Search results for: vector error correction model.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 8825

Search results for: vector error correction model.

7595 Forecasting Materials Demand from Multi-Source Ordering

Authors: Hui Hsin Huang

Abstract:

The downstream manufactures will order their materials from different upstream suppliers to maintain a certain level of the demand. This paper proposes a bivariate model to portray this phenomenon of material demand. We use empirical data to estimate the parameters of model and evaluate the RMSD of model calibration. The results show that the model has better fitness.

Keywords: Farlie-Gumbel-Morgenstern family of bivariate distributions, multi-source ordering, materials demand quantity, recency, ordering time.

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7594 Framework of TAZ_OPT Model for Ambulance Location and Allocation Problem

Authors: Adibah Shuib, Zati Aqmar Zaharudin

Abstract:

Our study is concerned with the development of an Emergency Medical Services (EMS) ambulance location and allocation model called the Time-based Ambulance Zoning Optimization Model (TAZ_OPT). This paper presents the framework of the study. The model is formulated using the goal programming (GP), where the goals are to determine the satellite locations of ambulances and the number of ambulances to be allocated at these locations. The model aims at maximizing the expected demand coverage based on probability of reaching the emergency location within targetted time, and minimizing the ambulance busyness likelihood value. Among the benefits of the model is the increased accessibility and availability of ambulances, thus, enhanced quality of the EMS ambulance services.

Keywords: Optimization, Ambulance Location, Location facilities.

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7593 SiC Merged PiN and Schottky (MPS) Power Diodes Electrothermal Modeling in SPICE

Authors: A. Lakrim, D. Tahri

Abstract:

This paper sets out a behavioral macro-model of a Merged PiN and Schottky (MPS) diode based on silicon carbide (SiC). This model holds good for both static and dynamic electrothermal simulations for industrial applications. Its parameters have been worked out from datasheets curves by drawing on the optimization method: Simulated Annealing (SA) for the SiC MPS diodes made available in the industry. The model also adopts the Analog Behavioral Model (ABM) of PSPICE in which it has been implemented. The thermal behavior of the devices was also taken into consideration by making use of Foster’ canonical network as figured out from electro-thermal measurement provided by the manufacturer of the device.

Keywords: SiC MPS Diode, electro-thermal, SPICE Model.

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7592 A Hidden Markov Model-Based Isolated and Meaningful Hand Gesture Recognition

Authors: Mahmoud Elmezain, Ayoub Al-Hamadi, Jörg Appenrodt, Bernd Michaelis

Abstract:

Gesture recognition is a challenging task for extracting meaningful gesture from continuous hand motion. In this paper, we propose an automatic system that recognizes isolated gesture, in addition meaningful gesture from continuous hand motion for Arabic numbers from 0 to 9 in real-time based on Hidden Markov Models (HMM). In order to handle isolated gesture, HMM using Ergodic, Left-Right (LR) and Left-Right Banded (LRB) topologies is applied over the discrete vector feature that is extracted from stereo color image sequences. These topologies are considered to different number of states ranging from 3 to 10. A new system is developed to recognize the meaningful gesture based on zero-codeword detection with static velocity motion for continuous gesture. Therefore, the LRB topology in conjunction with Baum-Welch (BW) algorithm for training and forward algorithm with Viterbi path for testing presents the best performance. Experimental results show that the proposed system can successfully recognize isolated and meaningful gesture and achieve average rate recognition 98.6% and 94.29% respectively.

Keywords: Computer Vision & Image Processing, Gesture Recognition, Pattern Recognition, Application

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7591 Parametric Study of Vertical Diffusion Still for Water Desalination

Authors: A. Seleem, M. Mortada, M. El Morsi, M. Younan

Abstract:

Diffusion stills have been effective in water desalination. The present work represents a model of the distillation process by using vertical single-effect diffusion stills. A semianalytical model has been developed to model the process. A software computer code using Engineering Equation Solver EES software has been developed to solve the equations of the developed model. An experimental setup has been constructed, and used for the validation of the model. The model is also validated against former literature results. The results obtained from the present experimental test rig, and the data from the literature, have been compared with the results of the code to find its best range of validity. In addition, a parametric analysis of the system has been developed using the model to determine the effect of operating conditions on the system's performance. The dominant parameters that affect the productivity of the still are the hot plate temperature that ranges from (55- 90°C) and feed flow rate in range of (0.00694-0.0211 kg/m2-s).

Keywords: Analytical Model, Solar Distillation, Sustainable Water Systems, Vertical Diffusion Still.

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7590 In Cognitive Radio the Analysis of Bit-Error- Rate (BER) by using PSO Algorithm

Authors: Shrikrishan Yadav, Akhilesh Saini, Krishna Chandra Roy

Abstract:

The electromagnetic spectrum is a natural resource and hence well-organized usage of the limited natural resources is the necessities for better communication. The present static frequency allocation schemes cannot accommodate demands of the rapidly increasing number of higher data rate services. Therefore, dynamic usage of the spectrum must be distinguished from the static usage to increase the availability of frequency spectrum. Cognitive radio is not a single piece of apparatus but it is a technology that can incorporate components spread across a network. It offers great promise for improving system efficiency, spectrum utilization, more effective applications, reduction in interference and reduced complexity of usage for users. Cognitive radio is aware of its environmental, internal state, and location, and autonomously adjusts its operations to achieve designed objectives. It first senses its spectral environment over a wide frequency band, and then adapts the parameters to maximize spectrum efficiency with high performance. This paper only focuses on the analysis of Bit-Error-Rate in cognitive radio by using Particle Swarm Optimization Algorithm. It is theoretically as well as practically analyzed and interpreted in the sense of advantages and drawbacks and how BER affects the efficiency and performance of the communication system.

Keywords: BER, Cognitive Radio, Environmental Parameters, PSO, Radio spectrum, Transmission Parameters

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7589 A Numerical Model for Studying Convectional Lifting Processes in the Tropics

Authors: Chantawan Noisri, Robert Harold Buchanan Exell

Abstract:

A simple model for studying convectional lifting processes in the tropics is described in this paper with some tests of the model in dry air. The model consists of the density equation, the wind equation, the vertical velocity equation, and the temperature equation. The model domain is two-dimensional with length 100 km and height 17.5 km. Plan for experiments to investigate the effects of the heating surface, the deep convection approximation and the treatment of velocities at the boundaries are discussed. Equations for the simplified treatment of moisture in the atmosphere in future numerical experiments are also given.

Keywords: Numerical weather prediction, Finite differences, Convection lifting.

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7588 Validity Domains of Beams Behavioural Models: Efficiency and Reduction with Artificial Neural Networks

Authors: Keny Ordaz-Hernandez, Xavier Fischer, Fouad Bennis

Abstract:

In a particular case of behavioural model reduction by ANNs, a validity domain shortening has been found. In mechanics, as in other domains, the notion of validity domain allows the engineer to choose a valid model for a particular analysis or simulation. In the study of mechanical behaviour for a cantilever beam (using linear and non-linear models), Multi-Layer Perceptron (MLP) Backpropagation (BP) networks have been applied as model reduction technique. This reduced model is constructed to be more efficient than the non-reduced model. Within a less extended domain, the ANN reduced model estimates correctly the non-linear response, with a lower computational cost. It has been found that the neural network model is not able to approximate the linear behaviour while it does approximate the non-linear behaviour very well. The details of the case are provided with an example of the cantilever beam behaviour modelling.

Keywords: artificial neural network, validity domain, cantileverbeam, non-linear behaviour, model reduction.

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7587 MPC of Single Phase Inverter for PV System

Authors: Irtaza M. Syed, Kaamran Raahemifar

Abstract:

This paper presents a model predictive control (MPC) of a utility interactive (UI) single phase inverter (SPI) for a photovoltaic (PV) system at residential/distribution level. The proposed model uses single-phase phase locked loop (PLL) to synchronize SPI with the grid and performs MPC control in a dq reference frame. SPI model consists of boost converter (BC), maximum power point tracking (MPPT) control, and a full bridge (FB) voltage source inverter (VSI). No PI regulators to tune and carrier and modulating waves are required to produce switching sequence. Instead, the operational model of VSI is used to synthesize sinusoidal current and track the reference. Model is validated using a three kW PV system at the input of UI-SPI in Matlab/Simulink. Implementation and results demonstrate simplicity and accuracy, as well as reliability of the model.

Keywords: Matlab/Simulink, Model Predictive Control, Phase Locked Loop, Single Phase Inverter, Voltage Source Inverter.

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7586 Model of Appropriate Science Teaching for Mathayomsuksa 3 (Grade 9) in Ang-Thong Province

Authors: Lertlop, W

Abstract:

This research aims to study the appropriate model of Science teaching for students, academic achievement and to survey students- attitudes toward using appropriate for students in Mathayomsuksa 3 in Ang-Thong province. The research results were as follows: 1. The appropriate model of Science teaching for Mathayomsuksa 3 students in Ang-Thong province including these following five steps: Step 1. The introduction of the lessons. Step 2. Setting the hypothesis. Step 3. Doing the experiment /survey. Step 4. Making conclusion. Step 5. Applying to daily life or other subjects. 2. There is no significant difference between using appropriate model teaching and regular teaching at 0.05 level significant difference. 3. There is a significant difference between before and after teaching using appropriate model of Science teaching at 0.05 level. 4. The satisfaction of students- attitudes to using the appropriate model of Science teaching for students was in intermediate level.

Keywords: Pedagogy, science teaching model, Ang-Thong province.

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7585 Fuel Economy and Stability Enhancement of the Hybrid Vehicles by Using Electrical Machines on Non-Driven Wheels

Authors: P. Naderi, S.M.T. Bathaee, R. Hoseinnezhad, R. Chini

Abstract:

Using electrical machine in conventional vehicles, also called hybrid vehicles, has become a promising control scheme that enables some manners for fuel economy and driver assist for better stability. In this paper, vehicle stability control, fuel economy and Driving/Regeneration braking for a 4WD hybrid vehicle is investigated by using an electrical machine on each non-driven wheels. In front wheels driven vehicles, fuel economy and regenerative braking can be obtained by summing torques applied on rear wheels. On the other hand, unequal torques applied to rear wheels provides enhanced safety and path correction in steering. In this paper, a model with fourteen degrees of freedom is considered for vehicle body, tires and, suspension systems. Thereafter, powertrain subsystems are modeled. Considering an electrical machine on each rear wheel, a fuzzy controller is designed for each driving, braking, and stability conditions. Another fuzzy controller recognizes the vehicle requirements between the driving/regeneration and stability modes. Intelligent vehicle control to multi objective operation and forward simulation are the paper advantages. For reaching to these aims, power management control and yaw moment control will be done by three fuzzy controllers. Also, the above mentioned goals are weighted by another fuzzy sub-controller base on vehicle dynamic. Finally, Simulations performed in MATLAB/SIMULINK environment show that the proposed structure can enhance the vehicle performance in different modes effectively.

Keywords: Hybrid, pitch, roll, regeneration, yaw.

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7584 Knowledge Management Model for Research Projects Masters Program

Authors: Víctor Hugo Medina García, Darío Alejandro Segura Torres

Abstract:

This paper presents the adaptation of the knowledge management model and intellectual capital measurement NOVA to the needs of work or research project must be developed when conducting a program of graduate-level master. Brackets are added in each of the blocks which is represented in the original model NOVA and which allows to represent those involved in each of these.

Keywords: Knowledge management, masters programs, Nova model, research projects

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7583 Toward a Risk Assessment Model Based On Multi-Agent System for Cloud Consumer

Authors: Saadia Drissi, Siham Benhadou, Hicham Medromi

Abstract:

The cloud computing is an innovative paradigm that introduces several changes in technology that have resulted a new ways for cloud providers to deliver their services to cloud consumers mainly in term of security risk assessment, thus, adapting a current risk assessment tools to cloud computing is a very difficult task due to its several characteristics that challenge the effectiveness of risk assessment approaches. As consequence, there is a need of risk assessment model adapted to cloud computing. This paper requires a new risk assessment model based on multi-agent system and AHP model as fundamental steps towards the development of flexible risk assessment approach regarding cloud consumers.

Keywords: Cloud computing, risk assessment model, multi-agent system, AHP model, cloud consumer.

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7582 2D and 3D Unsteady Simulation of the Heat Transfer in the Sample during Heat Treatment by Moving Heat Source

Authors: Z. Veselý, M. Honner, J. Mach

Abstract:

The aim of the performed work is to establish the 2D and 3D model of direct unsteady task of sample heat treatment by moving source employing computer model on the basis of finite element method. Complex boundary condition on heat loaded sample surface is the essential feature of the task. Computer model describes heat treatment of the sample during heat source movement over the sample surface. It is started from 2D task of sample cross section as a basic model. Possibilities of extension from 2D to 3D task are discussed. The effect of the addition of third model dimension on temperature distribution in the sample is showed. Comparison of various model parameters on the sample temperatures is observed. Influence of heat source motion on the depth of material heat treatment is shown for several velocities of the movement. Presented computer model is prepared for the utilization in laser treatment of machine parts.

Keywords: Computer simulation, unsteady model, heat treatment, complex boundary condition, moving heat source.

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7581 Intelligent Temperature Controller for Water-Bath System

Authors: Om Prakash Verma, Rajesh Singla, Rajesh Kumar

Abstract:

Conventional controller’s usually required a prior knowledge of mathematical modelling of the process. The inaccuracy of mathematical modelling degrades the performance of the process, especially for non-linear and complex control problem. The process used is Water-Bath system, which is most widely used and nonlinear to some extent. For Water-Bath system, it is necessary to attain desired temperature within a specified period of time to avoid the overshoot and absolute error, with better temperature tracking capability, else the process is disturbed.

To overcome above difficulties intelligent controllers, Fuzzy Logic (FL) and Adaptive Neuro-Fuzzy Inference System (ANFIS), are proposed in this paper. The Fuzzy controller is designed to work with knowledge in the form of linguistic control rules. But the translation of these linguistic rules into the framework of fuzzy set theory depends on the choice of certain parameters, for which no formal method is known. To design ANFIS, Fuzzy-Inference-System is combined with learning capability of Neural-Network.

It is analyzed that ANFIS is best suitable for adaptive temperature control of above system. As compared to PID and FLC, ANFIS produces a stable control signal. It has much better temperature tracking capability with almost zero overshoot and minimum absolute error.

Keywords: PID Controller, FLC, ANFIS, Non-Linear Control System, Water-Bath System, MATLAB-7.

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7580 Adaptive Gaussian Mixture Model for Skin Color Segmentation

Authors: Reza Hassanpour, Asadollah Shahbahrami, Stephan Wong

Abstract:

Skin color based tracking techniques often assume a static skin color model obtained either from an offline set of library images or the first few frames of a video stream. These models can show a weak performance in presence of changing lighting or imaging conditions. We propose an adaptive skin color model based on the Gaussian mixture model to handle the changing conditions. Initial estimation of the number and weights of skin color clusters are obtained using a modified form of the general Expectation maximization algorithm, The model adapts to changes in imaging conditions and refines the model parameters dynamically using spatial and temporal constraints. Experimental results show that the method can be used in effectively tracking of hand and face regions.

Keywords: Face detection, Segmentation, Tracking, Gaussian Mixture Model, Adaptation.

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7579 Infrastructure Change Monitoring Using Multitemporal Multispectral Satellite Images

Authors: U. Datta

Abstract:

The main objective of this study is to find a suitable approach to monitor the land infrastructure growth over a period of time using multispectral satellite images. Bi-temporal change detection method is unable to indicate the continuous change occurring over a long period of time. To achieve this objective, the approach used here estimates a statistical model from series of multispectral image data over a long period of time, assuming there is no considerable change during that time period and then compare it with the multispectral image data obtained at a later time. The change is estimated pixel-wise. Statistical composite hypothesis technique is used for estimating pixel based change detection in a defined region. The generalized likelihood ratio test (GLRT) is used to detect the changed pixel from probabilistic estimated model of the corresponding pixel. The changed pixel is detected assuming that the images have been co-registered prior to estimation. To minimize error due to co-registration, 8-neighborhood pixels around the pixel under test are also considered. The multispectral images from Sentinel-2 and Landsat-8 from 2015 to 2018 are used for this purpose. There are different challenges in this method. First and foremost challenge is to get quite a large number of datasets for multivariate distribution modelling. A large number of images are always discarded due to cloud coverage. Due to imperfect modelling there will be high probability of false alarm. Overall conclusion that can be drawn from this work is that the probabilistic method described in this paper has given some promising results, which need to be pursued further.

Keywords: Co-registration, GLRT, infrastructure growth, multispectral, multitemporal, pixel-based change detection.

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7578 External Effects on Dynamic Competitive Model of Domestic Airline and High Speed Rail

Authors: Shih-Ching Lo, Yu-Ping Liao

Abstract:

Social-economic variables influence transportation demand largely. Analyses of discrete choice model consider social-economic variables to study traveler-s mode choice and demand. However, to calibrate the discrete choice model needs to have plenty of questionnaire survey. Also, an aggregative model is proposed. The historical data of passenger volumes for high speed rail and domestic civil aviation are employed to calibrate and validate the model. In this study, models with different social-economic variables, which are oil price, GDP per capita, CPI and economic growth rate, are compared. From the results, the model with the oil price is better than models with the other social-economic variables.

Keywords: forecasting, passenger volume, dynamic competitive model, social-economic variables, oil price.

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7577 Sliding-Mode Control of Synchronous Reluctance Motor

Authors: Mostafa.A. Fellani, Dawo.E. Abaid

Abstract:

This paper presents a controller design technique for Synchronous Reluctance Motor to improve its dynamic performance with fast response and high accuracy. The sliding mode control is the most attractive and suitable method to use for this purpose, since it is simple in design and for its insensitivity to parameter variations or external disturbances. When this method implemented it yields fast dynamic response without overshoot and a zero steady-state error. The current loop control with decentralized sliding mode is presented in this paper. The mathematical model for the synchronous machine, the inverter and the controller is developed. The stability of the sliding mode controller is analyzed. Simulation of synchronous reluctance motor and the controller with PWM-inverter has been curried out, using the SIMULINK software package of MATLAB. Simulation results are presented to show the effectiveness of the approach.

Keywords: Dynamic Simulation, MATLAB, PWM-inverter, Reluctance Machine, Sliding-mode.

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7576 An Experimental Study of a Self-Supervised Classifier Ensemble

Authors: Neamat El Gayar

Abstract:

Learning using labeled and unlabelled data has received considerable amount of attention in the machine learning community due its potential in reducing the need for expensive labeled data. In this work we present a new method for combining labeled and unlabeled data based on classifier ensembles. The model we propose assumes each classifier in the ensemble observes the input using different set of features. Classifiers are initially trained using some labeled samples. The trained classifiers learn further through labeling the unknown patterns using a teaching signals that is generated using the decision of the classifier ensemble, i.e. the classifiers self-supervise each other. Experiments on a set of object images are presented. Our experiments investigate different classifier models, different fusing techniques, different training sizes and different input features. Experimental results reveal that the proposed self-supervised ensemble learning approach reduces classification error over the single classifier and the traditional ensemble classifier approachs.

Keywords: Multiple Classifier Systems, classifier ensembles, learning using labeled and unlabelled data, K-nearest neighbor classifier, Bayes classifier.

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7575 Javanese Character Recognition Using Hidden Markov Model

Authors: Anastasia Rita Widiarti, Phalita Nari Wastu

Abstract:

Hidden Markov Model (HMM) is a stochastic method which has been used in various signal processing and character recognition. This study proposes to use HMM to recognize Javanese characters from a number of different handwritings, whereby HMM is used to optimize the number of state and feature extraction. An 85.7 % accuracy is obtained as the best result in 16-stated vertical model using pure HMM. This initial result is satisfactory for prompting further research.

Keywords: Character recognition, off-line handwritingrecognition, Hidden Markov Model.

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7574 Modelling of Groundwater Resources for Al-Najaf City, Iraq

Authors: Hayder H. Kareem, Shunqi Pan

Abstract:

Groundwater is a vital water resource in many areas in the world, particularly in the Middle-East region where the water resources become scarce and depleting. Sustainable management and planning of the groundwater resources become essential and urgent given the impact of the global climate change. In the recent years, numerical models have been widely used to predict the flow pattern and assess the water resources security, as well as the groundwater quality affected by the contaminants transported. In this study, MODFLOW is used to study the current status of groundwater resources and the risk of water resource security in the region centred at Al-Najaf City, which is located in the mid-west of Iraq and adjacent to the Euphrates River. In this study, a conceptual model is built using the geologic and hydrogeologic collected for the region, together with the Digital Elevation Model (DEM) data obtained from the "Global Land Cover Facility" (GLCF) and "United State Geological Survey" (USGS) for the study area. The computer model is also implemented with the distributions of 69 wells in the area with the steady pro-defined hydraulic head along its boundaries. The model is then applied with the recharge rate (from precipitation) of 7.55 mm/year, given from the analysis of the field data in the study area for the period of 1980-2014. The hydraulic conductivity from the measurements at the locations of wells is interpolated for model use. The model is calibrated with the measured hydraulic heads at the locations of 50 of 69 wells in the domain and results show a good agreement. The standard-error-of-estimate (SEE), root-mean-square errors (RMSE), Normalized RMSE and correlation coefficient are 0.297 m, 2.087 m, 6.899% and 0.971 respectively. Sensitivity analysis is also carried out, and it is found that the model is sensitive to recharge, particularly when the rate is greater than (15mm/year). Hydraulic conductivity is found to be another parameter which can affect the results significantly, therefore it requires high quality field data. The results show that there is a general flow pattern from the west to east of the study area, which agrees well with the observations and the gradient of the ground surface. It is found that with the current operational pumping rates of the wells in the area, a dry area is resulted in Al-Najaf City due to the large quantity of groundwater withdrawn. The computed water balance with the current operational pumping quantity shows that the Euphrates River supplies water into the groundwater of approximately 11759 m3/day, instead of gaining water of 11178 m3/day from the groundwater if no pumping from the wells. It is expected that the results obtained from the study can provide important information for the sustainable and effective planning and management of the regional groundwater resources for Al-Najaf City.

Keywords: Al-Najaf city, conceptual modelling, groundwater, unconfined aquifer, visual MODFLOW.

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7573 Accelerating GLA with an M-Tree

Authors: Olli Luoma, Johannes Tuikkala, Olli Nevalainen

Abstract:

In this paper, we propose a novel improvement for the generalized Lloyd Algorithm (GLA). Our algorithm makes use of an M-tree index built on the codebook which makes it possible to reduce the number of distance computations when the nearest code words are searched. Our method does not impose the use of any specific distance function, but works with any metric distance, making it more general than many other fast GLA variants. Finally, we present the positive results of our performance experiments.

Keywords: Clustering, GLA, M-Tree, Vector Quantization .

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7572 Analytical Model to Predict the Shear Capacity of Reinforced Concrete Beams Externally Strengthened with CFRP Composites Conditions

Authors: Rajai Al-Rousan

Abstract:

This paper presents a proposed analytical model for predicting the shear strength of reinforced concrete beams strengthened with CFRP composites as external reinforcement. The proposed analytical model can predict the shear contribution of CFRP composites of RC beams with an acceptable coefficient of correlation with the tested results. Based on the comparison of the proposed model with the published well-known models (ACI model, Triantafillou model, and Colotti model), the ACI model had a wider range of 0.16 to 10.08 for the ratio between tested and predicted ultimate shears at failure. Also, an acceptable range of 0.27 to 2.78 for the ratio between tested and predicted ultimate shears by the Triantafillou model. Finally, the best prediction (the ratio between the tested and predicted ones) of the ultimate shear capacity is observed by using Colotti model with a range of 0.20 to 1.78. Thus, the contribution of the CFRP composites as external reinforcement can be predicted with high accuracy by using the proposed analytical model.

Keywords: Predicting, shear capacity, reinforced concrete, beams, strengthened, externally, CFRP composites.

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7571 Numerical Solution of Manning's Equation in Rectangular Channels

Authors: Abdulrahman Abdulrahman

Abstract:

When the Manning equation is used, a unique value of normal depth in the uniform flow exists for a given channel geometry, discharge, roughness, and slope. Depending on the value of normal depth relative to the critical depth, the flow type (supercritical or subcritical) for a given characteristic of channel conditions is determined whether or not flow is uniform. There is no general solution of Manning's equation for determining the flow depth for a given flow rate, because the area of cross section and the hydraulic radius produce a complicated function of depth. The familiar solution of normal depth for a rectangular channel involves 1) a trial-and-error solution; 2) constructing a non-dimensional graph; 3) preparing tables involving non-dimensional parameters. Author in this paper has derived semi-analytical solution to Manning's equation for determining the flow depth given the flow rate in rectangular open channel. The solution was derived by expressing Manning's equation in non-dimensional form, then expanding this form using Maclaurin's series. In order to simplify the solution, terms containing power up to 4 have been considered. The resulted equation is a quartic equation with a standard form, where its solution was obtained by resolving this into two quadratic factors. The proposed solution for Manning's equation is valid over a large range of parameters, and its maximum error is within -1.586%.

Keywords: Channel design, civil engineering, hydraulic engineering, open channel flow, Manning's equation, normal depth, uniform flow.

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7570 Transformations between Bivariate Polynomial Bases

Authors: Dimitris Varsamis, Nicholas Karampetakis

Abstract:

It is well known, that any interpolating polynomial p (x, y) on the vector space Pn,m of two-variable polynomials with degree less than n in terms of x and less than m in terms of y, has various representations that depends on the basis of Pn,m that we select i.e. monomial, Newton and Lagrange basis e.t.c.. The aim of this short note is twofold : a) to present transformations between the coordinates of the polynomial p (x, y) in the aforementioned basis and b) to present transformations between these bases.

Keywords: Bivariate interpolation polynomial, Polynomial basis, Transformations.

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7569 Discovering the Dimension of Abstractness: Structure-Based Model that Learns New Categories and Categorizes on Different Levels of Abstraction

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

Abstract:

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

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

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7568 A Mean–Variance–Skewness Portfolio Optimization Model

Authors: Kostas Metaxiotis

Abstract:

Portfolio optimization is one of the most important topics in finance. This paper proposes a mean–variance–skewness (MVS) portfolio optimization model. Traditionally, the portfolio optimization problem is solved by using the mean–variance (MV) framework. In this study, we formulate the proposed model as a three-objective optimization problem, where the portfolio's expected return and skewness are maximized whereas the portfolio risk is minimized. For solving the proposed three-objective portfolio optimization model we apply an adapted version of the non-dominated sorting genetic algorithm (NSGAII). Finally, we use a real dataset from FTSE-100 for validating the proposed model.

Keywords: Evolutionary algorithms, portfolio optimization, skewness, stock selection.

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7567 The Gasoil Hydrofining Kinetics Constants Identification

Authors: C. Patrascioiu, V. Matei, N. Nicolae

Abstract:

The paper describes the experiments and the kinetic parameters calculus of the gasoil hydrofining. They are presented experimental results of gasoil hidrofining using Mo and promoted with Ni on aluminum support catalyst. The authors have adapted a kinetic model gasoil hydrofining. Using this proposed kinetic model and the experimental data they have calculated the parameters of the model. The numerical calculus is based on minimizing the difference between the experimental sulf concentration and kinetic model estimation.

Keywords: Hydrofining, kinetic, modeling, optimization.

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7566 Effect of Transmission Codes on Hybrid SC/MRC Diversity Reception MQAM system over Rayleigh Fading Channels

Authors: J.S. Ubhi, M.S. Patterh, T.S. Kamal

Abstract:

In this paper, the effect of transmission codes on the performance of coherent square M-ary quadrature amplitude modulation (CSMQAM) under hybrid selection/maximal-ratio combining (H-S/MRC) diversity is analysed. The fading channels are modeled as frequency non-selective slow independent and identically distributed Rayleigh fading channels corrupted by additive white Gaussian noise (AWGN). The results for coded MQAM are computed numerically for the case of (24,12) extended Golay code and compared with uncoded MQAM under H-S/MRC diversity by plotting error probabilities versus average signal to noise ratio (SNR) for various values L and N in order to examine the improvement in the performance of the digital communications system as the number of selected diversity branches is increased. The results for no diversity, conventional SC and Lth order MRC schemes are also plotted for comparison. Closed form analytical results derived in this paper are sufficiently simple and therefore can be computed numerically without any approximations. The analytical results presented in this paper are expected to provide useful information needed for design and analysis of digital communication systems over wireless fading channels.

Keywords: Error probability, diversity reception, Rayleigh fading channels, wireless digital communications.

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