Search results for: Probabilistic models
2309 Measurement of CES Production Functions Considering Energy as an Input
Authors: Donglan Zha, Jiansong Si
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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.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9482308 Phosphine Mortality Estimation for Simulation of Controlling Pest of Stored Grain: Lesser Grain Borer (Rhyzopertha dominica)
Authors: Mingren Shi, Michael Renton
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There is a world-wide need for the development of sustainable management strategies to control pest infestation and the development of phosphine (PH3) resistance in lesser grain borer (Rhyzopertha dominica). Computer simulation models can provide a relatively fast, safe and inexpensive way to weigh the merits of various management options. However, the usefulness of simulation models relies on the accurate estimation of important model parameters, such as mortality. Concentration and time of exposure are both important in determining mortality in response to a toxic agent. Recent research indicated the existence of two resistance phenotypes in R. dominica in Australia, weak and strong, and revealed that the presence of resistance alleles at two loci confers strong resistance, thus motivating the construction of a two-locus model of resistance. Experimental data sets on purified pest strains, each corresponding to a single genotype of our two-locus model, were also available. Hence it became possible to explicitly include mortalities of the different genotypes in the model. In this paper we described how we used two generalized linear models (GLM), probit and logistic models, to fit the available experimental data sets. We used a direct algebraic approach generalized inverse matrix technique, rather than the traditional maximum likelihood estimation, to estimate the model parameters. The results show that both probit and logistic models fit the data sets well but the former is much better in terms of small least squares (numerical) errors. Meanwhile, the generalized inverse matrix technique achieved similar accuracy results to those from the maximum likelihood estimation, but is less time consuming and computationally demanding.
Keywords: mortality estimation, probit models, logistic model, generalized inverse matrix approach, pest control simulation
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15702307 Pricing European Options under Jump Diffusion Models with Fast L-stable Padé Scheme
Authors: Salah Alrabeei, Mohammad Yousuf
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The goal of option pricing theory is to help the investors to manage their money, enhance returns and control their financial future by theoretically valuing their options. Modeling option pricing by Black-School models with jumps guarantees to consider the market movement. However, only numerical methods can solve this model. Furthermore, not all the numerical methods are efficient to solve these models because they have nonsmoothing payoffs or discontinuous derivatives at the exercise price. In this paper, the exponential time differencing (ETD) method is applied for solving partial integrodifferential equations arising in pricing European options under Merton’s and Kou’s jump-diffusion models. Fast Fourier Transform (FFT) algorithm is used as a matrix-vector multiplication solver, which reduces the complexity from O(M2) into O(M logM). A partial fraction form of Pad`e schemes is used to overcome the complexity of inverting polynomial of matrices. These two tools guarantee to get efficient and accurate numerical solutions. We construct a parallel and easy to implement a version of the numerical scheme. Numerical experiments are given to show how fast and accurate is our scheme.Keywords: Integral differential equations, L-stable methods, pricing European options, Jump–diffusion model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 4842306 Modeling and Simulation Methods Using MATLAB/Simulink
Authors: Jamuna Konda, Umamaheswara Reddy Karumuri, Sriramya Muthugi, Varun Pishati, Ravi Shakya,
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This paper investigates the challenges involved in mathematical modeling of plant simulation models ensuring the performance of the plant models much closer to the real time physical model. The paper includes the analysis performed and investigation on different methods of modeling, design and development for plant model. Issues which impact the design time, model accuracy as real time model, tool dependence are analyzed. The real time hardware plant would be a combination of multiple physical models. It is more challenging to test the complete system with all possible test scenarios. There are possibilities of failure or damage of the system due to any unwanted test execution on real time.
Keywords: Model Based Design, MATLAB, Simulink, Stateflow, plant model, real time model, real-time workshop, target language compiler.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16822305 Generation of 3D Models Obtained with Low-Cost RGB and Thermal Sensors Mounted on Drones
Authors: Julio Manuel de Luis Ruiz, Javier Sedano Cibrián, Rubén Pérez Álvarez, Raúl Pereda García, Felipe Piña García
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Nowadays it is common to resort to aerial photography to carry out the prospection and/or exploration of archaeological sites. In recent years, Unmanned Aerial Vehicles (UAVs) have been applied as the vehicles that carry the sensor. This implies certain advantages, such as the possibility of including low-cost sensors, given that these vehicles can carry the sensor at relatively low altitudes. Due to this, low-cost dual sensors have recently begun to be used. This new equipment can collaborate with classic Digital Elevation Models (DEMs) in the exploration of archaeological sites, but this entails the need for a methodological setting to optimize the acquisition, processing and exploitation of the information provided by low-cost dual sensors. This research focuses on the design of an appropriate workflow to obtain 3D models with low-cost sensors carried on UAVs, both in the RGB and thermal domains. All the foregoing has been applied to the archaeological site of Juliobriga, located in Cantabria (Spain). To this end, a flight with this type of sensors has been planned, developed and analyzed. It has been applied to the archaeological site of Juliobriga (Cantabria, Spain). A strong dependence of the thermal sensor on the GSD, and the capability of this technique to interpret underground materials. This research allows to state that the thermal nature of the site does not provide main information about the site itself, but with combination with other types of information, such as the DEM, the typology of materials, etc., can produce very positive results with respect to the exploration and knowledge of the site.
Keywords: process optimization, RGB models, thermal models, UAV, workflow
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6012304 Comparisons of Co-Seismic Gravity Changes between GRACE Observations and the Predictions from the Finite-Fault Models for the 2012 Mw = 8.6 Indian Ocean Earthquake Off-Sumatra
Authors: Armin Rahimi
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The Gravity Recovery and Climate Experiment (GRACE) has been a very successful project in determining math redistribution within the Earth system. Large deformations caused by earthquakes are in the high frequency band. Unfortunately, GRACE is only capable to provide reliable estimate at the low-to-medium frequency band for the gravitational changes. In this study, we computed the gravity changes after the 2012 Mw8.6 Indian Ocean earthquake off-Sumatra using the GRACE Level-2 monthly spherical harmonic (SH) solutions released by the University of Texas Center for Space Research (UTCSR). Moreover, we calculated gravity changes using different fault models derived from teleseismic data. The model predictions showed non-negligible discrepancies in gravity changes. However, after removing high-frequency signals, using Gaussian filtering 350 km commensurable GRACE spatial resolution, the discrepancies vanished, and the spatial patterns of total gravity changes predicted from all slip models became similar at the spatial resolution attainable by GRACE observations, and predicted-gravity changes were consistent with the GRACE-detected gravity changes. Nevertheless, the fault models, in which give different slip amplitudes, proportionally lead to different amplitude in the predicted gravity changes.Keywords: Undersea earthquake, GRACE observation, gravity change, dislocation model, slip distribution.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9782303 Determining of Stage-Discharge Relationship for Meandering Compound Channels Using M5 Decision Tree Model
Authors: Mehdi Kheradmand, Mehdi Azhdary Moghaddam, Abdolreza Zahiri, Khalil Ghorbani
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In modeling phenomena, the presence of local conditions may cause the use of a general relation not to produce good results and thus fail to demonstrate local changes. If possible, identifying homogenous limits and providing simple linear relations for each of these limits will increase the accuracy of models. Accordingly, the models are divided into simpler and smaller problems to solve complicated problems, and the obtained answers will be combined. This simple idea can be applied to decision tree models. For this aim, the input data values are divided into several sub-intervals or sub-regions, and an appropriate model is extracted for an appropriate model or equation. This research proposes the M5 decision tree method as a solution to accurately compute the flow discharge in meandering compound channels.
Keywords: Stage-discharge relationship, decision tree, M5 decision tree model, meandering compound channels.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2182302 Modeling of PZ in Haunch Connections Systems
Authors: Peyman Shadman Heidari, Roohollah Ahmady Jazany, Mahmood Reza Mehran, Pouya Shadman Heidari, Mohammad khorasani
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Modeling of Panel Zone (PZ) seismic behavior, because of its role in overall ductility and lateral stiffness of steel moment frames, has been considered a challenge for years. There are some studies regarding the effects of different doubler plates thicknesses and geometric properties of PZ on its seismic behavior. However, there is not much investigation on the effects of number of provided continuity plates in case of presence of one triangular haunch, two triangular haunches and rectangular haunch (T shape haunches) for exterior columns. In this research first detailed finite element models of 12tested connection of SAC joint venture were created and analyzed then obtained cyclic behavior backbone curves of these models besides other FE models for similar tests were used for neural network training. Then seismic behavior of these data is categorized according to continuity plate-s arrangements and differences in type of haunches. PZ with one-sided haunches have little plastic rotation. As the number of continuity plates increases due to presence of two triangular haunches (four continuity plate), there will be no plastic rotation, in other words PZ behaves in its elastic range. In the case of rectangular haunch, PZ show more plastic rotation in comparison with one-sided triangular haunch and especially double-sided triangular haunches. Moreover, the models that will be presented in case of triangular one-sided and double- sided haunches and rectangular haunches as a result of this study seem to have a proper estimation of PZ seismic behavior.Keywords: Continuity plate, FE models, Neural network, Panel zone, Plastic rotation, Rectangular haunch, Seismic behavior
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19982301 Combining Similarity and Dissimilarity Measurements for the Development of QSAR Models Applied to the Prediction of Antiobesity Activity of Drugs
Authors: Irene Luque Ruiz, Manuel Urbano Cuadrado, Miguel Ángel Gómez-Nieto
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In this paper we study different similarity based approaches for the development of QSAR model devoted to the prediction of activity of antiobesity drugs. Classical similarity approaches are compared regarding to dissimilarity models based on the consideration of the calculation of Euclidean distances between the nonisomorphic fragments extracted in the matching process. Combining the classical similarity and dissimilarity approaches into a new similarity measure, the Approximate Similarity was also studied, and better results were obtained. The application of the proposed method to the development of quantitative structure-activity relationships (QSAR) has provided reliable tools for predicting of inhibitory activity of drugs. Acceptable results were obtained for the models presented here.Keywords: Graph similarity, Nonisomorphic dissimilarity, Approximate similarity, Drugs activity prediction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15502300 Computational Networks for Knowledge Representation
Authors: Nhon Van Do
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In the artificial intelligence field, knowledge representation and reasoning are important areas for intelligent systems, especially knowledge base systems and expert systems. Knowledge representation Methods has an important role in designing the systems. There have been many models for knowledge such as semantic networks, conceptual graphs, and neural networks. These models are useful tools to design intelligent systems. However, they are not suitable to represent knowledge in the domains of reality applications. In this paper, new models for knowledge representation called computational networks will be presented. They have been used in designing some knowledge base systems in education for solving problems such as the system that supports studying knowledge and solving analytic geometry problems, the program for studying and solving problems in Plane Geometry, the program for solving problems about alternating current in physics.Keywords: Artificial intelligence, artificial intelligence and education, knowledge engineering, knowledge representation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22092299 A Statistical Identification Approach by the Boundary Field Changes
Authors: Rumena D. Stancheva, Ilona I. Iatcheva
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In working mode some unexpected changes could be arise in inner structure of electromagnetic device. They influence modification in electromagnetic field propagation map. The field values at an observed boundary are also changed. The development of the process has to be watched because the arising structural changes would provoke the device to be gone out later. The probabilistic assessment of the state is possible to be made. The numerical assessment points if the resulting changes have only accidental character or they are due to the essential inner structural disturbances. The presented application example is referring to the 200MW turbine-generator. A part of the stator core end teeth zone is simulated broken. Quasi three-dimensional electromagnetic and temperature field are solved applying FEM. The stator core state diagnosis is proposed to be solved as an identification problem on the basis of a statistical criterion.Keywords: Identification, structural disturbance, statistical criterion.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12792298 Effective Charge Coupling in Low Dimensional Doped Quantum Antiferromagnets
Authors: Suraka Bhattacharjee, Ranjan Chaudhury
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The interaction between the charge degrees of freedom for itinerant antiferromagnets is investigated in terms of generalized charge stiffness constant corresponding to nearest neighbour t-J model and t1-t2-t3-J model. The low dimensional hole doped antiferromagnets are the well known systems that can be described by the t-J-like models. Accordingly, we have used these models to investigate the fermionic pairing possibilities and the coupling between the itinerant charge degrees of freedom. A detailed comparison between spin and charge couplings highlights that the charge and spin couplings show very similar behaviour in the over-doped region, whereas, they show completely different trends in the lower doping regimes. Moreover, a qualitative equivalence between generalized charge stiffness and effective Coulomb interaction is also established based on the comparisons with other theoretical and experimental results. Thus it is obvious that the enhanced possibility of fermionic pairing is inherent in the reduction of Coulomb repulsion with increase in doping concentration. However, the increased possibility can not give rise to pairing without the presence of any other pair producing mechanism outside the t-J model. Therefore, one can conclude that the t-J-like models themselves solely are not capable of producing conventional momentum-based superconducting pairing on their own.Keywords: Generalized charge stiffness constant, charge coupling, effective Coulomb interaction, t-J-like models, momentum-space pairing.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6042297 Modeling and Simulation of Practical Metamaterial Structures
Authors: Ridha Salhi, Mondher Labidi, Fethi Choubani
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Metamaterials have attracted much attention in recent years because of their electromagnetic exquisite proprieties. We will present, in this paper, the modeling of three metamaterial structures by equivalent circuit model. We begin by modeling the SRR (Split Ring Resonator), then we model the HIS (High Impedance Surfaces), and finally, we present the model of the CPW (Coplanar Wave Guide). In order to validate models, we compare the results obtained by an equivalent circuit models with numerical simulation.Keywords: Metamaterials, SRR, HIS, CPW, IDC.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17442296 A Stochastic Approach to Extreme Wind Speeds Conditions on a Small Axial Wind Turbine
Authors: Nkongho Ayuketang Arreyndip, Ebobenow Joseph
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In this paper, to model a real life wind turbine, a probabilistic approach is proposed to model the dynamics of the blade elements of a small axial wind turbine under extreme stochastic wind speeds conditions. It was found that the power and the torque probability density functions even-dough decreases at these extreme wind speeds but are not infinite. Moreover, we also fund that it is possible to stabilize the power coefficient (stabilizing the output power)above rated wind speeds by turning some control parameters. This method helps to explain the effect of turbulence on the quality and quantity of the harness power and aerodynamic torque.Keywords: Probability, Stochastic, Probability density function, Turbulence.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17352295 Statistical Assessment of Models for Determination of Soil – Water Characteristic Curves of Sand Soils
Authors: S. J. Matlan, M. Mukhlisin, M. R. Taha
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Characterization of the engineering behavior of unsaturated soil is dependent on the soil-water characteristic curve (SWCC), a graphical representation of the relationship between water content or degree of saturation and soil suction. A reasonable description of the SWCC is thus important for the accurate prediction of unsaturated soil parameters. The measurement procedures for determining the SWCC, however, are difficult, expensive, and timeconsuming. During the past few decades, researchers have laid a major focus on developing empirical equations for predicting the SWCC, with a large number of empirical models suggested. One of the most crucial questions is how precisely existing equations can represent the SWCC. As different models have different ranges of capability, it is essential to evaluate the precision of the SWCC models used for each particular soil type for better SWCC estimation. It is expected that better estimation of SWCC would be achieved via a thorough statistical analysis of its distribution within a particular soil class. With this in view, a statistical analysis was conducted in order to evaluate the reliability of the SWCC prediction models against laboratory measurement. Optimization techniques were used to obtain the best-fit of the model parameters in four forms of SWCC equation, using laboratory data for relatively coarse-textured (i.e., sandy) soil. The four most prominent SWCCs were evaluated and computed for each sample. The result shows that the Brooks and Corey model is the most consistent in describing the SWCC for sand soil type. The Brooks and Corey model prediction also exhibit compatibility with samples ranging from low to high soil water content in which subjected to the samples that evaluated in this study.
Keywords: Soil-water characteristic curve (SWCC), statistical analysis, unsaturated soil.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 26552294 Evaluating Generative Neural Attention Weights-Based Chatbot on Customer Support Twitter Dataset
Authors: Sinarwati Mohamad Suhaili, Naomie Salim, Mohamad Nazim Jambli
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Sequence-to-sequence (seq2seq) models augmented with attention mechanisms are increasingly important in automated customer service. These models, adept at recognizing complex relationships between input and output sequences, are essential for optimizing chatbot responses. Central to these mechanisms are neural attention weights that determine the model’s focus during sequence generation. Despite their widespread use, there remains a gap in the comparative analysis of different attention weighting functions within seq2seq models, particularly in the context of chatbots utilizing the Customer Support Twitter (CST) dataset. This study addresses this gap by evaluating four distinct attention-scoring functions—dot, multiplicative/general, additive, and an extended multiplicative function with a tanh activation parameter — in neural generative seq2seq models. Using the CST dataset, these models were trained and evaluated over 10 epochs with the AdamW optimizer. Evaluation criteria included validation loss and BLEU scores implemented under both greedy and beam search strategies with a beam size of k = 3. Results indicate that the model with the tanh-augmented multiplicative function significantly outperforms its counterparts, achieving the lowest validation loss (1.136484) and the highest BLEU scores (0.438926 under greedy search, 0.443000 under beam search, k = 3). These findings emphasize the crucial influence of selecting an appropriate attention-scoring function to enhance the performance of seq2seq models for chatbots, particularly highlighting the model integrating tanh activation as a promising approach to improving chatbot quality in customer support contexts.
Keywords: Attention weight, chatbot, encoder-decoder, neural generative attention, score function, sequence-to-sequence.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 622293 Moment Estimators of the Parameters of Zero-One Inflated Negative Binomial Distribution
Authors: Rafid Saeed Abdulrazak Alshkaki
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In this paper, zero-one inflated negative binomial distribution is considered, along with some of its structural properties, then its parameters were estimated using the method of moments. It is found that the method of moments to estimate the parameters of the zero-one inflated negative binomial models is not a proper method and may give incorrect conclusions.Keywords: Zero one inflated models, negative binomial distribution, moments estimator, non-negative integer sampling.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10812292 Selection of Designs in Ordinal Regression Models under Linear Predictor Misspecification
Authors: Ishapathik Das
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The purpose of this article is to find a method of comparing designs for ordinal regression models using quantile dispersion graphs in the presence of linear predictor misspecification. The true relationship between response variable and the corresponding control variables are usually unknown. Experimenter assumes certain form of the linear predictor of the ordinal regression models. The assumed form of the linear predictor may not be correct always. Thus, the maximum likelihood estimates (MLE) of the unknown parameters of the model may be biased due to misspecification of the linear predictor. In this article, the uncertainty in the linear predictor is represented by an unknown function. An algorithm is provided to estimate the unknown function at the design points where observations are available. The unknown function is estimated at all points in the design region using multivariate parametric kriging. The comparison of the designs are based on a scalar valued function of the mean squared error of prediction (MSEP) matrix, which incorporates both variance and bias of the prediction caused by the misspecification in the linear predictor. The designs are compared using quantile dispersion graphs approach. The graphs also visually depict the robustness of the designs on the changes in the parameter values. Numerical examples are presented to illustrate the proposed methodology.Keywords: Model misspecification, multivariate kriging, multivariate logistic link, ordinal response models, quantile dispersion graphs.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9892291 Profitability Assessment of Granite Aggregate Production and the Development of a Profit Assessment Model
Authors: Melodi Mbuyi Mata, Blessing Olamide Taiwo, Afolabi Ayodele David
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The purpose of this research is to create empirical models for assessing the profitability of granite aggregate production in Akure, Ondo state aggregate quarries. In addition, an Artificial Neural Network (ANN) model and multivariate predicting models for granite profitability were developed in the study. A formal survey questionnaire was used to collect data for the study. The data extracted from the case study mine for this study include granite marketing operations, royalty, production costs, and mine production information. The following methods were used to achieve the goal of this study: descriptive statistics, MATLAB 2017, and SPSS16.0 software in analyzing and modeling the data collected from granite traders in the study areas. The ANN and Multi Variant Regression models' prediction accuracy was compared using a coefficient of determination (R2), Root Mean Square Error (RMSE), and mean square error (MSE). Due to the high prediction error, the model evaluation indices revealed that the ANN model was suitable for predicting generated profit in a typical quarry. More quarries in Nigeria's southwest region and other geopolitical zones should be considered to improve ANN prediction accuracy.
Keywords: National development, granite, profitability assessment, ANN models.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 562290 Computational Studies of Binding Energies and Structures of Methylamine on Functionalized Activated Carbon Surfaces
Authors: R. C. J. Mphahlele, K. Bolton, H. Kasaini
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Empirical force fields and density functional theory (DFT) was used to study the binding energies and structures of methylamine on the surface of activated carbons (ACs). This is a first step in studying the adsorption of alkyl amines on the surface of functionalized ACs. The force fields used were Dreiding (DFF), Universal (UFF) and Compass (CFF) models. The generalized gradient approximation with Perdew Wang 91 (PW91) functional was used for DFT calculations. In addition to obtaining the aminecarboxylic acid adsorption energies, the results were used to establish reliability of the empirical models for these systems. CFF predicted a binding energy of -9.227 (kcal/mol) which agreed with PW91 at - 13.17 (kcal/mol), compared to DFF 0 (kcal/mol) and UFF -0.72 (kcal/mol). However, the CFF binding energies for the amine to ester and ketone disagreed with PW91 results. The structures obtained from all models agreed with PW91 results.Keywords: Activated Carbons, Binding energy, DFT, Force fields.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19362289 Analytical Solution of the Boundary Value Problem of Delaminated Doubly-Curved Composite Shells
Authors: András Szekrényes
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Delamination is one of the major failure modes in laminated composite structures. Delamination tips are mostly captured by spatial numerical models in order to predict crack growth. This paper presents some mechanical models of delaminated composite shells based on shallow shell theories. The mechanical fields are based on a third-order displacement field in terms of the through-thickness coordinate of the laminated shell. The undelaminated and delaminated parts are captured by separate models and the continuity and boundary conditions are also formulated in a general way providing a large size boundary value problem. The system of differential equations is solved by the state space method for an elliptic delaminated shell having simply supported edges. The comparison of the proposed and a numerical model indicates that the primary indicator of the model is the deflection, the secondary is the widthwise distribution of the energy release rate. The model is promising and suitable to determine accurately the J-integral distribution along the delamination front. Based on the proposed model it is also possible to develop finite elements which are able to replace the computationally expensive spatial models of delaminated structures.
Keywords: J-integral, Lévy method, third-order shell theory, state space solution.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5932288 Investigations of Flow Field with Different Turbulence Models on NREL Phase VI Blade
Authors: T. Y. Liu, C. H Lin., Y. M Ferng
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Wind energy is one of the clean renewable energy. However, the low frequency (20-200HZ) noise generated from the wind turbine blades, which bothers the residents, becomes the major problem to be developed. It is useful for predicting the aerodynamic noise by flow field and pressure distribution analysis on the wind turbine blades. Therefore, the main objective of this study is to use different turbulence models to analyze the flow field and pressure distributions of the wing blades.
Three-dimensional Computation Fluid Dynamics (CFD) simulation of the flow field was used to calculate the flow phenomena for the National Renewable Energy Laboratory (NREL) Phase VI horizontal axis wind turbine rotor. Two different flow cases with different wind speeds were investigated: 7m/s with 72rpm and 15m/s with 72rpm.
Four kinds of RANS-based turbulence models, Standard k-ε, Realizable k-ε, SST k-ω, and v2f, were used to predict and analyze the results in the present work. The results show that the predictions on pressure distributions with SST k-ω and v2f turbulence models have good agreements with experimental data.
Keywords: Horizontal Axis Wind Turbine, turbulence model, noise.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21542287 Ontologies for Social Media Digital Evidence
Authors: Edlira Kalemi, Sule Yildirim-Yayilgan
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Online Social Networks (OSNs) are nowadays being used widely and intensively for crime investigation and prevention activities. As they provide a lot of information they are used by the law enforcement and intelligence. An extensive review on existing solutions and models for collecting intelligence from this source of information and making use of it for solving crimes has been presented in this article. The main focus is on smart solutions and models where ontologies have been used as the main approach for representing criminal domain knowledge. A framework for a prototype ontology named SC-Ont will be described. This defines terms of the criminal domain ontology and the relations between them. The terms and the relations are extracted during both this review and the discussions carried out with domain experts. The development of SC-Ont is still ongoing work, where in this paper, we report mainly on the motivation for using smart ontology models and the possible benefits of using them for solving crimes.
Keywords: Criminal digital evidence, social media, ontologies, reasoning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 23652286 Short-Term Electric Load Forecasting Using Multiple Gaussian Process Models
Authors: Tomohiro Hachino, Hitoshi Takata, Seiji Fukushima, Yasutaka Igarashi
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This paper presents a Gaussian process model-based short-term electric load forecasting. The Gaussian process model is a nonparametric model and the output of the model has Gaussian distribution with mean and variance. The multiple Gaussian process models as every hour ahead predictors are used to forecast future electric load demands up to 24 hours ahead in accordance with the direct forecasting approach. The separable least-squares approach that combines the linear least-squares method and genetic algorithm is applied to train these Gaussian process models. Simulation results are shown to demonstrate the effectiveness of the proposed electric load forecasting.
Keywords: Direct method, electric load forecasting, Gaussian process model, genetic algorithm, separable least-squares method.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19692285 Statistical Estimation of Spring-back Degree Using Texture Database
Authors: Takashi Sakai, Shinsaku Kikuta, Jun-ichi Koyama
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Using a texture database, a statistical estimation of spring-back was conducted in this study on the basis of statistical analysis. Both spring-back in bending deformation and experimental data related to the crystal orientation show significant dispersion. Therefore, a probabilistic statistical approach was established for the proper quantification of these values. Correlation was examined among the parameters F(x) of spring-back, F(x) of the buildup fraction to three orientations after 92° bending, and F(x) at an as-received part on the basis of the three-parameter Weibull distribution. Consequent spring-back estimation using a texture database yielded excellent estimates compared with experimental values.
Keywords: Bending, Spring-back, Database, Crystallographic Orientation, Texture, SEM-EBSD, Weibull distribution, Statistical analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18902284 Synthetic Daily Flow Duration Curves for the Çoruh River Basin, Turkey
Authors: Fatih Tosunoğlu, İbrahim Can
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The flow duration curve (FDC) is an informative method that represents the flow regime’s properties for a river basin. Therefore, the FDC is widely used for water resource projects such as hydropower, water supply, irrigation and water quality management. The primary purpose of this study is to obtain synthetic daily flow duration curves for Çoruh Basin, Turkey. For this aim, we firstly developed univariate auto-regressive moving average (ARMA) models for daily flows of 9 stations located in Çoruh basin and then these models were used to generate 100 synthetic flow series each having same size as historical series. Secondly, flow duration curves of each synthetic series were drawn and the flow values exceeded 10, 50 and 95% of the time and 95% confidence limit of these flows were calculated. As a result, flood, mean and low flows potential of Çoruh basin will comprehensively be represented.Keywords: ARMA models, Çoruh basin, flow duration curve, Turkey.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 37822283 A Quantitative Approach to Strategic Design of Component-Based Business Process Models
Authors: Eakong Atiptamvaree, Twittie Senivongse
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A new paradigm for software design and development models software by its business process, translates the model into a process execution language, and has it run by a supporting execution engine. This process-oriented paradigm promotes modeling of software by less technical users or business analysts as well as rapid development. Since business process models may be shared by different organizations and sometimes even by different business domains, it is interesting to apply a technique used in traditional software component technology to design reusable business processes. This paper discusses an approach to apply a technique for software component fabrication to the design of process-oriented software units, called process components. These process components result from decomposing a business process of a particular application domain into subprocesses with an aim that the process components can be reusable in different process-based software models. The approach is quantitative because the quality of process component design is measured from technical features of the process components. The approach is also strategic because the measured quality is determined against business-oriented component management goals. A software tool has been developed to measure how good a process component design is, according to the required managerial goals and comparing to other designs. We also discuss how we benefit from reusable process components.
Keywords: Business process model, process component, component management goals, measurement
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16612282 A Comparative Study on ANN, ANFIS and SVM Methods for Computing Resonant Frequency of A-Shaped Compact Microstrip Antennas
Authors: Ahmet Kayabasi, Ali Akdagli
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In this study, three robust predicting methods, namely artificial neural network (ANN), adaptive neuro fuzzy inference system (ANFIS) and support vector machine (SVM) were used for computing the resonant frequency of A-shaped compact microstrip antennas (ACMAs) operating at UHF band. Firstly, the resonant frequencies of 144 ACMAs with various dimensions and electrical parameters were simulated with the help of IE3D™ based on method of moment (MoM). The ANN, ANFIS and SVM models for computing the resonant frequency were then built by considering the simulation data. 124 simulated ACMAs were utilized for training and the remaining 20 ACMAs were used for testing the ANN, ANFIS and SVM models. The performance of the ANN, ANFIS and SVM models are compared in the training and test process. The average percentage errors (APE) regarding the computed resonant frequencies for training of the ANN, ANFIS and SVM were obtained as 0.457%, 0.399% and 0.600%, respectively. The constructed models were then tested and APE values as 0.601% for ANN, 0.744% for ANFIS and 0.623% for SVM were achieved. The results obtained here show that ANN, ANFIS and SVM methods can be successfully applied to compute the resonant frequency of ACMAs, since they are useful and versatile methods that yield accurate results.Keywords: A-shaped compact microstrip antenna, Artificial Neural Network (ANN), adaptive Neuro-Fuzzy Inference System (ANFIS), Support Vector Machine (SVM).
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22062281 Wheat Yield Prediction through Agro Meteorological Indices for Ardebil District
Authors: Fariba Esfandiary, Ghafoor Aghaie, Ali Dolati Mehr
Abstract:
Wheat prediction was carried out using different meteorological variables together with agro meteorological indices in Ardebil district for the years 2004-2005 & 2005–2006. On the basis of correlation coefficients, standard error of estimate as well as relative deviation of predicted yield from actual yield using different statistical models, the best subset of agro meteorological indices were selected including daily minimum temperature (Tmin), accumulated difference of maximum & minimum temperatures (TD), growing degree days (GDD), accumulated water vapor pressure deficit (VPD), sunshine hours (SH) & potential evapotranspiration (PET). Yield prediction was done two months in advance before harvesting time which was coincide with commencement of reproductive stage of wheat (5th of June). It revealed that in the final statistical models, 83% of wheat yield variability was accounted for variation in above agro meteorological indices.
Keywords: Wheat yields prediction, agro meteorological indices, statistical models
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21302280 Fuzzy Estimation of Parameters in Statistical Models
Authors: A. Falsafain, S. M. Taheri, M. Mashinchi
Abstract:
Using a set of confidence intervals, we develop a common approach, to construct a fuzzy set as an estimator for unknown parameters in statistical models. We investigate a method to derive the explicit and unique membership function of such fuzzy estimators. The proposed method has been used to derive the fuzzy estimators of the parameters of a Normal distribution and some functions of parameters of two Normal distributions, as well as the parameters of the Exponential and Poisson distributions.Keywords: Confidence interval. Fuzzy number. Fuzzy estimation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2261