Search results for: Time Utility Function/ Utility Accrual (TUF/UA) scheduling
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 8433

Search results for: Time Utility Function/ Utility Accrual (TUF/UA) scheduling

7713 On Discretization of Second-order Derivatives in Smoothed Particle Hydrodynamics

Authors: R. Fatehi, M.A. Fayazbakhsh, M.T. Manzari

Abstract:

Discretization of spatial derivatives is an important issue in meshfree methods especially when the derivative terms contain non-linear coefficients. In this paper, various methods used for discretization of second-order spatial derivatives are investigated in the context of Smoothed Particle Hydrodynamics. Three popular forms (i.e. "double summation", "second-order kernel derivation", and "difference scheme") are studied using one-dimensional unsteady heat conduction equation. To assess these schemes, transient response to a step function initial condition is considered. Due to parabolic nature of the heat equation, one can expect smooth and monotone solutions. It is shown, however in this paper, that regardless of the type of kernel function used and the size of smoothing radius, the double summation discretization form leads to non-physical oscillations which persist in the solution. Also, results show that when a second-order kernel derivative is used, a high-order kernel function shall be employed in such a way that the distance of inflection point from origin in the kernel function be less than the nearest particle distance. Otherwise, solutions may exhibit oscillations near discontinuities unlike the "difference scheme" which unconditionally produces monotone results.

Keywords: Heat conduction, Meshfree methods, Smoothed ParticleHydrodynamics (SPH), Second-order derivatives.

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7712 Blind Image Deconvolution by Neural Recursive Function Approximation

Authors: Jiann-Ming Wu, Hsiao-Chang Chen, Chun-Chang Wu, Pei-Hsun Hsu

Abstract:

This work explores blind image deconvolution by recursive function approximation based on supervised learning of neural networks, under the assumption that a degraded image is linear convolution of an original source image through a linear shift-invariant (LSI) blurring matrix. Supervised learning of neural networks of radial basis functions (RBF) is employed to construct an embedded recursive function within a blurring image, try to extract non-deterministic component of an original source image, and use them to estimate hyper parameters of a linear image degradation model. Based on the estimated blurring matrix, reconstruction of an original source image from a blurred image is further resolved by an annealed Hopfield neural network. By numerical simulations, the proposed novel method is shown effective for faithful estimation of an unknown blurring matrix and restoration of an original source image.

Keywords: Blind image deconvolution, linear shift-invariant(LSI), linear image degradation model, radial basis functions (rbf), recursive function, annealed Hopfield neural networks.

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7711 Modelling for Temperature Non-Isothermal Continuous Stirred Tank Reactor Using Fuzzy Logic

Authors: Nasser Mohamed Ramli, Mohamad Syafiq Mohamad

Abstract:

Many types of controllers were applied on the continuous stirred tank reactor (CSTR) unit to control the temperature. In this research paper, Proportional-Integral-Derivative (PID) controller are compared with Fuzzy Logic controller for temperature control of CSTR. The control system for temperature non-isothermal of a CSTR will produce a stable response curve to its set point temperature. A mathematical model of a CSTR using the most general operating condition was developed through a set of differential equations into S-function using MATLAB. The reactor model and S-function are developed using m.file. After developing the S-function of CSTR model, User-Defined functions are used to link to SIMULINK file. Results that are obtained from simulation and temperature control were better when using Fuzzy logic control compared to PID control.

Keywords: CSTR, temperature, PID, fuzzy logic.

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7710 Effects of Polluted Water on the Metallic Water Pipelines

Authors: Abdul-Khaliq M. Hussain, Bashir A. Tantosh, El-Sadeg A. Abdalla

Abstract:

Corrosion of metallic water pipelines buried below ground surface is a function of the nature of the surrounding soil and groundwater. This gives the importance of knowing the physical and chemical characteristics of the pipe-s surrounding environment. The corrosion of externally – unprotected metallic water pipelines, specially ductile iron pipes, in localities with aggressive soil conditions is becoming a significant problem. Anticorrosive protection for metallic water pipelines, their fittings and accessories is very important, because they may be attached by corrosion with time. The tendency of a metallic substrate to corrode is a function of the surface characteristics of the metal and of the metal/protective film interface, the physical, electrical and electrochemical properties of the film, and the nature of the environment in which the pipelines system is placed. In this work the authors have looked at corrosion problems of water pipelines and their control. The corrosive properties of groundwater and soil environments are reviewed, and parameters affecting corrosion are discussed. The purpose of this work is to provide guidelines for materials selection in water and soil environments, and how the water pipelines can be protected against metallic corrosion.

Keywords: Corrosion, Drinking Water, Metallic WaterPipelines, Polluted Water.

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7709 Some Rotational Flows of an Incompressible Fluid of Variable Viscosity

Authors: Rana Khalid Naeem, Waseem Ahmed Khan, Muhammad Akhtar, Asif Mansoor

Abstract:

The Navier Stokes Equations (NSE) for an incompressible fluid of variable viscosity in the presence of an unknown external force in Von-Mises system x,\ are transformed, and some new exact solutions for a class of flows characterized by equation y f x a\b for an arbitrary state equation are determined, where f x is a function, \ the stream function, a z 0 and b are the arbitrary constants. In three, out of four cases, the function f x is arbitrary, and the solutions are the solutions of the flow equations for all the flows characterized by the equationy f x a\b. Streamline patterns for some forms of f x in unbounded and bounded regions are given.

Keywords: Bounded and unbounded region, Exact solution, Navier Stokes equations, Streamline pattern, Variable viscosity, Von- Mises system

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7708 Symbolic Analysis of Input Impedance of CMOS Floating Active Inductors with Application in Fully Differential Bandpass Amplifier

Authors: Kittipong Tripetch

Abstract:

This paper proposes a study of input impedance of 2 types of CMOS active inductors. It derives 2 input impedance formulas. The first formula is the input impedance of the grounded active inductor. The second formula is the input impedance of the floating active inductor. After that, these formulas can be used to simulate magnitude and phase response of input impedance as a function of current consumption with MATLAB. Common mode rejection ratio (CMRR) of the fully differential bandpass amplifier is derived based on superposition principle. CMRR as a function of input frequency is plotted as a function of current consumption. 

Keywords: Grounded active inductor, floating active inductor, Fully differential bandpass amplifier.

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7707 Leaching of Flotation Concentrate of Oxide Copper Ore from Sepon Mine, Lao PDR

Authors: C. Rattanakawin, S. Vasailor

Abstract:

Acid leaching of flotation concentrate of oxide copper ore containing mainly of malachite was performed in a standard agitation tank with various parameters. The effects of solid to liquid ratio, sulfuric acid concentration, agitation speed, leaching temperature and time were examined to get proper conditions. The best conditions are 1:8 solid to liquid ratio, 10% concentration by weight, 250 rev/min, 30 oC and 5-min leaching time in respect. About 20% Cu grade assayed by atomic absorption technique with 98% copper recovery was obtained from these combined optimum conditions. Dissolution kinetics of the concentrate was approximated as a logarithmic function. As a result, the first-order reaction rate is suggested from this leaching study.

Keywords: Agitation leaching, dissolution kinetics, flotation concentrate, oxide copper ore, sulfuric acid.

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7706 An Implementation of EURORADIO Protocol for ERTMS Systems

Authors: Gabriele Cecchetti, Anna Lina Ruscelli, Filippo Cugini, Piero Castoldi

Abstract:

European Rail Traffic Management System (ERTMS) is the European reference for interoperable and safer signaling systems to efficiently manage trains running. If implemented, it allows trains cross seamlessly intra-European national borders. ERTMS has defined a secure communication protocol, EURORADIO, based on open communication networks. Its RadioInfill function can improve the reaction of the signaling system to changes in line conditions, avoiding unnecessary braking: its advantages in terms of power saving and travel time has been analyzed. In this paper a software implementation of the EURORADIO protocol with RadioInfill for ERTMS Level 1 using GSM-R is illustrated as part of the SR-Secure Italian project. In this building-blocks architecture the EURORADIO layers communicates together through modular Application Programm Interfaces. Security coding rules and railway industry requirements specified by EN 50128 standard have been respected. The proposed implementation has successfully passed conformity tests and has been tested on a computer-based simulator.

Keywords: ERTMS, ETCS signalling, EURORADIO protocol, radio infill function.

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7705 Measurement of CES Production Functions Considering Energy as an Input

Authors: Donglan Zha, Jiansong Si

Abstract:

Because of its flexibility, CES attracts much interest in economic growth and programming models, and the macroeconomics or micro-macro models. This paper focuses on the development, estimating methods of CES production function considering energy as an input. We leave for future research work of relaxing the assumption of constant returns to scale, the introduction of potential input factors, and the generalization method of the optimal nested form of multi-factor production functions.

Keywords: Bias of technical change, CES production function, elasticity of substitution, energy input.

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7704 Application of Ant Colony Optimization for Multi-objective Production Problems

Authors: Teerapun Saeheaw, Nivit Charoenchai, Wichai Chattinnawat

Abstract:

This paper proposes a meta-heuristic called Ant Colony Optimization to solve multi-objective production problems. The multi-objective function is to minimize lead time and work in process. The problem is related to the decision variables, i.e.; distance and process time. According to decision criteria, the mathematical model is formulated. In order to solve the model an ant colony optimization approach has been developed. The proposed algorithm is parameterized by the number of ant colonies and the number of pheromone trails. One example is given to illustrate the effectiveness of the proposed model. The proposed formulations; Max-Min Ant system are then used to solve the problem and the results evaluate the performance and efficiency of the proposed algorithm using simulation.

Keywords: Ant colony optimization, multi-objective problems.

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7703 Zigbee Based Wireless Energy Surveillance System for Energy Savings

Authors: Won-Ho Kim, Chang-Ho Hyun, Moon-Jung Kim

Abstract:

In this paper, zigbee communication based wireless energy surveillance system is presented. The proposed system consists of multiple energy surveillance devices and an energy surveillance monitor. Each different standby power-off value of electric device is set automatically by using learning function of energy surveillance device. Thus adaptive standby power-off function provides user convenience and it maximizes the energy savings. Also, power consumption monitoring function is helpful to reduce inefficient energy consumption in home. The zigbee throughput simulator is designed to evaluate minimum transmission power and maximum allowable information quantity in the proposed system. The test result of prototype has been satisfied all the requirements. The proposed system has confirmed that can be used as an intelligent energy surveillance system for energy savings in home or office.

Keywords: Energy monitoring system, Energy surveillance system, Energy sensor network, Energy savings.

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7702 Optimal Aggregate Production Planning with Fuzzy Data

Authors: Wen-Lung Huang, Shih-Pin Chen

Abstract:

This paper investigates the optimization problem of multi-product aggregate production planning (APP) with fuzzy data. From a comprehensive viewpoint of conserving the fuzziness of input information, this paper proposes a method that can completely describe the membership function of the performance measure. The idea is based on the well-known Zadeh-s extension principle which plays an important role in fuzzy theory. In the proposed solution procedure, a pair of mathematical programs parameterized by possibility level a is formulated to calculate the bounds of the optimal performance measure at a . Then the membership function of the optimal performance measure is constructed by enumerating different values of a . Solutions obtained from the proposed method contain more information, and can offer more chance to achieve the feasible disaggregate plan. This is helpful to the decision-maker in practical applications.

Keywords: fuzzy data, aggregate production planning, membership function, parametric programming

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7701 Roles of Aquatic Plants on Erosion Relief of Stream Bed

Authors: Jin-Hong Kim

Abstract:

Roles of the vegetation to mitigate the erosion of the stream bed or to facilitate the deposition of the fine sediments by the species of the aquatic plants were presented. Field investigation on the estimation of the change of the bed level and the estimation of the flow characteristics were performed. The results showed that Phragmites japonica has the mitigation function of 0.3m-0.4m of the erosion in the range of higher than 1.0m/s of flow velocity at the vegetated region. Phragmites communis has the mitigation function of 0.2m-0.3m of the erosion in the range of higher than 0.7m/s of flow velocity at the vegetated region. Salix gracilistyla has greater role than Phragmites japonica and Phragmites communis to sustain the stable channel. It has the mitigation function of 0.4m-0.5m of the erosion in the range of higher than 1.4m/s of flow velocity. Miscanthus sacchariflorus has a weak role compared with that of Phragmites japonica and Salix gracilistyla, but it has still function for sustaining the stable bed. From these results, the vegetation has effective roles to mitigate the erosion or to facilitate the deposition of the stream bed.

Keywords: Aquatic plants, Phragmites japonica, Phragmites communis, Miscanthus sacchariflorus, Salix gracilistyla.

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7700 Evaluation of Short-Term Load Forecasting Techniques Applied for Smart Micro Grids

Authors: Xiaolei Hu, Enrico Ferrera, Riccardo Tomasi, Claudio Pastrone

Abstract:

Load Forecasting plays a key role in making today's and future's Smart Energy Grids sustainable and reliable. Accurate power consumption prediction allows utilities to organize in advance their resources or to execute Demand Response strategies more effectively, which enables several features such as higher sustainability, better quality of service, and affordable electricity tariffs. It is easy yet effective to apply Load Forecasting at larger geographic scale, i.e. Smart Micro Grids, wherein the lower available grid flexibility makes accurate prediction more critical in Demand Response applications. This paper analyses the application of short-term load forecasting in a concrete scenario, proposed within the EU-funded GreenCom project, which collect load data from single loads and households belonging to a Smart Micro Grid. Three short-term load forecasting techniques, i.e. linear regression, artificial neural networks, and radial basis function network, are considered, compared, and evaluated through absolute forecast errors and training time. The influence of weather conditions in Load Forecasting is also evaluated. A new definition of Gain is introduced in this paper, which innovatively serves as an indicator of short-term prediction capabilities of time spam consistency. Two models, 24- and 1-hour-ahead forecasting, are built to comprehensively compare these three techniques.

Keywords: Short-term load forecasting, smart micro grid, linear regression, artificial neural networks, radial basis function network, Gain.

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7699 Mathematical Simulation of Acid Concentration Effects during Acid Nitric Leaching of Cobalt from a Mixed Cobalt-Copper Oxide

Authors: Ek Ngoy, A F Mulaba-Bafubiandi

Abstract:

Cobalt was acid nitric leached from a mixed cobaltcopper oxide with variable acid concentration. Resulting experimental data were used to analyze effects of increase in acid concentration, based on a shrinking core model of the process. The mathematical simulation demonstrated that the time rate of the dissolution mechanism is an increasing function of acid concentration. It was also shown that the magnitude of the acid concentration effect is time dependent and the increase in acid concentration is more effective at earlier stage of the dissolution than at later stage. The remaining process parameters are comprehensively affected by acid concentration and their interaction is synergetic.

Keywords: Acid effect, Cobalt, Cobalt-copper oxide, Leaching, Simulation

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7698 Hybrid Algorithm for Hammerstein System Identification Using Genetic Algorithm and Particle Swarm Optimization

Authors: Tomohiro Hachino, Kenji Shimoda, Hitoshi Takata

Abstract:

This paper presents a method of model selection and identification of Hammerstein systems by hybridization of the genetic algorithm (GA) and particle swarm optimization (PSO). An unknown nonlinear static part to be estimated is approximately represented by an automatic choosing function (ACF) model. The weighting parameters of the ACF and the system parameters of the linear dynamic part are estimated by the linear least-squares method. On the other hand, the adjusting parameters of the ACF model structure are properly selected by the hybrid algorithm of the GA and PSO, where the Akaike information criterion is utilized as the evaluation value function. Simulation results are shown to demonstrate the effectiveness of the proposed hybrid algorithm.

Keywords: Hammerstein system, identification, automatic choosing function model, genetic algorithm, particle swarm optimization.

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7697 Cardiac Function and Morphological Adaptations in Endurance and Resistance Athletes: Evaluation using a new Method

Authors: K. Hosseini, MD., R. Mazaheri, MD., H.R. Khoddami Vishteh, MD., M.A. Mansournia, MD., H. Angoorani, MD

Abstract:

Background: Tissue Doppler Echocardiography (TDE) assesses diastolic function more accurately than routine pulse Doppler echo. Assessment of the effects of dynamic and static exercises on the heart by using TDE can provides new information about the athlete-s heart syndrome. Methods: This study was conducted on 20 elite wrestlers, 14 endurance runners at national level and 21 non-athletes as the control group. Participants underwent two-dimensional echocardiography, standard Doppler and TDE. Results: Wrestlers had the highest left ventricular mass index, enddiastolic inter-ventricular septum thickness and left ventricular Posterior wall thickness. Runners had the highest Left ventricular end-diastolic volume, LV ejection fraction, stroke volume and cardiac output. In TDE, the early diastolic velocity of mitral annulus to the late diastolic velocity ratio in athletic groups was greater than the controls with no significant difference. Conclusion: In spite of cardiac morphological changes in athletes, TDE shows that cardiac diastolic function won-t be adversely affected.

Keywords: Tissue Doppler Echocardiography, Diastolic function, Athlete's heart syndrome, Static exercise, Dynamic exercise

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7696 Interactive Garments: Flexible Technologies for Textile Integration

Authors: Anupam Bhatia

Abstract:

Upon reviewing the literature and the pragmatic work done in the field of E- textiles, it is observed that the applications of wearable technologies have found a steady growth in the field of military, medical, industrial, sports; whereas fashion is at a loss to know how to treat this technology and bring it to market. The purpose of this paper is to understand the practical issues of integration of electronics in garments; cutting patterns for mass production, maintaining the basic properties of textiles and daily maintenance of garments that hinder the wide adoption of interactive fabric technology within Fashion and leisure wear. To understand the practical hindrances an experimental and laboratory approach is taken. “Techno Meets Fashion” has been an interactive fashion project where sensor technologies have been embedded with textiles that result in set of ensembles that are light emitting garments, sound sensing garments, proximity garments, shape memory garments etc. Smart textiles, especially in the form of textile interfaces, are drastically underused in fashion and other lifestyle product design. Clothing and some other textile products must be washable, which subjects to the interactive elements to water and chemical immersion, physical stress, and extreme temperature. The current state of the art tends to be too fragile for this treatment. The process for mass producing traditional textiles becomes difficult in interactive textiles. As cutting patterns from larger rolls of cloth and sewing them together to make garments breaks and reforms electronic connections in an uncontrolled manner. Because of this, interactive fabric elements are integrated by hand into textiles produced by standard methods. The Arduino has surely made embedding electronics into textiles much easier than before; even then electronics are not integral to the daily wear garments. Soft and flexible interfaces of MEMS (micro sensors and Micro actuators) can be an option to make this possible by blending electronics within E-textiles in a way that’s seamless and still retains functions of the circuits as well as the garment. Smart clothes, which offer simultaneously a challenging design and utility value, can be only mass produced if the demands of the body are taken care of i.e. protection, anthropometry, ergonomics of human movement, thermo- physiological regulation.

Keywords: Ambient Intelligence, Proximity Sensors, Shape Memory Materials, Sound sensing garments, Wearable Technology.

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7695 The Whale Optimization Algorithm and Its Implementation in MATLAB

Authors: S. Adhirai, R. P. Mahapatra, Paramjit Singh

Abstract:

Optimization is an important tool in making decisions and in analysing physical systems. In mathematical terms, an optimization problem is the problem of finding the best solution from among the set of all feasible solutions. The paper discusses the Whale Optimization Algorithm (WOA), and its applications in different fields. The algorithm is tested using MATLAB because of its unique and powerful features. The benchmark functions used in WOA algorithm are grouped as: unimodal (F1-F7), multimodal (F8-F13), and fixed-dimension multimodal (F14-F23). Out of these benchmark functions, we show the experimental results for F7, F11, and F19 for different number of iterations. The search space and objective space for the selected function are drawn, and finally, the best solution as well as the best optimal value of the objective function found by WOA is presented. The algorithmic results demonstrate that the WOA performs better than the state-of-the-art meta-heuristic and conventional algorithms.

Keywords: Optimization, optimal value, objective function, optimization problems, meta-heuristic optimization algorithms, Whale Optimization Algorithm, Implementation, MATLAB.

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7694 Use of Radial Basis Function Neural Network for Bearing Pressure Prediction of Strip Footing on Reinforced Granular Bed Overlying Weak Soil

Authors: Srinath Shetty K., Shivashankar R., Rashmi P. Shetty

Abstract:

Earth reinforcing techniques have become useful and economical to solve problems related to difficult grounds and provide satisfactory foundation performance. In this context, this paper uses radial basis function neural network (RBFNN) for predicting the bearing pressure of strip footing on reinforced granular bed overlying weak soil. The inputs for the neural network models included plate width, thickness of granular bed and number of layers of reinforcements, settlement ratio, water content, dry density, cohesion and angle of friction. The results indicated that RBFNN model exhibited more than 84 % prediction accuracy, thereby demonstrating its application in a geotechnical problem.

Keywords: Bearing pressure, granular bed, radial basis function neural network, strip footing.

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7693 DWT Based Robust Watermarking Embed Using CRC-32 Techniques

Authors: Sadi Vural, Hiromi Tomii, Hironori Yamauchi

Abstract:

As far as the latest technological improvements are concerned, digital systems more become popular than the past. Despite this growing demand to the digital systems, content copy and attack against the digital cinema contents becomes a serious problem. To solve the above security problem, we propose “traceable watermarking using Hash functions for digital cinema system. Digital Cinema is a great application for traceable watermarking since it uses watermarking technology during content play as well as content transmission. The watermark is embedded into the randomly selected movie frames using CRC-32 techniques. CRC-32 is a Hash function. Using it, the embedding position is distributed by Hash Function so that any party cannot break off the watermarking or will not be able to change. Finally, our experimental results show that proposed DWT watermarking method using CRC-32 is much better than the convenient watermarking techniques in terms of robustness, image quality and its simple but unbreakable algorithm.

Keywords: Decoder, Digital content, JPEG2000 Frame, System-On-Chip, traceable watermark, Hash Function, CRC-32.

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7692 Distortion Estimation in Digital Image Watermarking using Genetic Programming

Authors: Labiba Gilani, Asifullah Khan, Anwar M. Mirza

Abstract:

This paper introduces a technique of distortion estimation in image watermarking using Genetic Programming (GP). The distortion is estimated by considering the problem of obtaining a distorted watermarked signal from the original watermarked signal as a function regression problem. This function regression problem is solved using GP, where the original watermarked signal is considered as an independent variable. GP-based distortion estimation scheme is checked for Gaussian attack and Jpeg compression attack. We have used Gaussian attacks of different strengths by changing the standard deviation. JPEG compression attack is also varied by adding various distortions. Experimental results demonstrate that the proposed technique is able to detect the watermark even in the case of strong distortions and is more robust against attacks.

Keywords: Blind Watermarking, Genetic Programming (GP), Fitness Function, Discrete Cosine Transform (DCT).

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7691 Dimension Free Rigid Point Set Registration in Linear Time

Authors: Jianqin Qu

Abstract:

This paper proposes a rigid point set matching algorithm in arbitrary dimensions based on the idea of symmetric covariant function. A group of functions of the points in the set are formulated using rigid invariants. Each of these functions computes a pair of correspondence from the given point set. Then the computed correspondences are used to recover the unknown rigid transform parameters. Each computed point can be geometrically interpreted as the weighted mean center of the point set. The algorithm is compact, fast, and dimension free without any optimization process. It either computes the desired transform for noiseless data in linear time, or fails quickly in exceptional cases. Experimental results for synthetic data and 2D/3D real data are provided, which demonstrate potential applications of the algorithm to a wide range of problems.

Keywords: Covariant point, point matching, dimension free, rigid registration.

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7690 Performance Evaluation of a ‘Priority-Controlled’ Intersection Converted to Signal-Controlled Intersection

Authors: Ezenwa Chinenye Amanamba

Abstract:

There is a call to ensure that the issues of safety and efficient throughput are considered during design; the solutions to these issues can also be retrofitted at locations where they were not captured during design, but have become problems to road users over time. This paper adopts several methods to analyze the performance of an intersection which was formerly a ‘priority-controlled’ intersection, but has now been converted to a ‘signal-controlled’ intersection. Extensive review of literature helped form the basis for result analysis and discussion. The Ikot-Ekpene/Anagha-Ezikpe intersection, located at the heart of Umuahia was adopted as case study; considering the high traffic volume on the route. Anecdotal evidence revealed that traffic signals imposed enormous delays at the intersection, especially for traffic on the major road. The major road has arrival flow which surpasses the saturation flow obtained from modelling of the isolated signalized intersection. Similarly, there were several geometric elements that did not agree with the specific function of the road. A roundabout, particularly flower roundabout was recommended as a better traffic control measure.

Keywords: Highway function, level of service, roundabout, traffic delays, Umuahia.

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7689 A Wavelet-Based Watermarking Method Exploiting the Contrast Sensitivity Function

Authors: John N. Ellinas, Panagiotis Kenterlis

Abstract:

The efficiency of an image watermarking technique depends on the preservation of visually significant information. This is attained by embedding the watermark transparently with the maximum possible strength. The current paper presents an approach for still image digital watermarking in which the watermark embedding process employs the wavelet transform and incorporates Human Visual System (HVS) characteristics. The sensitivity of a human observer to contrast with respect to spatial frequency is described by the Contrast Sensitivity Function (CSF). The strength of the watermark within the decomposition subbands, which occupy an interval on the spatial frequencies, is adjusted according to this sensitivity. Moreover, the watermark embedding process is carried over the subband coefficients that lie on edges where distortions are less noticeable. The experimental evaluation of the proposed method shows very good results in terms of robustness and transparency.

Keywords: Image watermarking, wavelet transform, human visual system, contrast sensitivity function.

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7688 Fault Detection and Isolation using RBF Networks for Polymer Electrolyte Membrane Fuel Cell

Authors: Mahanijah Md Kamal., Dingli Yu

Abstract:

This paper presents a new method of fault detection and isolation (FDI) for polymer electrolyte membrane (PEM) fuel cell (FC) dynamic systems under an open-loop scheme. This method uses a radial basis function (RBF) neural network to perform fault identification, classification and isolation. The novelty is that the RBF model of independent mode is used to predict the future outputs of the FC stack. One actuator fault, one component fault and three sensor faults have been introduced to the PEMFC systems experience faults between -7% to +10% of fault size in real-time operation. To validate the results, a benchmark model developed by Michigan University is used in the simulation to investigate the effect of these five faults. The developed independent RBF model is tested on MATLAB R2009a/Simulink environment. The simulation results confirm the effectiveness of the proposed method for FDI under an open-loop condition. By using this method, the RBF networks able to detect and isolate all five faults accordingly and accurately.

Keywords: Polymer electrolyte membrane fuel cell, radial basis function neural networks, fault detection, fault isolation.

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7687 Forecasting for Financial Stock Returns Using a Quantile Function Model

Authors: Yuzhi Cai

Abstract:

In this talk, we introduce a newly developed quantile function model that can be used for estimating conditional distributions of financial returns and for obtaining multi-step ahead out-of-sample predictive distributions of financial returns. Since we forecast the whole conditional distributions, any predictive quantity of interest about the future financial returns can be obtained simply as a by-product of the method. We also show an application of the model to the daily closing prices of Dow Jones Industrial Average (DJIA) series over the period from 2 January 2004 - 8 October 2010. We obtained the predictive distributions up to 15 days ahead for the DJIA returns, which were further compared with the actually observed returns and those predicted from an AR-GARCH model. The results show that the new model can capture the main features of financial returns and provide a better fitted model together with improved mean forecasts compared with conventional methods. We hope this talk will help audience to see that this new model has the potential to be very useful in practice.

Keywords: DJIA, Financial returns, predictive distribution, quantile function model.

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7686 The Design of Axisymmetric Ducts for Incompressible Flow with a Parabolic Axial Velocity Inlet Profile

Authors: V.Pavlika

Abstract:

In this paper a numerical algorithm is described for solving the boundary value problem associated with axisymmetric, inviscid, incompressible, rotational (and irrotational) flow in order to obtain duct wall shapes from prescribed wall velocity distributions. The governing equations are formulated in terms of the stream function ψ (x,y)and the function φ (x,y)as independent variables where for irrotational flow φ (x,y)can be recognized as the velocity potential function, for rotational flow φ (x,y)ceases being the velocity potential function but does remain orthogonal to the stream lines. A numerical method based on the finite difference scheme on a uniform mesh is employed. The technique described is capable of tackling the so-called inverse problem where the velocity wall distributions are prescribed from which the duct wall shape is calculated, as well as the direct problem where the velocity distribution on the duct walls are calculated from prescribed duct geometries. The two different cases as outlined in this paper are in fact boundary value problems with Neumann and Dirichlet boundary conditions respectively. Even though both approaches are discussed, only numerical results for the case of the Dirichlet boundary conditions are given. A downstream condition is prescribed such that cylindrical flow, that is flow which is independent of the axial coordinate, exists.

Keywords: Inverse problem, irrotational incompressible flow, Boundary value problem.

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7685 An Energy-Efficient Distributed Unequal Clustering Protocol for Wireless Sensor Networks

Authors: Sungju Lee, Jangsoo Lee , Hongjoong Sin, Seunghwan Yoo, Sanghyuck Lee, Jaesik Lee, Yongjun Lee, Sungchun Kim

Abstract:

The wireless sensor networks have been extensively deployed and researched. One of the major issues in wireless sensor networks is a developing energy-efficient clustering protocol. Clustering algorithm provides an effective way to prolong the lifetime of a wireless sensor networks. In the paper, we compare several clustering protocols which significantly affect a balancing of energy consumption. And we propose an Energy-Efficient Distributed Unequal Clustering (EEDUC) algorithm which provides a new way of creating distributed clusters. In EEDUC, each sensor node sets the waiting time. This waiting time is considered as a function of residual energy, number of neighborhood nodes. EEDUC uses waiting time to distribute cluster heads. We also propose an unequal clustering mechanism to solve the hot-spot problem. Simulation results show that EEDUC distributes the cluster heads, balances the energy consumption well among the cluster heads and increases the network lifetime.

Keywords: Wireless Sensor Network, Distributed UnequalClustering, Multi-hop, Lifetime.

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7684 Establishing a Probabilistic Model of Extrapolated Wind Speed Data for Wind Energy Prediction

Authors: Mussa I. Mgwatu, Reuben R. M. Kainkwa

Abstract:

Wind is among the potential energy resources which can be harnessed to generate wind energy for conversion into electrical power. Due to the variability of wind speed with time and height, it becomes difficult to predict the generated wind energy more optimally. In this paper, an attempt is made to establish a probabilistic model fitting the wind speed data recorded at Makambako site in Tanzania. Wind speeds and direction were respectively measured using anemometer (type AN1) and wind Vane (type WD1) both supplied by Delta-T-Devices at a measurement height of 2 m. Wind speeds were then extrapolated for the height of 10 m using power law equation with an exponent of 0.47. Data were analysed using MINITAB statistical software to show the variability of wind speeds with time and height, and to determine the underlying probability model of the extrapolated wind speed data. The results show that wind speeds at Makambako site vary cyclically over time; and they conform to the Weibull probability distribution. From these results, Weibull probability density function can be used to predict the wind energy.

Keywords: Probabilistic models, wind speed, wind energy

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