Search results for: dental implant finite element method.
Commenced in January 2007
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Edition: International
Paper Count: 9181

Search results for: dental implant finite element method.

2191 Predicting the Life Cycle of Complex Technical Systems (CTS)

Authors: Khalil A. Yaghi, Samer Barakat

Abstract:

Complex systems are composed of several plain interacting independent entities. Interaction between these entities creates a unified behavior at the global level that cannot be predicted by examining the behavior of any single individual component of the system. In this paper we consider a welded frame of an automobile trailer as a real example of Complex Technical Systems, The purpose of this paper is to introduce a Statistical method for predicting the life cycle of complex technical systems. To organize gathering of primary data for modeling the life cycle of complex technical systems an “Automobile Trailer Frame" were used as a prototype in this research. The prototype represents a welded structure of several pieces. Both information flows underwent a computerized analysis and classification for the acquisition of final results to reach final recommendations for improving the trailers structure and their operational conditions.

Keywords: Complex Technical System (CTS), AutomobileTrailer Frame, Automobile Service.

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2190 Neuro-Fuzzy Network Based On Extended Kalman Filtering for Financial Time Series

Authors: Chokri Slim

Abstract:

The neural network's performance can be measured by efficiency and accuracy. The major disadvantages of neural network approach are that the generalization capability of neural networks is often significantly low, and it may take a very long time to tune the weights in the net to generate an accurate model for a highly complex and nonlinear systems. This paper presents a novel Neuro-fuzzy architecture based on Extended Kalman filter. To test the performance and applicability of the proposed neuro-fuzzy model, simulation study of nonlinear complex dynamic system is carried out. The proposed method can be applied to an on-line incremental adaptive learning for the prediction of financial time series. A benchmark case studie is used to demonstrate that the proposed model is a superior neuro-fuzzy modeling technique.

Keywords: Neuro-fuzzy, Extended Kalman filter, nonlinear systems, financial time series.

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2189 Improved Lung Nodule Visualization on Chest Radiographs using Digital Filtering and Contrast Enhancement

Authors: Benjamin Y. M. Kwan, Hon Keung Kwan

Abstract:

Early detection of lung cancer through chest radiography is a widely used method due to its relatively affordable cost. In this paper, an approach to improve lung nodule visualization on chest radiographs is presented. The approach makes use of linear phase high-frequency emphasis filter for digital filtering and histogram equalization for contrast enhancement to achieve improvements. Results obtained indicate that a filtered image can reveal sharper edges and provide more details. Also, contrast enhancement offers a way to further enhance the global (or local) visualization by equalizing the histogram of the pixel values within the whole image (or a region of interest). The work aims to improve lung nodule visualization of chest radiographs to aid detection of lung cancer which is currently the leading cause of cancer deaths worldwide.

Keywords: Chest radiographs, Contrast enhancement, Digital filtering, Lung nodule detection

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2188 Multi-View Neural Network Based Gait Recognition

Authors: Saeid Fazli, Hadis Askarifar, Maryam Sheikh Shoaie

Abstract:

Human identification at a distance has recently gained growing interest from computer vision researchers. Gait recognition aims essentially to address this problem by identifying people based on the way they walk [1]. Gait recognition has 3 steps. The first step is preprocessing, the second step is feature extraction and the third one is classification. This paper focuses on the classification step that is essential to increase the CCR (Correct Classification Rate). Multilayer Perceptron (MLP) is used in this work. Neural Networks imitate the human brain to perform intelligent tasks [3].They can represent complicated relationships between input and output and acquire knowledge about these relationships directly from the data [2]. In this paper we apply MLP NN for 11 views in our database and compare the CCR values for these views. Experiments are performed with the NLPR databases, and the effectiveness of the proposed method for gait recognition is demonstrated.

Keywords: Human motion analysis, biometrics, gait recognition, principal component analysis, MLP neural network.

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2187 A Hypercube Social Feature Extraction and Multipath Routing in Delay Tolerant Networks

Authors: S. Balaji, M. Rajaram, Y. Harold Robinson, E. Golden Julie

Abstract:

Delay Tolerant Networks (DTN) which have sufficient state information include trajectory and contact information, to protect routing efficiency. However, state information is dynamic and hard to obtain without a global and/or long-term collection process. To deal with these problems, the internal social features of each node are introduced in the network to perform the routing process. This type of application is motivated from several human contact networks where people contact each other more frequently if they have more social features in common. Two unique processes were developed for this process; social feature extraction and multipath routing. The routing method then becomes a hypercube–based feature matching process. Furthermore, the effectiveness of multipath routing is evaluated and compared to that of single-path routing.

Keywords: Delay tolerant networks, entropy, human contact networks, hyper cubes, multipath Routing, social features.

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2186 Critical Analysis of Heat Exchanger Cycle for its Maintainability Using Failure Modes and Effect Analysis and Pareto Analysis

Authors: Sayali Vyas, Atharva Desai, Shreyas Badave, Apurv Kulkarni, B. Rajiv

Abstract:

The Failure Modes and Effect Analysis (FMEA) is an efficient evaluation technique to identify potential failures in products, processes, and services. FMEA is designed to identify and prioritize failure modes. It proves to be a useful method for identifying and correcting possible failures at its earliest possible level so that one can avoid consequences of poor performance. In this paper, FMEA tool is used in detection of failures of various components of heat exchanger cycle and to identify critical failures of the components which may hamper the system’s performance. Further, a detailed Pareto analysis is done to find out the most critical components of the cycle, the causes of its failures, and possible recommended actions. This paper can be used as a checklist which will help in maintainability of the system.

Keywords: FMEA, heat exchanger cycle, Ishikawa diagram, Pareto analysis, risk priority number.

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2185 The Relationship between Fatigue Crack Growth and Residual Stress in Rails

Authors: F. Husem, M. E. Turan, Y. Sun, H. Ahlatci, I. Tozlu

Abstract:

Residual stress and fatigue crack growth rates are important to determine mechanical behavior of rails. This study aims to make relationship between residual stress and fatigue crack growth values in rails. For this purpose, three R260 quality rails (0.6-0.8% C, 0.6-1.25 Mn) were chosen. Residual stress of samples was measured by cutting method that is related in railway standard. Then samples were machined for fatigue crack growth test and analyze was completed according to the ASTM E647 standard which gives information about parameters of rails for this test. Microstructure characterizations were examined by Light Optic Microscope (LOM). The results showed that residual stress change with fatigue crack growth rate. The sample has highest residual stress exhibits highest crack growth rate and pearlitic structure can be seen clearly for all samples by microstructure analyze.

Keywords: Residual stress, fatigue crack growth, R260, LOM, ASTM E647.

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2184 Mathematical Programming on Multivariate Calibration Estimation in Stratified Sampling

Authors: Dinesh Rao, M.G.M. Khan, Sabiha Khan

Abstract:

Calibration estimation is a method of adjusting the original design weights to improve the survey estimates by using auxiliary information such as the known population total (or mean) of the auxiliary variables. A calibration estimator uses calibrated weights that are determined to minimize a given distance measure to the original design weights while satisfying a set of constraints related to the auxiliary information. In this paper, we propose a new multivariate calibration estimator for the population mean in the stratified sampling design, which incorporates information available for more than one auxiliary variable. The problem of determining the optimum calibrated weights is formulated as a Mathematical Programming Problem (MPP) that is solved using the Lagrange multiplier technique.

Keywords: Calibration estimation, Stratified sampling, Multivariate auxiliary information, Mathematical programming problem, Lagrange multiplier technique.

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2183 Five-axis Strip Machining with Barrel Cutter Based On Tolerance Constraint for Sculptured Surfaces

Authors: YaoAn Lu, QingZhen Bi, BaoRui Du, ShuLin Chen, LiMin Zhu, Kai Huang

Abstract:

Taking the design tolerance into account, this paper presents a novel efficient approach to generate iso-scallop tool path for five-axis strip machining with a barrel cutter. The cutter location is first determined on the scallop surface instead of the design surface, and then the cutter is adjusted to locate the optimal tool position based on the differential rotation of the tool axis and satisfies the design tolerance simultaneously. The machining strip width and error are calculated with the aid of the grazing curve of the cutter. Based on the proposed tool positioning algorithm, the tool paths are generated by keeping the scallop height formed by adjacent tool paths constant. An example is conducted to confirm the validity of the proposed method.

Keywords: Strip machining, barrel cutter, iso-scallop tool path, sculptured surfaces, differential motion.

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2182 Vision Based Hand Gesture Recognition

Authors: Pragati Garg, Naveen Aggarwal, Sanjeev Sofat

Abstract:

With the development of ubiquitous computing, current user interaction approaches with keyboard, mouse and pen are not sufficient. Due to the limitation of these devices the useable command set is also limited. Direct use of hands as an input device is an attractive method for providing natural Human Computer Interaction which has evolved from text-based interfaces through 2D graphical-based interfaces, multimedia-supported interfaces, to fully fledged multi-participant Virtual Environment (VE) systems. Imagine the human-computer interaction of the future: A 3Dapplication where you can move and rotate objects simply by moving and rotating your hand - all without touching any input device. In this paper a review of vision based hand gesture recognition is presented. The existing approaches are categorized into 3D model based approaches and appearance based approaches, highlighting their advantages and shortcomings and identifying the open issues.

Keywords: Computer Vision, Hand Gesture, Hand Posture, Human Computer Interface.

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2181 Synthetic Daily Flow Duration Curves for the Çoruh River Basin, Turkey

Authors: Fatih Tosunoğlu, İbrahim Can

Abstract:

The flow duration curve (FDC) is an informative method that represents the flow regime’s properties for a river basin. Therefore, the FDC is widely used for water resource projects such as hydropower, water supply, irrigation and water quality management. The primary purpose of this study is to obtain synthetic daily flow duration curves for Çoruh Basin, Turkey. For this aim, we firstly developed univariate auto-regressive moving average (ARMA) models for daily flows of 9 stations located in Çoruh basin and then these models were used to generate 100 synthetic flow series each having same size as historical series. Secondly, flow duration curves of each synthetic series were drawn and the flow values exceeded 10, 50 and 95% of the time and 95% confidence limit of these flows were calculated. As a result, flood, mean and low flows potential of Çoruh basin will comprehensively be represented.

Keywords: ARMA models, Çoruh basin, flow duration curve, Turkey.

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2180 Exploring the Role of Private Commercial Banks in Increasing Small and Medium Size Enterprises’ Financial Accessibility in Developing Countries: A Study in Bangladesh

Authors: Khondokar Farid Ahmmed, Robin Bown

Abstract:

It is widely recognized that the formal financing of Small and Medium Size Enterprises (SMEs) by Private Commercial Banks (PCBs) is restricted. Due to changing financial market competition, SMEs are now important customers to PCBs in the member countries of the Asian Development Bank (ADB). Various initiatives in enhancing the efficiency of risk assessment of PCBs have failed in increasing financing accessibility in the traditional financing system where information asymmetry is a key constraint. In this circumstance, PCBs need to undertake a holistic approach. Holistic approach refers to methods that attempt to fundamentally change established traditions. To undertake holistic approach, this study intends to find the entire established financing culture between PCBs and SMEs in a new lens beyond the tradition on the basis of two basic questions: “What is the traditional lending culture between PCBs and SMEs” and “What could be potential role of PCBs to develop that culture where focusing on SME financing to PCBs". This study considered formal SME financing in Bangladesh by focusing on SMEs applying for their first loan. Bangladesh is a member country of ADB. The data collection method is semi-structured and we utilized face-to-face interviews with in-depth branch managers, higher officials and owner-managers of SME customers of PCBs and higher officials of SME Foundation and the Bangladesh central bank. Discourse analysis method was used for data analysis on the frame of thematic discussion fully based on participants’ views. The research found that branch managers and loan officers have a high level of power in assessing and financing decision-making. There is a changing attitude in PCB sector in requiring flexible collateral assets. Branch managers (Loan Officers) consider value of business prospect of owner-mangers as complementary of collateral assets. However, the study found the assessment process of business prospect is entirely unstructured and linked with socio-cultural settings that does not support PCBs’ changing manner in terms of collateral requirement. The study redefined and classified collateral assets to include all financing constructs in a structure. The degree of value of the collateral assets determines the degree of business prospects. This study suggested applying an outside classroom-learning paradigm such as “knowledge tour” to enhance the value of the kinds of collateral assets. This is the scope of PCBs in increasing SMEs’ financing eligibility in win-win basis. The findings and proposition could be effective in other ADB member countries and audiences in the field.

Keywords: CCA, financing, information asymmetry, PCA, PCB, financing.

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2179 Frequency Transformation with Pascal Matrix Equations

Authors: Phuoc Si Nguyen

Abstract:

Frequency transformation with Pascal matrix equations is a method for transforming an electronic filter (analogue or digital) into another filter. The technique is based on frequency transformation in the s-domain, bilinear z-transform with pre-warping frequency, inverse bilinear transformation and a very useful application of the Pascal’s triangle that simplifies computing and enables calculation by hand when transforming from one filter to another. This paper will introduce two methods to transform a filter into a digital filter: frequency transformation from the s-domain into the z-domain; and frequency transformation in the z-domain. Further, two Pascal matrix equations are derived: an analogue to digital filter Pascal matrix equation and a digital to digital filter Pascal matrix equation. These are used to design a desired digital filter from a given filter.

Keywords: Frequency transformation, Bilinear z-transformation, Pre-warping frequency, Digital filters, Analog filters, Pascal’s triangle.

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2178 Dynamic Slope Scaling Procedure for Stochastic Integer Programming Problem

Authors: Takayuki Shiina

Abstract:

Mathematical programming has been applied to various problems. For many actual problems, the assumption that the parameters involved are deterministic known data is often unjustified. In such cases, these data contain uncertainty and are thus represented as random variables, since they represent information about the future. Decision-making under uncertainty involves potential risk. Stochastic programming is a commonly used method for optimization under uncertainty. A stochastic programming problem with recourse is referred to as a two-stage stochastic problem. In this study, we consider a stochastic programming problem with simple integer recourse in which the value of the recourse variable is restricted to a multiple of a nonnegative integer. The algorithm of a dynamic slope scaling procedure for solving this problem is developed by using a property of the expected recourse function. Numerical experiments demonstrate that the proposed algorithm is quite efficient. The stochastic programming model defined in this paper is quite useful for a variety of design and operational problems.

Keywords: stochastic programming problem with recourse, simple integer recourse, dynamic slope scaling procedure

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2177 Designing a Single-Floor Structure for the Control Room of a Petroleum Refinery and Assessing the Resistance of Such a Structure against Gas Explosion Load

Authors: Amin Lotfi Eghlim, Mehran pourgholi

Abstract:

Explosion occurs due to sudden release of energy. Common examples of explosion include chemical, atomic, heat, and pressure tank (due to ignition) explosions. Petroleum, gas, and petrochemical industries operations are threatened by natural risks and processes. Fires and explosions are the greatest process risks which cause financial damages. This study aims at designing a single-floor structure for the control room of a petroleum refinery to be resistant against gas explosion loads, and the information related to the structure specifications have been provided regarding the fact that the structure is made on the ground's surface. In this research, the lateral stiffness of single pile is calculated by SPPLN.FOR computer program, and its value for 13624 KN/m single pile has been assessed. The analysis used due to the loading conditions, is dynamic nonlinear analysis with direct integration method.

Keywords: Gas Explosion Load, Petroleum Refinery, Single-Floor Structure

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2176 Numerical Simulation of Convective Heat Transfer and Fluid Flow through Porous Media with Different Moving and Heated Walls

Authors: Laith Jaafer Habeeb

Abstract:

The present study is concerned with the free convective two dimensional flow and heat transfer, within the framework of Boussinesq approximation, in anisotropic fluid filled porous rectangular enclosure subjected to end-to-end temperature difference have been investigated using Lattice Boltzmann method fornon-Darcy flow model. Effects of the moving lid direction (top, bottom, left, and right wall moving in the negative and positive x&ydirections), number of moving walls (one or two opposite walls), the sliding wall velocity, and four different constant temperatures opposite walls cases (two surfaces are being insulated and the twoother surfaces areimposed to be at constant hot and cold temperature)have been conducted. The results obtained are discussed in terms of the Nusselt number, vectors, contours, and isotherms.

Keywords: Numerical simulation, lid-driven cavity flow, saturated porous medium, different velocity and heated walls.

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2175 Enhanced Genetic Algorithm Approach for Security Constrained Optimal Power Flow Including FACTS Devices

Authors: R.Narmatha Banu, D.Devaraj

Abstract:

This paper presents a genetic algorithm based approach for solving security constrained optimal power flow problem (SCOPF) including FACTS devices. The optimal location of FACTS devices are identified using an index called overload index and the optimal values are obtained using an enhanced genetic algorithm. The optimal allocation by the proposed method optimizes the investment, taking into account its effects on security in terms of the alleviation of line overloads. The proposed approach has been tested on IEEE-30 bus system to show the effectiveness of the proposed algorithm for solving the SCOPF problem.

Keywords: Optimal Power Flow, Genetic Algorithm, FlexibleAC transmission system (FACTS) devices, Severity Index (SI), Security Enhancement, Thyristor controlled series capacitor (TCSC).

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2174 3A Distributed Method Algorithm for Exact Side Load Managing Smart Grid Using LABVIEW

Authors: N. Ravi Kumar, R. Kamalakannan

Abstract:

The advancement of hybrid energy resources such as solar and wind power leading to the emergence of customer owned grid. It provides an opportunity to regulars to obtain low energy costs as well as enabling the power supplier to regulate the utility grid. There is a need to develop smart systems that will automatically submit energy demand schedule and monitors energy price signals in real-time without the prompt of customers. In this paper, a demand side energy management for a grid connected household and also smart preparation of electrical appliance have been presented. It also reduces electricity bill for the consumers in the grid. In addition to this, when production is high, the surplus energy fashioned in the customer owned grid is given to main grid or neighboring micro grids. The simulation of the entire system is presented using LabVIEW software.

Keywords: Distributed renewable energy resource, power storage devices, scheduling, smart meters, smart micro grid, electric vehicle.

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2173 Efficiency Improvements of GaAs-based Solar Cells by Hydrothermally-deposited ZnO Nanostructure Array

Authors: Chun-Yuan Huang, Chiao-Yang Cheng, Chun-Yem Huang, Yan-Kuin Su, James Chin-Lung Fang

Abstract:

ZnO nanostructures including nanowires, nanorods, and nanoneedles were successfully deposited on GaAs substrates, respectively, by simple two-step chemical method for the first time. A ZnO seed layer was firstly pre-coated on the O2-plasma treated substrate by sol-gel process, followed by the nucleation of ZnO nanostructures through hydrothermal synthesis. Nanostructures with different average diameter (15-250 nm), length (0.9-1.8 μm), density (0.9-16×109 cm-2) were obtained via adjusting the growth time and concentration of precursors. From the reflectivity spectra, we concluded ordered and taper nanostructures were preferential for photovoltaic applications. ZnO nanoneedles with an average diameter of 106 nm, a moderate length of 2.4 μm, and the density of 7.2×109 cm-2 could be synthesized in the concentration of 0.04 M for 18 h. Integrated with the nanoneedle array, the power conversion efficiency of single junction solar cell was increased from 7.3 to 12.2%, corresponding to a 67% improvement.

Keywords: Anti-reflection, Chemical synthesis, Solar cells, ZnO nanostructures.

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2172 Determining Earthquake Performances of Existing Reinforced Concrete Buildings by Using ANN

Authors: Musa H. Arslan, Murat Ceylan, Tayfun Koyuncu

Abstract:

In this study, an Artificial Neural Network (ANN) analytical method has been developed for analyzing earthquake performances of the Reinforced Concrete (RC) buildings. 66 RC buildings with four to ten storeys were subjected to performance analysis according to the parameters which are the existing material, loading and geometrical characteristics of the buildings. The selected parameters have been thought to be effective on the performance of RC buildings. In the performance analyses stage of the study, level of performance possible to be shown by these buildings in case of an earthquake was determined on the basis of the 4-grade performance levels specified in Turkish Earthquake Code-2007 (TEC-2007). After obtaining the 4-grade performance level, selected 23 parameters of each building have been matched with the performance level. In this stage, ANN-based fast evaluation algorithm mentioned above made an economic and rapid evaluation of four to ten storey RC buildings. According to the study, the prediction accuracy of ANN has been found about 74%.

Keywords: Artificial neural network, earthquake, performance, reinforced concrete.

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2171 Time Series Modelling and Prediction of River Runoff: Case Study of Karkheh River, Iran

Authors: Karim Hamidi Machekposhti, Hossein Sedghi, Abdolrasoul Telvari, Hossein Babazadeh

Abstract:

Rainfall and runoff phenomenon is a chaotic and complex outcome of nature which requires sophisticated modelling and simulation methods for explanation and use. Time Series modelling allows runoff data analysis and can be used as forecasting tool. In the paper attempt is made to model river runoff data and predict the future behavioural pattern of river based on annual past observations of annual river runoff. The river runoff analysis and predict are done using ARIMA model. For evaluating the efficiency of prediction to hydrological events such as rainfall, runoff and etc., we use the statistical formulae applicable. The good agreement between predicted and observation river runoff coefficient of determination (R2) display that the ARIMA (4,1,1) is the suitable model for predicting Karkheh River runoff at Iran.

Keywords: Time series modelling, ARIMA model, River runoff, Karkheh River, CLS method.

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2170 Deep iCrawl: An Intelligent Vision-Based Deep Web Crawler

Authors: R.Anita, V.Ganga Bharani, N.Nityanandam, Pradeep Kumar Sahoo

Abstract:

The explosive growth of World Wide Web has posed a challenging problem in extracting relevant data. Traditional web crawlers focus only on the surface web while the deep web keeps expanding behind the scene. Deep web pages are created dynamically as a result of queries posed to specific web databases. The structure of the deep web pages makes it impossible for traditional web crawlers to access deep web contents. This paper, Deep iCrawl, gives a novel and vision-based approach for extracting data from the deep web. Deep iCrawl splits the process into two phases. The first phase includes Query analysis and Query translation and the second covers vision-based extraction of data from the dynamically created deep web pages. There are several established approaches for the extraction of deep web pages but the proposed method aims at overcoming the inherent limitations of the former. This paper also aims at comparing the data items and presenting them in the required order.

Keywords: Crawler, Deep web, Web Database

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2169 Peculiarities of Implementation of Branding Principles

Authors: Maia Seturi

Abstract:

One of the topical issues for the companies operating in the present-day conditions is making decisions about creation and development of brands. The goal of the research was to study peculiarities of implementation of branding principles using the well-known Georgian mineral water Borjomi as an example, to establish the attitude of consumers to Borjomi at Georgian market, to determine the discovered weaknesses based on the result of the research and to make certain proposals and give recommendations, which would help Georgian companies interested in branding issues to pay proper attention to fundamental principles of branding in their marketing activities. As a result of the marketing research, it was found out that Borjomi adhere to a number of branding principles in its activity, although it has certain shortcomings in that respect. The research method was of exploratory and descriptive nature. In the conclusive part of the work is given sum up research results, draw conclusions and give recommendations. If companies existing in Georgia will take them into consideration, it will help them to better make sense of branding and main aspects of using its principles.

Keywords: Marketing research, brand, branding principles, brand awareness, brand originality.

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2168 iCCS: Development of a Mobile Web-Based Student Integrated Information System Using Hill Climbing Algorithm

Authors: Maria Cecilia G. Cantos, Lorena W. Rabago, Bartolome T. Tanguilig III

Abstract:

This paper describes a conducive and structured information exchange environment for the students of the College of Computer Studies in Manuel S. Enverga University Foundation in. The system was developed to help the students to check their academic result, manage profile, make self-enlistment and assist the students to manage their academic status that can be viewed also in mobile phones. Developing class schedules in a traditional way is a long process that involves making many numbers of choices. With Hill Climbing Algorithm, however, the process of class scheduling, particularly with regards to courses to be taken by the student aligned with the curriculum, can perform these processes and end up with an optimum solution. The proponent used Rapid Application Development (RAD) for the system development method. The proponent also used the PHP as the programming language and MySQL as the database.

Keywords: Hill climbing algorithm, integrated system, mobile web-based, student information system.

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2167 Hybrid Machine Learning Approach for Text Categorization

Authors: Nerijus Remeikis, Ignas Skucas, Vida Melninkaite

Abstract:

Text categorization - the assignment of natural language documents to one or more predefined categories based on their semantic content - is an important component in many information organization and management tasks. Performance of neural networks learning is known to be sensitive to the initial weights and architecture. This paper discusses the use multilayer neural network initialization with decision tree classifier for improving text categorization accuracy. An adaptation of the algorithm is proposed in which a decision tree from root node until a final leave is used for initialization of multilayer neural network. The experimental evaluation demonstrates this approach provides better classification accuracy with Reuters-21578 corpus, one of the standard benchmarks for text categorization tasks. We present results comparing the accuracy of this approach with multilayer neural network initialized with traditional random method and decision tree classifiers.

Keywords: Text categorization, decision trees, neural networks, machine learning.

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2166 The Potency of Sandfish (Holothuria scraba) as a Source of Natural Aphrodisiacs

Authors: Etty Riani, Endang Gumbira-Said, Kashwar Syamsu, Kustiariyah, Kaseno, Muhammad Reza Cordova

Abstract:

Sandfish is one of marine biota that has a biomedicine (bioactive compound) potency. People in Gorontalo Province, Indonesia, have been sandfish as an aphrodisiac for men as it is believed that sandfish has a steroid hormone potency. This research aims at studying using the steroid hormone potency from every fraction of sandfish (meat and innards) and its activity of male reproduction (rooster) as an aphrodisiac. Steroid extraction was done using Touchstone and Kasparow method, and then it was utilized to study the effectiveness of bioassay of rooster. This research had five treatments and was done in complete randomized design. Based on Lieberman-Burchard and bioassay test, the author found that sandfish extract contains steroid hormone. Sandfish extract was able to enrich testosterone and cholesterol concentration in blood serum; fastening secondary reproduction characteristics of the rooster, and increasing growth as well as improving rooster’s comb. Therefore, sandfish steroid is potential to be used as an aphrodisiac for men.

Keywords: Aphrodisiac, sandfish, secondary reproduction characteristic, steroid.

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2165 Optimizing Boiler Combustion System in a Petrochemical Plant Using Neuro-Fuzzy Inference System and Genetic Algorithm

Authors: Yul Y. Nazaruddin, Anas Y. Widiaribowo, Satriyo Nugroho

Abstract:

Boiler is one of the critical unit in a petrochemical plant. Steam produced by the boiler is used for various processes in the plant such as urea and ammonia plant. An alternative method to optimize the boiler combustion system is presented in this paper. Adaptive Neuro-Fuzzy Inference System (ANFIS) approach is applied to model the boiler using real-time operational data collected from a boiler unit of the petrochemical plant. Nonlinear equation obtained is then used to optimize the air to fuel ratio using Genetic Algorithm, resulting an optimal ratio of 15.85. This optimal ratio is then maintained constant by ratio controller designed using inverse dynamics based on ANFIS. As a result, constant value of oxygen content in the flue gas is obtained which indicates more efficient combustion process.

Keywords: ANFIS, boiler, combustion process, genetic algorithm, optimization.

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2164 Detection of Voltage Sag and Voltage Swell in Power Quality Using Wavelet Transforms

Authors: Nor Asrina Binti Ramlee

Abstract:

Voltage sag, voltage swell, high-frequency noise and voltage transients are kinds of disturbances in power quality. They are also known as power quality events. Equipment used in the industry nowadays has become more sensitive to these events with the increasing complexity of equipment. This leads to the importance of distributing clean power quality to the consumer. To provide better service, the best analysis on power quality is very vital. Thus, this paper presents the events detection focusing on voltage sag and swell. The method is developed by applying time domain signal analysis using wavelet transform approach in MATLAB. Four types of mother wavelet namely Haar, Dmey, Daubechies, and Symlet are used to detect the events. This project analyzed real interrupted signal obtained from 22 kV transmission line in Skudai, Johor Bahru, Malaysia. The signals will be decomposed through the wavelet mothers. The best mother is the one that is capable to detect the time location of the event accurately.

Keywords: Power quality, voltage sag, voltage swell, wavelet transform.

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2163 Economic Factors Affecting Rice Export of Thailand

Authors: Somphoom Sawaengkun

Abstract:

The purpose of this study was primarily assessing how important economic factors namely: The Thai export price of white rice, the exchange rate, and the world rice consumption affect the overall Thai white rice export, using historical data during the period 1989-2013 from the Thai Rice Exporters Association, and Food and Agricultural Organization of the United Nations. The co-integration method, regression analysis, and error correction model were applied to investigate the econometric model. The findings indicated that in the long-run, the world rice consumption, the exchange rate, and the Thai export price of white rice were the important factors affecting the export quantity of Thai white rice respectively, as indicated by their significant coefficients. Meanwhile, the rice export price was an important factor affecting the export quantity of Thai white rice in the short-run. This information is useful in the business, export opportunities, price competitiveness, and policymaker in Thailand.

Keywords: Economic Factors, Rice Export, White Rice.

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2162 Big Bang – Big Crunch Learning Method for Fuzzy Cognitive Maps

Authors: Engin Yesil, Leon Urbas

Abstract:

Modeling of complex dynamic systems, which are very complicated to establish mathematical models, requires new and modern methodologies that will exploit the existing expert knowledge, human experience and historical data. Fuzzy cognitive maps are very suitable, simple, and powerful tools for simulation and analysis of these kinds of dynamic systems. However, human experts are subjective and can handle only relatively simple fuzzy cognitive maps; therefore, there is a need of developing new approaches for an automated generation of fuzzy cognitive maps using historical data. In this study, a new learning algorithm, which is called Big Bang-Big Crunch, is proposed for the first time in literature for an automated generation of fuzzy cognitive maps from data. Two real-world examples; namely a process control system and radiation therapy process, and one synthetic model are used to emphasize the effectiveness and usefulness of the proposed methodology.

Keywords: Big Bang-Big Crunch optimization, Dynamic Systems, Fuzzy Cognitive Maps, Learning.

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