Search results for: RLT test results
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 14589

Search results for: RLT test results

8169 Adsorption of Paracetamol Using Activated Carbon of Dende and Babassu Coconut Mesocarp

Authors: R. C. Ferreira, H. H. C. De Lima, A. A. Cândido, O. M. Couto Junior, P. A. Arroyo, K. Q De Carvalho, G. F. Gauze, M. A. S. D. Barros

Abstract:

Removal of the widespread used drug paracetamol from water was investigated using activated carbon originated from dende coconut mesocarp and babassu coconut mesocarp. Kinetic and equilibrium data were obtained at different values of pH. Both activated carbons showed high efficiency when pH ≤ pHPZC as the carbonil group of paracetamol molecule are adsorbed due to positively charged carbon surface. Microporosity also played an important role in such process. Pseudo-second order model was better adjusted to the kinetic results. Equilibrium data may be represented by Langmuir equation.

Keywords: Adsorption, activated carbon, babassu, dende.

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8168 On Improving Breast Cancer Prediction Using GRNN-CP

Authors: Kefaya Qaddoum

Abstract:

The aim of this study is to predict breast cancer and to construct a supportive model that will stimulate a more reliable prediction as a factor that is fundamental for public health. In this study, we utilize general regression neural networks (GRNN) to replace the normal predictions with prediction periods to achieve a reasonable percentage of confidence. The mechanism employed here utilises a machine learning system called conformal prediction (CP), in order to assign consistent confidence measures to predictions, which are combined with GRNN. We apply the resulting algorithm to the problem of breast cancer diagnosis. The results show that the prediction constructed by this method is reasonable and could be useful in practice.

Keywords: Neural network, conformal prediction, cancer classification, regression.

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8167 An Expert System for Car Failure Diagnosis

Authors: Ahmad T. Al-Taani

Abstract:

Car failure detection is a complicated process and requires high level of expertise. Any attempt of developing an expert system dealing with car failure detection has to overcome various difficulties. This paper describes a proposed knowledge-based system for car failure detection. The paper explains the need for an expert system and the some issues on developing knowledge-based systems, the car failure detection process and the difficulties involved in developing the system. The system structure and its components and their functions are described. The system has about 150 rules for different types of failures and causes. It can detect over 100 types of failures. The system has been tested and gave promising results.

Keywords: Expert system, car failure diagnosis, knowledgebasedsystem, CLIPS.

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8166 Direct Block Backward Differentiation Formulas for Solving Second Order Ordinary Differential Equations

Authors: Zarina Bibi Ibrahim, Mohamed Suleiman, Khairil Iskandar Othman

Abstract:

In this paper, a direct method based on variable step size Block Backward Differentiation Formula which is referred as BBDF2 for solving second order Ordinary Differential Equations (ODEs) is developed. The advantages of the BBDF2 method over the corresponding sequential variable step variable order Backward Differentiation Formula (BDFVS) when used to solve the same problem as a first order system are pointed out. Numerical results are given to validate the method.

Keywords: Backward Differentiation Formula, block, secondorder.

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8165 Hydrodynamic Simulation of Fixed Bed GTL Reactor Using CFD

Authors: Sh. Shahhosseini, S. Alinia, M. Irani

Abstract:

In this work, axisymetric CFD simulation of fixed bed GTL reactor has been conducted, using computational fluid dynamics (CFD). In fixed bed CFD modeling, when N (tube-to-particle diameter ratio) has a large value, it is common to consider the packed bed as a porous media. Synthesis gas (a mixture of predominantly carbon monoxide and hydrogen) was fed to the reactor. The reactor length was 20 cm, divided to three sections. The porous zone was in the middle section of the reactor. The model equations were solved employing finite volume method. The effects of particle diameter, bed voidage, fluid velocity and bed length on pressure drop have been investigated. Simulation results showed these parameters could have remarkable impacts on the reactor pressure drop.

Keywords: GTL Process, Fixed bed reactor, Pressure drop, CFDsimulation.

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8164 An 8-Bit, 100-MSPS Fully Dynamic SAR ADC for Ultra-High Speed Image Sensor

Authors: F. Rarbi, D. Dzahini, W. Uhring

Abstract:

In this paper, a dynamic and power efficient 8-bit and 100-MSPS Successive Approximation Register (SAR) Analog-to-Digital Converter (ADC) is presented. The circuit uses a non-differential capacitive Digital-to-Analog (DAC) architecture segmented by 2. The prototype is produced in a commercial 65-nm 1P7M CMOS technology with 1.2-V supply voltage. The size of the core ADC is 208.6 x 103.6 µm2. The post-layout noise simulation results feature a SNR of 46.9 dB at Nyquist frequency, which means an effective number of bit (ENOB) of 7.5-b. The total power consumption of this SAR ADC is only 1.55 mW at 100-MSPS. It achieves then a figure of merit of 85.6 fJ/step.

Keywords: CMOS analog to digital converter, dynamic comparator, image sensor application, successive approximation register.

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8163 Influence of Single and Multiple Skin-Core Debonding on Free Vibration Characteristics of Innovative GFRP Sandwich Panels

Authors: Indunil Jayatilake, Warna Karunasena, Weena Lokuge

Abstract:

An Australian manufacturer has fabricated an innovative GFRP sandwich panel made from E-glass fiber skin and a modified phenolic core for structural applications. Debonding, which refers to separation of skin from the core material in composite sandwiches, is one of the most common types of damage in composites. The presence of debonding is of great concern because it not only severely affects the stiffness but also modifies the dynamic behaviour of the structure. Generally it is seen that the majority of research carried out has been concerned about the delamination of laminated structures whereas skin-core debonding has received relatively minor attention. Furthermore it is observed that research done on composite slabs having multiple skin-core debonding is very limited. To address this gap, a comprehensive research investigating dynamic behaviour of composite panels with single and multiple debonding is presented. The study uses finite-element modelling and analyses for investigating the influence of debonding on free vibration behaviour of single and multilayer composite sandwich panels. A broad parametric investigation has been carried out by varying debonding locations, debonding sizes and support conditions of the panels in view of both single and multiple debonding. Numerical models were developed with Strand7 finite element package by innovatively selecting the suitable elements to diligently represent their actual behavior. Three-dimensional finite element models were employed to simulate the physically real situation as close as possible, with the use of an experimentally and numerically validated finite element model. Comparative results and conclusions based on the analyses are presented. For similar extents and locations of debonding, the effect of debonding on natural frequencies appears greatly dependent on the end conditions of the panel, giving greater decrease in natural frequency when the panels are more restrained. Some modes are more sensitive to debonding and this sensitivity seems to be related to their vibration mode shapes. The fundamental mode seems generally the least sensitive mode to debonding with respect to the variation in free vibration characteristics. The results indicate the effectiveness of the developed three dimensional finite element models in assessing debonding damage in composite sandwich panels.

Keywords: Debonding, free vibration behaviour, GFRP sandwich panels, three dimensional finite element modelling.

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8162 Decision Making under Strict Uncertainty: Case Study in Sewer Network Planning

Authors: Zhen Wu, David Lupien St-Pierre, Georges Abdul-Nour

Abstract:

In decision making under strict uncertainty, decision makers have to choose a decision without any information about the states of nature. The classic criteria of Laplace, Wald, Savage, Hurwicz and Starr are introduced and compared in a case study of sewer network planning. Furthermore, results from different criteria are discussed and analyzed. Moreover, this paper discusses the idea that decision making under strict uncertainty (DMUSU) can be viewed as a two-player game and thus be solved by a solution concept in game theory: Nash equilibrium.

Keywords: Decision criteria, decision making, sewer network planning, strict uncertainty.

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8161 What Deter Academia to Share Knowledge within Research-Based University Status

Authors: S. Roziana, R. Azizah, A.R. Hamidah

Abstract:

This paper discusses the issues and challenge that academia faced in knowledge sharing at a research university in Malaysia. The partial results of interview are presented from the actual study. The main issues in knowledge sharing practices are university structure and designation and title. The academia awareness in sharing knowledge is also influenced by culture. Our investigation highlight that the concept of reciprocal relationship of sharing knowledge may hinder knowledge sharing awareness among academia. Hence, we concluded that further investigation could be carried out on the social interaction and trust culture among academia in sharing knowledge within research/ranking university environment.

Keywords: Knowledge sharing awareness, knowledge sharing practices, research university.

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8160 Arabic Character Recognition using Artificial Neural Networks and Statistical Analysis

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

Abstract:

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

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

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8159 Determination of Cadmium and Lead in Sewage Sludge from the Middle Region (Misrata, Msallata and Tarhünah Cities) of Libya

Authors: J. A. Mayouf, Q. A. Najim, H. S. Al-Bayati

Abstract:

The concentrations of cadmium and lead in sewage sludge samples were determined by Atomic Absorption Spectrometric Method. Samples of sewage sludge were obtained from three sewage treatment plants localised in Middle Region of Libya (Misrata, Msallata and Tarhünah cities). The results shows that, the mean levels of Cadmium for all regions are ranges from 81 to 123.4 ppm and these values are higher than the limitations for the international standard which are not registered more than 50 ppm (dry weight) in USA, Egypt and the EU countries. While, the lead concentrations are ranged from 8.0 to 189.2 ppm and all values are within the standard limits which graduated between (275–613) ppm.

Keywords: Cadmium, Lead, Sewage, Spectrometry.

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8158 Energy and Exergy Analysis of Dual Purpose Solar Collector

Authors: I. Jafari, A. Ershadi, E. Najafpour, N. Hedayat

Abstract:

Energy and exergy study of air-water combined solar collector which is called dual purpose solar collector (DPSC) is investigated. The method of ε - NTU is used. Analysis is performed for triangle channels. Parameters like the air flow rate and water inlet temperature are studied. Results are shown that DPSC has better energy and exergy efficiency than single collector. In addition, the triangle passage with water inlet temperature of 60O C has shown better exergy and energy efficiency.

Keywords: Efficiency, Exergy, Irreversibility, Solar collector.

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8157 Optimal ECG Sampling Frequency for Multiscale Entropy-Based HRV

Authors: Manjit Singh

Abstract:

Multiscale entropy (MSE) is an extensively used index to provide a general understanding of multiple complexity of physiologic mechanism of heart rate variability (HRV) that operates on a wide range of time scales. Accurate selection of electrocardiogram (ECG) sampling frequency is an essential concern for clinically significant HRV quantification; high ECG sampling rate increase memory requirements and processing time, whereas low sampling rate degrade signal quality and results in clinically misinterpreted HRV. In this work, the impact of ECG sampling frequency on MSE based HRV have been quantified. MSE measures are found to be sensitive to ECG sampling frequency and effect of sampling frequency will be a function of time scale.

Keywords: ECG, heart rate variability, HRV, multiscale entropy, sampling frequency.

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8156 Consumer Load Profile Determination with Entropy-Based K-Means Algorithm

Authors: Ioannis P. Panapakidis, Marios N. Moschakis

Abstract:

With the continuous increment of smart meter installations across the globe, the need for processing of the load data is evident. Clustering-based load profiling is built upon the utilization of unsupervised machine learning tools for the purpose of formulating the typical load curves or load profiles. The most commonly used algorithm in the load profiling literature is the K-means. While the algorithm has been successfully tested in a variety of applications, its drawback is the strong dependence in the initialization phase. This paper proposes a novel modified form of the K-means that addresses the aforementioned problem. Simulation results indicate the superiority of the proposed algorithm compared to the K-means.

Keywords: Clustering, load profiling, load modeling, machine learning, energy efficiency and quality.

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8155 Effects of Dust on the Performance of PV Panels

Authors: Shaharin A. Sulaiman, Haizatul H. Hussain, Nik Siti H. Nik Leh, Mohd S. I. Razali

Abstract:

Accumulation of dust from the outdoor environment on the panels of solar photovoltaic (PV) system is natural. There were studies that showed that the accumulated dust can reduce the performance of solar panels, but the results were not clearly quantified. The objective of this research was to study the effects of dust accumulation on the performance of solar PV panels. Experiments were conducted using dust particles on solar panels with a constant-power light source, to determine the resulting electrical power generated and efficiency. It was found from the study that the accumulated dust on the surface of photovoltaic solar panel can reduce the system-s efficiency by up to 50%.

Keywords: Dust, Photovoltaic, Solar Energy.

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8154 A Study on Cancer-Cell Invasion Based On the Diffuse Interface Model

Authors: Zhang Linan, Jihwan Song, Dongchoul Kim

Abstract:

In this study, a three-dimensional haptotaxis model to simulate the migration of a population of cancer cells has been proposed. The invasion of cancer cells is related with the hapto-attractant and the effect of the interface energies between the cells and the ECM. The diffuse interface model, which incorporates the haptotaxis mechanism and interface energies, is employed. The semi-implicit Fourier spectral scheme is adopted for efficient evaluation of the simulation. The simulation results thoroughly reveal the dynamics of cancer-cell migration.

Keywords: Haptotaxis, Cancer Cells, Cell Migration, Interface Energy, Diffuse Interface Model

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8153 Hutchinson-Barnsley Operator in Intuitionistic Fuzzy Metric Spaces

Authors: R. Uthayakumar, D. Easwaramoorthy

Abstract:

The main purpose of this paper is to prove the intuitionistic fuzzy contraction properties of the Hutchinson-Barnsley operator on the intuitionistic fuzzy hyperspace with respect to the Hausdorff intuitionistic fuzzy metrics. Also we discuss about the relationships between the Hausdorff intuitionistic fuzzy metrics on the intuitionistic fuzzy hyperspaces. Our theorems generalize and extend some recent results related with Hutchinson-Barnsley operator in the metric spaces to the intuitionistic fuzzy metric spaces.

Keywords: Contraction, Iterated Function System, Hutchinson- Barnsley Operator, Intuitionistic Fuzzy Metric Space, Hausdorff Intuitionistic Fuzzy Metric.

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8152 Investigation of VN/TiN Multilayer Coatings on AZ91D Mg Alloys

Authors: M. Ertas, A. C. Onel, G. Ekinci, B. Toydemir, S. Durdu, M. Usta, L. Colakerol Arslan

Abstract:

To develop AZ91D magnesium alloys with improved properties, we have applied TiN and VN/TiN multilayer coatings using DC magnetron sputter technique. Coating structure, surface morphology, chemical bonding and corrosion resistance of coatings were analyzed by x-ray diffraction (XRD), scanning electron microscope (SEM), x-ray photoelectron spectroscopy (XPS), and tafel extrapolation method, respectively. XPS analysis reveal that VN overlayer reacts with oxygen at the VN/TiN interface and forms more stable TiN layer. Morphological investigations and the corrosion results show that VN/TiN multilayer thin film coatings are quite effective to optimize the corrosion resistance of Mg alloys.

Keywords: AZ91D Mg alloys, High corrosion resistance, Transition metal nitride coatings, Magnetron sputter.

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8151 Index t-SNE: Tracking Dynamics of High-Dimensional Datasets with Coherent Embeddings

Authors: G. Candel, D. Naccache

Abstract:

t-SNE is an embedding method that the data science community has widely used. It helps two main tasks: to display results by coloring items according to the item class or feature value; and for forensic, giving a first overview of the dataset distribution. Two interesting characteristics of t-SNE are the structure preservation property and the answer to the crowding problem, where all neighbors in high dimensional space cannot be represented correctly in low dimensional space. t-SNE preserves the local neighborhood, and similar items are nicely spaced by adjusting to the local density. These two characteristics produce a meaningful representation, where the cluster area is proportional to its size in number, and relationships between clusters are materialized by closeness on the embedding. This algorithm is non-parametric. The transformation from a high to low dimensional space is described but not learned. Two initializations of the algorithm would lead to two different embedding. In a forensic approach, analysts would like to compare two or more datasets using their embedding. A naive approach would be to embed all datasets together. However, this process is costly as the complexity of t-SNE is quadratic, and would be infeasible for too many datasets. Another approach would be to learn a parametric model over an embedding built with a subset of data. While this approach is highly scalable, points could be mapped at the same exact position, making them indistinguishable. This type of model would be unable to adapt to new outliers nor concept drift. This paper presents a methodology to reuse an embedding to create a new one, where cluster positions are preserved. The optimization process minimizes two costs, one relative to the embedding shape and the second relative to the support embedding’ match. The embedding with the support process can be repeated more than once, with the newly obtained embedding. The successive embedding can be used to study the impact of one variable over the dataset distribution or monitor changes over time. This method has the same complexity as t-SNE per embedding, and memory requirements are only doubled. For a dataset of n elements sorted and split into k subsets, the total embedding complexity would be reduced from O(n2) to O(n2/k), and the memory requirement from n2 to 2(n/k)2 which enables computation on recent laptops. The method showed promising results on a real-world dataset, allowing to observe the birth, evolution and death of clusters. The proposed approach facilitates identifying significant trends and changes, which empowers the monitoring high dimensional datasets’ dynamics.

Keywords: Concept drift, data visualization, dimension reduction, embedding, monitoring, reusability, t-SNE, unsupervised learning.

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8150 Annual Power Load Forecasting Using Support Vector Regression Machines: A Study on Guangdong Province of China 1985-2008

Authors: Zhiyong Li, Zhigang Chen, Chao Fu, Shipeng Zhang

Abstract:

Load forecasting has always been the essential part of an efficient power system operation and planning. A novel approach based on support vector machines is proposed in this paper for annual power load forecasting. Different kernel functions are selected to construct a combinatorial algorithm. The performance of the new model is evaluated with a real-world dataset, and compared with two neural networks and some traditional forecasting techniques. The results show that the proposed method exhibits superior performance.

Keywords: combinatorial algorithm, data mining, load forecasting, support vector machines

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8149 User Survey on Food and Drinks in Japanese Public Libraries

Authors: Marika Kawamoto, Keita Tsuji

Abstract:

Several decades ago, food and drinks were disallowed in most Japanese libraries. However, as discussions of “Library as a Place” have increased in recent years, the number of public and university libraries that have relaxed their policies to allow food and drinks have been increasing. This study focused on the opinions of library users on allowing food and drinks in public libraries and conducted a questionnaire survey among users of nine Japanese libraries. The results indicated that many users favored allowing food and drinks in libraries. Furthermore, it was found that users tend to frequently visit and stay longer in libraries where food and drinks are allowed.

Keywords: Food and drinks, Japanese libraries, opinions of users, public libraries.

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8148 A Hybrid Feature Subset Selection Approach based on SVM and Binary ACO. Application to Industrial Diagnosis

Authors: O. Kadri, M. D. Mouss, L.H. Mouss, F. Merah

Abstract:

This paper proposes a novel hybrid algorithm for feature selection based on a binary ant colony and SVM. The final subset selection is attained through the elimination of the features that produce noise or, are strictly correlated with other already selected features. Our algorithm can improve classification accuracy with a small and appropriate feature subset. Proposed algorithm is easily implemented and because of use of a simple filter in that, its computational complexity is very low. The performance of the proposed algorithm is evaluated through a real Rotary Cement kiln dataset. The results show that our algorithm outperforms existing algorithms.

Keywords: Binary Ant Colony algorithm, Support VectorMachine, feature selection, classification.

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8147 Mathematical Modeling of Machining Parameters in Electrical Discharge Machining of FW4 Welded Steel

Authors: M.R.Shabgard, R.M.Shotorbani

Abstract:

FW4 is a newly developed hot die material widely used in Forging Dies manufacturing. The right selection of the machining conditions is one of the most important aspects to take into consideration in the Electrical Discharge Machining (EDM) of FW4. In this paper an attempt has been made to develop mathematical models for relating the Material Removal Rate (MRR), Tool Wear Ratio (TWR) and surface roughness (Ra) to machining parameters (current, pulse-on time and voltage). Furthermore, a study was carried out to analyze the effects of machining parameters in respect of listed technological characteristics. The results of analysis of variance (ANOVA) indicate that the proposed mathematical models, can adequately describe the performance within the limits of the factors being studied.

Keywords: Electrical Discharge Machining (EDM), linearregression technique, Response Surface Methodology (RSM)

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8146 Actuator Fault Detection and Fault Tolerant Control of a Nonlinear System Using Sliding Mode Observer

Authors: R. Loukil, M. Chtourou, T. Damak

Abstract:

In this work, we use the Fault detection and isolation and the Fault tolerant control based on sliding mode observer in order to introduce the well diagnosis of a nonlinear system. The robustness of the proposed observer for the two techniques is tested through a physical example. The results in this paper show the interaction between the Fault tolerant control and the Diagnosis procedure.

Keywords: Fault detection and isolation “FDI”, Fault tolerant control “FTC”, sliding mode observer, nonlinear system, robustness, stability.

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8145 Performance Enhancement Employing Vertical Beamforming for FFR Technique

Authors: P. Chaipanya, P. Uthansakul, M. Uthansakul

Abstract:

This paper proposes a vertical beamforming concept to a cellular network employing Fractional Frequency Reuse technique including with cell sectorization. Two different beams are utilized in cell-center and cell-edge, separately. The proposed concept is validated through computer simulation in term of SINR and channel capacity. Also, comparison when utilizing horizontal and vertical beam formation is in focus. The obtained results indicate that the proposed concept can improve the performance of the cellular networks comparing with the one using horizontal beamforming.

Keywords: Beamforming, Fractional Frequency Reuse, Inter- Cell Interference, cell sectorization.

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8144 A Numerical Study of a Droplet Impinging on a Liquid Surface

Authors: S.Asadi, H.Panahi

Abstract:

The Navier–Stokes equations for unsteady, incompressible, viscous fluids in the axisymmetric coordinate system are solved using a control volume method. The volume-of-fluid (VOF) technique is used to track the free-surface of the liquid. Model predictions are in good agreement with experimental measurements. It is found that the dynamic processes after impact are sensitive to the initial droplet velocity and the liquid pool depth. The time evolution of the crown height and diameter are obtained by numerical simulation. The critical We number for splashing (Wecr) is studied for Oh (Ohnesorge) numbers in the range of 0.01~0.1; the results compares well with those of the experiments.

Keywords: Droplet impingement, free surface flows, liquid crown, numerical simulation, thin liquid film.

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8143 Transaction Costs in Institutional Environment and Entry Mode Choice

Authors: K. D. Mroczek

Abstract:

In the study presented institutional context is discussed in terms of companies’ entry mode choice. In contrary to many previous analyses, instead of using one or two aggregated variables, a set of eleven determinants is used to establish equity and non-equity internationalization friendly conditions. Based on secondary data, 140 countries are analyzed and grouped into clusters revealing similar framework. The range of the economies explored is wide as it covers all regions distinguished by The World Bank. The results can prove a useful alternative for operationalization of institutional variables in further research concerning entry modes or strategic management in international markets.

Keywords: Clustering, entry mode choice, institutional environment, transaction costs.

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8142 Assessment of Sediment Quality in the West Port Based On the Index Analysis Approach

Authors: S.B. Tavakoly Sany, A. Salleh, A.H. Sulaiman, G.H. Monazami

Abstract:

The coastal sediments of West Port of Malaysia was monitored from Nov. 2009 to Oct. 2010 to assess spatial distribution of heavy metals As, Cu, Cd, Cr, Hg, Ni, Zn and Pb. Sediment samples were collected from 10 stations in dry and rainy season in West Port. The range concentrations measured (Mg/g dry weight ) were from 23.4 to 98.3 for Zn, 22.3 to 80 for Pb, 7.4 to 27.6 Cu, 0.244 to 3.53 for Cd, 7.2 to 22.2 for Ni, 20.2 to 162 for As, 0.11 to 0.409 for Hg and 11.5 to 61.5 for Cr. The geochemical indexes used in this study were Geoaccumulation (Igeo), Contamination Factor (CF) and Pollution Load Index (PLI); these indexes were used to evaluate the levels of sediment contaminations. The results of these indexes show that, the status of West Port sediment quality are moderately polluted by heavy metals except in arsenic which shows the high level of pollution.

Keywords: Heavy metals, Sediment Quality, West Port.

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8141 A Unified Framework for a Robust Conflict-Free Robot Navigation

Authors: S. Veera Ragavan, V. Ganapathy

Abstract:

Many environment specific methods and systems for Robot Navigation exist. However vast strides in the evolution of navigation technologies and system techniques create the need for a general unified framework that is scalable, modular and dynamic. In this paper a Unified Framework for a Robust Conflict-free Robot Navigation System that can be used for either a structured or unstructured and indoor or outdoor environments has been proposed. The fundamental design aspects and implementation issues encountered during the development of the module are discussed. The results of the deployment of three major peripheral modules of the framework namely the GSM based communication module, GIS Module and GPS module are reported in this paper.

Keywords: Localization, Sensor Fusion, Mapping, GIS, GPS, and Autonomous Mobile Robot Navigation.

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8140 Highly Flexible Modularized Sensor Platform

Authors: Kai-Chao Yang, Chun-Ming Huang, Chih-Chiao Yang, Chien-Ming Wu

Abstract:

Sensors have been used in various kinds of academic fields and applications. In this article, we propose the idea of modularized sensors that combine multiple sensor modules into a unique sensor. We divide a sensor into several units according to functionalities. Each unit has different sensor modules, which share the same type of connectors and can be serially and arbitrarily connected each other. A user can combine different sensor modules into a sensor platform according to requirements. Compared with current modularized sensors, the proposed sensor platform is highly flexible and reusable. We have implemented the prototype of the proposed sensor platform, and the experimental results show the proposed platform can work correctly.

Keywords: Sensor device, sensor fusion.

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