Search results for: Gaussian-Wishart emission model
5123 Effect of Biomass Feedstocks on the Production of Hydrogenated Biodiesel
Authors: Panatcha Bovornseripatai, Siriporn Jongpatiwut, Somchai Osuwan, Suchada Butnark
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Hydrogenated biodiesel is one of the most promising renewable fuels. It has many advantages over conventional biodiesel, including higher cetane number, higher heating value, lower viscosity, and lower corrosiveness due to its absence of oxygen. From previous work, Pd/TiO2 gave high conversion and selectivity in hydrogenated biodiesel. In this work, the effect of biomass feedstocks (i.e. beef fat, chicken fat, pork fat, and jatropha oil) on the production of hydrogenated biodiesel over Pd/TiO2 has been studied. Biomass feedstocks were analyzed by ICP-OES (inductively coupled plasma optical emission spectrometry) to identify the content of impurities (i.e. P, K, Ca, Na, and Mg). The deoxygenation catalyst, Pd/TiO2, was prepared by incipient wetness impregnation (IWI) and tested in a continuous flow packed-bed reactor at 500 psig, 325°C, H2/feed molar ratio of 30, and LHSV of 4 h-1 for its catalytic activity and selectivity in hydrodeoxygenation. All feedstocks gave high selectivity in diesel specification range hydrocarbons and the main hydrocarbons were n-pentadecane (n-C15) and n-heptadecane (n- C17), resulting from the decarbonylation/decarboxylation reaction. Intermediates such as oleic acid, stearic acid, palmitic acid, and esters were also detected in minor amount. The conversion of triglycerides in jatropha oil is higher than those of chicken fat, pork fat, and beef fat, respectively. The higher concentration of metal impurities in feedstock, the lower conversion of feedstock.Keywords: Hydrogenated biodiesel, hydrodeoxygenation, Pd/TiO2, biomass feedstock
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19585122 State Estimation of a Biotechnological Process Using Extended Kalman Filter and Particle Filter
Authors: R. Simutis, V. Galvanauskas, D. Levisauskas, J. Repsyte, V. Grincas
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This paper deals with advanced state estimation algorithms for estimation of biomass concentration and specific growth rate in a typical fed-batch biotechnological process. This biotechnological process was represented by a nonlinear mass-balance based process model. Extended Kalman Filter (EKF) and Particle Filter (PF) was used to estimate the unmeasured state variables from oxygen uptake rate (OUR) and base consumption (BC) measurements. To obtain more general results, a simplified process model was involved in EKF and PF estimation algorithms. This model doesn’t require any special growth kinetic equations and could be applied for state estimation in various bioprocesses. The focus of this investigation was concentrated on the comparison of the estimation quality of the EKF and PF estimators by applying different measurement noises. The simulation results show that Particle Filter algorithm requires significantly more computation time for state estimation but gives lower estimation errors both for biomass concentration and specific growth rate. Also the tuning procedure for Particle Filter is simpler than for EKF. Consequently, Particle Filter should be preferred in real applications, especially for monitoring of industrial bioprocesses where the simplified implementation procedures are always desirable.
Keywords: Biomass concentration, Extended Kalman Filter, Particle Filter, State estimation, Specific growth rate.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 29395121 Multiple Regression based Graphical Modeling for Images
Authors: Pavan S., Sridhar G., Sridhar V.
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Super resolution is one of the commonly referred inference problems in computer vision. In the case of images, this problem is generally addressed using a graphical model framework wherein each node represents a portion of the image and the edges between the nodes represent the statistical dependencies. However, the large dimensionality of images along with the large number of possible states for a node makes the inference problem computationally intractable. In this paper, we propose a representation wherein each node can be represented as acombination of multiple regression functions. The proposed approach achieves a tradeoff between the computational complexity and inference accuracy by varying the number of regression functions for a node.
Keywords: Belief propagation, Graphical model, Regression, Super resolution.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15355120 MP-SMC-I Method for Slip Suppression of Electric Vehicles under Braking
Authors: Tohru Kawabe
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In this paper, a new SMC (Sliding Mode Control) method with MP (Model Predictive Control) integral action for the slip suppression of EV (Electric Vehicle) under braking is proposed. The proposed method introduce the integral term with standard SMC gain , where the integral gain is optimized for each control period by the MPC algorithms. The aim of this method is to improve the safety and the stability of EVs under braking by controlling the wheel slip ratio. There also include numerical simulation results to demonstrate the effectiveness of the method.Keywords: Sliding Mode Control, Model Predictive Control, Integral Action, Electric Vehicle, Slip suppression.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22535119 Spectral Amplitude Coding Optical CDMA: Performance Analysis of PIIN Reduction Using VC Code Family
Authors: Hassan Yousif Ahmed, Ibrahima Faye, N.M.Saad, S.A. Aljined
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Multi-user interference (MUI) is the main reason of system deterioration in the Spectral Amplitude Coding Optical Code Division Multiple Access (SAC-OCDMA) system. MUI increases with the number of simultaneous users, resulting into higher probability bit rate and limits the maximum number of simultaneous users. On the other hand, Phase induced intensity noise (PIIN) problem which is originated from spontaneous emission of broad band source from MUI severely limits the system performance should be addressed as well. Since the MUI is caused by the interference of simultaneous users, reducing the MUI value as small as possible is desirable. In this paper, an extensive study for the system performance specified by MUI and PIIN reducing is examined. Vectors Combinatorial (VC) codes families are adopted as a signature sequence for the performance analysis and a comparison with reported codes is performed. The results show that, when the received power increases, the PIIN noise for all the codes increases linearly. The results also show that the effect of PIIN can be minimized by increasing the code weight leads to preserve adequate signal to noise ratio over bit error probability. A comparison study between the proposed code and the existing codes such as Modified frequency hopping (MFH), Modified Quadratic- Congruence (MQC) has been carried out.
Keywords: FBG, MUI, PIIN, SAC-OCDMA, VCC.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22025118 Visual Object Tracking in 3D with Color Based Particle Filter
Authors: Pablo Barrera, Jose M. Canas, Vicente Matellan
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This paper addresses the problem of determining the current 3D location of a moving object and robustly tracking it from a sequence of camera images. The approach presented here uses a particle filter and does not perform any explicit triangulation. Only the color of the object to be tracked is required, but not any precisemotion model. The observation model we have developed avoids the color filtering of the entire image. That and the Monte Carlotechniques inside the particle filter provide real time performance.Experiments with two real cameras are presented and lessons learned are commented. The approach scales easily to more than two cameras and new sensor cues.
Keywords: Monte Carlo sampling, multiple view, particle filters, visual tracking.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19145117 Mathematical Model for Dengue Disease with Maternal Antibodies
Authors: Rujira Kongnuy, Puntani Pongsumpun, I-Ming Tang
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Mathematical models can be used to describe the dynamics of the spread of infectious disease between susceptibles and infectious populations. Dengue fever is a re-emerging disease in the tropical and subtropical regions of the world. Its incidence has increased fourfold since 1970 and outbreaks are now reported quite frequently from many parts of the world. In dengue endemic regions, more cases of dengue infection in pregnancy and infancy are being found due to the increasing incidence. It has been reported that dengue infection was vertically transmitted to the infants. Primary dengue infection is associated with mild to high fever, headache, muscle pain and skin rash. Immune response includes IgM antibodies produced by the 5th day of symptoms and persist for 30-60 days. IgG antibodies appear on the 14th day and persist for life. Secondary infections often result in high fever and in many cases with hemorrhagic events and circulatory failure. In the present paper, a mathematical model is proposed to simulate the succession of dengue disease transmission in pregnancy and infancy. Stability analysis of the equilibrium points is carried out and a simulation is given for the different sets of parameter. Moreover, the bifurcation diagrams of our model are discussed. The controlling of this disease in infant cases is introduced in the term of the threshold condition.Keywords: Dengue infection, equilibrium states, maternalantibodies, pregnancy and infancy.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20105116 GMDH Modeling Based on Polynomial Spline Estimation and Its Applications
Authors: LI qiu-min, TIAN yi-xiang, ZHANG gao-xun
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GMDH algorithm can well describe the internal structure of objects. In the process of modeling, automatic screening of model structure and variables ensure the convergence rate.This paper studied a new GMDH model based on polynomial spline stimation. The polynomial spline function was used to instead of the transfer function of GMDH to characterize the relationship between the input variables and output variables. It has proved that the algorithm has the optimal convergence rate under some conditions. The empirical results show that the algorithm can well forecast Consumer Price Index (CPI).
Keywords: spline, GMDH, nonparametric, bias, forecast.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21195115 Managing the Information System Life Cycle in Construction and Manufacturing
Authors: Carlos J. Costa, Manuela Aparício
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In this paper we present the information life cycle and analyze the importance of managing the corporate application portfolio across this life cycle. The approach presented here corresponds not just to the extension of the traditional information system development life cycle. This approach is based in the generic life cycle. In this paper it is proposed a model of an information system life cycle, supported in the assumption that a system has a limited life. But, this limited life may be extended. This model is also applied in several cases; being reported here two examples of the framework application in a construction enterprise and in a manufacturing enterprise.
Keywords: Information systems/technology, information systems life cycle, organization engineering, information economics.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17975114 A Competitive Replica Placement Methodology for Ad Hoc Networks
Authors: Samee Ullah Khan, C. Ardil
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In this paper, a mathematical model for data object replication in ad hoc networks is formulated. The derived model is general, flexible and adaptable to cater for various applications in ad hoc networks. We propose a game theoretical technique in which players (mobile hosts) continuously compete in a non-cooperative environment to improve data accessibility by replicating data objects. The technique incorporates the access frequency from mobile hosts to each data object, the status of the network connectivity, and communication costs. The proposed technique is extensively evaluated against four well-known ad hoc network replica allocation methods. The experimental results reveal that the proposed approach outperforms the four techniques in both the execution time and solution qualityKeywords: Data replication, auctions, static allocation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13945113 Speaker Identification by Joint Statistical Characterization in the Log Gabor Wavelet Domain
Authors: Suman Senapati, Goutam Saha
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Real world Speaker Identification (SI) application differs from ideal or laboratory conditions causing perturbations that leads to a mismatch between the training and testing environment and degrade the performance drastically. Many strategies have been adopted to cope with acoustical degradation; wavelet based Bayesian marginal model is one of them. But Bayesian marginal models cannot model the inter-scale statistical dependencies of different wavelet scales. Simple nonlinear estimators for wavelet based denoising assume that the wavelet coefficients in different scales are independent in nature. However wavelet coefficients have significant inter-scale dependency. This paper enhances this inter-scale dependency property by a Circularly Symmetric Probability Density Function (CS-PDF) related to the family of Spherically Invariant Random Processes (SIRPs) in Log Gabor Wavelet (LGW) domain and corresponding joint shrinkage estimator is derived by Maximum a Posteriori (MAP) estimator. A framework is proposed based on these to denoise speech signal for automatic speaker identification problems. The robustness of the proposed framework is tested for Text Independent Speaker Identification application on 100 speakers of POLYCOST and 100 speakers of YOHO speech database in three different noise environments. Experimental results show that the proposed estimator yields a higher improvement in identification accuracy compared to other estimators on popular Gaussian Mixture Model (GMM) based speaker model and Mel-Frequency Cepstral Coefficient (MFCC) features.Keywords: Speaker Identification, Log Gabor Wavelet, Bayesian Bivariate Estimator, Circularly Symmetric Probability Density Function, SIRP.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16435112 Effect of Unbound Granular Materials Nonlinear Resilient Behavior on Pavement Response and Performance of Low Volume Roads
Authors: K. Sandjak, B. Tiliouine
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Structural analysis of flexible pavements has been and still is currently performed using multi-layer elastic theory. However, for thinly surfaced pavements subjected to low to medium volumes of traffics, the importance of non-linear stress-strain behavior of unbound granular materials (UGM) requires the use of more sophisticated numerical models for structural design and performance of such pavements. In the present work, nonlinear unbound aggregates constitutive model is implemented within an axisymmetric finite element code developed to simulate the nonlinear behavior of pavement structures including two local aggregates of different mineralogical nature, typically used in Algerian pavements. The performance of the mechanical model is examined about its capability of representing adequately, under various conditions, the granular material non-linearity in pavement analysis. In addition, deflection data collected by Falling Weight Deflectometer (FWD) are incorporated into the analysis in order to assess the sensitivity of critical pavement design criteria and pavement design life to the constitutive model. Finally, conclusions of engineering significance are formulated.
Keywords: Nonlinear resilient behavior, unbound granular materials, RLT test results, FWD backcalculations, finite element simulations, pavement response and performance.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22805111 Analyzing Data on Breastfeeding Using Dispersed Statistical Models
Authors: Naushad Mamode Khan, Cheika Jahangeer, Maleika Heenaye-Mamode Khan
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Exclusive breastfeeding is the feeding of a baby on no other milk apart from breast milk. Exclusive breastfeeding during the first 6 months of life is very important as it supports optimal growth and development during infancy and reduces the risk of obliterating diseases and problems. Moreover, it helps to reduce the incidence and/or severity of diarrhea, lower respiratory infection and urinary tract infection. In this paper, we make a survey of the factors that influence exclusive breastfeeding and use two dispersed statistical models to analyze data. The models are the Generalized Poisson regression model and the Com-Poisson regression models.
Keywords: Exclusive breastfeeding, regression model, generalized poisson, com-poisson.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15505110 Modeling Directional Thermal Radiance Anisotropy for Urban Canopy
Authors: Limin Zhao, Xingfa Gu, C. Tao Yu
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one of the significant factors for improving the accuracy of Land Surface Temperature (LST) retrieval is the correct understanding of the directional anisotropy for thermal radiance. In this paper, the multiple scattering effect between heterogeneous non-isothermal surfaces is described rigorously according to the concept of configuration factor, based on which a directional thermal radiance model is built, and the directional radiant character for urban canopy is analyzed. The model is applied to a simple urban canopy with row structure to simulate the change of Directional Brightness Temperature (DBT). The results show that the DBT is aggrandized because of the multiple scattering effects, whereas the change range of DBT is smoothed. The temperature difference, spatial distribution, emissivity of the components can all lead to the change of DBT. The “hot spot" phenomenon occurs when the proportion of high temperature component in the vision field came to a head. On the other hand, the “cool spot" phenomena occur when low temperature proportion came to the head. The “spot" effect disappears only when the proportion of every component keeps invariability. The model built in this paper can be used for the study of directional effect on emissivity, the LST retrieval over urban areas and the adjacency effect of thermal remote sensing pixels.Keywords: Directional thermal radiance, multiple scattering, configuration factor, urban canopy, hot spot effect
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15965109 The Using Artificial Neural Network to Estimate of Chemical Oxygen Demand
Authors: S. Areerachakul
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Nowadays, the increase of human population every year results in increasing of water usage and demand. Saen Saep canal is important canal in Bangkok. The main objective of this study is using Artificial Neural Network (ANN) model to estimate the Chemical Oxygen Demand (COD) on data from 11 sampling sites. The data is obtained from the Department of Drainage and Sewerage, Bangkok Metropolitan Administration, during 2007-2011. The twelve parameters of water quality are used as the input of the models. These water quality indices affect the COD. The experimental results indicate that the ANN model provides a high correlation coefficient (R=0.89).
Keywords: Artificial neural network, chemical oxygen demand, estimate, surface water.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22525108 Using the Combined Model of PROMETHEE and Fuzzy Analytic Network Process for Determining Question Weights in Scientific Exams through Data Mining Approach
Authors: Hassan Haleh, Amin Ghaffari, Parisa Farahpour
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Need for an appropriate system of evaluating students- educational developments is a key problem to achieve the predefined educational goals. Intensity of the related papers in the last years; that tries to proof or disproof the necessity and adequacy of the students assessment; is the corroborator of this matter. Some of these studies tried to increase the precision of determining question weights in scientific examinations. But in all of them there has been an attempt to adjust the initial question weights while the accuracy and precision of those initial question weights are still under question. Thus In order to increase the precision of the assessment process of students- educational development, the present study tries to propose a new method for determining the initial question weights by considering the factors of questions like: difficulty, importance and complexity; and implementing a combined method of PROMETHEE and fuzzy analytic network process using a data mining approach to improve the model-s inputs. The result of the implemented case study proves the development of performance and precision of the proposed model.Keywords: Assessing students, Analytic network process, Clustering, Data mining, Fuzzy sets, Multi-criteria decision making, and Preference function.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15735107 Context Modeling and Reasoning Approach in Context-Aware Middleware for URC System
Authors: Chung-Seong Hong, Hyung-Sun Kim, Joonmyun Cho, Hyun Kyu Cho, Hyun-Chan Lee
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To realize the vision of ubiquitous computing, it is important to develop a context-aware infrastructure which can help ubiquitous agents, services, and devices become aware of their contexts because such computational entities need to adapt themselves to changing situations. A context-aware infrastructure manages the context model representing contextual information and provides appropriate information. In this paper, we introduce Context-Aware Middleware for URC System (hereafter CAMUS) as a context-aware infrastructure for a network-based intelligent robot system and discuss the ontology-based context modeling and reasoning approach which is used in that infrastructure.Keywords: CAMUS, Context-Aware, Context Model, Ontology.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19065106 Design Modelling Control and Simulation of DC/DC Power Buck Converter
Authors: H. Abaali
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The power buck converter is the most widely used DC/DC converter topology. They have a very large application area such as DC motor drives, photovoltaic power system which require fast transient responses and high efficiency over a wide range of load current. This work proposes, the modelling of DC/DC power buck converter using state-space averaging method and the current-mode control using a proportional-integral controller. The efficiency of the proposed model and control loop are evaluated with operating point changes. The simulation results proved the effectiveness of the linear model of DC/DC power buck converter.Keywords: DC/DC power buck converter, Linear current control, State-space averaging method.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 34685105 On One Mathematical Model for Filtration of Weakly Compressible Chemical Compound in the Porous Heterogeneous 3D Medium. Part I: Model Construction with the Aid of the Ollendorff Approach
Authors: Sharif E. Guseynov, Jekaterina V. Aleksejeva, Janis S. Rimshans
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A filtering problem of almost incompressible liquid chemical compound in the porous inhomogeneous 3D domain is studied. In this work general approaches to the solution of twodimensional filtering problems in ananisotropic, inhomogeneous and multilayered medium are developed, and on the basis of the obtained results mathematical models are constructed (according to Ollendorff method) for studying the certain engineering and technical problem of filtering the almost incompressible liquid chemical compound in the porous inhomogeneous 3D domain. For some of the formulated mathematical problems with additional requirements for the structure of the porous inhomogeneous medium, namely, its isotropy, spatial periodicity of its permeability coefficient, solution algorithms are proposed. Continuation of the current work titled ”On one mathematical model for filtration of weakly compressible chemical compound in the porous heterogeneous 3D medium. Part II: Determination of the reference directions of anisotropy and permeabilities on these directions” will be prepared in the shortest terms by the authors.
Keywords: Porous media, filtering, permeability, elliptic PDE.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17455104 Optimization of the Input Layer Structure for Feed-Forward Narx Neural Networks
Authors: Zongyan Li, Matt Best
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This paper presents an optimization method for reducing the number of input channels and the complexity of the feed-forward NARX neural network (NN) without compromising the accuracy of the NN model. By utilizing the correlation analysis method, the most significant regressors are selected to form the input layer of the NN structure. An application of vehicle dynamic model identification is also presented in this paper to demonstrate the optimization technique and the optimal input layer structure and the optimal number of neurons for the neural network is investigated.Keywords: Correlation analysis, F-ratio, Levenberg-Marquardt, MSE, NARX, neural network, optimisation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21835103 Model Reference Adaptive Approach for Power System Stabilizer for Damping of Power Oscillations
Authors: Jožef Ritonja, Bojan Grčar, Boštjan Polajžer
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In recent years, electricity trade between neighboring countries has become increasingly intense. Increasing power transmission over long distances has resulted in an increase in the oscillations of the transmitted power. The damping of the oscillations can be carried out with the reconfiguration of the network or the replacement of generators, but such solution is not economically reasonable. The only cost-effective solution to improve the damping of power oscillations is to use power system stabilizers. Power system stabilizer represents a part of synchronous generator control system. It utilizes semiconductor’s excitation system connected to the rotor field excitation winding to increase the damping of the power system. The majority of the synchronous generators are equipped with the conventional power system stabilizers with fixed parameters. The control structure of the conventional power system stabilizers and the tuning procedure are based on the linear control theory. Conventional power system stabilizers are simple to realize, but they show non-sufficient damping improvement in the entire operating conditions. This is the reason that advanced control theories are used for development of better power system stabilizers. In this paper, the adaptive control theory for power system stabilizers design and synthesis is studied. The presented work is focused on the use of model reference adaptive control approach. Control signal, which assures that the controlled plant output will follow the reference model output, is generated by the adaptive algorithm. Adaptive gains are obtained as a combination of the "proportional" term and with the σ-term extended "integral" term. The σ-term is introduced to avoid divergence of the integral gains. The necessary condition for asymptotic tracking is derived by means of hyperstability theory. The benefits of the proposed model reference adaptive power system stabilizer were evaluated as objectively as possible by means of a theoretical analysis, numerical simulations and laboratory realizations. Damping of the synchronous generator oscillations in the entire operating range was investigated. Obtained results show the improved damping in the entire operating area and the increase of the power system stability. The results of the presented work will help by the development of the model reference power system stabilizer which should be able to replace the conventional stabilizers in power systems.
Keywords: Power system, stability, oscillations, power system stabilizer, model reference adaptive control.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6145102 Puff Noise Detection and Cancellation for Robust Speech Recognition
Authors: Sangjun Park, Jungpyo Hong, Byung-Ok Kang, Yun-keun Lee, Minsoo Hahn
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In this paper, an algorithm for detecting and attenuating puff noises frequently generated under the mobile environment is proposed. As a baseline system, puff detection system is designed based on Gaussian Mixture Model (GMM), and 39th Mel Frequency Cepstral Coefficient (MFCC) is extracted as feature parameters. To improve the detection performance, effective acoustic features for puff detection are proposed. In addition, detected puff intervals are attenuated by high-pass filtering. The speech recognition rate was measured for evaluation and confusion matrix and ROC curve are used to confirm the validity of the proposed system.Keywords: Gaussian mixture model, puff detection and cancellation, speech enhancement.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22225101 Metabolic Analysis of Fibroblast Conditioned Media and Comparison with Theoretical Modeling
Authors: Priyanka Gupta, Paul Verma, Kerry Hourigan, Jayesh Bellare, Sameer Jadhav
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Understanding the consumption and production of various metabolites of fibroblast conditioned media is needed for its proper and optimized use in expansion of pluripotent stem cells. For this purpose, we have used the HPLC method to analyse the consumption of glucose and the production of lactate over time by mouse embryonic fibroblasts. The experimental data have also been compared with mathematical model fits. 0.025 moles of lactate was produced after 72 hrs while the glucose concentration decreased from 0.017 moles to 0.011 moles. The mathematical model was able to predict the trends of glucose consumption and lactate production.Keywords: Conditioned media, HPLC, metabolite analysis, mouse embryonic fibroblast.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25945100 Competitors’ Influence Analysis of a Retailer by Using Customer Value and Huff’s Gravity Model
Authors: Yepeng Cheng, Yasuhiko Morimoto
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Customer relationship analysis is vital for retail stores, especially for supermarkets. The point of sale (POS) systems make it possible to record the daily purchasing behaviors of customers as an identification point of sale (ID-POS) database, which can be used to analyze customer behaviors of a supermarket. The customer value is an indicator based on ID-POS database for detecting the customer loyalty of a store. In general, there are many supermarkets in a city, and other nearby competitor supermarkets significantly affect the customer value of customers of a supermarket. However, it is impossible to get detailed ID-POS databases of competitor supermarkets. This study firstly focused on the customer value and distance between a customer's home and supermarkets in a city, and then constructed the models based on logistic regression analysis to analyze correlations between distance and purchasing behaviors only from a POS database of a supermarket chain. During the modeling process, there are three primary problems existed, including the incomparable problem of customer values, the multicollinearity problem among customer value and distance data, and the number of valid partial regression coefficients. The improved customer value, Huff’s gravity model, and inverse attractiveness frequency are considered to solve these problems. This paper presents three types of models based on these three methods for loyal customer classification and competitors’ influence analysis. In numerical experiments, all types of models are useful for loyal customer classification. The type of model, including all three methods, is the most superior one for evaluating the influence of the other nearby supermarkets on customers' purchasing of a supermarket chain from the viewpoint of valid partial regression coefficients and accuracy.Keywords: Customer value, Huff's Gravity Model, POS, retailer.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5975099 Parametric Cost Estimating Relationships for Design Effort Estimation
Authors: Adil Salam, Nadia Bhuiyan, Gerard J. Gouw
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The Canadian aerospace industry faces many challenges. One of them is the difficulty in estimating costs. In particular, the design effort required in a project impacts resource requirements and lead-time, and consequently the final cost. This paper presents the findings of a case study conducted for recognized global leader in the design and manufacturing of aircraft engines. The study models parametric cost estimation relationships to estimate the design effort of integrated blade-rotor low-pressure compressor fans. Several effort drivers are selected to model the relationship. Comparative analyses of three types of models are conducted. The model with the best accuracy and significance in design estimation is retained.
Keywords: Effort estimation, design, aerospace.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25665098 BIDENS: Iterative Density Based Biclustering Algorithm With Application to Gene Expression Analysis
Authors: Mohamed A. Mahfouz, M. A. Ismail
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Biclustering is a very useful data mining technique for identifying patterns where different genes are co-related based on a subset of conditions in gene expression analysis. Association rules mining is an efficient approach to achieve biclustering as in BIMODULE algorithm but it is sensitive to the value given to its input parameters and the discretization procedure used in the preprocessing step, also when noise is present, classical association rules miners discover multiple small fragments of the true bicluster, but miss the true bicluster itself. This paper formally presents a generalized noise tolerant bicluster model, termed as μBicluster. An iterative algorithm termed as BIDENS based on the proposed model is introduced that can discover a set of k possibly overlapping biclusters simultaneously. Our model uses a more flexible method to partition the dimensions to preserve meaningful and significant biclusters. The proposed algorithm allows discovering biclusters that hard to be discovered by BIMODULE. Experimental study on yeast, human gene expression data and several artificial datasets shows that our algorithm offers substantial improvements over several previously proposed biclustering algorithms.Keywords: Machine learning, biclustering, bi-dimensional clustering, gene expression analysis, data mining.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19485097 A Comparison of Recent Methods for Solving a Model 1D Convection Diffusion Equation
Authors: Ashvin Gopaul, Jayrani Cheeneebash, Kamleshsing Baurhoo
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In this paper we study some numerical methods to solve a model one-dimensional convection–diffusion equation. The semi-discretisation of the space variable results into a system of ordinary differential equations and the solution of the latter involves the evaluation of a matrix exponent. Since the calculation of this term is computationally expensive, we study some methods based on Krylov subspace and on Restrictive Taylor series approximation respectively. We also consider the Chebyshev Pseudospectral collocation method to do the spatial discretisation and we present the numerical solution obtained by these methods.
Keywords: Chebyshev Pseudospectral collocation method, convection-diffusion equation, restrictive Taylor approximation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16675096 Improvement of Soft Clay Using Floating Cement Dust-Lime Columns
Authors: Adel Belal, Sameh Aboelsoud, Mohy Elmashad, Mohammed Abdelmonem
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The two main criteria that control the design and performance of footings are bearing capacity and settlement of soil. In soft soils, the construction of buildings, storage tanks, warehouse, etc. on weak soils usually involves excessive settlement problems. To solve bearing capacity or reduce settlement problems, soil improvement may be considered by using different techniques, including encased cement dust–lime columns. The proposed research studies the effect of adding floating encased cement dust and lime mix columns to soft clay on the clay-bearing capacity. Four experimental tests were carried out. Columns diameters of 3.0 cm, 4.0 cm, and 5.0 cm and columns length of 60% of the clay layer thickness were used. Numerical model was constructed and verified using commercial finite element package (PLAXIS 2D, V8.5). The verified model was used to study the effect of distributing columns around the footing at different distances. The study showed that the floating cement dust lime columns enhanced the clay-bearing capacity with 262%. The numerical model showed that the columns around the footing have a limit effect on the clay improvement.
Keywords: Bearing capacity, cement dust – lime columns, ground improvement, soft clay.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11045095 A Novel Web Metric for the Evaluation of Internet Trends
Authors: Radek Malinský, Ivan Jelínek
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Web 2.0 (social networking, blogging and online forums) can serve as a data source for social science research because it contains vast amount of information from many different users. The volume of that information has been growing at a very high rate and becoming a network of heterogeneous data; this makes things difficult to find and is therefore not almost useful. We have proposed a novel theoretical model for gathering and processing data from Web 2.0, which would reflect semantic content of web pages in better way. This article deals with the analysis part of the model and its usage for content analysis of blogs. The introductory part of the article describes methodology for the gathering and processing data from blogs. The next part of the article is focused on the evaluation and content analysis of blogs, which write about specific trend.Keywords: Blog, Sentiment Analysis, Web 2.0, Webometrics
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 35325094 Modeling of the Process Parameters using Soft Computing Techniques
Authors: Miodrag T. Manić, Dejan I. Tanikić, Miloš S. Stojković, Dalibor M. ðenadić
Abstract:
The design of technological procedures for manufacturing certain products demands the definition and optimization of technological process parameters. Their determination depends on the model of the process itself and its complexity. Certain processes do not have an adequate mathematical model, thus they are modeled using heuristic methods. First part of this paper presents a state of the art of using soft computing techniques in manufacturing processes from the perspective of applicability in modern CAx systems. Methods of artificial intelligence which can be used for this purpose are analyzed. The second part of this paper shows some of the developed models of certain processes, as well as their applicability in the actual calculation of parameters of some technological processes within the design system from the viewpoint of productivity.Keywords: fuzzy logic, manufacturing, neural networks
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