Search results for: Model Order Formulation
10537 In-Flight Radiometric Performances Analysis of an Airborne Optical Payload
Authors: Caixia Gao, Chuanrong Li, Lingli Tang, Lingling Ma, Yaokai Liu, Xinhong Wang, Yongsheng Zhou
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Performances analysis of remote sensing sensor is required to pursue a range of scientific research and application objectives. Laboratory analysis of any remote sensing instrument is essential, but not sufficient to establish a valid inflight one. In this study, with the aid of the in situ measurements and corresponding image of three-gray scale permanent artificial target, the in-flight radiometric performances analyses (in-flight radiometric calibration, dynamic range and response linearity, signal-noise-ratio (SNR), radiometric resolution) of self-developed short-wave infrared (SWIR) camera are performed. To acquire the inflight calibration coefficients of the SWIR camera, the at-sensor radiances (Li) for the artificial targets are firstly simulated with in situ measurements (atmosphere parameter and spectral reflectance of the target) and viewing geometries using MODTRAN model. With these radiances and the corresponding digital numbers (DN) in the image, a straight line with a formulation of L = G × DN + B is fitted by a minimization regression method, and the fitted coefficients, G and B, are inflight calibration coefficients. And then the high point (LH) and the low point (LL) of dynamic range can be described as LH= (G × DNH + B) and LL= B, respectively, where DNH is equal to 2n − 1 (n is the quantization number of the payload). Meanwhile, the sensor’s response linearity (δ) is described as the correlation coefficient of the regressed line. The results show that the calibration coefficients (G and B) are 0.0083 W·sr−1m−2µm−1 and −3.5 W·sr−1m−2µm−1; the low point of dynamic range is −3.5 W·sr−1m−2µm−1 and the high point is 30.5 W·sr−1m−2µm−1; the response linearity is approximately 99%. Furthermore, a SNR normalization method is used to assess the sensor’s SNR, and the normalized SNR is about 59.6 when the mean value of radiance is equal to 11.0 W·sr−1m−2µm−1; subsequently, the radiometric resolution is calculated about 0.1845 W•sr-1m-2μm-1. Moreover, in order to validate the result, a comparison of the measured radiance with a radiative-transfer-code-predicted over four portable artificial targets with reflectance of 20%, 30%, 40%, 50% respectively, is performed. It is noted that relative error for the calibration is within 6.6%.
Keywords: Calibration, dynamic range, radiometric resolution, SNR.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 133110536 Design of Moving Sliding Surfaces in A Variable Structure Plant and Chattering Phenomena
Authors: T.C. Manjunath
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This paper deals with the design of a moving sliding surface in a variable structure plant for a second order system. The chattering phenomena is also dealt with during the switching process for an unstable sliding surface condition. The simulation examples considered in this paper shows the effectiveness of the sliding mode control method used for the design of the moving sliding surfaces. A simulink model of the continuous system was also developed in MATLAB-SIMULINK for the design and hence demonstrated. The phase portraits and the state plots shows the demonstration of the powerful control technique which can be applied for second order systems.Keywords: Sliding mode control, VSC, Reaching phase, Sliding phase, Moving surfaces, Chattering, Trajectories.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 232110535 High Speed Video Transmission for Telemedicine using ATM Technology
Authors: J. P. Dubois, H. M. Chiu
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In this paper, we study statistical multiplexing of VBR video in ATM networks. ATM promises to provide high speed realtime multi-point to central video transmission for telemedicine applications in rural hospitals and in emergency medical services. Video coders are known to produce variable bit rate (VBR) signals and the effects of aggregating these VBR signals need to be determined in order to design a telemedicine network infrastructure capable of carrying these signals. We first model the VBR video signal and simulate it using a generic continuous-data autoregressive (AR) scheme. We carry out the queueing analysis by the Fluid Approximation Model (FAM) and the Markov Modulated Poisson Process (MMPP). The study has shown a trade off: multiplexing VBR signals reduces burstiness and improves resource utilization, however, the buffer size needs to be increased with an associated economic cost. We also show that the MMPP model and the Fluid Approximation model fit best, respectively, the cell region and the burst region. Therefore, a hybrid MMPP and FAM completely characterizes the overall performance of the ATM statistical multiplexer. The ramifications of this technology are clear: speed, reliability (lower loss rate and jitter), and increased capacity in video transmission for telemedicine. With migration to full IP-based networks still a long way to achieving both high speed and high quality of service, the proposed ATM architecture will remain of significant use for telemedicine.Keywords: ATM, multiplexing, queueing, telemedicine, VBR.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 173410534 Preparation and in vitro Bactericidal and Fungicidal Efficiency of NanoSilver/Methylcellulose Hydrogel
Authors: A. Panacek, M. Kilianova, R. Prucek, V. Husickova, R. Vecerova, M. Kolar, L. Kvitek, R. Zboril
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In this work we describe the preparation of NanoSilver/methylcellulose hydrogel containing silver nanoparticles (NPs) for topical bactericidal applications. Highly concentrated dispersion of silver NPs as high as of 5g/L of silver with diameter of 10nm was prepared by reduction of AgNO3 via strong reducing agent NaBH4. Silver NPs were stabilized by addition of sodium polyacrylate in order to prevent their aggregation at such high concentration. This way synthesized silver NPs were subsequently incorporated into methylcellulose suspension at elevated temperature resulting in formation of NanoSilver/methylcellulose hydrogel when temperature cooled down to laboratory conditions. In vitro antibacterial activity assay proved high bactericidal and fungicidal efficiency of silver NPs alone in the form of dispersion as well as in the form of hydrogel against broad spectrum of bacteria and yeasts including highly multiresistant strains such as methicillin-resistant Staphylococcus aureus. A very low concentrations of silver as low as 0.84mg/L Ag in as-prepared dispersion gave antibacterial performance. NanoSilver/methylcellulose hydrogel showed antibacterial action at the lowest used silver concentration equal to 25mg/L. Such prepared NanoSilver/methylcellulose hydrogel represent promising topical antimicrobial formulation for treatment of burns and wounds.
Keywords: Antimicrobial, burn, hydrogel, silver NPs.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 326610533 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
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 203010532 Image Ranking to Assist Object Labeling for Training Detection Models
Authors: Tonislav Ivanov, Oleksii Nedashkivskyi, Denis Babeshko, Vadim Pinskiy, Matthew Putman
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Training a machine learning model for object detection that generalizes well is known to benefit from a training dataset with diverse examples. However, training datasets usually contain many repeats of common examples of a class and lack rarely seen examples. This is due to the process commonly used during human annotation where a person would proceed sequentially through a list of images labeling a sufficiently high total number of examples. Instead, the method presented involves an active process where, after the initial labeling of several images is completed, the next subset of images for labeling is selected by an algorithm. This process of algorithmic image selection and manual labeling continues in an iterative fashion. The algorithm used for the image selection is a deep learning algorithm, based on the U-shaped architecture, which quantifies the presence of unseen data in each image in order to find images that contain the most novel examples. Moreover, the location of the unseen data in each image is highlighted, aiding the labeler in spotting these examples. Experiments performed using semiconductor wafer data show that labeling a subset of the data, curated by this algorithm, resulted in a model with a better performance than a model produced from sequentially labeling the same amount of data. Also, similar performance is achieved compared to a model trained on exhaustive labeling of the whole dataset. Overall, the proposed approach results in a dataset that has a diverse set of examples per class as well as more balanced classes, which proves beneficial when training a deep learning model.Keywords: Computer vision, deep learning, object detection, semiconductor.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 80510531 Channels Splitting Strategy for Optical Local Area Networks of Passive Star Topology
Authors: Peristera Baziana
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In this paper, we present a network configuration for a WDM LANs of passive star topology that assume that the set of data WDM channels is split into two separate sets of channels, with different access rights over them. Especially, a synchronous transmission WDMA access algorithm is adopted in order to increase the probability of successful transmission over the data channels and consequently to reduce the probability of data packets transmission cancellation in order to avoid the data channels collisions. Thus, a control pre-transmission access scheme is followed over a separate control channel. An analytical Markovian model is studied and the average throughput is mathematically derived. The performance is studied for several numbers of data channels and various values of control phase duration.Keywords: Access algorithm, channels division, collisions avoidance, wavelength division multiplexing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 100310530 Application of Extreme Learning Machine Method for Time Series Analysis
Authors: Rampal Singh, S. Balasundaram
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In this paper, we study the application of Extreme Learning Machine (ELM) algorithm for single layered feedforward neural networks to non-linear chaotic time series problems. In this algorithm the input weights and the hidden layer bias are randomly chosen. The ELM formulation leads to solving a system of linear equations in terms of the unknown weights connecting the hidden layer to the output layer. The solution of this general system of linear equations will be obtained using Moore-Penrose generalized pseudo inverse. For the study of the application of the method we consider the time series generated by the Mackey Glass delay differential equation with different time delays, Santa Fe A and UCR heart beat rate ECG time series. For the choice of sigmoid, sin and hardlim activation functions the optimal values for the memory order and the number of hidden neurons which give the best prediction performance in terms of root mean square error are determined. It is observed that the results obtained are in close agreement with the exact solution of the problems considered which clearly shows that ELM is a very promising alternative method for time series prediction.Keywords: Chaotic time series, Extreme learning machine, Generalization performance.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 350710529 Adaptive Gaussian Mixture Model for Skin Color Segmentation
Authors: Reza Hassanpour, Asadollah Shahbahrami, Stephan Wong
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 240310528 A Description Logics Based Approach for Building Multi-Viewpoints Ontologies
Authors: M. Hemam, M. Djezzar, T. Djouad
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We are interested in the problem of building an ontology in a heterogeneous organization, by taking into account different viewpoints and different terminologies of communities in the organization. Such ontology, that we call multi-viewpoint ontology, confers to the same universe of discourse, several partial descriptions, where each one is relative to a particular viewpoint. In addition, these partial descriptions share at global level, ontological elements constituent a consensus between the various viewpoints. In order to provide response elements to this problem we define a multi-viewpoints knowledge model based on viewpoint and ontology notions. The multi-viewpoints knowledge model is used to formalize the multi-viewpoints ontology in description logics language.Keywords: Description logic, knowledge engineering, ontology, viewpoint.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 101010527 Formulation of Mortars with Marine Sediments
Authors: Nor-Edine Abriak, Mouhamadou Amar, Mahfoud Benzerzour
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The transition to a more sustainable economy is directed by a reduction in the consumption of raw materials in equivalent production. The recovery of byproducts and especially the dredged sediment as mineral addition in cements matrix represents an alternative to reduce raw material consumption and construction sector’s carbon footprint. However, the efficient use of sediment requires adequate and optimal treatment. Several processing techniques have so far been applied in order to improve some physicochemical properties. The heat treatment by calcination was effective in removing the organic fraction and activates the pozzolanic properties. In this article, the effect of the optimized heat treatment of marine sediments in the physico-mechanical and environmental properties of mortars are shown. A finding is that the optimal substitution of a portion of cement by treated sediments by calcination at 750 °C helps to maintain or improve the mechanical properties of the cement matrix in comparison with a standard reference mortar. The use of calcined sediment enhances mortar behavior in terms of mechanical strength and durability. From an environmental point of view and life cycle, mortars formulated containing treated sediments are considered inert with respect to the inert waste storage facilities reference (ISDI-France).Keywords: Sediment, calcination, cement, reuse.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 87810526 External Effects on Dynamic Competitive Model of Domestic Airline and High Speed Rail
Authors: Shih-Ching Lo, Yu-Ping Liao
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 157510525 Sixth-Order Two-Point Efficient Family of Super-Halley Type Methods
Authors: Ramandeep Behl, S. S. Motsa
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The main focus of this manuscript is to provide a highly efficient two-point sixth-order family of super-Halley type methods that do not require any second-order derivative evaluation for obtaining simple roots of nonlinear equations, numerically. Each member of the proposed family requires two evaluations of the given function and two evaluations of the first-order derivative per iteration. By using Mathematica-9 with its high precision compatibility, a variety of concrete numerical experiments and relevant results are extensively treated to confirm t he t heoretical d evelopment. From their basins of attraction, it has been observed that the proposed methods have better stability and robustness as compared to the other sixth-order methods available in the literature.Keywords: Basins of attraction, nonlinear equations, simple roots, Super-Halley.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 69010524 Automatic Fluid-Structure Interaction Modeling and Analysis of Butterfly Valve Using Python Script
Authors: N. Guru Prasath, Sangjin Ma, Chang-Wan Kim
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A butterfly valve is a quarter turn valve which is used to control the flow of a fluid through a section of pipe. Generally, butterfly valve is used in wide range of applications such as water distribution, sewage, oil and gas plants. In particular, butterfly valve with larger diameter finds its immense applications in hydro power plants to control the fluid flow. In-lieu with the constraints in cost and size to run laboratory setup, analysis of large diameter values will be mostly studied by computational method which is the best and inexpensive solution. For fluid and structural analysis, CFD and FEM software is used to perform large scale valve analyses, respectively. In order to perform above analysis in butterfly valve, the CAD model has to recreate and perform mesh in conventional software’s for various dimensions of valve. Therefore, its limitation is time consuming process. In-order to overcome that issue, python code was created to outcome complete pre-processing setup automatically in Salome software. Applying dimensions of the model clearly in the python code makes the running time comparatively lower and easier way to perform analysis of the valve. Hence, in this paper, an attempt was made to study the fluid-structure interaction (FSI) of butterfly valves by varying the valve angles and dimensions using python code in pre-processing software, and results are produced.
Keywords: Butterfly valve, fluid-structure interaction, automatic CFD analysis, flow coefficient.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 128110523 Data Analysis Techniques for Predictive Maintenance on Fleet of Heavy-Duty Vehicles
Authors: Antonis Sideris, Elias Chlis Kalogeropoulos, Konstantia Moirogiorgou
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The present study proposes a methodology for the efficient daily management of fleet vehicles and construction machinery. The application covers the area of remote monitoring of heavy-duty vehicles operation parameters, where specific sensor data are stored and examined in order to provide information about the vehicle’s health. The vehicle diagnostics allow the user to inspect whether maintenance tasks need to be performed before a fault occurs. A properly designed machine learning model is proposed for the detection of two different types of faults through classification. Cross validation is used and the accuracy of the trained model is checked with the confusion matrix.
Keywords: Fault detection, feature selection, machine learning, predictive maintenance.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 76610522 Javanese Character Recognition Using Hidden Markov Model
Authors: Anastasia Rita Widiarti, Phalita Nari Wastu
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 197810521 Hybrid Association Control Scheme and Load Balancing in Wireless LANs
Authors: Chutima Prommak, Airisa Jantaweetip
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This paper presents a hybrid association control scheme that can maintain load balancing among access points in the wireless LANs and can satisfy the quality of service requirements of the multimedia traffic applications. The proposed model is mathematically described as a linear programming model. Simulation study and analysis were conducted in order to demonstrate the performance of the proposed hybrid load balancing and association control scheme. Simulation results shows that the proposed scheme outperforms the other schemes in term of the percentage of blocking and the quality of the data transfer rate providing to the multimedia and real-time applications.Keywords: Association control, Load balancing, Wireless LANs
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 151510520 An Examination and Validation of the Theoretical Resistivity-Temperature Relationship for Conductors
Authors: Fred Lacy
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Electrical resistivity is a fundamental parameter of metals or electrical conductors. Since resistivity is a function of temperature, in order to completely understand the behavior of metals, a temperature dependent theoretical model is needed. A model based on physics principles has recently been developed to obtain an equation that relates electrical resistivity to temperature. This equation is dependent upon a parameter associated with the electron travel time before being scattered, and a parameter that relates the energy of the atoms and their separation distance. Analysis of the energy parameter reveals that the equation is optimized if the proportionality term in the equation is not constant but varies over the temperature range. Additional analysis reveals that the theoretical equation can be used to determine the mean free path of conduction electrons, the number of defects in the atomic lattice, and the ‘equivalent’ charge associated with the metallic bonding of the atoms. All of this analysis provides validation for the theoretical model and provides insight into the behavior of metals where performance is affected by temperatures (e.g., integrated circuits and temperature sensors).
Keywords: Callendar–van Dusen, conductivity, mean free path, resistance temperature detector, temperature sensor.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 217310519 Analytical Model to Predict the Shear Capacity of Reinforced Concrete Beams Externally Strengthened with CFRP Composites Conditions
Authors: Rajai Al-Rousan
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 85810518 An Enhanced Artificial Neural Network for Air Temperature Prediction
Authors: Brian A. Smith, Ronald W. McClendon, Gerrit Hoogenboom
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The mitigation of crop loss due to damaging freezes requires accurate air temperature prediction models. An improved model for temperature prediction in Georgia was developed by including information on seasonality and modifying parameters of an existing artificial neural network model. Alternative models were compared by instantiating and training multiple networks for each model. The inclusion of up to 24 hours of prior weather information and inputs reflecting the day of year were among improvements that reduced average four-hour prediction error by 0.18°C compared to the prior model. Results strongly suggest model developers should instantiate and train multiple networks with different initial weights to establish appropriate model parameters.
Keywords: Time-series forecasting, weather modeling.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 185310517 Zero-Dissipative Explicit Runge-Kutta Method for Periodic Initial Value Problems
Authors: N. Senu, I. A. Kasim, F. Ismail, N. Bachok
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In this paper zero-dissipative explicit Runge-Kutta method is derived for solving second-order ordinary differential equations with periodical solutions. The phase-lag and dissipation properties for Runge-Kutta (RK) method are also discussed. The new method has algebraic order three with dissipation of order infinity. The numerical results for the new method are compared with existing method when solving the second-order differential equations with periodic solutions using constant step size.
Keywords: Dissipation, Oscillatory solutions, Phase-lag, Runge- Kutta methods.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 189610516 Synthesis of Logic Circuits Using Fractional-Order Dynamic Fitness Functions
Authors: Cecília Reis, J. A. Tenreiro Machado, J. Boaventura Cunha
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This paper analyses the performance of a genetic algorithm using a new concept, namely a fractional-order dynamic fitness function, for the synthesis of combinational logic circuits. The experiments reveal superior results in terms of speed and convergence to achieve a solution.
Keywords: Circuit design, fractional-order systems, genetic algorithms, logic circuits
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 172510515 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
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 77110514 CFD Simulation for Flow Behavior in Boiling Water Reactor Vessel and Upper Pool under Decommissioning Condition
Authors: Y. T. Ku, S. W. Chen, J. R. Wang, C. Shih, Y. F. Chang
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In order to respond the policy decision of non-nuclear homes, Tai Power Company (TPC) will provide the decommissioning project of Kuosheng Nuclear power plant (KSNPP) to meet the regulatory requirement in near future. In this study, the computational fluid dynamics (CFD) methodology has been employed to develop a flow prediction model for boiling water reactor (BWR) with upper pool under decommissioning stage. The model can be utilized to investigate the flow behavior as the vessel combined with upper pool and continuity cooling system. At normal operating condition, different parameters are obtained for the full fluid area, including velocity, mass flow, and mixing phenomenon in the reactor pressure vessel (RPV) and upper pool. Through the efforts of the study, an integrated simulation model will be developed for flow field analysis of decommissioning KSNPP under normal operating condition. It can be expected that a basis result for future analysis application of TPC can be provide from this study.
Keywords: CFD, BWR, decommissioning, upper pool.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 74610513 Fuzzy Logic Based Determination of Battery Charging Efficiency Applied to Hybrid Power System
Authors: Priyanka Paliwal, N. P. Patidar, R. K. Nema
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Battery storage system is emerging as an essential component of hybrid power system based on renewable energy resources such as solar and wind in order to make these sources dispatchable. Accurate modeling of battery storage system is ssential in order to ensure optimal planning of hybrid power systems incorporating battery storage. Majority of the system planning studies involving battery storage assume battery charging efficiency to be constant. However a strong correlation exists between battery charging efficiency and battery state of charge. In this work a Fuzzy logic based model has been presented for determining battery charging efficiency relative to a particular SOC. In order to demonstrate the efficacy of proposed approach, reliability evaluation studies are carried out for a hypothetical autonomous hybrid power system located in Jaisalmer, Rajasthan, India. The impact of considering battery charging efficiency as a function of state of charge is compared against the assumption of fixed battery charging efficiency for three different configurations comprising of wind-storage, solar-storage and wind-solar-storage.
Keywords: Battery Storage, Charging efficiency, Fuzzy Logic, Hybrid Power System, Reliability
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 207810512 A Mean–Variance–Skewness Portfolio Optimization Model
Authors: Kostas Metaxiotis
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 139610511 Application of the Piloting Law Based on Adaptive Differentiators via Second Order Sliding Mode for a Fixed Wing Aircraft
Authors: Zaouche Mohammed, Amini Mohammed, Foughali Khaled, Hamissi Aicha, Aktouf Mohand Arezki, Boureghda Ilyes
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In this paper, we present a piloting law based on the adaptive differentiators via high order sliding mode controller, by using an aircraft in virtual simulated environment. To deal with the design of an autopilot controller, we propose a framework based on Software in the Loop (SIL) methodology and we use MicrosoftTM Flight Simulator (FS-2004) as the environment for plane simulation. The aircraft dynamic model is nonlinear, Multi-Input Multi-Output (MIMO) and tightly coupled. The nonlinearity resides in the dynamic equations and also in the aerodynamic coefficients' variability. In our case, two (02) aircrafts are used in the flight tests, the Zlin-142 and MQ-1 Predator. For both aircrafts and in a very low altitude flight, we send the piloting control inputs to the aircraft which has stalled due to a command disconnection. Then, we present the aircraft’s dynamic behavior analysis while reestablishing the command transmission. Finally, a comparative study between the two aircraft’s dynamic behaviors is presented.
Keywords: Adaptive differentiators, Microsoft Flight Simulator, MQ-1 predator, second order sliding modes, Zlin-142.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 121010510 Time-Dependent Behavior of Damaged Reinforced Concrete Shear Walls Strengthened with Composite Plates Having Variable Fibers Spacing
Authors: R. Yeghnem, L. Boulefrakh, S. A. Meftah, A. Tounsi, E. A. Adda Bedia
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In this study, the time-dependent behavior of damaged reinforced concrete shear wall structures strengthened with composite plates having variable fibers spacing was investigated to analyze their seismic response. In the analytical formulation, the adherent and the adhesive layers are all modeled as shear walls, using the mixed Finite Element Method (FEM). The anisotropic damage model is adopted to describe the damage extent of the Reinforced Concrete shear walls. The phenomenon of creep and shrinkage of concrete has been determined by Eurocode 2. Large earthquakes recorded in Algeria (El-Asnam and Boumerdes) have been tested to demonstrate the accuracy of the proposed method. Numerical results are obtained for non-uniform distributions of carbon fibers in epoxy matrices. The effects of damage extent and the delay mechanism creep and shrinkage of concrete are highlighted. Prospects are being studied.Keywords: RC shear wall structures, composite plates, creep and shrinkage, damaged reinforced concrete structures, finite element method.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 166310509 The Gasoil Hydrofining Kinetics Constants Identification
Authors: C. Patrascioiu, V. Matei, N. Nicolae
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 200710508 Aeroelastic Analysis of Engine Nacelle Strake Considering Geometric Nonlinear Behavior
Authors: N. Manoj
Abstract:
The aeroelastic behavior of engine nacelle strake when subjected to unsteady aerodynamic flows is investigated in this paper. Geometric nonlinear characteristics and modal parameters of nacelle strake are studied when it is under dynamic loading condition. Here, an N-S based Finite Volume solver is coupled with Finite Element (FE) based nonlinear structural solver to investigate the nonlinear characteristics of nacelle strake over a range of dynamic pressures at various phases of flight like takeoff, climb, and cruise conditions. The combination of high fidelity models for both aerodynamics and structural dynamics is used to predict the nonlinearities of strake (chine). The methodology adopted for present aeroelastic analysis is partitioned-based time domain coupled CFD and CSD solvers and it is validated by the consideration of experimental and numerical comparison of aeroelastic data for a cropped delta wing model which has a proven record. The present strake geometry is derived from theoretical formulation. The amplitude and frequency obtained from the coupled solver at various dynamic pressures is discussed, which gives a better understanding of its impact on aerodynamic design-sizing of strake.
Keywords: Aeroelasticity, finite volume, geometric nonlinearity, limit cycle oscillations, strake.
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