Search results for: Taylor Rule.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 414

Search results for: Taylor Rule.

234 Interaction of Electroosmotic Flow on Isotachophoretic Transport of Ions

Authors: S. Bhattacharyya, Partha P. Gopmandal

Abstract:

A numerical study on the influence of electroosmotic flow on analyte preconcentration by isotachophoresis ( ITP) is made. We consider that the double layer induced electroosmotic flow ( EOF) counterbalance the electrophoretic velocity and a stationary ITP stacked zones results. We solve the Navier-Stokes equations coupled with the Nernst-Planck equations to determine the local convective velocity and the preconcentration dynamics of ions. Our numerical algorithm is based on a finite volume method along with a secondorder upwind scheme. The present numerical algorithm can capture the the sharp boundaries of step-changes ( plateau mode) or zones of steep gradients ( peak mode) accurately. The convection of ions due to EOF reduces the resolution of the ITP transition zones and produces a dispersion in analyte zones. The role of the electrokinetic parameters which induces dispersion is analyzed. A one-dimensional model for the area-averaged concentrations based on the Taylor-Aristype effective diffusivity is found to be in good agreement with the computed solutions.

Keywords: Interfaces, Electroosmotic flow, QUICK Scheme, Dispersion, Effective Diffusivity.

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233 Classification of Health Risk Factors to Predict the Risk of Falling in Older Adults

Authors: L. Lindsay, S. A. Coleman, D. Kerr, B. J. Taylor, A. Moorhead

Abstract:

Cognitive decline and frailty is apparent in older adults leading to an increased likelihood of the risk of falling. Currently health care professionals have to make professional decisions regarding such risks, and hence make difficult decisions regarding the future welfare of the ageing population. This study uses health data from The Irish Longitudinal Study on Ageing (TILDA), focusing on adults over the age of 50 years, in order to analyse health risk factors and predict the likelihood of falls. This prediction is based on the use of machine learning algorithms whereby health risk factors are used as inputs to predict the likelihood of falling. Initial results show that health risk factors such as long-term health issues contribute to the number of falls. The identification of such health risk factors has the potential to inform health and social care professionals, older people and their family members in order to mitigate daily living risks.

Keywords: Classification, falls, health risk factors, machine learning, older adults.

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232 Compressible Lattice Boltzmann Method for Turbulent Jet Flow Simulations

Authors: K. Noah, F.-S. Lien

Abstract:

In Computational Fluid Dynamics (CFD), there are a variety of numerical methods, of which some depend on macroscopic model representatives. These models can be solved by finite-volume, finite-element or finite-difference methods on a microscopic description. However, the lattice Boltzmann method (LBM) is considered to be a mesoscopic particle method, with its scale lying between the macroscopic and microscopic scales. The LBM works well for solving incompressible flow problems, but certain limitations arise from solving compressible flows, particularly at high Mach numbers. An improved lattice Boltzmann model for compressible flow problems is presented in this research study. A higher-order Taylor series expansion of the Maxwell equilibrium distribution function is used to overcome limitations in LBM when solving high-Mach-number flows. Large eddy simulation (LES) is implemented in LBM to simulate turbulent jet flows. The results have been validated with available experimental data for turbulent compressible free jet flow at subsonic speeds.

Keywords: Compressible lattice Boltzmann metho-, large eddy simulation, turbulent jet flows.

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231 Control and Navigation with Knowledge Bases

Authors: Miloš Šeda, Tomáš Březina

Abstract:

In this paper, we focus on the use of knowledge bases in two different application areas – control of systems with unknown or strongly nonlinear models (i.e. hardly controllable by the classical methods), and robot motion planning in eight directions. The first one deals with fuzzy logic and the paper presents approaches for setting and aggregating the rules of a knowledge base. Te second one is concentrated on a case-based reasoning strategy for finding the path in a planar scene with obstacles.

Keywords: fuzzy controller, fuzzification, rule base, inference, defuzzification, genetic algorithm, neural network, case-based reasoning

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230 Application of Differential Transformation Method for Solving Dynamical Transmission of Lassa Fever Model

Authors: M. A. Omoloye, M. I. Yusuff, O. K. S. Emiola

Abstract:

The use of mathematical models for solving biological problems varies from simple to complex analyses, depending on the nature of the research problems and applicability of the models. The method is more common nowadays. Many complex models become impractical when transmitted analytically. However, alternative approach such as numerical method can be employed. It appropriateness in solving linear and non-linear model equation in Differential Transformation Method (DTM) which depends on Taylor series make it applicable. Hence this study investigates the application of DTM to solve dynamic transmission of Lassa fever model in a population. The mathematical model was formulated using first order differential equation. Firstly, existence and uniqueness of the solution was determined to establish that the model is mathematically well posed for the application of DTM. Numerically, simulations were conducted to compare the results obtained by DTM and that of fourth-order Runge-Kutta method. As shown, DTM is very effective in predicting the solution of epidemics of Lassa fever model.

Keywords: Differential Transform Method, Existence and uniqueness, Lassa fever, Runge-Kutta Method.

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229 Development and Validation of Cylindrical Linear Oscillating Generator

Authors: Sungin Jeong

Abstract:

This paper presents a linear oscillating generator of cylindrical type for hybrid electric vehicle application. The focus of the study is the suggestion of the optimal model and the design rule of the cylindrical linear oscillating generator with permanent magnet in the back-iron translator. The cylindrical topology is achieved using equivalent magnetic circuit considering leakage elements as initial modeling. This topology with permanent magnet in the back-iron translator is described by number of phases and displacement of stroke. For more accurate analysis of an oscillating machine, it will be compared by moving just one-pole pitch forward and backward the thrust of single-phase system and three-phase system. Through the analysis and comparison, a single-phase system of cylindrical topology as the optimal topology is selected. Finally, the detailed design of the optimal topology takes the magnetic saturation effects into account by finite element analysis. Besides, the losses are examined to obtain more accurate results; copper loss in the conductors of machine windings, eddy-current loss of permanent magnet, and iron-loss of specific material of electrical steel. The considerations of thermal performances and mechanical robustness are essential, because they have an effect on the entire efficiency and the insulations of the machine due to the losses of the high temperature generated in each region of the generator. Besides electric machine with linear oscillating movement requires a support system that can resist dynamic forces and mechanical masses. As a result, the fatigue analysis of shaft is achieved by the kinetic equations. Also, the thermal characteristics are analyzed by the operating frequency in each region. The results of this study will give a very important design rule in the design of linear oscillating machines. It enables us to more accurate machine design and more accurate prediction of machine performances.

Keywords: Equivalent magnetic circuit, finite element analysis, hybrid electric vehicle, free piston engine, cylindrical linear oscillating generator

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228 Identifying an Unknown Source in the Poisson Equation by a Modified Tikhonov Regularization Method

Authors: Ou Xie, Zhenyu Zhao

Abstract:

In this paper, we consider the problem for identifying the unknown source in the Poisson equation. A modified Tikhonov regularization method is presented to deal with illposedness of the problem and error estimates are obtained with an a priori strategy and an a posteriori choice rule to find the regularization parameter. Numerical examples show that the proposed method is effective and stable.

Keywords: Ill-posed problem, Unknown source, Poisson equation, Tikhonov regularization method, Discrepancy principle

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227 Two-dimensional Differential Transform Method for Solving Linear and Non-linear Goursat Problem

Authors: H. Taghvafard, G. H. Erjaee

Abstract:

A method for solving linear and non-linear Goursat problem is given by using the two-dimensional differential transform method. The approximate solution of this problem is calculated in the form of a series with easily computable terms and also the exact solutions can be achieved by the known forms of the series solutions. The method can easily be applied to many linear and non-linear problems and is capable of reducing the size of computational work. Several examples are given to demonstrate the reliability and the performance of the presented method.

Keywords: Quadrature, Spline interpolation, Trapezoidal rule, Numericalintegration, Error analysis.

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226 A Study on the Mobile Web Generating using Element of User Experience

Authors: Heeae Ko, Jongkeun Kim, Kunjung Sim, Kunho Sim, Yonghwan Lim

Abstract:

As mobile service's subscriber is increasing; mobile contents services are getting more and more variables. So, mobile contents development needs not only contents design but also guideline for just mobile. And when mobile contents are developed, it is important to pass the limit and restriction of the mobile. The restrictions of mobile are small browser and screen size, limited download size and uncomfortable navigation. So each contents of mobile guideline will be presented for user's usability, easy of development and consistency of rule. This paper will be proposed methodology which is each contents of mobile guideline. Mobile web will be developed by mobile guideline which I proposed.

Keywords: Guideline, interface, mobile, mobile computing, userexperience.

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225 A Study on using N-Pattern Chains of Design Patterns based on Software Quality Metrics

Authors: Niloofar Khedri, Masoud Rahgozar, MahmoudReza Hashemi

Abstract:

Design patterns describe good solutions to common and reoccurring problems in program design. Applying design patterns in software design and implementation have significant effects on software quality metrics such as flexibility, usability, reusability, scalability and robustness. There is no standard rule for using design patterns. There are some situations that a pattern is applied for a specific problem and this pattern uses another pattern. In this paper, we study the effect of using chain of patterns on software quality metrics.

Keywords: Design Patterns, Design patterns' Relationship, Software quality Metrics, Software Engineering.

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224 Proposition for a New Approach of Version Control System Based On ECA Active Rules

Authors: S. Benhamed, S. Hocine, D. Benhamamouch

Abstract:

We try to give a solution of version control for documents in web service, that-s why we propose a new approach used specially for the XML documents. The new approach is applied in a centralized repository, this repository coexist with other repositories in a decentralized system. To achieve the activities of this approach in a standard model we use the ECA active rules. We also show how the Event-Condition-Action rules (ECA rules) have been incorporated as a mechanism for the version control of documents. The need to integrate ECA rules is that it provides a clear declarative semantics and induces an immediate operational realization in the system without the need for human intervention.

Keywords: ECA Rule, Web service, version control system, propagation.

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223 TRS: System for Recommending Semantic Web Service Composition Approaches

Authors: Sandeep Kumar, R. B. Mishra

Abstract:

A large number of semantic web service composition approaches are developed by the research community and one is more efficient than the other one depending on the particular situation of use. So a close look at the requirements of ones particular situation is necessary to find a suitable approach to use. In this paper, we present a Technique Recommendation System (TRS) which using a classification of state-of-art semantic web service composition approaches, can provide the user of the system with the recommendations regarding the use of service composition approach based on some parameters regarding situation of use. TRS has modular architecture and uses the production-rules for knowledge representation.

Keywords: Classification, composition techniques, recommendation system, rule-based, semantic web service.

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222 Performance of Neural Networks vs. Radial Basis Functions When Forming a Metamodel for Residential Buildings

Authors: Philip Symonds, Jon Taylor, Zaid Chalabi, Michael Davies

Abstract:

Average temperatures worldwide are expected to continue to rise. At the same time, major cities in developing countries are becoming increasingly populated and polluted. Governments are tasked with the problem of overheating and air quality in residential buildings. This paper presents the development of a model, which is able to estimate the occupant exposure to extreme temperatures and high air pollution within domestic buildings. Building physics simulations were performed using the EnergyPlus building physics software. An accurate metamodel is then formed by randomly sampling building input parameters and training on the outputs of EnergyPlus simulations. Metamodels are used to vastly reduce the amount of computation time required when performing optimisation and sensitivity analyses. Neural Networks (NNs) have been compared to a Radial Basis Function (RBF) algorithm when forming a metamodel. These techniques were implemented using the PyBrain and scikit-learn python libraries, respectively. NNs are shown to perform around 15% better than RBFs when estimating overheating and air pollution metrics modelled by EnergyPlus.

Keywords: Neural Networks, Radial Basis Functions, Metamodelling, Python machine learning libraries.

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221 Knowledge Acquisition and Client Organisations: Case Study of a Student as Producer

Authors: Barry Ardley, Abi Hunt, Nick Taylor

Abstract:

As a theoretical and practical framework this study uses the student as producer approach to learning in higher education, as adopted by the Lincoln International Business School, University of Lincoln, UK. Student as producer positions learners as skilled and capable agents, able to participate as partners with tutors in live research projects. To illuminate the nature of this approach to learning and to highlight its critical issues, the authors report on two guided student consultancy projects. These were set up with the assistance of two local organisations in the city of Lincoln UK. Using the student as producer model to deliver the projects enabled learners to acquire and develop a range of key skills and knowledge, not easily accessible in more traditional educational settings. This paper presents a systematic case study analysis of the eight organising principles of the student as producer model, as adopted by university tutors. The experience of tutors implementing student as producer suggests that the model can be widely applied to benefit not only the learning and teaching experiences of higher education students, and staff, but additionally, a university’s research programme and its community partners.

Keywords: Experiential learning, consultancy clients, student as producer.

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220 Fuzzy Processing of Uncertain Data

Authors: Petr Morávek, Miloš Šeda

Abstract:

In practice, we often come across situations where it is necessary to make decisions based on incomplete or uncertain data. In control systems it may be due to the unknown exact mathematical model, or its excessive complexity (e.g. nonlinearity) when it is necessary to simplify it, respectively, to solve it using a rule base. In the case of databases, searching data we compare a similarity measure with of the requirements of the selection with stored data, where both the select query and the data itself may contain vague terms, for example in the form of linguistic qualifiers. In this paper, we focus on the processing of uncertain data in databases and demonstrate it on the example multi-criteria decision making in the selection of variants, specified by higher number of technical parameters.

Keywords: fuzzy logic, linguistic variable, multicriteria decision

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219 Determination of Q and R Matrices for Optimal Pitch Aircraft Control

Authors: N. Popovich, P. Yan

Abstract:

In this paper, the process of obtaining Q and R matrices for optimal pitch aircraft control system has been described. Since the innovation of optimal control method, the determination of Q and R matrices for such system has not been fully specified. The value of Q and R for optimal pitch aircraft control application, have been simulated and calculated. The suitable results for Q and R have been observed through the performance index (PI). If the PI is small “enough", we would say the Q & R values are suitable for that certain type of optimal control system. Moreover, for the same value of PI, we could have different Q and R sets. Due to the rule-free determination of Q and R matrices, a specific method is brought to find out the rough value of Q and R referring to rather small value of PI.

Keywords: Aircraft, control, digital, optimal, Q and R matrices

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218 Discovery of Production Rules with Fuzzy Hierarchy

Authors: Fadl M. Ba-Alwi, Kamal K. Bharadwaj

Abstract:

In this paper a novel algorithm is proposed that integrates the process of fuzzy hierarchy generation and rule discovery for automated discovery of Production Rules with Fuzzy Hierarchy (PRFH) in large databases.A concept of frequency matrix (Freq) introduced to summarize large database that helps in minimizing the number of database accesses, identification and removal of irrelevant attribute values and weak classes during the fuzzy hierarchy generation.Experimental results have established the effectiveness of the proposed algorithm.

Keywords: Data Mining, Degree of subsumption, Freq matrix, Fuzzy hierarchy.

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217 A Constitutional Approach to the Rights to Water and Energy

Authors: Antonios Maniatis

Abstract:

The present paper focuses on human rights to the water and to the energy and has a scope to promote the legal status on sustainable construction. The right to water constitutes a typical example of 3G fundamental rights, like the right to enjoyment of energy, particularly of electricity, whilst the right to energy efficiency is a right of fourth generation. Both rights to water and energy are examined through their consecration in the framework of the above-mentioned generations. It results that not only decision-makers but also citizens should fight for the further consecration and adequate use of these crucial rights, having to do with the urgent problem of climate change and the sustainable development. The time for the principle of water and energy “rule of law” has come.

Keywords: Climate change law, energy (en + ergon) efficiency, fundamental rights, prosumer, water.

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216 An Improved Limited Tolerance Rough Set Model

Authors: Chen Wu, Komal Narejo, Dandan Li

Abstract:

Some extended rough set models in incomplete information system cannot distinguish the two objects that have few known attributes and more unknown attributes; some cannot make a flexible and accurate discrimination. In order to solve this problem, this paper suggests an improved limited tolerance rough set model using two thresholds to control what two objects have a relationship between them in limited tolerance relation and to classify objects. Our practical study case shows the model can get fine and reasonable decision results.

Keywords: Decision rule, incomplete information system, limited tolerance relation, rough set model.

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215 Modeling of Crude Oil Blending via Discrete-Time Neural Networks

Authors: Xiaoou Li, Wen Yu

Abstract:

Crude oil blending is an important unit operation in petroleum refining industry. A good model for the blending system is beneficial for supervision operation, prediction of the export petroleum quality and realizing model-based optimal control. Since the blending cannot follow the ideal mixing rule in practice, we propose a static neural network to approximate the blending properties. By the dead-zone approach, we propose a new robust learning algorithm and give theoretical analysis. Real data of crude oil blending is applied to illustrate the neuro modeling approach.

Keywords: Neural networks, modeling, stability, crude oil.

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214 Mining Educational Data to Analyze the Student Motivation Behavior

Authors: Kunyanuth Kularbphettong, Cholticha Tongsiri

Abstract:

The purpose of this research aims to discover the knowledge for analysis student motivation behavior on e-Learning based on Data Mining Techniques, in case of the Information Technology for Communication and Learning Course at Suan Sunandha Rajabhat University. The data mining techniques was applied in this research including association rules, classification techniques. The results showed that using data mining technique can indicate the important variables that influence the student motivation behavior on e-Learning.

Keywords: association rule mining, classification techniques, e- Learning, Moodle log Motivation Behavior

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213 A Semantic Recommendation Procedure for Electronic Product Catalog

Authors: Hadi Khosravi Farsani, Mohammadali Nematbakhsh

Abstract:

To overcome the product overload of Internet shoppers, we introduce a semantic recommendation procedure which is more efficient when applied to Internet shopping malls. The suggested procedure recommends the semantic products to the customers and is originally based on Web usage mining, product classification, association rule mining, and frequently purchasing. We applied the procedure to the data set of MovieLens Company for performance evaluation, and some experimental results are provided. The experimental results have shown superior performance in terms of coverage and precision.

Keywords: Personalization, Recommendation, OWL Ontology, Electronic Catalogs, Classification.

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212 Numerical Investigation of Non-Newtonians Fluids Flows between Two Rotating Cylinders Using Lattice Boltzmann Method

Authors: S. Khali, R. Nebbali, K. Bouhadef

Abstract:

A numerical investigation is performed for non Newtonian fluids flow between two concentric cylinders. The D2Q9 lattice Boltzmann model developed from the Bhatangar-Gross-Krook (LBGK) approximation is used to obtain the flow field for fluids obeying to the power-law model. The inner and outer cylinders rotate in the same and the opposite direction while the end walls are maintained at rest. The combined effects of the Reynolds number (Re) of the inner and outer cylinders, the radius ratio (η) as well as the power-law index (n) on the flow characteristics are analyzed for an annular space of a finite aspect ratio (Γ). Two flow modes are obtained: a primary mode (laminar stable regime) and a secondary mode (laminar unstable regime). The so obtained flow structures are different from one mode to another. The transition critical Reynolds number Rec from the primary to the secondary mode is analyzed for the co-courant and counter-courant flows. This critical value increases as n increases. The prediction of the swirling flow of non Newtonians fluids in axisymmetric geometries is shown in the present work.

Keywords: Taylor-Couette flows, non Newtonian fluid, Lattice Boltzmann method.

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211 Algebraic Quantum Error Correction Codes

Authors: Ming-Chung Tsai, Kuan-Peng Chen, Zheng-Yao

Abstract:

A systematic and exhaustive method based on the group structure of a unitary Lie algebra is proposed to generate an enormous number of quantum codes. With respect to the algebraic structure, the orthogonality condition, which is the central rule of generating quantum codes, is proved to be fully equivalent to the distinguishability of the elements in this structure. In addition, four types of quantum codes are classified according to the relation of the codeword operators and some initial quantum state. By linking the unitary Lie algebra with the additive group, the classical correspondences of some of these quantum codes can be rendered.

Keywords: Quotient-Algebra Partition, Codeword Spinors, Basis Codewords, Syndrome Spinors

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210 An Analysis of Digital Forensic Laboratory Development among Malaysia’s Law Enforcement Agencies

Authors: Sarah K. Taylor, Miratun M. Saharuddin, Zabri A. Talib

Abstract:

Cybercrime is on the rise, and yet many Law Enforcement Agencies (LEAs) in Malaysia have no Digital Forensics Laboratory (DFL) to assist them in the attrition and analysis of digital evidence. From the estimated number of 30 LEAs in Malaysia, sadly, only eight of them owned a DFL. All of the DFLs are concentrated in the capital of Malaysia and none at the state level. LEAs are still depending on the national DFL (CyberSecurity Malaysia) even for simple and straightforward cases. A survey was conducted among LEAs in Malaysia owning a DFL to understand their history of establishing the DFL, the challenges that they faced and the significance of the DFL to their case investigation. The results showed that the while some LEAs faced no challenge in establishing a DFL, some of them took seven to 10 years to do so. The reason was due to the difficulty in convincing their management because of the high costs involved. The results also revealed that with the establishment of a DFL, LEAs were better able to get faster forensic result and to meet agency’s timeline expectation. It is also found that LEAs were also able to get more meaningful forensic results on cases that require niche expertise, compared to sending off cases to the national DFL. Other than that, cases are getting more complex, and hence, a continuous stream of budget for equipment and training is inevitable. The result derived from the study is hoped to be used by other LEAs in justifying to their management the benefits of establishing an in-house DFL.

Keywords: Digital forensics, digital forensics laboratory, digital evidence, law enforcement agency.

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209 Support Vector Fuzzy Based Neural Networks For Exchange Rate Modeling

Authors: Prof. Chokri SLIM

Abstract:

A Novel fuzzy neural network combining with support vector learning mechanism called support-vector-based fuzzy neural networks (SVBFNN) is proposed. The SVBFNN combine the capability of minimizing the empirical risk (training error) and expected risk (testing error) of support vector learning in high dimensional data spaces and the efficient human-like reasoning of FNN.

Keywords: Neural network, fuzzy inference, machine learning, fuzzy modeling and rule extraction, support vector regression.

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208 Design and Implementation of Rule-based Expert System for Fault Management

Authors: Su Myat Marlar Soe, May Paing Paing Zaw

Abstract:

It has been defined that the “network is the system". This implies providing levels of service, reliability, predictability and availability that are commensurate with or better than those that individual computers provide today. To provide this requires integrated network management for interconnected networks of heterogeneous devices covering both the local campus. In this paper we are addressing a framework to effectively deal with this issue. It consists of components and interactions between them which are required to perform the service fault management. A real-world scenario is used to derive the requirements which have been applied to the component identification. An analysis of existing frameworks and approaches with respect to their applicability to the framework is also carried out.

Keywords: To diagnose the possible network faults by using thepredetermined rules.

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207 A New Technique for Multi Resolution Characterization of Epileptic Spikes in EEG

Authors: H. N. Suresh, Dr. V. Udaya Shankara

Abstract:

A technique proposed for the automatic detection of spikes in electroencephalograms (EEG). A multi-resolution approach and a non-linear energy operator are exploited. The signal on each EEG channel is decomposed into three sub bands using a non-decimated wavelet transform (WT). The WT is a powerful tool for multi-resolution analysis of non-stationary signal as well as for signal compression, recognition and restoration. Each sub band is analyzed by using a non-linear energy operator, in order to detect spikes. A decision rule detects the presence of spikes in the EEG, relying upon the energy of the three sub-bands. The effectiveness of the proposed technique was confirmed by analyzing both test signals and EEG layouts.

Keywords: EEG, Spike, SNEO, Wavelet Transform

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206 Auto Regressive Tree Modeling for Parametric Optimization in Fuzzy Logic Control System

Authors: Arshia Azam, J. Amarnath, Ch. D. V. Paradesi Rao

Abstract:

The advantage of solving the complex nonlinear problems by utilizing fuzzy logic methodologies is that the experience or expert-s knowledge described as a fuzzy rule base can be directly embedded into the systems for dealing with the problems. The current limitation of appropriate and automated designing of fuzzy controllers are focused in this paper. The structure discovery and parameter adjustment of the Branched T-S fuzzy model is addressed by a hybrid technique of type constrained sparse tree algorithms. The simulation result for different system model is evaluated and the identification error is observed to be minimum.

Keywords: Fuzzy logic, branch T-S fuzzy model, tree modeling, complex nonlinear system.

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205 Investigation of VMAT Algorithms and Dosimetry

Authors: A. Taqaddas

Abstract:

Purpose: Planning and dosimetry of different VMAT algorithms (SmartArc, Ergo++, Autobeam) is compared with IMRT for Head and Neck Cancer patients. Modelling was performed to rule out the causes of discrepancies between planned and delivered dose. Methods: Five HNC patients previously treated with IMRT were re-planned with SmartArc (SA), Ergo++ and Autobeam. Plans were compared with each other and against IMRT and evaluated using DVHs for PTVs and OARs, delivery time, monitor units (MU) and dosimetric accuracy. Modelling of control point (CP) spacing, Leaf-end Separation and MLC/Aperture shape was performed to rule out causes of discrepancies between planned and delivered doses. Additionally estimated arc delivery times, overall plan generation times and effect of CP spacing and number of arcs on plan generation times were recorded. Results: Single arc SmartArc plans (SA4d) were generally better than IMRT and double arc plans (SA2Arcs) in terms of homogeneity and target coverage. Double arc plans seemed to have a positive role in achieving improved Conformity Index (CI) and better sparing of some Organs at Risk (OARs) compared to Step and Shoot IMRT (ss-IMRT) and SA4d. Overall Ergo++ plans achieved best CI for both PTVs. Dosimetric validation of all VMAT plans without modelling was found to be lower than ss-IMRT. Total MUs required for delivery were on average 19%, 30%, 10.6% and 6.5% lower than ss-IMRT for SA4d, SA2d (Single arc with 20 Gantry Spacing), SA2Arcs and Autobeam plans respectively. Autobeam was most efficient in terms of actual treatment delivery times whereas Ergo++ plans took longest to deliver. Conclusion: Overall SA single arc plans on average achieved best target coverage and homogeneity for both PTVs. SA2Arc plans showed improved CI and some OARs sparing. Very good dosimetric results were achieved with modelling. Ergo++ plans achieved best CI. Autobeam resulted in fastest treatment delivery times.

Keywords: Dosimetry, Intensity Modulated Radiotherapy, Optimization Algorithms, Volumetric Modulated Arc Therapy.

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