Search results for: predictive modeling
2212 Building a Scalable Telemetry Based Multiclass Predictive Maintenance Model in R
Authors: Jaya Mathew
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Many organizations are faced with the challenge of how to analyze and build Machine Learning models using their sensitive telemetry data. In this paper, we discuss how users can leverage the power of R without having to move their big data around as well as a cloud based solution for organizations willing to host their data in the cloud. By using ScaleR technology to benefit from parallelization and remote computing or R Services on premise or in the cloud, users can leverage the power of R at scale without having to move their data around.
Keywords: Predictive maintenance, machine learning, big data, cloud, on premise SQL, R.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19072211 Data Oriented Modeling of Uniform Random Variable: Applied Approach
Authors: Ahmad Habibizad Navin, Mehdi Naghian Fesharaki, Mirkamal Mirnia, Mohamad Teshnelab, Ehsan Shahamatnia
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In this paper we introduce new data oriented modeling of uniform random variable well-matched with computing systems. Due to this conformity with current computers structure, this modeling will be efficiently used in statistical inference.Keywords: Uniform random variable, Data oriented modeling, Statistical inference, Prodigraph, Statistically complete tree, Uniformdigital probability digraph, Uniform n-complete probability tree.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16152210 Are Economic Crises and Government Changes Related? A Descriptive Statistic Analysis
Authors: Şakir Görmüş, Ali Kabasakal
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The main purpose of this study is to provide a detailed statistical overview of the time and regional distribution, relative timing occurrence of economic crises and government changes in 51 economies over the 1990–2007 periods. At the same time, the predictive power of the economic crises on set government changes will be examined using “signal approach". The result showed that the percentage of government changes is highest in transition economies (86 percent of observations) and lowest in Latin American economies (39 percent of observations). The percentages of government changes are same in both developed and developing countries (43 percent of observations). However, average crises per year (frequency of crises) are higher (lower) in developing (developed) countries than developed (developing) countries. Also, the predictive power of economic crises about the onset of a government change is highest in Transition economies (81 percent) and lowest in Latin American countries (30 percent). The predictive power of economic crises in developing countries (43 percent) is lower than developed countries (55 percent).Keywords: Economic crises, Government Changes, PoliticalEconomy, Signal Approach.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14372209 The Comparison of Anchor and Star Schema from a Query Performance Perspective
Authors: Radek Němec
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Today's business environment requires that companies have access to highly relevant information in a matter of seconds. Modern Business Intelligence tools rely on data structured mostly in traditional dimensional database schemas, typically represented by star schemas. Dimensional modeling is already recognized as a leading industry standard in the field of data warehousing although several drawbacks and pitfalls were reported. This paper focuses on the analysis of another data warehouse modeling technique - the anchor modeling, and its characteristics in context with the standardized dimensional modeling technique from a query performance perspective. The results of the analysis show information about performance of queries executed on database schemas structured according to principles of each database modeling technique.Keywords: Data warehousing, anchor modeling, star schema, anchor schema, query performance.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 33062208 Investigations into Effect of Neural Network Predictive Control of UPFC for Improving Transient Stability Performance of Multimachine Power System
Authors: Sheela Tiwari, R. Naresh, R. Jha
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The paper presents an investigation in to the effect of neural network predictive control of UPFC on the transient stability performance of a multimachine power system. The proposed controller consists of a neural network model of the test system. This model is used to predict the future control inputs using the damped Gauss-Newton method which employs ‘backtracking’ as the line search method for step selection. The benchmark 2 area, 4 machine system that mimics the behavior of large power systems is taken as the test system for the study and is subjected to three phase short circuit faults at different locations over a wide range of operating conditions. The simulation results clearly establish the robustness of the proposed controller to the fault location, an increase in the critical clearing time for the circuit breakers, and an improved damping of the power oscillations as compared to the conventional PI controller.
Keywords: Identification, Neural networks, Predictive control, Transient stability, UPFC.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20662207 Data Mining Applied to the Predictive Model of Triage System in Emergency Department
Authors: Wen-Tsann Lin, Yung-Tsan Jou, Yih-Chuan Wu, Yuan-Du Hsiao
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The Emergency Department of a medical center in Taiwan cooperated to conduct the research. A predictive model of triage system is contracted from the contract procedure, selection of parameters to sample screening. 2,000 pieces of data needed for the patients is chosen randomly by the computer. After three categorizations of data mining (Multi-group Discriminant Analysis, Multinomial Logistic Regression, Back-propagation Neural Networks), it is found that Back-propagation Neural Networks can best distinguish the patients- extent of emergency, and the accuracy rate can reach to as high as 95.1%. The Back-propagation Neural Networks that has the highest accuracy rate is simulated into the triage acuity expert system in this research. Data mining applied to the predictive model of the triage acuity expert system can be updated regularly for both the improvement of the system and for education training, and will not be affected by subjective factors.Keywords: Back-propagation Neural Networks, Data Mining, Emergency Department, Triage System.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22952206 Modeling Approaches for Large-Scale Reconfigurable Engineering Systems
Authors: Kwa-Sur Tam
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This paper reviews various approaches that have been used for the modeling and simulation of large-scale engineering systems and determines their appropriateness in the development of a RICS modeling and simulation tool. Bond graphs, linear graphs, block diagrams, differential and difference equations, modeling languages, cellular automata and agents are reviewed. This tool should be based on linear graph representation and supports symbolic programming, functional programming, the development of noncausal models and the incorporation of decentralized approaches.Keywords: Interdisciplinary, dynamic, functional programming, object-oriented.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14832205 Agent-Based Modeling of Power Systems Infrastructure Cyber Security
Authors: Raman Paranjape
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We present a new approach to evaluation of Cyber Security in Power Systems using the method of modeling the power systems Infrastructure using software agents. Interfaces between module and the home smart meter are recognized as the primary points of intrusion.
Keywords: Power Systems, Modeling and Simulation, Agent systems.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24322204 The Strengths and Limitations of the Statistical Modeling of Complex Social Phenomenon: Focusing on SEM, Path Analysis, or Multiple Regression Models
Authors: Jihye Jeon
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This paper analyzes the conceptual framework of three statistical methods, multiple regression, path analysis, and structural equation models. When establishing research model of the statistical modeling of complex social phenomenon, it is important to know the strengths and limitations of three statistical models. This study explored the character, strength, and limitation of each modeling and suggested some strategies for accurate explaining or predicting the causal relationships among variables. Especially, on the studying of depression or mental health, the common mistakes of research modeling were discussed.Keywords: Multiple regression, path analysis, structural equation models, statistical modeling, social and psychological phenomenon.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 92232203 Experimental Implementation of Model Predictive Control for Permanent Magnet Synchronous Motor
Authors: Abdelsalam A. Ahmed
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Fast speed drives for Permanent Magnet Synchronous Motor (PMSM) is a crucial performance for the electric traction systems. In this paper, PMSM is derived with a Model-based Predictive Control (MPC) technique. Fast speed tracking is achieved through optimization of the DC source utilization using MPC. The technique is based on predicting the optimum voltage vector applied to the driver. Control technique is investigated by comparing to the cascaded PI control based on Space Vector Pulse Width Modulation (SVPWM). MPC and SVPWM-based FOC are implemented with the TMS320F2812 DSP and its power driver circuits. The designed MPC for a PMSM drive is experimentally validated on a laboratory test bench. The performances are compared with those obtained by a conventional PI-based system in order to highlight the improvements, especially regarding speed tracking response.Keywords: Permanent magnet synchronous motor, mode predictive control, optimization of DC source utilization, cascaded PI control, space vector pulse width modulation, TMS320F2812 DSP.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 30872202 Spectral Analysis of Speech: A New Technique
Authors: Neeta Awasthy, J.P.Saini, D.S.Chauhan
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ICA which is generally used for blind source separation problem has been tested for feature extraction in Speech recognition system to replace the phoneme based approach of MFCC. Applying the Cepstral coefficients generated to ICA as preprocessing has developed a new signal processing approach. This gives much better results against MFCC and ICA separately, both for word and speaker recognition. The mixing matrix A is different before and after MFCC as expected. As Mel is a nonlinear scale. However, cepstrals generated from Linear Predictive Coefficient being independent prove to be the right candidate for ICA. Matlab is the tool used for all comparisons. The database used is samples of ISOLET.Keywords: Cepstral Coefficient, Distance measures, Independent Component Analysis, Linear Predictive Coefficients.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19432201 Modeling the Human Cardiovascular System with Aspecial Focus on the Heart Using Dymola
Authors: Stefanie Heinke, Carina Pereira, Jan Spillner, Steffen Leonhardt
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Severe heart failure is a common problem that has a significant effect on health expenditures in industrialized countries; moreover it reduces patient-s quality of life. However, current research usually focuses either on detailed modeling of the heart or on detailed modeling of the cardiovascular system. Thus, this paper aims to present a sophisticated model of the heart enhanced with an extensive model of the cardiovascular system. Special interest is on the pressure and flow values close to the heart since these values are critical to accurately diagnose causes of heart failure. The model is implemented in Dymola an object-oriented, physical modeling language. Results achieved with the novel model show overall feasibility of the approach. Moreover, results are illustrated and compared to other models. The novel model shows significant improvements.
Keywords: Cardiovascular system, heart, modeling.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18342200 Predictive Model of Sensor Readings for a Mobile Robot
Authors: Krzysztof Fujarewicz
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This paper presents a predictive model of sensor readings for mobile robot. The model predicts sensor readings for given time horizon based on current sensor readings and velocities of wheels assumed for this horizon. Similar models for such anticipation have been proposed in the literature. The novelty of the model presented in the paper comes from the fact that its structure takes into account physical phenomena and is not just a black box, for example a neural network. From this point of view it may be regarded as a semi-phenomenological model. The model is developed for the Khepera robot, but after certain modifications, it may be applied for any robot with distance sensors such as infrared or ultrasonic sensors.
Keywords: Mobile robot, sensors, prediction, anticipation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14382199 UML Modeling for Instruction Pipeline Design
Authors: Vipin Saxena, Deepa Raj
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Unified Modeling language (UML) is one of the important modeling languages used for the visual representation of the research problem. In the present paper, UML model is designed for the Instruction pipeline which is used for the evaluation of the instructions of software programs. The class and sequence diagrams are designed & performance is evaluated for instructions of a sample program through a case study.Keywords: UML, Instruction Pipeline, Class Diagram &Sequence Diagram.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 25272198 Performance Modeling for Web based J2EE and .NET Applications
Authors: Shankar Kambhampaty, Venkata Srinivas Modali
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When architecting an application, key nonfunctional requirements such as performance, scalability, availability and security, which influence the architecture of the system, are some times not adequately addressed. Performance of the application may not be looked at until there is a concern. There are several problems with this reactive approach. If the system does not meet its performance objectives, the application is unlikely to be accepted by the stakeholders. This paper suggests an approach for performance modeling for web based J2EE and .Net applications to address performance issues early in the development life cycle. It also includes a Performance Modeling Case Study, with Proof-of-Concept (PoC) and implementation details for .NET and J2EE platforms.
Keywords: Performance Measures, Performance Modeling, Performance Testing, Resource Utilization, Response Time, Throughput.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22472197 Predictive Semi-Empirical NOx Model for Diesel Engine
Authors: Saurabh Sharma, Yong Sun, Bruce Vernham
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Accurate prediction of NOx emission is a continuous challenge in the field of diesel engine-out emission modeling. Performing experiments for each conditions and scenario cost significant amount of money and man hours, therefore model-based development strategy has been implemented in order to solve that issue. NOx formation is highly dependent on the burn gas temperature and the O2 concentration inside the cylinder. The current empirical models are developed by calibrating the parameters representing the engine operating conditions with respect to the measured NOx. This makes the prediction of purely empirical models limited to the region where it has been calibrated. An alternative solution to that is presented in this paper, which focus on the utilization of in-cylinder combustion parameters to form a predictive semi-empirical NOx model. The result of this work is shown by developing a fast and predictive NOx model by using the physical parameters and empirical correlation. The model is developed based on the steady state data collected at entire operating region of the engine and the predictive combustion model, which is developed in Gamma Technology (GT)-Power by using Direct Injected (DI)-Pulse combustion object. In this approach, temperature in both burned and unburnt zone is considered during the combustion period i.e. from Intake Valve Closing (IVC) to Exhaust Valve Opening (EVO). Also, the oxygen concentration consumed in burnt zone and trapped fuel mass is also considered while developing the reported model. Several statistical methods are used to construct the model, including individual machine learning methods and ensemble machine learning methods. A detailed validation of the model on multiple diesel engines is reported in this work. Substantial numbers of cases are tested for different engine configurations over a large span of speed and load points. Different sweeps of operating conditions such as Exhaust Gas Recirculation (EGR), injection timing and Variable Valve Timing (VVT) are also considered for the validation. Model shows a very good predictability and robustness at both sea level and altitude condition with different ambient conditions. The various advantages such as high accuracy and robustness at different operating conditions, low computational time and lower number of data points requires for the calibration establishes the platform where the model-based approach can be used for the engine calibration and development process. Moreover, the focus of this work is towards establishing a framework for the future model development for other various targets such as soot, Combustion Noise Level (CNL), NO2/NOx ratio etc.
Keywords: Diesel engine, machine learning, NOx emission, semi-empirical.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8422196 Modelling and Simulation of the Freezing Systems and Heat Pumps Using Unisim® Design
Authors: C. Patrascioiu
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The paper describes the modeling and simulation of the heat pumps domain processes. The main objective of the study is the use of the heat pump in propene–propane distillation processes. The modeling and simulation instrument is the Unisim® Design simulator. The paper is structured in three parts: An overview of the compressing gases, the modeling and simulation of the freezing systems, and the modeling and simulation of the heat pumps. For each of these systems, there are presented the Unisim® Design simulation diagrams, the input–output system structure and the numerical results. Future studies will consider modeling and simulation of the propene–propane distillation process with heat pump.
Keywords: Distillation, heat pump, simulation, Unisim Design.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 24332195 Supply Air Pressure Control of HVAC System Using MPC Controller
Authors: P. Javid, A. Aeenmehr, J. Taghavifar
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In this paper, supply air pressure of HVAC system has been modeled with second-order transfer function plus dead-time. In HVAC system, the desired input has step changes, and the output of proposed control system should be able to follow the input reference, so the idea of using model based predictive control is proceeded and designed in this paper. The closed loop control system is implemented in MATLAB software and the simulation results are provided. The simulation results show that the model based predictive control is able to control the plant properly.
Keywords: Air conditioning system, GPC, dead time, Air supply control.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22652194 LMI Approach to Regularization and Stabilization of Linear Singular Systems: The Discrete-time Case
Authors: Salim Ibrir
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Sufficient linear matrix inequalities (LMI) conditions for regularization of discrete-time singular systems are given. Then a new class of regularizing stabilizing controllers is discussed. The proposed controllers are the sum of predictive and memoryless state feedbacks. The predictive controller aims to regularizing the singular system while the memoryless state feedback is designed to stabilize the resulting regularized system. A systematic procedure is given to calculate the controller gains through linear matrix inequalities.
Keywords: Singular systems, Discrete-time systems, Regularization, LMIs
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15852193 Integrate Communication Modeling into the Design Modeling at Early Stages of the Design Flow Case Study: Unmanned Aerial Vehicle (UAV)
Authors: Ibrahim A. Aref, Tarek A. El-Mihoub
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This paper shows how we can integrate communication modeling into the design modeling at early stages of the design flow. We consider effect of incorporating noise such as impulsive noise on system stability. We show that with change of the system model and investigate the system performance under the different communication effects. We modeled a unmanned aerial vehicle (UAV) as a demonstration using SystemC methodology. Moreover the system is modeled by joining the capabilities of UML and SystemC to operate at system level.Keywords: Modelling, SoC, SystemC, UAV, Simulation, SoC.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22532192 Real Time Monitoring of Long Slender Shaft by Distributed-Lumped Modeling Techniques
Authors: Sina Babadi, K. M. Ebrahimi
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The aim of this paper is to determine the stress levels at the end of a long slender shaft such as a drilling assembly used in the oil or gas industry using a mathematical model in real-time. The torsional deflection experienced by this type of drilling shaft (about 4 KM length and 20 cm diameter hollow shaft with a thickness of 1 cm) can only be determined using a distributed modeling technique. The main objective of this project is to calculate angular velocity and torque at the end of the shaft by TLM method and also analyzing of the behavior of the system by transient response. The obtained result is compared with lumped modeling technique the importance of these results will be evident only after the mentioned comparison. Two systems have different transient responses and in this project because of the length of the shaft transient response is very important.Keywords: Distributed Lumped modeling, Lumped modeling, Drill string, Angular Velocity, Torque.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14432191 Methodologies, Systems Development Life Cycle and Modeling Languages in Agile Software Development
Authors: I. D. Arroyo
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This article seeks to integrate different concepts from contemporary software engineering with an agile development approach. We seek to clarify some definitions and uses, we make a difference between the Systems Development Life Cycle (SDLC) and the methodologies, we differentiate the types of frameworks such as methodological, philosophical and behavioral, standards and documentation. We define relationships based on the documentation of the development process through formal and ad hoc models, and we define the usefulness of using DevOps and Agile Modeling as integrative methodologies of principles and best practices.Keywords: Methodologies, SDLC, modeling languages, agile modeling, DevOps, UML, agile software development.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 9302190 Protein Profiling in Alanine Aminotransferase Induced Patient cohort using Acetaminophen
Authors: Gry M, Bergström J, Lengquist J, Lindberg J, Drobin K, Schwenk J, Nilsson P, Schuppe-Koistinen I.
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Sensitive and predictive DILI (Drug Induced Liver Injury) biomarkers are needed in drug R&D to improve early detection of hepatotoxicity. The discovery of DILI biomarkers that demonstrate the predictive power to identify individuals at risk to DILI would represent a major advance in the development of personalized healthcare approaches. In this healthy volunteer acetaminophen study (4g/day for 7 days, with 3 monitored nontreatment days before and 4 after), 450 serum samples from 32 subjects were analyzed using protein profiling by antibody suspension bead arrays. Multiparallel protein profiles were generated using a DILI target protein array with 300 antibodies, where the antibodies were selected based on previous literature findings of putative DILI biomarkers and a screening process using pre dose samples from the same cohort. Of the 32 subjects, 16 were found to develop an elevated ALT value (2Xbaseline, responders). Using the plasma profiling approach together with multivariate statistical analysis some novel findings linked to lipid metabolism were found and more important, endogenous protein profiles in baseline samples (prior to treatment) with predictive power for ALT elevations were identified.Keywords: DILI, Plasma profiling, PLSDA, Randomforest.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13062189 Modeling and Analysis of SVPWM Based Dynamic Voltage Restorer
Authors: Ahmed Helal, Sherif Zain Elabideen, Ahmed Lotfy
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In this paper the modeling and analysis of Space Vector Pulse Width Modulation (SVPWM) based Dynamic Voltage Restorer (DVR) using PSCAD/EMTDC software will be presented in details. The simulation includes full modeling of the SVPWM technique used to control the DVR inverter. A test power system composed of three phase voltage source, sag generator, DVR and three phase resistive load is used to demonstrate restoration capability of the DVR. The simulation results of the presented DVR proved excellent voltage sag mitigation to protect sensitive loads.Keywords: Dynamic voltage restorer, power quality, simulationand modeling, voltage sag.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 37042188 Object-Oriented Programming for Modeling and Simulation of Systems in Physiology
Authors: J. Fernandez de Canete
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Object-oriented modeling is spreading in current simulation of physiological systems through the use of the individual components of the model and its interconnections to define the underlying dynamic equations. In this paper we describe the use of both the SIMSCAPE and MODELICA simulation environments in the object-oriented modeling of the closed loop cardiovascular system. The performance of the controlled system was analyzed by simulation in light of the existing hypothesis and validation tests previously performed with physiological data. The described approach represents a valuable tool in the teaching of physiology for graduate medical students.
Keywords: Object-Oriented Modeling, SIMSCAPE Simulation Language, MODELICA Simulation Language, Cardiovascular System.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 28512187 Improved Blood Glucose-Insulin Monitoring with Dual-Layer Predictive Control Design
Authors: Vahid Nademi
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In response to widely used wearable medical devices equipped with a continuous glucose monitor (CGM) and insulin pump, the advanced control methods are still demanding to get the full benefit of these devices. Unlike costly clinical trials, implementing effective insulin-glucose control strategies can provide significant contributions to the patients suffering from chronic diseases such as diabetes. This study deals with a key role of two-layer insulin-glucose regulator based on model-predictive-control (MPC) scheme so that the patient’s predicted glucose profile is in compliance with the insulin level injected through insulin pump automatically. It is achieved by iterative optimization algorithm which is called an integrated perturbation analysis and sequential quadratic programming (IPA-SQP) solver for handling uncertainties due to unexpected variations in glucose-insulin values and body’s characteristics. The feasibility evaluation of the discussed control approach is also studied by means of numerical simulations of two case scenarios via measured data. The obtained results are presented to verify the superior and reliable performance of the proposed control scheme with no negative impact on patient safety.
Keywords: Blood glucose monitoring, insulin pump, optimization, predictive control, diabetes disease.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 7332186 Combined Fuzzy and Predictive Controller for Unity Power Factor Converter
Authors: Abdelhalim Kessal
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This paper treats a design of combined control of a single phase power factor correction (PFC). The strategy of the proposed control is based on two parts, the first, for the outer loop (DC output regulated voltage), and the second govern the input current of the converter in order to achieve a sinusoidal form in phase with the grid voltage. Two kinds of regulators are used, Fuzzy controller for the outer loop and predictive controller for the inner loop. The controllers are verified and discussed through simulation under MATLAB/Simulink platform. Also an experimental confirmation is applied. Results present a high dynamic performance under various parameters changes.Keywords: Boost converter, harmonic distortion, Fuzzy, prediction, unity power factor.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 11482185 Modeling and Simulation of Standalone Photovoltaic Charging Stations for Electric Vehicles
Authors: R. Mkahl, A. Nait-Sidi-Moh, M. Wack
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Batteries of electric vehicles (BEV) are becoming more attractive with the advancement of new battery technologies and promotion of electric vehicles. BEV batteries are recharged on board vehicles using either the grid (G2V for Grid to Vehicle) or renewable energies in a stand-alone application (H2V for Home to Vehicle). This paper deals with the modeling, sizing and control of a photovoltaic stand-alone application that can charge the BEV at home. The modeling approach and developed mathematical models describing the system components are detailed. Simulation and experimental results are presented and commented.
Keywords: Electric vehicles, photovoltaic energy, lead-acid batteries, charging process, modeling, simulation, experimental tests.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 41862184 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 22532183 Systems Versioning: A Features-Based Meta-Modeling Approach
Authors: Ola A. Younis, Said Ghoul
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Systems running these days are huge, complex and exist in many versions. Controlling these versions and tracking their changes became a very hard process as some versions are created using meaningless names or specifications. Many versions of a system are created with no clear difference between them. This leads to mismatching between a user’s request and the version he gets. In this paper, we present a system versions meta-modeling approach that produces versions based on system’s features. This model reduced the number of steps needed to configure a release and gave each version its unique specifications. This approach is applicable for systems that use features in its specification.
Keywords: Features, Meta-modeling, Semantic Modeling, SPL, VCS, Versioning.
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