Search results for: normal and inverse Weibull models
947 Systolic Blood Pressure and Its Determinants: Study in a Population Attending Pharmacies in a Portuguese Coastal City
Authors: M. J. Reis Lima, J. Oliveira, M. Brito, C. Lemos, A. Mascarenhas, E. Teixeira Lemos
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Hypertension is a common condition causing cardio and cerebrovascular complications. Portugal has one of the highest mortality rates from stroke and a high prevalence of hypertension. Systolic Blood Pressure (SBP) is an important risk factor for cardiovascular events (myocardial infarction and stroke) and premature mortality, particularly in the elderly population. The present study aims to estimate the prevalence of hypertension in a Portuguese population living in a coastal city and to identify some of its determinants (namely gender, age, the body mass index and physical activity frequency). A total of 91 adults who attended three pharmacies of a coastal city in the center of Portugal, between May and August of 2013 were evaluated. Attendants who reported to have diabetes or taking antihypertensive drugs in the 2 previous weeks were excluded from the study. Sociodemographic factors, BMI, habits of exercise and BP were assessed. Hypertension was defined as blood pressure ≥140/90 mmHg. The majority of the studied population was constituted by women (75.8%), with a mean age of 54.2±1.6 years old, married or living in civil union and that had completed secondary school or had higher education (40%). They presented a mean BMI of 26.2±4.76 Kg/m2., and were sedentary. The mean BP was 127.0±17.77mmHg- 74.69 ± 9.53. In this population we found 4.3% of people with hypertension and 16.1% with normal high blood pressure. Men exhibit a tendency to present higher systolic blood pressure values than women. Of all the factors considered, SBP values also tended to be higher with age and higher BMI values. Despite the fact that the mean values of SBP did not present values higher than 140 mmHg we must be concerned because the studied population is undiagnosed for hypertension. Although this is a preliminary study, it might be a prelude to the upcoming research about the underlying factors responsible for the occurrence of SBP.Keywords: Hypertension, age, exercise, obesity, gender.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1787946 Digital Terrestrial Broadcasting Technologies and Implementation Status
Authors: Nerey H. Mvungi, Justinian Anatory, Fatuma Simba
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Digital broadcasting has been an area of active research, development, innovation and business models development in recent years. This paper presents a survey on the characteristics of the digital terrestrial television broadcasting (DTTB) standards, and implementation status of DTTB worldwide showing the standards adopted. It is clear that only the developed countries and some in the developing ones shall be able to beat the ITU set analogue to digital broadcasting migration deadline because of the challenges that these countries faces in digitizing their terrestrial broadcasting. The challenges to keep on track the DTTB migration plan are also discussed in this paper. They include financial, technology gap, policies alignment with DTTB technology, etc. The reported performance comparisons for the different standards are also presented. The interesting part is that the results for many comparative studies depends to a large extent on the objective behind such studies, hence counter claims are common.Keywords: Digital terrestrial television broadcasting (DTTB) technologies, DTTB standards comparison, DTTB implementation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2830945 The Influence of User Involvement and Personal Innovativeness on User Behavior
Authors: Anne M. Sørebø, Øystein Sørebø, Maung K. Sein
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The search for factors that influence user behavior has remained an important theme for both the academic and practitioner Information Systems Communities. In this paper we examine relevant user behaviors in the phase after adoption and investigate two factors that are expected to influence such behaviors, namely User Involvement (UI) and Personal Innovativeness in IT (PIIT). We conduct a field study to examine how these factors influence postadoption behavior and how they are interrelated. Building on theoretical premises and prior empirical findings, we propose and test two alternative models of the relationship between these factors. Our results reveal that the best explanation of post-adoption behavior is provided by the model where UI and PIIT independently influence post-adoption behavior. Our findings have important implications for research and practice. To that end, we offer directions for future research.
Keywords: User involvement, personal innovativeness in IT, use of systems, user support, post-adoption behavior.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1542944 A Timed and Colored Petri Nets for Modeling and Verifying Cloud System Elasticity
Authors: W. Louhichi, M.Berrima, N. Ben Rajeb Robbana
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Elasticity is the essential property of cloud computing. As the name suggests, it constitutes the ability of a cloud system to adjust resource provisioning in relation to fluctuating workloads. There are two types of elasticity operations, vertical and horizontal. In this work, we are interested in horizontal scaling, which is ensured by two mechanisms; scaling in and scaling out. Following the sizing of the system, we can adopt scaling in the event of over-supply and scaling out in the event of under-supply. In this paper, we propose a formal model, based on temporized and colored Petri nets (TdCPNs), for the modeling of the duplication and the removal of a virtual machine from a server. This model is based on formal Petri Nets (PNs) modeling language. The proposed models are edited, verified, and simulated with two examples implemented in colored Petri nets (CPNs)tools, which is a modeling tool for colored and timed PNs.
Keywords: Cloud computing, elasticity, elasticity controller, petri nets, scaling in, scaling out.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 605943 Modelling Medieval Vaults: Digital Simulation of the North Transept Vault of St Mary, Nantwich, England
Authors: N. Webb, A. Buchanan
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Digital and virtual heritage is often associated with the recreation of lost artefacts and architecture; however, we can also investigate works that were not completed, using digital tools and techniques. Here we explore physical evidence of a fourteenth-century Gothic vault located in the north transept of St Mary’s church in Nantwich, Cheshire, using existing springer stones that are built into the walls as a starting point. Digital surveying tools are used to document the architecture, followed by an analysis process to hypothesise and simulate possible design solutions, had the vault been completed. A number of options, both two-dimensionally and three-dimensionally, are discussed based on comparison with examples of other contemporary vaults, thus adding another specimen to the corpus of vault designs. Dissemination methods such as digital models and 3D prints are also explored as possible resources for demonstrating what the finished vault might have looked like for heritage interpretation and other purposes.Keywords: Digital simulation, heritage interpretation, medieval vaults, virtual heritage, 3D scanning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1167942 Multiscale Modelization of Multilayered Bi-Dimensional Soils
Authors: I. Hosni, L. Bennaceur Farah, N. Saber, R Bennaceur
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Soil moisture content is a key variable in many environmental sciences. Even though it represents a small proportion of the liquid freshwater on Earth, it modulates interactions between the land surface and the atmosphere, thereby influencing climate and weather. Accurate modeling of the above processes depends on the ability to provide a proper spatial characterization of soil moisture. The measurement of soil moisture content allows assessment of soil water resources in the field of hydrology and agronomy. The second parameter in interaction with the radar signal is the geometric structure of the soil. Most traditional electromagnetic models consider natural surfaces as single scale zero mean stationary Gaussian random processes. Roughness behavior is characterized by statistical parameters like the Root Mean Square (RMS) height and the correlation length. Then, the main problem is that the agreement between experimental measurements and theoretical values is usually poor due to the large variability of the correlation function, and as a consequence, backscattering models have often failed to predict correctly backscattering. In this study, surfaces are considered as band-limited fractal random processes corresponding to a superposition of a finite number of one-dimensional Gaussian process each one having a spatial scale. Multiscale roughness is characterized by two parameters, the first one is proportional to the RMS height, and the other one is related to the fractal dimension. Soil moisture is related to the complex dielectric constant. This multiscale description has been adapted to two-dimensional profiles using the bi-dimensional wavelet transform and the Mallat algorithm to describe more correctly natural surfaces. We characterize the soil surfaces and sub-surfaces by a three layers geo-electrical model. The upper layer is described by its dielectric constant, thickness, a multiscale bi-dimensional surface roughness model by using the wavelet transform and the Mallat algorithm, and volume scattering parameters. The lower layer is divided into three fictive layers separated by an assumed plane interface. These three layers were modeled by an effective medium characterized by an apparent effective dielectric constant taking into account the presence of air pockets in the soil. We have adopted the 2D multiscale three layers small perturbations model including, firstly air pockets in the soil sub-structure, and then a vegetable canopy in the soil surface structure, that is to simulate the radar backscattering. A sensitivity analysis of backscattering coefficient dependence on multiscale roughness and new soil moisture has been performed. Later, we proposed to change the dielectric constant of the multilayer medium because it takes into account the different moisture values of each layer in the soil. A sensitivity analysis of the backscattering coefficient, including the air pockets in the volume structure with respect to the multiscale roughness parameters and the apparent dielectric constant, was carried out. Finally, we proposed to study the behavior of the backscattering coefficient of the radar on a soil having a vegetable layer in its surface structure.
Keywords: Multiscale, bi-dimensional, wavelets, SPM, backscattering, multilayer, air pockets, vegetable.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 596941 Big Bang – Big Crunch Learning Method for Fuzzy Cognitive Maps
Authors: Engin Yesil, Leon Urbas
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Modeling of complex dynamic systems, which are very complicated to establish mathematical models, requires new and modern methodologies that will exploit the existing expert knowledge, human experience and historical data. Fuzzy cognitive maps are very suitable, simple, and powerful tools for simulation and analysis of these kinds of dynamic systems. However, human experts are subjective and can handle only relatively simple fuzzy cognitive maps; therefore, there is a need of developing new approaches for an automated generation of fuzzy cognitive maps using historical data. In this study, a new learning algorithm, which is called Big Bang-Big Crunch, is proposed for the first time in literature for an automated generation of fuzzy cognitive maps from data. Two real-world examples; namely a process control system and radiation therapy process, and one synthetic model are used to emphasize the effectiveness and usefulness of the proposed methodology.Keywords: Big Bang-Big Crunch optimization, Dynamic Systems, Fuzzy Cognitive Maps, Learning.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1830940 New Technologies for Modeling of Gas Turbine Cooled Blades
Authors: A. Pashayev, D. Askerov, R.Sadiqov, A. Samedov, C. Ardil
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In contrast to existing methods which do not take into account multiconnectivity in a broad sense of this term, we develop mathematical models and highly effective combination (BIEM and FDM) numerical methods of calculation of stationary and cvazistationary temperature field of a profile part of a blade with convective cooling (from the point of view of realization on PC). The theoretical substantiation of these methods is proved by appropriate theorems. For it, converging quadrature processes have been developed and the estimations of errors in the terms of A.Ziqmound continuity modules have been received. For visualization of profiles are used: the method of the least squares with automatic conjecture, device spline, smooth replenishment and neural nets. Boundary conditions of heat exchange are determined from the solution of the corresponding integral equations and empirical relationships. The reliability of designed methods is proved by calculation and experimental investigations heat and hydraulic characteristics of the gas turbine 1st stage nozzle blade
Keywords: multiconnected systems, method of the boundary integrated equations, splines, neural networks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1641939 Numerical Modeling of Gas Turbine Engines
Authors: A. Pashayev, D. Askerov, C. Ardil, R. Sadiqov
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In contrast to existing methods which do not take into account multiconnectivity in a broad sense of this term, we develop mathematical models and highly effective combination (BIEM and FDM) numerical methods of calculation of stationary and quasi-stationary temperature field of a profile part of a blade with convective cooling (from the point of view of realization on PC). The theoretical substantiation of these methods is proved by appropriate theorems. For it, converging quadrature processes have been developed and the estimations of errors in the terms of A.Ziqmound continuity modules have been received. For visualization of profiles are used: the method of the least squares with automatic conjecture, device spline, smooth replenishment and neural nets. Boundary conditions of heat exchange are determined from the solution of the corresponding integral equations and empirical relationships. The reliability of designed methods is proved by calculation and experimental investigations heat and hydraulic characteristics of the gas turbine first stage nozzle blade.
Keywords: Multiconnected systems, method of the boundary integrated equations, splines, neural networks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1614938 Big Data Analytics and Data Security in the Cloud via Fully Homomorphic Encryption
Authors: Victor Onomza Waziri, John K. Alhassan, Idris Ismaila, Moses Noel Dogonyaro
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This paper describes the problem of building secure computational services for encrypted information in the Cloud Computing without decrypting the encrypted data; therefore, it meets the yearning of computational encryption algorithmic aspiration model that could enhance the security of big data for privacy, confidentiality, availability of the users. The cryptographic model applied for the computational process of the encrypted data is the Fully Homomorphic Encryption Scheme. We contribute a theoretical presentations in a high-level computational processes that are based on number theory and algebra that can easily be integrated and leveraged in the Cloud computing with detail theoretic mathematical concepts to the fully homomorphic encryption models. This contribution enhances the full implementation of big data analytics based cryptographic security algorithm.
Keywords: Data Analytics, Security, Privacy, Bootstrapping, and Fully Homomorphic Encryption Scheme.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3443937 Effect of Stiffeners on the Behavior of Slender Built up Steel I-Beams
Authors: M. E. Abou-Hashem El Dib, M. K. Swailem, M. M. Metwally, A. I. El Awady
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This paper presents the effect of stiffeners on the behavior of slender steel I-beams. Nonlinear three dimensional finite element models are developed to represent the stiffened steel I-beams. The well established finite element (ANSYS 13.0) program is used to simulate the geometric and material nonlinear nature of the problem. Verification is achieved by comparing the obtained numerical results with the results of previous published experimental work. The parameters considered in the analysis are the horizontal stiffener's position and the horizontal stiffener's dimensions as well as the number of vertical stiffeners. The studied dimensions of the horizontal stiffeners include the stiffener width, the stiffener thickness and the stiffener length. The results of the achieved numerical parametric study for slender steel I-beams show the significant effect of stiffeners on the beam behavior and its failure load.Keywords: Steel I-beams, local buckling, slender, stiffener, thin walled section.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1643936 Design of Thermal Control Subsystem for TUSAT Telecommunication Satellite
Authors: N. Sozbir, M. Bulut, M.F.Oktem, A.Kahriman, A. Chaix
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TUSAT is a prospective Turkish Communication Satellite designed for providing mainly data communication and broadcasting services through Ku-Band and C-Band channels. Thermal control is a vital issue in satellite design process. Therefore, all satellite subsystems and equipments should be maintained in the desired temperature range from launch to end of maneuvering life. The main function of the thermal control is to keep the equipments and the satellite structures in a given temperature range for various phases and operating modes of spacecraft during its lifetime. This paper describes the thermal control design which uses passive and active thermal control concepts. The active thermal control is based on heaters regulated by software via thermistors. Alternatively passive thermal control composes of heat pipes, multilayer insulation (MLI) blankets, radiators, paints and surface finishes maintaining temperature level of the overall carrier components within an acceptable value. Thermal control design is supported by thermal analysis using thermal mathematical models (TMM).Keywords: Spacecraft thermal control, design of thermal control.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3674935 Multi-view Description of Real-Time Systems- Architecture
Authors: A. Bessam, M. T. Kimour
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Real-time embedded systems should benefit from component-based software engineering to handle complexity and deal with dependability. In these systems, applications should not only be logically correct but also behave within time windows. However, in the current component based software engineering approaches, a few of component models handles time properties in a manner that allows efficient analysis and checking at the architectural level. In this paper, we present a meta-model for component-based software description that integrates timing issues. To achieve a complete functional model of software components, our meta-model focuses on four functional aspects: interface, static behavior, dynamic behavior, and interaction protocol. With each aspect we have explicitly associated a time model. Such a time model can be used to check a component-s design against certain properties and to compute the timing properties of component assemblies.Keywords: Real-time systems, Software architecture, software component, dependability, time properties, ADL, metamodeling.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1622934 Optimal Design of Motorcycle Crash Bar Using CAD and Finite Element Analysis
Authors: Sharon S. Wu, Yong S. Park
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This project aims to study and evaluate the motorcycle crash bar, which is used to reduce injuries caused by side impacts to the motorcycle, and then develop an improved design using the engineering design process theory based on the current benchmark crash bar in order to lower the severity of motorcycle crash injuries. For this purpose, simulations for the crash bar are set up so that it travels at an angle towards a fixed concrete wall and collides at certain velocities. 3D CAD models are first designed in SolidWorks and dynamic crash simulations are then carried out using ANSYS to determine the lowest maximum Von-Mises stress over time and deformations by adjusting the parameters used in manufacturing the crash bar, including the velocity of the crash, material used, geometries with various radius fillets, and different thicknesses for the bar. The results of the simulation are used to determine the optimum parameters for a safer crash bar to withstand higher stress and deformation. Specifically, the von-Mises stress was reduced by at least 75% compared with the benchmark design by choosing aluminum alloy and a true unibar design.
Keywords: Crash bar, crash simulation, engineering design, motorcycle safety.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 404933 An Experimental Study of a Self-Supervised Classifier Ensemble
Authors: Neamat El Gayar
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Learning using labeled and unlabelled data has received considerable amount of attention in the machine learning community due its potential in reducing the need for expensive labeled data. In this work we present a new method for combining labeled and unlabeled data based on classifier ensembles. The model we propose assumes each classifier in the ensemble observes the input using different set of features. Classifiers are initially trained using some labeled samples. The trained classifiers learn further through labeling the unknown patterns using a teaching signals that is generated using the decision of the classifier ensemble, i.e. the classifiers self-supervise each other. Experiments on a set of object images are presented. Our experiments investigate different classifier models, different fusing techniques, different training sizes and different input features. Experimental results reveal that the proposed self-supervised ensemble learning approach reduces classification error over the single classifier and the traditional ensemble classifier approachs.Keywords: Multiple Classifier Systems, classifier ensembles, learning using labeled and unlabelled data, K-nearest neighbor classifier, Bayes classifier.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1626932 Multimode Dynamics of the Beijing Road Traffic System
Authors: Zundong Zhang, Limin Jia, Xiaoliang Sun
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The Beijing road traffic system, as a typical huge urban traffic system, provides a platform for analyzing the complex characteristics and the evolving mechanisms of urban traffic systems. Based on dynamic network theory, we construct the dynamic model of the Beijing road traffic system in which the dynamical properties are described completely. Furthermore, we come into the conclusion that urban traffic systems can be viewed as static networks, stochastic networks and complex networks at different system phases by analyzing the structural randomness. As well as, we demonstrate the evolving process of the Beijing road traffic network based on real traffic data, validate the stochastic characteristics and the scale-free property of the network at different phasesKeywords: Dynamic Network Models, Structural Randomness, Scale-free Property, Multi-mode character
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1519931 Analysis of Boiling in Rectangular Micro Channel Heat Sink
Authors: Ahmed Jassim Shkarah, Mohd Yusoff Bin Sulaiman, Md Razali bin Hj Ayob
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A 3D-conjugate numerical investigation was conducted to predict heat transfer characteristics in a rectangular cross-sectional micro-channel employing simultaneously developing Tow-phase flows. The sole purpose for analyzing two phase flow heat transfer in rectangular micro channel is to pin point what are the different factors affecting this phenomenon. Different methods and techniques have been undertaken to analyze the equations arising constituting the flow of heat from gas phase to liquid phase and vice versa.Different models of micro channels have been identified and analyzed. How the geometry of micro channels affects their activity i.e. of circular and non-circular geometry has also been reviewed. To the study the results average Nusselt no plotted against the Reynolds no has been taken into consideration to study average heat exchange in micro channels against applied heat flux. High heat fluxes up to 140 W/cm2 were applied to investigate micro-channel thermal characteristics.
Keywords: Tow Phase flow, Micro channel, VOF.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1964930 Fuzzy Time Series Forecasting Using Percentage Change as the Universe of Discourse
Authors: Meredith Stevenson, John E. Porter
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Since the pioneering work of Zadeh, fuzzy set theory has been applied to a myriad of areas. Song and Chissom introduced the concept of fuzzy time series and applied some methods to the enrollments of the University of Alabama. In recent years, a number of techniques have been proposed for forecasting based on fuzzy set theory methods. These methods have either used enrollment numbers or differences of enrollments as the universe of discourse. We propose using the year to year percentage change as the universe of discourse. In this communication, the approach of Jilani, Burney, and Ardil is modified by using the year to year percentage change as the universe of discourse. We use enrollment figures for the University of Alabama to illustrate our proposed method. The proposed method results in better forecasting accuracy than existing models.
Keywords: Fuzzy forecasting, fuzzy time series, fuzzified enrollments, time-invariant model
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2481929 Investigation of Dissolution in Diammonium Hydrogen Phosphate Solutions of Gypsum
Authors: Turan Çalban, Nursel Keskin, Sabri Çolak, Soner Kuşlu
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Gypsum (CaSO4.2H2O) is a mineral that is found in large quantities in the Turkey and in the World. In this study, the dissolution of this mineral in the diammonium hydrogen phosphate solutions has been studied. The dissolution and dissolution kinetics of gypsum in diammonium hydrogen phosphate solutions will be useful for evaluating of solid wastes containing gypsum. Parameters such as diammonium hydrogen phosphate concentration, temperature and stirring speed affecting on the dissolution rate of the gypsum in diammonium hydrogen phosphate solutions were investigated. In experimental studies have researched effectiveness of the selected parameters. The dissolution of gypsum were examined in two parts at low and high temperatures. The experimental results were successfully correlated by linear regression using Statistica program. Dissolution curves were evaluated shrinking core models for solidfluid systems. The activation energy was found to be 34.58 kJ/mol and 44.45 kJ/mol for the low and the high temperatures. The dissolution of gypsum was controlled by chemical reaction both low temperatures and high temperatures.
Keywords: Diammonium hydrogen phosphate, Dissolution, Gypsum, Kinetics.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2035928 Development and Performance Analysis of Multifunctional City Smart Card System
Authors: Vedat Coskun, Fahri Soylemezgiller, Busra Ozdenizci, Kerem Ok
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In recent years, several smart card solutions for transportation services of cities with different technical infrastructures and business models has emerged considerably, which triggers new business and technical opportunities. In order to create a unique system, we present a novel, promising system called Multifunctional City Smart Card System to be used in all cities that provides transportation and loyalty services based on the MasterCard M/Chip Advance standards. The proposed system provides a unique solution for transportation services of large cities over the world, aiming to answer all transportation needs of citizens. In this paper, development of the Multifunctional City Smart Card system and system requirements are briefly described. Moreover, performance analysis results of M/Chip Advance Compatible Validators which is the system's most important component are presented.
Keywords: Smart Card, M/Chip Advance Standard, City Transportation, Performance Analysis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2768927 CBIR Using Multi-Resolution Transform for Brain Tumour Detection and Stages Identification
Authors: H. Benjamin Fredrick David, R. Balasubramanian, A. Anbarasa Pandian
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Image retrieval is the most interesting technique which is being used today in our digital world. CBIR, commonly expanded as Content Based Image Retrieval is an image processing technique which identifies the relevant images and retrieves them based on the patterns that are extracted from the digital images. In this paper, two research works have been presented using CBIR. The first work provides an automated and interactive approach to the analysis of CBIR techniques. CBIR works on the principle of supervised machine learning which involves feature selection followed by training and testing phase applied on a classifier in order to perform prediction. By using feature extraction, the image transforms such as Contourlet, Ridgelet and Shearlet could be utilized to retrieve the texture features from the images. The features extracted are used to train and build a classifier using the classification algorithms such as Naïve Bayes, K-Nearest Neighbour and Multi-class Support Vector Machine. Further the testing phase involves prediction which predicts the new input image using the trained classifier and label them from one of the four classes namely 1- Normal brain, 2- Benign tumour, 3- Malignant tumour and 4- Severe tumour. The second research work includes developing a tool which is used for tumour stage identification using the best feature extraction and classifier identified from the first work. Finally, the tool will be used to predict tumour stage and provide suggestions based on the stage of tumour identified by the system. This paper presents these two approaches which is a contribution to the medical field for giving better retrieval performance and for tumour stages identification.
Keywords: Brain tumour detection, content based image retrieval, classification of tumours, image retrieval.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 750926 Clustering Protein Sequences with Tailored General Regression Model Technique
Authors: G. Lavanya Devi, Allam Appa Rao, A. Damodaram, GR Sridhar, G. Jaya Suma
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Cluster analysis divides data into groups that are meaningful, useful, or both. Analysis of biological data is creating a new generation of epidemiologic, prognostic, diagnostic and treatment modalities. Clustering of protein sequences is one of the current research topics in the field of computer science. Linear relation is valuable in rule discovery for a given data, such as if value X goes up 1, value Y will go down 3", etc. The classical linear regression models the linear relation of two sequences perfectly. However, if we need to cluster a large repository of protein sequences into groups where sequences have strong linear relationship with each other, it is prohibitively expensive to compare sequences one by one. In this paper, we propose a new technique named General Regression Model Technique Clustering Algorithm (GRMTCA) to benignly handle the problem of linear sequences clustering. GRMT gives a measure, GR*, to tell the degree of linearity of multiple sequences without having to compare each pair of them.Keywords: Clustering, General Regression Model, Protein Sequences, Similarity Measure.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1552925 A Quantitative Analysis of GSM Air Interface Based on Radiating Columns and Prediction Model
Authors: K. M. Doraiswamy, Lakshminarayana Merugu, B. C. Jinaga
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This paper explains the cause of nonlinearity in floor attenuation hither to left unexplained. The performance degradation occurring in air interface for GSM signals is quantitatively analysed using the concept of Radiating Columns of buildings. The signal levels were measured using Wireless Network Optimising Drive Test Tool (E6474A of Agilent Technologies). The measurements were taken in reflected signal environment under usual fading conditions on actual GSM signals radiated from base stations. A mathematical model is derived from the measurements to predict the GSM signal levels in different floors. It was applied on three buildings and found that the predicted signal levels deviated from the measured levels with in +/- 2 dB for all floors. It is more accurate than the prediction models based on Floor Attenuation Factor. It can be used for planning proper indoor coverage in multi storey buildings.Keywords: GSM air interface, nonlinear attenuation, multistory building, radiating columns, ground conduction and floor attenuation factor.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1560924 Cascaded Neural Network for Internal Temperature Forecasting in Induction Motor
Authors: Hidir S. Nogay
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In this study, two systems were created to predict interior temperature in induction motor. One of them consisted of a simple ANN model which has two layers, ten input parameters and one output parameter. The other one consisted of eight ANN models connected each other as cascaded. Cascaded ANN system has 17 inputs. Main reason of cascaded system being used in this study is to accomplish more accurate estimation by increasing inputs in the ANN system. Cascaded ANN system is compared with simple conventional ANN model to prove mentioned advantages. Dataset was obtained from experimental applications. Small part of the dataset was used to obtain more understandable graphs. Number of data is 329. 30% of the data was used for testing and validation. Test data and validation data were determined for each ANN model separately and reliability of each model was tested. As a result of this study, it has been understood that the cascaded ANN system produced more accurate estimates than conventional ANN model.Keywords: Cascaded neural network, internal temperature, three-phase induction motor, inverter.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 855923 Application of Feed-Forward Neural Networks Autoregressive Models in Gross Domestic Product Prediction
Authors: Ε. Giovanis
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In this paper we present an autoregressive model with neural networks modeling and standard error backpropagation algorithm training optimization in order to predict the gross domestic product (GDP) growth rate of four countries. Specifically we propose a kind of weighted regression, which can be used for econometric purposes, where the initial inputs are multiplied by the neural networks final optimum weights from input-hidden layer after the training process. The forecasts are compared with those of the ordinary autoregressive model and we conclude that the proposed regression-s forecasting results outperform significant those of autoregressive model in the out-of-sample period. The idea behind this approach is to propose a parametric regression with weighted variables in order to test for the statistical significance and the magnitude of the estimated autoregressive coefficients and simultaneously to estimate the forecasts.Keywords: Autoregressive model, Error back-propagation Feed-Forward neural networks, , Gross Domestic Product
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1411922 Defluoridation of Water by Schwertmannite
Authors: Aparajita Goswami, Mihir K Purkait
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In the present study Schwertmannite (an iron oxide hydroxide) is selected as an adsorbent for defluoridation of water. The adsorbent was prepared by wet chemical process and was characterized by SEM, XRD and BET. The fluoride adsorption efficiency of the prepared adsorbent was determined with respect to contact time, initial fluoride concentration, adsorbent dose and pH of the solution. The batch adsorption data revealed that the fluoride adsorption efficiency was highly influenced by the studied factors. Equilibrium was attained within one hour of contact time indicating fast kinetics and the adsorption data followed pseudo second order kinetic model. Equilibrium isotherm data fitted to both Langmuir and Freundlich isotherm models for a concentration range of 5-30 mg/L. The adsorption system followed Langmuir isotherm model with maximum adsorption capacity of 11.3 mg/g. The high adsorption capacity of Schwertmannite points towards the potential of this adsorbent for fluoride removal from aqueous medium.Keywords: Adsorption, fluoride, isotherm study, kinetics, schwertmannite.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2158921 Application of GM (1, 1) Model Group Based on Recursive Solution in China's Energy Demand Forecasting
Authors: Yeqing Guan, Fen Yang
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To learn about China-s future energy demand, this paper first proposed GM(1,1) model group based on recursive solutions of parameters estimation, setting up a general solving-algorithm of the model group. This method avoided the problems occurred on the past researches that remodeling, loss of information and large amount of calculation. This paper established respectively all-data-GM(1,1), metabolic GM(1,1) and new information GM (1,1)model according to the historical data of energy consumption in China in the year 2005-2010 and the added data of 2011, then modeling, simulating and comparison of accuracies we got the optimal models and to predict. Results showed that the total energy demand of China will be 37.2221 billion tons of equivalent coal in 2012 and 39.7973 billion tons of equivalent coal in 2013, which are as the same as the overall planning of energy demand in The 12th Five-Year Plan.
Keywords: energy demands, GM(1, 1) model group, least square estimation, prediction
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1542920 Numerical Study of Modulus of Subgrade Reaction in Eccentrically Loaded Circular Footing Resting
Authors: Seyed Abolhasan Naeini, Mohammad Hossein Zade
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This article is an attempt to present a numerically study of the behaviour of an eccentrically loaded circular footing resting on sand to determine its ultimate bearing capacity. A surface circular footing of diameter 12 cm (D) was used as shallow foundation. For this purpose, three dimensional models consist of foundation, and medium sandy soil was modelled by ABAQUS software. Bearing capacity of footing was evaluated and the effects of the load eccentricity on bearing capacity, its settlement, and modulus of subgrade reaction were studied. Three different values of load eccentricity with equal space from inside the core on the core boundary and outside the core boundary, which were respectively e=0.75, 1.5, and 2.25 cm, were considered. The results show that by increasing the load eccentricity, the ultimate load and the modulus of subgrade reaction decreased.
Keywords: Circular foundation, eccentric loading, sand, modulus of subgrade reaction.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1634919 The Delaying Influence of Degradation on the Divestment of Gas Turbines for Associated Gas Utilisation: Part 1
Authors: Mafel Obhuo, Dodeye I. Igbong, Duabari S. Aziaka, Pericles Pilidis
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An important feature of the exploitation of associated gas as fuel for gas turbine engines is a declining supply. So when exploiting this resource, the divestment of prime movers is very important as the fuel supply diminishes with time. This paper explores the influence of engine degradation on the timing of divestments. Hypothetical but realistic gas turbine engines were modelled with Turbomatch, the Cranfield University gas turbine performance simulation tool. The results were deployed in three degradation scenarios within the TERA (Techno-economic and environmental risk analysis) framework to develop economic models. An optimisation with Genetic Algorithms was carried out to maximize the economic benefit. The results show that degradation will have a significant impact. It will delay the divestment of power plants, while they are running less efficiently. Over a 20 year investment, a decrease of $0.11bn, $0.26bn and $0.45bn (billion US dollars) were observed for the three degradation scenarios as against the clean case.
Keywords: Economic return, flared associated gas, net present value, optimisation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1087918 Derivation of Fractional Black-Scholes Equations Driven by Fractional G-Brownian Motion and Their Application in European Option Pricing
Authors: Changhong Guo, Shaomei Fang, Yong He
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In this paper, fractional Black-Scholes models for the European option pricing were established based on the fractional G-Brownian motion (fGBm), which generalizes the concepts of the classical Brownian motion, fractional Brownian motion and the G-Brownian motion, and that can be used to be a tool for considering the long range dependence and uncertain volatility for the financial markets simultaneously. A generalized fractional Black-Scholes equation (FBSE) was derived by using the Taylor’s series of fractional order and the theory of absence of arbitrage. Finally, some explicit option pricing formulas for the European call option and put option under the FBSE were also solved, which extended the classical option pricing formulas given by F. Black and M. Scholes.Keywords: European option pricing, fractional Black-Scholes equations, fractional G-Brownian motion, Taylor’s series of fractional order, uncertain volatility.
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