Search results for: elaboration likelihood model

Authors: Sarra Roubi, Mohammed Erramdani, Samir Mbarki

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This paper presents an approach for the model-driven generating of Rich Internet Application (RIA) focusing on the graphical aspect. We used well known Model-Driven Engineering (MDE) frameworks and technologies, such as Eclipse Modeling Framework (EMF), Graphical Modeling Framework (GMF), Query View Transformation (QVTo) and Acceleo to enable the design and the code automatic generation of the RIA. During the development of the approach, we focused on the graphical aspect of the application in terms of interfaces while opting for the Model View Presenter pattern that is designed for graphics interfaces. The paper describes the process followed to define the approach, the supporting tool and presents the results from a case study.

Keywords: metamodel, model-driven engineering, MVP, rich internet application, transformation, user interface

Procedia PDF Downloads 353

Authors: Elida Gastelum-Martinez, Neith A. Pacheco-Lopez, Juan L. Morales-Landa

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Cashew agroindustry obtained from cashew apple crop (Anacardium occidentale L.) generates large amounts of unused waste in Campeche, Mexico. Despite having a high content of nutritional compounds such as ascorbic acid, carotenoids, fiber, carbohydrates, and minerals, it is not consumed due to its astringent sensation. The aim of this work was to develop a processing method for cashew apple waste in order to obtain a powder with reduced astringency able to be used as an additive in the food industry. The processing method consisted first in reducing astringency by inducing tannins from cashew apple peel to react and form precipitating complexes with a colloid rich in proline and histidine. Then cashew apples were processed to obtain a dry powder. Astringency reduction was determined by total phenolic content and evaluated by sensorial analysis in cashew-apple-powder based cookies. Total phenolic content in processed powders showed up to 72% lower concentration compared to control samples. The sensorial evaluation indicated that cookies baked using cashew apple powder with reduced astringency were 96.8% preferred. Sensorial characteristics like texture, color and taste were also well-accepted attributes. In conclusion, the method applied for astringency reduction is a viable tool to produce cashew apple powder with desirable sensorial properties to be used in the development of food products.

Keywords: astringency reduction, cashew apple waste, food industry, sensorial evaluation

Procedia PDF Downloads 351

Authors: Johannes J. Schneider, Mathias S. Weyland, Peter Eggenberger Hotz, William D. Jamieson, Oliver Castell, Alessia Faggian, Rudolf M. Füchslin

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In the description of the origin of life, there are still some open gaps, e.g., the formation of macromolecules cannot be fully explained so far. The Kauffman model proposes the existence of autocatalytic sets of macromolecules which mutually catalyze reactions leading to each other’s formation. Usually, this model is simulated in one well-stirred pot only, with a continuous inflow of small building blocks, from which larger molecules are created by a set of catalyzed ligation and cleavage reactions. This approach represents the picture of the primordial soup. However, the conditions on the early Earth must have differed geographically, leading to spatially different outcomes whether a specific reaction could be performed or not. Guided by this picture, the Kauffman model is simulated in a large number of containers in parallel, with neighboring containers being connected by diffusion. In each container, only a subset of the overall reaction set can be performed. Under specific conditions, this approach leads to a larger probability for the existence of an autocatalytic metabolism than in the original Kauffman model.

Keywords: agglomeration, autocatalytic set, differential equation, Kauffman model

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Authors: Seon Soon Choi

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The essential purpose is to present the good fatigue crack propagation model describing a stochastic fatigue crack growth behavior in a rolled magnesium alloy, AZ31, under various load ratio conditions. Fatigue crack propagation experiments were carried out in laboratory air under four conditions of load ratio, R, using AZ31 to investigate the crack growth behavior. The stochastic fatigue crack growth behavior was analyzed using an interpolation of random variable, Z, introduced to an empirical fatigue crack propagation model. The empirical fatigue models used in this study are Paris-Erdogan model, Walker model, Forman model, and modified Forman model. It was found that the random variable is useful in describing the stochastic fatigue crack growth behaviors under various load ratio conditions. The good probabilistic model describing a stochastic fatigue crack growth behavior under various load ratio conditions was also proposed.

Keywords: magnesium alloys, fatigue crack propagation model, load ratio, interpolation of random variable

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Authors: Tudor Barbu

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We present a robust nonlinear parabolic partial differential equation (PDE)-based denoising scheme in this article. Our approach is based on a second-order anisotropic diffusion model that is described first. Then, a consistent and explicit numerical approximation algorithm is constructed for this continuous model by using the finite-difference method. Finally, our restoration experiments and method comparison, which prove the effectiveness of this proposed technique, are discussed in this paper.

Keywords: anisotropic diffusion, finite differences, image denoising and restoration, nonlinear PDE model, anisotropic diffusion, numerical approximation schemes

Procedia PDF Downloads 312

Authors: Amr Sadek, Abdelrahaman Al-Qahtany, Turkey Salem Al-Qahtany

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In this study, a backpropagation artificial neural network (ANN) model has been used to predict the cooling and heating capacities of air conditioners (AC) under different conditions. Sufficiently large measurement results were obtained from the national energy-efficiency laboratories in Saudi Arabia and were used for the learning process of the ANN model. The parameters affecting the performance of the AC, including temperature, humidity level, specific heat enthalpy indoors and outdoors, and the air volume flow rate of indoor units, have been considered. These parameters were used as inputs for the ANN model, while the cooling and heating capacity values were set as the targets. A backpropagation ANN model with two hidden layers and one output layer could successfully correlate the input parameters with the targets. The characteristics of the ANN model including the input-processing, transfer, neurons-distance, topology, and training functions have been discussed. The performance of the ANN model was monitored over the training epochs and assessed using the mean squared error function. The model was then used to predict the performance of the AC under conditions that were not included in the measurement results. The optimum performance of the AC was also predicted under the different environmental conditions in Saudi Arabia. The uncertainty of the ANN model predictions has been evaluated taking into account the randomness of the data and lack of learning.

Keywords: artificial neural network, uncertainty of model predictions, efficiency of air conditioners, cooling and heating capacities

Procedia PDF Downloads 74

Authors: Shahroz Khan, Osman Taha Şen

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In automotive brake systems, brake noise has been a major problem, and brake squeal is one of the critical ones which is an instability issue. The brake squeal produces an audible sound at high frequency that is irritating to the human ear. To study this critical problem, first a nonlinear mathematical model with three degree of freedom is developed. This model consists of a point mass that simulates the brake pad and a sliding surface that simulates the brake rotor. The model exposes kinematic and clearance nonlinearities, but no friction nonlinearity. In the formulation, the friction coefficient is assumed to be constant and the friction force does not change direction. The nonlinear governing equations of the model are first obtained, and numerical solutions are sought for different cases. Second, a computational model for the squeal problem is developed with a commercial software, and computational solutions are obtained with two different types of contact cases (solid-to-solid and sphere-to-plane). This model consists of three rigid bodies and several elastic elements that simulate the key characteristics of a brake system. The response obtained from this model is compared with numerical solutions in time and frequency domain.

Keywords: contact force, nonlinearities, brake squeal, vehicle brake

Procedia PDF Downloads 246

Authors: Jerome T. Tolentino, Ma. Victoria Rejuso, Jara Kaye Villanueva, Loureal Camille Inocencio, Ma. Rosario Concepcion O. Ang

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Wind energy is rapidly emerging as the primary source of electricity in the Philippines, although developing an accurate wind resource model is difficult. In this study, Weather Research and Forecasting (WRF) Model, an open source mesoscale Numerical Weather Prediction (NWP) model, was used to produce a 1-year atmospheric simulation with 4 km resolution on the Ilocos Region of the Philippines. The WRF output (netCDF) extracts the annual mean wind speed data using a Python-based Graphical User Interface. Lastly, wind resource assessment was produced using a GIS software. Results of the study showed that it is more flexible to use Python scripts than using other post-processing tools in dealing with netCDF files. Using WRF Model, Python, and Geographic Information Systems, a reliable wind resource map is produced.

Keywords: wind resource assessment, weather research and forecasting (WRF) model, python, GIS software

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Authors: M. Mikušová

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The main aim of this paper is to present a clear and comprehensive picture of the process of a crisis in the organization which will help to better understand its possible developments. For a description of the sequence of individual steps and an indication of their causation and possible variants of the developments, a detailed flow diagram with verbal comment is applied. For simplicity, the process of the crisis is observed in four basic phases called: symptoms of the crisis, diagnosis, action and prevention. The model highlights the complexity of the phenomenon of the crisis and that the various phases of the crisis are interweaving.

Keywords: crisis, management, model, organization

Procedia PDF Downloads 291

Authors: Yasser F. Hassan

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Deep learning structure is a branch of machine learning science and greet achievement in research and applications. Cellular neural networks are regarded as array of nonlinear analog processors called cells connected in a way allowing parallel computations. The paper discusses how to use deep learning structure for representing neural cellular automata model. The proposed learning technique in cellular automata model will be examined from structure of deep learning. A deep automata neural cellular system modifies each neuron based on the behavior of the individual and its decision as a result of multi-level deep structure learning. The paper will present the architecture of the model and the results of simulation of approach are given. Results from the implementation enrich deep neural cellular automata system and shed a light on concept formulation of the model and the learning in it.

Keywords: cellular automata, neural cellular automata, deep learning, classification

Procedia PDF Downloads 198

Authors: Zouhair Issa Ahmed, Ahmed Abdulrasool Ahmed, Falah Hassan Abdulsada

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This paper presents a layout of a factory using Pro-Model simulation by choosing the best layout that gives the highest productivity and least work in process. The general problem is to find the best sequence in which jobs pass between the machines which are compatible with the technological constraints and optimal with respect to some performance criteria. The best simulation with Pro-Model program increased productivity and reduced work in process by balancing lines of production compared with the current layout of factory when productivity increased from 45 products to 180 products through 720 hours.

Keywords: scheduling, Pro-Model, simulation, balancing lines of production, layout planning, WIP

Procedia PDF Downloads 635

Authors: Nicolas Plamondon, Stuart Atkinson, Shuzi Zhou

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The insurance industry is usually not the first topic one has in mind when thinking about applications of data science. However, the use of data science in the finance and insurance industry is growing quickly for several reasons, including an abundance of reliable customer data, ferocious competition requiring more accurate pricing, etc. Among the top use cases of data science, we find pricing optimization, customer segmentation, customer risk assessment, fraud detection, marketing, and triage analytics. The objective of this paper is to present an application of the generalized additive model (GAM) on a commercial automobile insurance product: an individually rated commercial automobile. These are vehicles used for commercial purposes, but for which there is not enough volume to apply pricing to several vehicles at the same time. The GAM model was selected as an improvement over GLM for its ease of use and its wide range of applications. The model was trained using the largest split of the data to determine model parameters. The remaining part of the data was used as testing data to verify the quality of the modeling activity. We used the Gini coefficient to evaluate the performance of the model. For long-term monitoring, commonly used metrics such as RMSE and MAE will be used. Another topic of interest in the insurance industry is to process of producing the model. We will discuss at a high level the interactions between the different teams with an insurance company that needs to work together to produce a model and then monitor the performance of the model over time. Moreover, we will discuss the regulations in place in the insurance industry. Finally, we will discuss the maintenance of the model and the fact that new data does not come constantly and that some metrics can take a long time to become meaningful.

Keywords: insurance, data science, modeling, monitoring, regulation, processes

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Authors: E. A. Krasikov

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Dependence of the materials properties on neutron irradiation intensity (flux) is a key problem while usage data of the accelerated materials irradiation in test reactors for forecasting of their capacity for work in realistic (practical) circumstances of operation. Investigations of the reactor pressure vessel steel radiation degradation dependence on fast neutron fluence (embrittlement kinetics) at low flux reveal the instability in the form of the scatter of the experimental data and wave-like sections of embrittlement kinetics appearance. Disclosure of the steel degradation oscillating is a sign of the steel structure cyclic self-recovery transformation as it take place in self-organization processes. This assumption has received support through the discovery of the similar ‘anomalous’ data in scientific publications and by means of own additional experiments. Data obtained stimulate looking-for ways to management of the structural steel radiation stability (for example, by means of nano - structure modification for radiation defects annihilation intensification) for creation of the intelligent self-recovering material. Expected results: - radiation degradation theory and mechanisms development, - more adequate models of the radiation embrittlement elaboration, - surveillance specimen programs improvement, - methods and facility development for usage data of the accelerated materials irradiation for forecasting of their capacity for work in realistic (practical) circumstances of operation, - search of the ways for creating of the radiation stable self-recovery intelligent materials.

Keywords: degradation, radiation, steel, wave-like kinetics

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Authors: I. Behroyan, P. Ganesan, S. He, S. Sivasankaran

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This study compares the predictions of five types of Computational Fluid Dynamics (CFD) models, including two single-phase models (i.e. Newtonian and non-Newtonian) and three two-phase models (Eulerian-Eulerian, mixture and Eulerian-Lagrangian), to investigate turbulent forced convection of Cu-water nanofluid in a tube with a constant heat flux on the tube wall. The Reynolds (Re) number of the flow is between 10,000 and 25,000, while the volume fraction of Cu particles used is in the range of 0 to 2%. The commercial CFD package of ANSYS-Fluent is used. The results from the CFD models are compared with results from experimental investigations from literature. According to the results of this study, non-Newtonian single-phase model, in general, does not show a good agreement with Xuan and Li correlation in prediction of Nu number. Eulerian-Eulerian model gives inaccurate results expect for φ=0.5%. Mixture model gives a maximum error of 15%. Newtonian single-phase model and Eulerian-Lagrangian model, in overall, are the recommended models. This work can be used as a reference for selecting an appreciate model for future investigation. The study also gives a proper insight about the important factors such as Brownian motion, fluid behavior parameters and effective nanoparticle conductivity which should be considered or changed by the each model.

Keywords: heat transfer, nanofluid, single-phase models, two-phase models

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Authors: T. Kobayashi, K. Shiba, T. Kaburagi, Y. Kurihara

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For the elderly living alone, falls can be a serious problem encountered in daily life. Some elderly people are unable to stand up without the assistance of a caregiver. They may become unconscious after a fall, which can lead to serious aftereffects such as hypothermia, dehydration, and sometimes even death. We treat the subject as an inverted pendulum and model its angle from the equilibrium position and its angular velocity. As the model is non-linear, we implement the filtering method with a particle filter which can estimate true states of the non-linear model. In order to evaluate the accuracy of the particle filter estimation results, we calculate the root mean square error (RMSE) between the estimated angle/angular velocity and the true values generated by the simulation. The experimental results give the highest accuracy RMSE of 0.0141 rad and 0.1311 rad/s for the angle and angular velocity, respectively.

Keywords: fall, microwave Doppler sensor, non-linear dynamics model, particle filter

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Authors: Pompa Marcello, Mauro Capocelli, Vincenzo Piemonte

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This work focuses on a mathematical model able to describe the gastro-intestinal physiology and providing a rational tool for the design of an artificial gastro-intestinal system. This latter is mainly devoted to analyse the absorption and bioavailability of drugs and nutrients through in vitro tests in order to overcome (or, at least, to partially replace) in vivo trials. The provided model realizes a conjunction ring (with extended prediction capability) between in vivo tests and mechanical-laboratory models emulating the human body. On this basis, no empirical equations controlling the gastric emptying are implemented in this model as frequent in the cited literature and all the sub-unit and the related system of equations are physiologically based. More in detail, the model structure consists of six compartments (stomach, duodenum, jejunum, ileum, colon and blood) interconnected through pipes and valves. Paracetamol, Ketoprofen, Irbesartan and Ketoconazole are considered and analysed in this work as reference drugs. The mathematical model has been validated against in vivo literature data. Results obtained show a very good model reliability and highlight the possibility to realize tailored simulations for different couples patient-drug, including food adsorption dynamics.

Keywords: gastro-intestinal model, drugs bioavailability, paracetamol, ketoprofen

Procedia PDF Downloads 168

Authors: André Smith, Amr Abdel-Dayem

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The stereo matching problem, while having been present for several decades, continues to be an active area of research. The goal of this research is to find correspondences between elements found in a set of stereoscopic images. With these pairings, it is possible to infer the distance of objects within a scene, relative to the observer. Advancements in this field have led to experimentations with various techniques, from graph-cut energy minimization to artificial neural networks. At the basis of these techniques is a cost function, which is used to evaluate the likelihood of a particular match between points in each image. While at its core, the cost is based on comparing the image pixel data; there is a general lack of consistency as to what image data representation to use. This paper presents an experimental analysis to compare the effectiveness of more common image data representations. The goal is to determine the effectiveness of these data representations to reduce the cost for the correct correspondence relative to other possible matches.

Keywords: colour data, local stereo matching, stereo correspondence, disparity map

Procedia PDF Downloads 370

Authors: Yilei Song, Linlin Tian, Ning Zhao

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Turbulence energetics and structures in the wake of large-scale wind turbines under the stably-stratified atmospheric boundary layer (SABL) can be complicated due to the presence of low-level jets (LLJs), a region of higher wind speeds than the geostrophic wind speed. With a modified one-k-equation, eddy viscosity model specified for atmospheric flows as the sub-grid scale (SGS) model, a realistic atmospheric state of the stable ABL is well reproduced by large-eddy simulation (LES) techniques. Corresponding to the precursor stably stratification, the detailed wake properties of a standard 5-MW wind turbine represented as an actuator line model are provided. An engineering model is proposed for wake prediction based on the simulation statistics and gets validated. Results confirm that the proposed wake model can provide good predictions for wind turbines under the SABL.

Keywords: large-eddy simulation, stably-stratified atmospheric boundary layer, wake model, wind turbine wake

Procedia PDF Downloads 174

Authors: Adrian Rettig, Silvan Schneider, Reto Tamburini, Mirko Kleingries, Ulf Christian Muller

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Industrial adsorption processes are, mainly due to si-multaneous heat and mass transfer, characterized by a high level of complexity. The conception of such processes often does not take place systematically; instead scale-up/down respectively number-up/down methods based on existing systems are used. This paper shows how Modelica® can be used to develop a transient model enabling a more systematic design of such ad- and desorption components and processes. The core of this model is a lumped-element submodel of a single adsorbent grain, where the thermodynamic equilibria and the kinetics of the ad- and desorption processes are implemented and solved on the basis of mass-, momentum and energy balances. For validation of this submodel, a fixed bed adsorber, whose characteristics are described in detail in the literature, was modeled and simulated. The simulation results are in good agreement with the experimental results from the literature. Therefore, the model development will be continued, and the extended model will be applied to further adsorber types like rotor adsorbers and moving bed adsorbers.

Keywords: adsorption, desorption, linear driving force, dynamic model, Modelica®, integral equation approach

Procedia PDF Downloads 371

Authors: Chen-Yin Kuo, Yung-Hsin Lee

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Previous studies applying residual income valuation (RIV) model generally use panel data and single-equation model to forecast stock prices. Unlike these, this paper uses Taiwan longitudinal data to estimate multi-equation time-series models such as Vector Autoregressive (VAR), Vector Error Correction Model (VECM), and conduct out-of-sample forecasting. Further, this work assesses their forecasting performance by two instruments. In favor of extant research, the major finding shows that VECM outperforms other three models in forecasting for three stock sectors over entire horizons. It implies that an error correction term containing long-run information contributes to improve forecasting accuracy. Moreover, the pattern of composite shows that at longer horizon, VECM produces the greater reduction in errors, and performs substantially better than VAR.

Keywords: residual income valuation model, vector error correction model, out of sample forecasting, forecasting accuracy

Procedia PDF Downloads 316

Authors: M. J. Kang, Y. N. Jo, H. H. Yoo

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Pendulum tests were used to identify a stretch reflex and diagnose spasticity. Some researches tried to make a mathematical model to simulate the motions. Thighs are subject to compressive forces due to gravity during a pendulum test. Therefore, it affects knee trajectories. However, the most studies on the pendulum tests did not consider that conditions. We used Kelvin-Voight model as compression model of skin and muscles. In this study, we investigated viscoelastic behaviors of skin and muscles using gelatin blocks from experiments of the vibration of the compliantly supported beam. Then we calculated a dynamic stiffness and loss factors from the experiment and estimated a damping coefficient of the model. We also did pendulum tests of human lower limbs to validate the stiffness and damping coefficient of a skin model. To simulate the pendulum motion, we derive equations of motion. We used stretch reflex activation model to estimate muscle forces induced by the stretch reflex. To validate the results, we compared the activation with electromyography signals during experiments. The compression behavior of skin and muscles in this study can be applied to analyze sitting posture as wee as developing surgical techniques.

Keywords: Kelvin-Voight model, pendulum test, skin and muscles under compression, stretch reflex

Procedia PDF Downloads 445

Authors: Yasmine Ahmed Shemeis

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Determining the impact of productivity increases on wage levels is often difficult due to the unavailability of individual-level productivity data. Accordingly, we proxy for productivity using a self-perceived measure of health based on the postulated positive relationship between better health and productivity improvements. Using Egypt’s labour market data for the years 2012 and 2018 and utilizing a Maximum Likelihood Estimation method, we address two issues: the endogeneity of health in the estimation of wages and a sample selection bias. Our findings indicate the great value that better health has in enhancing wage levels in Egypt’s private sector. Also, we find that overlooking the endogeneity of health underestimates its effect on wages. Thus, the improvement of health states is likely to be beneficial in improving labour market outcomes in terms of wages as well as labour productivity in Egypt.

Keywords: labour, Productivity, Wages, Endogeneity, Sample Selection

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Authors: Aymen Rhouma, Khaled Hcheichi, Sami Hafsi

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The article presents an application of Fractional Model Predictive Control (FMPC) to a fractional order thermal system using Controlled Auto Regressive Integrated Moving Average (CARIMA) model obtained by discretization of a continuous fractional differential equation. Moreover, the output deviation approach is exploited to design the K -step ahead output predictor, and the corresponding control law is obtained by solving a quadratic cost function. Experiment results onto a thermal system are presented to emphasize the performances and the effectiveness of the proposed predictive controller.

Keywords: fractional model predictive control, fractional order systems, thermal system, predictive control

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Authors: Y. S. Yusoff, G. Streftaris, H. R Waters

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Death within 30 days is an important factor to be looked into, as there is a significant risk of deaths immediately following or soon after, Myocardial Infarction (MI) or stroke. In this paper, we will model the deaths within 30 days following a Myocardial Infarction (MI) or stroke in the UK. We will see how the probabilities of sudden deaths from MI or stroke have changed over the period 1981-2000. We will model the sudden deaths using a Generalized Linear Model (GLM), fitted using the R statistical package, under a Binomial distribution for the number of sudden deaths. We parameterize our model using the extensive and detailed data from the Framingham Heart Study, adjusted to match UK rates. The results show that there is a reduction for the sudden deaths following a MI over time but no significant improvement for sudden deaths following a stroke.

Keywords: sudden deaths, myocardial infarction, stroke, ischemic heart disease

Procedia PDF Downloads 286

Authors: CarlyWill Sloan

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Racial disparities in criminal justice outcomes are well-documented. However, there is little evidence on the extent to which racial bias by prosecutors is responsible for these disparities. This paper tests for racial bias in conviction by prosecutors. To identify effects, this paper leverages as good as random variation in prosecutor race using detailed administrative data on the case assignment process and case outcomes in New York County, New York. This paper shows that the assignment of an opposite-race prosecutor leads to a 5 percentage point (~ 8 percent) increase in the likelihood of conviction for property crimes. There is no evidence of effects for other types of crimes. Additional results indicate decreased dismissals by opposite-race prosecutors likely drive my property crime estimates.

Keywords: criminal justice, discrimination, prosecutors, racial disparities

Procedia PDF Downloads 191

Authors: C. Castro-Egler, A. Durán-Escalante, A. García-González

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This paper presents a method to generate a finite element model of the human auditory inner ear system. The geometric model has been realized using 2D images from a virtual model of temporal bones. A point cloud has been gotten manually from those images to construct a whole mesh with hexahedral elements. The main difference with the predecessor models is the spiral shape of the cochlea with its three scales completely defined: scala tympani, scala media and scala vestibuli; which are separate by basilar membrane and Reissner membrane. To validate this model, numerical simulations have been realised with two models: an isolated inner ear and a whole model of human auditory system. Ideal conditions of displacement are applied over the oval window in the isolated Inner Ear model. The whole model is made up of the outer auditory channel, the tympani, the ossicular chain, and the inner ear. The boundary condition for the whole model is 1Pa over the auditory channel entrance. The numerical simulations by FEM have been done using a harmonic analysis with a frequency range between 100-10.000 Hz with an interval of 100Hz. The following results have been carried out: basilar membrane displacement; the scala media pressure according to the cochlea length and the transfer function of the middle ear normalized with the pressure in the tympanic membrane. The basilar membrane displacements and the pressure in the scala media make it possible to validate the response in frequency of the basilar membrane.

Keywords: finite elements method, human auditory system model, numerical analysis, 3D modelling cochlea

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Authors: Amr Mansour Mohsen, Hesham Ahmed Hassan, Amira M. Idrees

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Emotions classification of text documents is applied to reveal if the document expresses a determined emotion from its writer. As different supervised methods are previously used for emotion documents’ classification, in this research we present a novel model that supports the classification algorithms for more accurate results by the support of TF-IDF measure. Different experiments have been applied to reveal the applicability of the proposed model, the model succeeds in raising the accuracy percentage according to the determined metrics (precision, recall, and f-measure) based on applying the refinement of the lexicon, integration of lexicons using different perspectives, and applying the TF-IDF weighting measure over the classifying features. The proposed model has also been compared with other research to prove its competence in raising the results’ accuracy.

Keywords: emotion detection, TF-IDF, WEKA tool, classification algorithms

Procedia PDF Downloads 484

Authors: John Lorenzo Bautista, Yoon-Joong Kim

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This paper presents the development of a Filipino speech recognition tool using the HTK System. The system was trained from a subset of the Filipino Speech Corpus developed by the DSP Laboratory of the University of the Philippines-Diliman. The speech corpus was both used in training and testing the system by estimating the parameters for phonetic HMM-based (Hidden-Markov Model) acoustic models. Experiments on different mixture-weights were incorporated in the study. The phoneme-level word-based recognition of a 5-state HMM resulted in an average accuracy rate of 80.13 for a single-Gaussian mixture model, 81.13 after implementing a phoneme-alignment, and 87.19 for the increased Gaussian-mixture weight model. The highest accuracy rate of 88.70% was obtained from a 5-state model with 6 Gaussian mixtures.

Keywords: Filipino language, Hidden Markov Model, HTK system, speech recognition

Procedia PDF Downloads 480

Authors: Jia-Jang Wu

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This paper presents the scaling laws that provide the criteria of geometry and dynamic similitude between the full-size rotor-shaft system and its scale model, and can be used to predict the torsional vibration characteristics of the full-size rotor-shaft system by manipulating the corresponding data of its scale model. The scaling factors, which play fundamental roles in predicting the geometry and dynamic relationships between the full-size rotor-shaft system and its scale model, for torsional free vibration problems between scale and full-size rotor-shaft systems are firstly obtained from the equation of motion of torsional free vibration. Then, the scaling factor of external force (i.e., torque) required for the torsional forced vibration problems is determined based on the Newton’s second law. Numerical results show that the torsional free and forced vibration characteristics of a full-size rotor-shaft system can be accurately predicted from those of its scale models by using the foregoing scaling factors. For this reason, it is believed that the presented approach will be significant for investigating the relevant phenomenon in the scale model tests.

Keywords: torsional vibration, full-size model, scale model, scaling laws

Procedia PDF Downloads 396

Authors: Seyed Mohammadbagher Jafari, Elahe Mahdizadeh, Masomeh Ghahremani

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Nowadays almost all organizations depend on information systems to run their businesses. Investment on information systems and their maintenance to keep them always in best situation to support firm business is one of the main issues for every organization. The new concept of cloud computing was developed as a technical and economic model to address this issue. In cloud computing the computing resources, including networks, applications, hardwares and services are configured as needed and are available at the moment of request. However, migration to cloud is not an easy task and there are many issues that should be taken into account. This study tries to provide a comprehensive model to assess a firm readiness to implement cloud computing. By conducting a systematic literature review, four dimensions of readiness were extracted which include technological, human, organizational and environmental dimensions. Every dimension has various criteria that have been discussed in details. This model provides a framework for cloud computing readiness assessment. Organizations that intend to migrate to cloud can use this model as a tool to assess their firm readiness before making any decision on cloud implementation.

Keywords: cloud computing, human readiness, organizational readiness, readiness assessment model

Procedia PDF Downloads 395