Search results for: predictive functional control
4454 Neural Network-Based Control Strategies Applied to a Fed-Batch Crystallization Process
Authors: P. Georgieva, S. Feyo de Azevedo
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This paper is focused on issues of process modeling and two model based control strategies of a fed-batch sugar crystallization process applying the concept of artificial neural networks (ANNs). The control objective is to force the operation into following optimal supersaturation trajectory. It is achieved by manipulating the feed flow rate of sugar liquor/syrup, considered as the control input. The control task is rather challenging due to the strong nonlinearity of the process dynamics and variations in the crystallization kinetics. Two control alternatives are considered – model predictive control (MPC) and feedback linearizing control (FLC). Adequate ANN process models are first built as part of the controller structures. MPC algorithm outperforms the FLC approach with respect to satisfactory reference tracking and smooth control action. However, the MPC is computationally much more involved since it requires an online numerical optimization, while for the FLC an analytical control solution was determined.Keywords: artificial neural networks, nonlinear model control, process identification, crystallization process
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18454453 Application of Functional Network to Solving Classification Problems
Authors: Yong-Quan Zhou, Deng-Xu He, Zheng Nong
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In this paper two models using a functional network were employed to solving classification problem. Functional networks are generalized neural networks, which permit the specification of their initial topology using knowledge about the problem at hand. In this case, and after analyzing the available data and their relations, we systematically discuss a numerical analysis method used for functional network, and apply two functional network models to solving XOR problem. The XOR problem that cannot be solved with two-layered neural network can be solved by two-layered functional network, which reveals a potent computational power of functional networks, and the performance of the proposed model was validated using classification problems.Keywords: Functional network, neural network, XOR problem, classification, numerical analysis method.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13144452 A Posterior Predictive Model-Based Control Chart for Monitoring Healthcare
Authors: Yi-Fan Lin, Peter P. Howley, Frank A. Tuyl
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Quality measurement and reporting systems are used in healthcare internationally. In Australia, the Australian Council on Healthcare Standards records and reports hundreds of clinical indicators (CIs) nationally across the healthcare system. These CIs are measures of performance in the clinical setting, and are used as a screening tool to help assess whether a standard of care is being met. Existing analysis and reporting of these CIs incorporate Bayesian methods to address sampling variation; however, such assessments are retrospective in nature, reporting upon the previous six or twelve months of data. The use of Bayesian methods within statistical process control for monitoring systems is an important pursuit to support more timely decision-making. Our research has developed and assessed a new graphical monitoring tool, similar to a control chart, based on the beta-binomial posterior predictive (BBPP) distribution to facilitate the real-time assessment of health care organizational performance via CIs. The BBPP charts have been compared with the traditional Bernoulli CUSUM (BC) chart by simulation. The more traditional “central” and “highest posterior density” (HPD) interval approaches were each considered to define the limits, and the multiple charts were compared via in-control and out-of-control average run lengths (ARLs), assuming that the parameter representing the underlying CI rate (proportion of cases with an event of interest) required estimation. Preliminary results have identified that the BBPP chart with HPD-based control limits provides better out-of-control run length performance than the central interval-based and BC charts. Further, the BC chart’s performance may be improved by using Bayesian parameter estimation of the underlying CI rate.
Keywords: Average run length, Bernoulli CUSUM chart, beta binomial posterior predictive distribution, clinical indicator, health care organization, highest posterior density interval.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 8844451 Automotive ECU Design with Functional Safety for Electro-Mechanical Actuator Systems
Authors: Kyung-Jung Lee, Young-Hun Ki, Hyun-Sik Ahn
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In this paper, we propose a hardware and software design method for automotive Electronic Control Units (ECU) considering the functional safety. The proposed ECU is considered for the application to Electro-Mechanical Actuator systems and the validity of the design method is shown by the application to the Electro-Mechanical Brake (EMB) control system which is used as a brake actuator in Brake-By-Wire (BBW) systems. The importance of a functional safety-based design approach to EMB ECU design has been emphasized because of its safety-critical functions, which are executed with the aid of many electric actuators, sensors, and application software. Based on hazard analysis and risk assessment according to ISO26262, the EMB system should be ASIL-D-compliant, the highest ASIL level. To this end, an external signature watchdog and an Infineon 32-bit microcontroller TriCore are used to reduce risks considering common-cause hardware failure. Moreover, a software design method is introduced for implementing functional safety-oriented monitoring functions based on an asymmetric dual core architecture considering redundancy and diversity. The validity of the proposed ECU design approach is verified by using the EMB Hardware-In-the-Loop (HILS) system, which consists of the EMB assembly, actuator ECU, a host PC, and a few debugging devices. Furthermore, it is shown that the existing sensor fault tolerant control system can be used more effectively for mitigating the effects of hardware and software faults by applying the proposed ECU design method.
Keywords: BBW (Brake-By-wire), EMB (Electro-Mechanical Brake), Functional Safety, ISO26262.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 70024450 Identification of a PWA Model of a Batch Reactor for Model Predictive Control
Authors: Gorazd Karer, Igor Skrjanc, Borut Zupancic
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The complex hybrid and nonlinear nature of many processes that are met in practice causes problems with both structure modelling and parameter identification; therefore, obtaining a model that is suitable for MPC is often a difficult task. The basic idea of this paper is to present an identification method for a piecewise affine (PWA) model based on a fuzzy clustering algorithm. First we introduce the PWA model. Next, we tackle the identification method. We treat the fuzzy clustering algorithm, deal with the projections of the fuzzy clusters into the input space of the PWA model and explain the estimation of the parameters of the PWA model by means of a modified least-squares method. Furthermore, we verify the usability of the proposed identification approach on a hybrid nonlinear batch reactor example. The result suggest that the batch reactor can be efficiently identified and thus formulated as a PWA model, which can eventually be used for model predictive control purposes.
Keywords: Batch reactor, fuzzy clustering, hybrid systems, identification, nonlinear systems, PWA systems.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21984449 Design and Development of Real-Time Optimal Energy Management System for Hybrid Electric Vehicles
Authors: Masood Roohi, Amir Taghavipour
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This paper describes a strategy to develop an energy management system (EMS) for a charge-sustaining power-split hybrid electric vehicle. This kind of hybrid electric vehicles (HEVs) benefit from the advantages of both parallel and series architecture. However, it gets relatively more complicated to manage power flow between the battery and the engine optimally. The applied strategy in this paper is based on nonlinear model predictive control approach. First of all, an appropriate control-oriented model which was accurate enough and simple was derived. Towards utilization of this controller in real-time, the problem was solved off-line for a vast area of reference signals and initial conditions and stored the computed manipulated variables inside look-up tables. Look-up tables take a little amount of memory. Also, the computational load dramatically decreased, because to find required manipulated variables the controller just needed a simple interpolation between tables.Keywords: Hybrid electric vehicles, energy management system, nonlinear model predictive control, real-time.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13964448 Periodic Control of a Wastewater Treatment Process to Improve Productivity
Authors: Muhammad Rizwan Azhar, Emadadeen Ali
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In this paper, periodic force operation of a wastewater treatment process has been studied for the improved process performance. A previously developed dynamic model for the process is used to conduct the performance analysis. The static version of the model was utilized first to determine the optimal productivity conditions for the process. Then, feed flow rate in terms of dilution rate i.e. (D) is transformed into sinusoidal function. Nonlinear model predictive control algorithm is utilized to regulate the amplitude and period of the sinusoidal function. The parameters of the feed cyclic functions are determined which resulted in improved productivity than the optimal productivity under steady state conditions. The improvement in productivity is found to be marginal and is satisfactory in substrate conversion compared to that of the optimal condition and to the steady state condition, which corresponds to the average value of the periodic function. Successful results were also obtained in the presence of modeling errors and external disturbances.
Keywords: Dilution rate, nonlinear model predictive control, sinusoidal function, wastewater treatment.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 22124447 Combined Model Predictive Controller Technique for Enhancing NAO Gait Stabilization
Authors: Brahim Brahmi, Mohammed Hamza Laraki, Mohammad Habibur Rahman, Islam M. Rasedul, M. Assad Uz-Zaman
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The humanoid robot, specifically the NAO robot must be able to provide a highly dynamic performance on the soccer field. Maintaining the balance of the humanoid robot during the required motion is considered as one of a challenging problems especially when the robot is subject to external disturbances, as contact with other robots. In this paper, a dynamic controller is proposed in order to ensure a robust walking (stabilization) and to improve the dynamic balance of the robot during its contact with the environment (external disturbances). The generation of the trajectory of the center of mass (CoM) is done by a model predictive controller (MPC) conjoined with zero moment point (ZMP) technique. Taking into account the properties of the rotational dynamics of the whole-body system, a modified previous control mixed with feedback control is employed to manage the angular momentum and the CoM’s acceleration, respectively. This latter is dedicated to provide a robust gait of the robot in the presence of the external disturbances. Simulation results are presented to show the feasibility of the proposed strategy.Keywords: Preview control, walking, stabilization, humanoid robot.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 5944446 An Artificial Neural Network Based Model for Predicting H2 Production Rates in a Sucrose-Based Bioreactor System
Authors: Nikhil, Bestamin Özkaya, Ari Visa, Chiu-Yue Lin, Jaakko A. Puhakka, Olli Yli-Harja
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The performance of a sucrose-based H2 production in a completely stirred tank reactor (CSTR) was modeled by neural network back-propagation (BP) algorithm. The H2 production was monitored over a period of 450 days at 35±1 ºC. The proposed model predicts H2 production rates based on hydraulic retention time (HRT), recycle ratio, sucrose concentration and degradation, biomass concentrations, pH, alkalinity, oxidation-reduction potential (ORP), acids and alcohols concentrations. Artificial neural networks (ANNs) have an ability to capture non-linear information very efficiently. In this study, a predictive controller was proposed for management and operation of large scale H2-fermenting systems. The relevant control strategies can be activated by this method. BP based ANNs modeling results was very successful and an excellent match was obtained between the measured and the predicted rates. The efficient H2 production and system control can be provided by predictive control method combined with the robust BP based ANN modeling tool.Keywords: Back-propagation, biohydrogen, bioprocessmodeling, neural networks.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 17794445 A Fuzzy Predictive Filter for Sinusoidal Signals with Time-Varying Frequencies
Authors: X. Z. Gao, S. J. Ovaska, X. Wang
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Prediction of sinusoidal signals with time-varying frequencies has been an important research topic in power electronics systems. To solve this problem, we propose a new fuzzy predictive filtering scheme, which is based on a Finite Impulse Response (FIR) filter bank. Fuzzy logic is introduced here to provide appropriate interpolation of individual filter outputs. Therefore, instead of regular 'hard' switching, our method has the advantageous 'soft' switching among different filters. Simulation comparisons between the fuzzy predictive filtering and conventional filter bank-based approach are made to demonstrate that the new scheme can achieve an enhanced prediction performance for slowly changing sinusoidal input signals.Keywords: Predictive filtering, fuzzy logic, sinusoidal signals, time-varying frequencies.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14984444 ATM Service Analysis Using Predictive Data Mining
Authors: S. Madhavi, S. Abirami, C. Bharathi, B. Ekambaram, T. Krishna Sankar, A. Nattudurai, N. Vijayarangan
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The high utilization rate of Automated Teller Machine (ATM) has inevitably caused the phenomena of waiting for a long time in the queue. This in turn has increased the out of stock situations. The ATM utilization helps to determine the usage level and states the necessity of the ATM based on the utilization of the ATM system. The time in which the ATM used more frequently (peak time) and based on the predicted solution the necessary actions are taken by the bank management. The analysis can be done by using the concept of Data Mining and the major part are analyzed based on the predictive data mining. The results are predicted from the historical data (past data) and track the relevant solution which is required. Weka tool is used for the analysis of data based on predictive data mining.
Keywords: ATM, Bank Management, Data Mining, Historical data, Predictive Data Mining, Weka tool.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 56174443 Systematic Functional Analysis Methods for Design Retrieval and Documentation
Authors: L. Zehtaban, D. Roller
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Apart from geometry, functionality is one of the most significant hallmarks of a product. The functionality of a product can be considered as the fundamental justification for a product existence. Therefore a functional analysis including a complete and reliable descriptor has a high potential to improve product development process in various fields especially in knowledge-based design. One of the important applications of the functional analysis and indexing is in retrieval and design reuse concept. More than 75% of design activity for a new product development contains reusing earlier and existing design know-how. Thus, analysis and categorization of product functions concluded by functional indexing, influences directly in design optimization. This paper elucidates and evaluates major classes for functional analysis by discussing their major methods. Moreover it is finalized by presenting a noble hybrid approach for functional analysis.Keywords: Functional analysis, design reuse, functionalindexing and representation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 51834442 Distributed Detection and Optimal Traffic-blocking of Network Worms
Authors: Zoran Nikoloski, Narsingh Deo, Ludek Kucera
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Despite the recent surge of research in control of worm propagation, currently, there is no effective defense system against such cyber attacks. We first design a distributed detection architecture called Detection via Distributed Blackholes (DDBH). Our novel detection mechanism could be implemented via virtual honeypots or honeynets. Simulation results show that a worm can be detected with virtual honeypots on only 3% of the nodes. Moreover, the worm is detected when less than 1.5% of the nodes are infected. We then develop two control strategies: (1) optimal dynamic trafficblocking, for which we determine the condition that guarantees minimum number of removed nodes when the worm is contained and (2) predictive dynamic traffic-blocking–a realistic deployment of the optimal strategy on scale-free graphs. The predictive dynamic traffic-blocking, coupled with the DDBH, ensures that more than 40% of the network is unaffected by the propagation at the time when the worm is contained.Keywords: Network worms, distributed detection, optimaltraffic-blocking, individual-based simulation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14404441 Distributed Coordination of Connected and Automated Vehicles at Multiple Interconnected Intersections
Authors: Zhiyuan Du, Baisravan Hom Chaudhuri, Pierluigi Pisu
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In connected vehicle systems where wireless communication is available among the involved vehicles and intersection controllers, it is possible to design an intersection coordination strategy that leads the connected and automated vehicles (CAVs) travel through the road intersections without the conventional traffic light control. In this paper, we present a distributed coordination strategy for the CAVs at multiple interconnected intersections that aims at improving system fuel efficiency and system mobility. We present a distributed control solution where in the higher level, the intersection controllers calculate the road desired average velocity and optimally assign reference velocities of each vehicle. In the lower level, every vehicle is considered to use model predictive control (MPC) to track their reference velocity obtained from the higher level controller. The proposed method has been implemented on a simulation-based case with two-interconnected intersection network. Additionally, the effects of mixed vehicle types on the coordination strategy has been explored. Simulation results indicate the improvement on vehicle fuel efficiency and traffic mobility of the proposed method.
Keywords: Connected vehicles, automated vehicles, intersection coordination systems, multiple interconnected intersections, model predictive control.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 18554440 Profit Optimization for Solar Plant Electricity Production
Authors: Fl. Loury, P. Sablonière
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In this paper a stochastic scenario-based model predictive control applied to molten salt storage systems in concentrated solar tower power plant is presented. The main goal of this study is to build up a tool to analyze current and expected future resources for evaluating the weekly power to be advertised on electricity secondary market. This tool will allow plant operator to maximize profits while hedging the impact on the system of stochastic variables such as resources or sunlight shortage.
Solving the problem first requires a mixed logic dynamic modeling of the plant. The two stochastic variables, respectively the sunlight incoming energy and electricity demands from secondary market, are modeled by least square regression. Robustness is achieved by drawing a certain number of random variables realizations and applying the most restrictive one to the system. This scenario approach control technique provides the plant operator a confidence interval containing a given percentage of possible stochastic variable realizations in such a way that robust control is always achieved within its bounds. The results obtained from many trajectory simulations show the existence of a ‘’reliable’’ interval, which experimentally confirms the algorithm robustness.
Keywords: Molten Salt Storage System, Concentrated Solar Tower Power Plant, Robust Stochastic Model Predictive Control.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 19304439 Programmable Logic Controller for Cassava Centrifugal Machine
Authors: R. Oonsivilai, M. Oonsivilai, J. Sanguemrum, N. Thumsirirat, A. Oonsivilai
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Chaiyaphum Starch Co. Ltd. is one of many starch manufacturers that has introduced machinery to aid in manufacturing. Even though machinery has replaced many elements and is now a significant part in manufacturing processes, problems that must be solved with respect to current process flow to increase efficiency still exist. The paper-s aim is to increase productivity while maintaining desired quality of starch, by redesigning the flipping machine-s mechanical control system which has grossly low functional lifetime. Such problems stem from the mechanical control system-s bearings, as fluids and humidity can access into said bearing directly, in tandem with vibrations from the machine-s function itself. The wheel which is used to sense starch thickness occasionally falls from its shaft, due to high speed rotation during operation, while the shaft may bend from impact when processing dried bread. Redesigning its mechanical control system has increased its efficiency, allowing quality thickness measurement while increasing functional lifetime an additional 62 days.Keywords: Control system, Machinery, Measurement, Potato starch
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 21014438 Consumer Choice Determinants in Context of Functional Food
Authors: E. Grochowska-Niedworok, K. Brukało, M. Kardas
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The aim of this study was to analyze and evaluate the consumption of functional food by consumers by: age, sex, formal education level, place of residence and diagnosed diseases. The study employed an ad hoc questionnaire in a group of 300 inhabitants of Upper Silesia voivodship. Knowledge of functional food among the group covered in the study was far from satisfactory. The choice of functional food was of intuitive character. In addition, the group covered was more likely to choose pharmacotherapy instead of diet-related prevention then, which can be associated with presumption of too distant effects and a long period of treatment.Keywords: Consumer choice, consumer knowledge, functional food, healthy lifestyle.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10564437 Feature Analysis of Predictive Maintenance Models
Authors: Zhaoan Wang
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Research in predictive maintenance modeling has improved in the recent years to predict failures and needed maintenance with high accuracy, saving cost and improving manufacturing efficiency. However, classic prediction models provide little valuable insight towards the most important features contributing to the failure. By analyzing and quantifying feature importance in predictive maintenance models, cost saving can be optimized based on business goals. First, multiple classifiers are evaluated with cross-validation to predict the multi-class of failures. Second, predictive performance with features provided by different feature selection algorithms are further analyzed. Third, features selected by different algorithms are ranked and combined based on their predictive power. Finally, linear explainer SHAP (SHapley Additive exPlanations) is applied to interpret classifier behavior and provide further insight towards the specific roles of features in both local predictions and global model behavior. The results of the experiments suggest that certain features play dominant roles in predictive models while others have significantly less impact on the overall performance. Moreover, for multi-class prediction of machine failures, the most important features vary with type of machine failures. The results may lead to improved productivity and cost saving by prioritizing sensor deployment, data collection, and data processing of more important features over less importance features.
Keywords: Automated supply chain, intelligent manufacturing, predictive maintenance machine learning, feature engineering, model interpretation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 20164436 The Feedback Control for Distributed Systems
Authors: Kamil Aida-zade, C. Ardil
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We study the problem of synthesis of lumped sources control for the objects with distributed parameters on the basis of continuous observation of phase state at given points of object. In the proposed approach the phase state space (phase space) is beforehand somehow partitioned at observable points into given subsets (zones). The synthesizing control actions therewith are taken from the class of piecewise constant functions. The current values of control actions are determined by the subset of phase space that contains the aggregate of current states of object at the observable points (in these states control actions take constant values). In the paper such synthesized control actions are called zone control actions. A technique to obtain optimal values of zone control actions with the use of smooth optimization methods is given. With this aim, the formulas of objective functional gradient in the space of zone control actions are obtained.Keywords: Feedback control, distributed systems, smooth optimization methods, lumped control synthesis.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6184435 Forecasting for Financial Stock Returns Using a Quantile Function Model
Authors: Yuzhi Cai
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In this talk, we introduce a newly developed quantile function model that can be used for estimating conditional distributions of financial returns and for obtaining multi-step ahead out-of-sample predictive distributions of financial returns. Since we forecast the whole conditional distributions, any predictive quantity of interest about the future financial returns can be obtained simply as a by-product of the method. We also show an application of the model to the daily closing prices of Dow Jones Industrial Average (DJIA) series over the period from 2 January 2004 - 8 October 2010. We obtained the predictive distributions up to 15 days ahead for the DJIA returns, which were further compared with the actually observed returns and those predicted from an AR-GARCH model. The results show that the new model can capture the main features of financial returns and provide a better fitted model together with improved mean forecasts compared with conventional methods. We hope this talk will help audience to see that this new model has the potential to be very useful in practice.Keywords: DJIA, Financial returns, predictive distribution, quantile function model.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 16384434 Functional Food Knowledge and Perceptions among Young Consumers in Malaysia
Authors: G. Rezai, P.K.Teng, Z. Mohamed, M.N Shamsudin
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Changing in consumers lifestyles and food consumption patterns provide a great opportunity in developing the functional food sector in Malaysia. There is only a little knowledge about whether Malaysian consumers are aware of functional food and if so what image consumers have of this product. The objective of this research is to determine the extent to which selected socioeconomic characteristics and attitudes influence consumers- awareness of functional food. A survey was conducted in the Klang Valley, Malaysia where 439 respondents were interviewed using a structured questionnaire. The result shows that most respondents have a positive attitude towards functional food. For the binary logistic estimation, the results indicate that age, income and other factors such as concern about food safety, subscribing to cooking or health magazines, being a vegetarian and consumers who have been involved in a food production company significantly influence Malaysian consumers- awareness towards functional food.Keywords: Binary logistic model, functional foods, knowledge and awareness, perception
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 57874433 Evaluation of Environmental, Technical, and Economic Indicators of a Fused Deposition Modeling Process
Authors: M. Yosofi, S. Ezeddini, A. Ollivier, V. Lavaste, C. Mayousse
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Additive manufacturing processes have changed significantly in a wide range of industries and their application progressed from rapid prototyping to production of end-use products. However, their environmental impact is still a rather open question. In order to support the growth of this technology in the industrial sector, environmental aspects should be considered and predictive models may help monitor and reduce the environmental footprint of the processes. This work presents predictive models based on a previously developed methodology for the environmental impact evaluation combined with a technical and economical assessment. Here we applied the methodology to the Fused Deposition Modeling process. First, we present the predictive models relative to different types of machines. Then, we present a decision-making tool designed to identify the optimum manufacturing strategy regarding technical, economic, and environmental criteria.
Keywords: Additive manufacturing, decision-makings, environmental impact, predictive models.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 10684432 Effects of Functional Protein on Osteoblasts in Rat
Authors: Jie Sun, Guoyou Yin, Xianqing Zhang, Qiusheng She, Zhaohui Xie, Lanying Chen, Anfang Zhao
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To assess the effects of functional protein on osteoblast, Large quantity of high-purity osteoblasts had been cultivated successfully by adopting sequential enzyme digestion. The growth curve of osteoblasts was protracted by cell counting. Proliferation of osteoblasts was assessed by MTT colorimetry. The experimental results show the functional protein can enhance proliferation, the properties of adhesion and discuss the effect of osteopontin on osteoblast.
Keywords: functional protein, osteoblast, MTT
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12444431 Multiplicative Functional on Upper Triangular Fuzzy Matrices
Authors: Liu Ping
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In this paper, for an arbitrary multiplicative functional f from the set of all upper triangular fuzzy matrices to the fuzzy algebra, we prove that there exist a multiplicative functional F and a functional G from the fuzzy algebra to the fuzzy algebra such that the image of an upper triangular fuzzy matrix under f can be represented as the product of all the images of its main diagonal elements under F and other elements under G.Keywords: Multiplicative functional, triangular fuzzy matrix, fuzzy addition operation, fuzzy multiplication operation.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 12004430 Toward an Architecture of a Component-Based System Supporting Separation of Non- Functional Concerns
Authors: Jerzy Nogiec, Kelley Trombly-Freytag, Shangping Ren
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The promises of component-based technology can only be fully realized when the system contains in its design a necessary level of separation of concerns. The authors propose to focus on the concerns that emerge throughout the life cycle of the system and use them as an architectural foundation for the design of a component-based framework. The proposed model comprises a set of superimposed views of the system describing its functional and non-functional concerns. This approach is illustrated by the design of a specific framework for data analysis and data acquisition and supplemented with experiences from using the systems developed with this framework at the Fermi National Accelerator Laboratory.Keywords: Distributed system, component-based technology, separation of concerns, software development, supervisory and control, QoS
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 13424429 A Lactose-Free Yogurt Using Membrane Systems and Modified Milk Protein Concentrate: Production and Characterization
Authors: Shahram Naghizadeh Raeisi, Ali Alghooneh
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Using membrane technology and modification of milk protein structural properties, a lactose free yogurt was developed. The functional, textural and structural properties of the sample were evaluated and compared with the commercial ones. Results showed that the modification of protein in high fat set yogurt resulted in 11.55%, 18%, 20.21% and 7.08% higher hardness, consistency, water holding capacity, and shininess values compared with the control one. Furthermore, these indices of modified low fat set yogurt were 21.40%, 25.41%, 28.15% & 10.58% higher than the control one, which could be related to the gel network microstructural properties in yogurt formulated with modified protein. In this way, in comparison with the control one, the index of linkage strength (A), the number of linkages (z), and time scale of linkages (λrel) of the high fat modified yogurt were 22.10%, 50.68%, 21.82% higher than the control one; whereas, the average linear distance between two adjacent crosslinks (ξ), was 16.77% lower than the control one. For low fat modified yogurt, A, z, λrel, and ξ indices were 34.30%, 61.70% and 42.60% higher and 19.20% lower than the control one, respectively. The shelf life of modified yogurt was extended to 10 weeks in the refrigerator, while, the control set yogurt had a 3 weeks shelf life. The acidity of high fat and low fat modified yogurts increased from 76 to 84 and 72 to 80 Dornic degrees during 10 weeks of storage, respectively, whereas for control high fat and low fat yogurts they increased from 82 to 122 and 77 to 112 Dornic degrees, respectively. This behavior could be due to the elimination of microorganism’s source of energy in modified yogurt. Furthermore, the calories of high fat and low fat lactose free yogurts were 25% and 40% lower than their control samples, respectively. Generally, results showed that the lactose free yogurt with modified protein, despite of 1% lower protein content than the control one, showed better functional properties, nutritional properties, network parameters, and shelf stability, which could be promising in the set yogurt industry.
Keywords: Lactose free, low calorie, network properties, protein modification.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2804428 GA Based Optimal Feature Extraction Method for Functional Data Classification
Authors: Jun Wan, Zehua Chen, Yingwu Chen, Zhidong Bai
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Classification is an interesting problem in functional data analysis (FDA), because many science and application problems end up with classification problems, such as recognition, prediction, control, decision making, management, etc. As the high dimension and high correlation in functional data (FD), it is a key problem to extract features from FD whereas keeping its global characters, which relates to the classification efficiency and precision to heavens. In this paper, a novel automatic method which combined Genetic Algorithm (GA) and classification algorithm to extract classification features is proposed. In this method, the optimal features and classification model are approached via evolutional study step by step. It is proved by theory analysis and experiment test that this method has advantages in improving classification efficiency, precision and robustness whereas using less features and the dimension of extracted classification features can be controlled.Keywords: Classification, functional data, feature extraction, genetic algorithm, wavelet.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 15624427 Optimal Control of Piezo-Thermo-Elastic Beams
Authors: Marwan Abukhaled, Ibrahim Sadek
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This paper presents the vibrations suppression of a thermoelastic beam subject to sudden heat input by a distributed piezoelectric actuators. An optimization problem is formulated as the minimization of a quadratic functional in terms of displacement and velocity at a given time and with the least control effort. The solution method is based on a combination of modal expansion and variational approaches. The modal expansion approach is used to convert the optimal control of distributed parameter system into the optimal control of lumped parameter system. By utilizing the variational approach, an explicit optimal control law is derived and the determination of the corresponding displacement and velocity is reduced to solving a set of ordinary differential equations.
Keywords: Optimal control, Thermoelastic beam, variational approach, modal expansion approach
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 14234426 Solving the Flexible Job Shop Scheduling Problem with Uniform Processing Time Uncertainty
Authors: Nasr Al-Hinai, Tarek Y. ElMekkawy
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The performance of schedules released to a shop floor may greatly be affected by unexpected disruptions. Thus, this paper considers the flexible job shop scheduling problem when processing times of some operations are represented by a uniform distribution with given lower and upper bounds. The objective is to find a predictive schedule that can deal with this uncertainty. The paper compares two genetic approaches to obtain predictive schedule. To determine the performance of the predictive schedules obtained by both approaches, an experimental study is conducted on a number of benchmark problems.
Keywords: Genetic algorithm, met-heuristic, robust scheduling, uncertainty of processing times
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 28794425 Hyers-Ulam Stability of Functional Equationf(3x) = 4f(3x − 3) + f(3x − 6)
Authors: Soon-Mo Jung
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The functional equation f(3x) = 4f(3x-3)+f(3x- 6) will be solved and its Hyers-Ulam stability will be also investigated in the class of functions f : R → X, where X is a real Banach space.Keywords: Functional equation, Lucas sequence of the first kind, Hyers-Ulam stability.
Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1360