by the use of chemical vapor deposition technique with iron and tin as the catalysts. The fabricated coils have the external diameter of ranging few hundred nm to few thousand nm. The Scanning Electro-Microscope (SEM) and Tunneling Electro-Microscope has shown detail images of the coil-s structure. The fabrication of the carbon nano-coils can be grown on the metal and non-metal substrates, such as the stainless steel and silicon substrates. Besides growth on the flat substrate; they also can be grown on the stainless steel wires. After the synthesis of the coils, the mechanical and electro-mechanical property is measured. The experimental results were reported.

Keywords: Carbon nanocoils, chemical vapor deposition, nano-materials

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225 Stress Ratio and Notch Effect on Fatigue Crack Initiation and Propagation in 2024 Al-alloy

Authors: N. Benachour, A. Hadjoui, M. Benachour, M. Benguediab

Abstract:

This study reports an empirical investigation of fatigue crack initiation and propagation in 2024 T351 aluminium alloy using constant amplitude loading. In initiation stage, local strain approach at the notch was used and in stable propagation stage NASGRO model was applied. In this investigation, the flat plate of double through crack at hole is used. Based on experimental results (AFGROW Database), effect of stress ratio, R, is highlights on fatigue initiation life (FIL) and fatigue crack growth rate (FCGR). The increasing of dimension of hole characterizing the notch effect decrease the fatigue life.

Keywords: Fatigue crack growth, initiation life, Al-Alloy, stressratio, notch effect

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224 Numerical Study of Some Coupled PDEs by using Differential Transformation Method

Authors: Reza Abazari, Rasool Abazari

Abstract:

In this paper, the two-dimension differential transformation method (DTM) is employed to obtain the closed form solutions of the three famous coupled partial differential equation with physical interest namely, the coupled Korteweg-de Vries(KdV) equations, the coupled Burgers equations and coupled nonlinear Schrödinger equation. We begin by showing that how the differential transformation method applies to a linear and non-linear part of any PDEs and apply on these coupled PDEs to illustrate the sufficiency of the method for this kind of nonlinear differential equations. The results obtained are in good agreement with the exact solution. These results show that the technique introduced here is accurate and easy to apply.

Keywords: Coupled Korteweg-de Vries(KdV) equation, Coupled Burgers equation, Coupled Schrödinger equation, differential transformation method.

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223 Influence of Deep Cold Rolling and Low Plasticity Burnishing on Surface Hardness and Surface Roughness of AISI 4140 Steel

Authors: P. R. Prabhu, S. M. Kulkarni, S. S. Sharma

Abstract:

Deep cold rolling (DCR) and low plasticity burnishing (LPB) process are cold working processes, which easily produce a smooth and work-hardened surface by plastic deformation of surface irregularities. The present study focuses on the surface roughness and surface hardness aspects of AISI 4140 work material, using fractional factorial design of experiments. The assessment of the surface integrity aspects on work material was done, in order to identify the predominant factors amongst the selected parameters. They were then categorized in order of significance followed by setting the levels of the factors for minimizing surface roughness and/or maximizing surface hardness. In the present work, the influence of main process parameters (force, feed rate, number of tool passes/overruns, initial roughness of the work piece, ball material, ball diameter and lubricant used) on the surface roughness and the hardness of AISI 4140 steel were studied for both LPB and DCR process and the results are compared. It was observed that by using LPB process surface hardness has been improved by 167% and in DCR process surface hardness has been improved by 442%. It was also found that the force, ball diameter, number of tool passes and initial roughness of the workpiece are the most pronounced parameters, which has a significant effect on the work piece-s surface during deep cold rolling and low plasticity burnishing process.

Keywords: Deep cold rolling, burnishing, surface roughness, surface hardness, design of experiments, AISI4140 steel.

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222 Human Body Configuration using Bayesian Model

Authors: Rui. Zhang, Yiming. Pi

Abstract:

In this paper we present a novel approach for human Body configuration based on the Silhouette. We propose to address this problem under the Bayesian framework. We use an effective Model based MCMC (Markov Chain Monte Carlo) method to solve the configuration problem, in which the best configuration could be defined as MAP (maximize a posteriori probability) in Bayesian model. This model based MCMC utilizes the human body model to drive the MCMC sampling from the solution space. It converses the original high dimension space into a restricted sub-space constructed by the human model and uses a hybrid sampling algorithm. We choose an explicit human model and carefully select the likelihood functions to represent the best configuration solution. The experiments show that this method could get an accurate configuration and timesaving for different human from multi-views.

Keywords: Bayesian framework, MCMC, model based, human body configuration.

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221 Numerical Study of Microscale Gas Flow-Separation Using Explicit Finite Volume Method

Authors: A. Chaudhuri, C. Guha, T. K. Dutta

Abstract:

Pressure driven microscale gas flow-separation has been investigated by solving the compressible Navier-Stokes (NS) system of equations. A two dimensional explicit finite volume (FV) compressible flow solver has been developed using modified advection upwind splitting methods (AUSM+) with no-slip/first order Maxwell-s velocity slip conditions to predict the flowseparation behavior in microdimensions. The effects of scale-factor of the flow geometry and gas species on the microscale gas flowseparation have been studied in this work. The intensity of flowseparation gets reduced with the decrease in scale of the flow geometry. In reduced dimension, flow-separation may not at all be present under similar flow conditions compared to the larger flow geometry. The flow-separation patterns greatly depend on the properties of the medium under similar flow conditions.

Keywords: AUSM+, FVM, Flow-separation, Microflow.

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220 A Framework for Ranking Quality of Information on Weblog

Authors: Mohammad Javad Kargar, Fatemeh Azimzadeh

Abstract:

The vast amount of information on the World Wide Web is created and published by many different types of providers. Unlike books and journals, most of this information is not subject to editing or peer review by experts. This lack of quality control and the explosion of web sites make the task of finding quality information on the web especially critical. Meanwhile new facilities for producing web pages such as Blogs make this issue more significant because Blogs have simple content management tools enabling nonexperts to build easily updatable web diaries or online journals. On the other hand despite a decade of active research in information quality (IQ) there is no framework for measuring information quality on the Blogs yet. This paper presents a novel experimental framework for ranking quality of information on the Weblog. The results of data analysis revealed seven IQ dimensions for the Weblog. For each dimension, variables and related coefficients were calculated so that presented framework is able to assess IQ of Weblogs automatically.

Keywords: Information Quality, Weblog, Web Ranking, Web- Quality.

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219 Cubic Trigonometric B-spline Approach to Numerical Solution of Wave Equation

Authors: Shazalina Mat Zin, Ahmad Abd. Majid, Ahmad Izani Md. Ismail, Muhammad Abbas

Abstract:

The generalized wave equation models various problems in sciences and engineering. In this paper, a new three-time level implicit approach based on cubic trigonometric B-spline for the approximate solution of wave equation is developed. The usual finite difference approach is used to discretize the time derivative while cubic trigonometric B-spline is applied as an interpolating function in the space dimension. Von Neumann stability analysis is used to analyze the proposed method. Two problems are discussed to exhibit the feasibility and capability of the method. The absolute errors and maximum error are computed to assess the performance of the proposed method. The results were found to be in good agreement with known solutions and with existing schemes in literature.

Keywords: Collocation method, Cubic trigonometric B-spline, Finite difference, Wave equation.

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218 The Role of European Union in Global Governance

Authors: Yrfet Shkreli

Abstract:

Despite all the wide research and literature on the subject, changing and challenging times often present themselves with new objectives, fluid politics, and everlasting point of views. Much is said about the subject and the trend nowadays is watching every European Union (EU) intervention as a form of neo colonialism or a form of establishing new markets. The paper will try to establish a perspective on EU influences, policies and impacts analyzed from multidimensional point of view, not limiting itself on a narrow external dimension, focusing on a broader understanding of it diverse contribution to global governance and peace keeping. Tending to be critical, this paper tends to fall out of extremes, nether holding a Eurocentric position, nor falling for cheap critic to the whole failures and impact of EU policies. The ambition is to show EU as a contributing factor while keeping in mind its nature as a multi layered actor and with not necessarily coinciding interests among its member states.

Keywords: European Union, global governance, globalization, normative power.

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217 Designing a Low Speed Wind Tunnel for Investigating Effects of Blockage Ratio on Heat Transfer of a Non-Circular Tube

Authors: Arash Mirabdolah Lavasani, Taher Maarefdoost

Abstract:

Effect of blockage ratio on heat transfer from non-circular tube is studied experimentally. For doing this experiment a suction type low speed wind tunnel with test section dimension of 14×14×40 and velocity in rage of 7-20 m/s was designed. The blockage ratios varied between 1.5 to 7 and Reynolds number based on equivalent diameter varies in range of 7.5×103 to 17.5×103. The results show that by increasing blockage ratio from 1.5 to 7, drag coefficient of the cam shaped tube decreased about 55 percent. By increasing Reynolds number, Nusselt number of the cam shaped tube increases about 40 to 48 percent in all ranges of blockage ratios.

Keywords: Wind tunnel, non-circular tube, blockage ratio, experimental heat transfer, cross-flow.

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216 Comparison of the Parameter using ECG with Bisepctrum Parameter using EEG during General Anesthesia

Authors: Seong-wan Baik, Soo-young Ye, Byeong-cheol Choi, Gye-rok Jeon

Abstract:

The measurement of anesthetic depth is necessary in anesthesiology. NN10 is very simple method among the RR intervals analysis methods. NN10 parameter means the numbers of above the 10 ms intervals of the normal to normal RR intervals. Bispectrum analysis is defined as 2D FFT. EEG signal reflected the non-linear peristalsis phenomena according to the change brain function. After analyzing the bispectrum of the 2 dimension, the most significant power spectrum density peaks appeared abundantly at the specific area in awakening and anesthesia state. These points are utilized to create the new index since many peaks appeared at the specific area in the frequency coordinate. The measured range of an index was 0-100. An index is 20-50 at an anesthesia, while the index is 90-60 at the awake. In this paper, the relation between NN10 parameter using ECG and bisepctrum index using EEG is observed to estimate the depth of anesthesia during anesthesia and then we estimated the utility of the anesthetic.

Keywords: Anesthesia, Bispectrum index, ECG, EEG

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215 Improving the Quality of e-learning Courses in Higher Education through Student Satisfaction

Authors: Susana Lemos, Neuza Pedro

Abstract:

Thepurpose of the research is to characterize the levels of satisfaction of the students in e-learning post-graduate courses, taking into account specific dimensions of the course which were considered as benchmarks for the quality of this type of online learning initiative, as well as the levels of satisfaction towards each specific indicator identified in each dimension. It was also an aim of this study to understand how thesedimensions relate to one another. Using a quantitative research approach in the collection and analysis of the data, the study involves the participation of the students who attended on e-learning course in 2010/2011. The conclusions of this study suggest that online students present relatively high levels of satisfaction, which points towards a positive experience during the course. It is possible to note that there is a correlation between the different dimensions studied, consequently leading to different improvement strategies. Ultimately, this investigation aims to contribute to the promotion of quality and the success of e-learning initiatives in Higher Education.

Keywords: e-learning, higher education, quality, students satisfaction

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