Current Issue : July - September Volume : 2014 Issue Number : 3 Articles : 6 Articles
Developing a suitable nonlinear model is the most challenging problem in the application of nonlinear model based controllers\nto distillation column. Hammerstein model consists of a nonlinear static element described by wavenet based nonlinear function,\nfollowed by a linear dynamic element described by the Output Error(OE) model was used in this study to represent the nonlinear\ndynamics of the distillation column. The model parameters were identified using iterative prediction-error minimization method.\nThe model validation results proved that the Hammerstein model was capable of capturing the nonlinear dynamics of distillation\ncolumn....
Rainfall-runoff simulation in hydrology using artificial intelligence presents the nonlinear relationships using neural networks. In\nthis study, a hybrid network presented as a feedforward modular neural network (FF-MNN) has been developed to predict the\ndaily rainfall-runoff of the Roodan watershed at the southern part of Iran. This FF-MNN has three layersââ?¬â?input, hidden, and\noutput.The hidden layer has two types of neural expert or module. Hydrometeorological data of the catchment were collected for\n21 years. Heuristic method was used to develop the MNN for exploring daily flow generalization. Two training algorithms, namely,\nbackpropagation with momentum and Levenberg-Marquardt, were used. Sigmoid and linear transfer functions were employed\nto explore the networkââ?¬â?¢s optimum behavior. Cross-validation and predictive uncertainty assessments were carried out to protect\novertiring and overparameterization, respectively. Results showed that the FF-MNN could satisfactorily predict streamflow during\ntesting period. The Nash-Sutcliff coefficient, coefficient of determination, and root mean square error obtained usingMNN during\ntraining and test periods were 0.85, 0.85, and 39.4 and 0.57, 0.58, and 32.2, respectively.The predictive uncertainties for both periods\nwere 0.39 and 0.44, respectively. Generally, the study showed that the FF-MNN can give promising prediction for rainfall-runoff\nrelations....
Devices used for glucose measurement are generally realized by the use of electrochemical detection methods. In this paper, MEMS (micro electro mechanical systems) capacitive glucose sensor measures glucose molecule’s concentration in the human blood sample through detection of capacitance generated in the fixed beam structure due to variation in the displacement of upper beam which is directly proportional to the weight of glucose accumulated over the beam. Glucose is accumulated over the beam by its reaction with the glucose sensing polymer PHEAA-ran-PAAPBA [poly (N – hydroxyethylacrylamide – ran – 3 - acrylamidophenylboronicacid)] considered over the beam. The other beam with reference polymer PAA (polyacrylamide) over it is neutral to the glucose molecule is used to get the differential value of the capacitance for more accurate results. The differential capacitance is taken into consideration for effective rejection of environmental interferences such as osmotic pressure, variation in temperature, changes in acceleration due to gravity at different altitudes. Fixed beams can be used in measuring glucose from blood samples by invasive technique and by urine sample for non-invasive technique under consideration. The simulation results of the sensor are presented using coventor and comsol software. The sensitivity of this sensor has been increased/ optimized by varying sensor parameters like the material of the beam, distance between the two electrodes or surfaces of the beam, increasing the surface area of electrode and proper selection of the polymers....
Thestudy of free-surface and pressurized water flows in channels has many interesting application, one of the most important being\nthemodeling of the phenomena in the area of natural water systems (rivers, estuaries) aswell as in that of man-made systems (canals,\npipes). For the development ofmajor river engineering projects, such as flood prevention and flood control, there is an essential need\nto have an instrument that be able to model and predict the consequences of any possible phenomenon on the environment and\nin particular the new hydraulic characteristics of the system. The basic equations expressing hydraulic principles were formulated\nin the 19th century by Barre de Saint Venant and Valentin Joseph Boussinesq. The original hydraulic model of the Saint Venant\nequations is written in the form of a system of two partial differential equations and it is derived under the assumption that the\nflow is one-dimensional, the cross-sectional velocity is uniform, the streamline curvature is small and the pressure distribution is\nhydrostatic. The St. Venant equations must be solved with continuity equation at the same time. Until now no analytical solution\nfor Saint Venant equations is presented. In this paper the Saint Venant equations and continuity equation are solved with homotopy\nperturbation method (HPM) and comparison by explicit forward finite difference method (FDM). For decreasing the present error\nbetween HPM and FDM, the st.venant equations and continuity equation are solved by HAM. The homotopy analysis method\n(HAM) contains the auxiliary parameter ? that allows us to adjust and control the convergence region of solution series.The study\nhas highlighted the efficiency and capability of HAMin solving Saint Venant equations andmodeling of unsteady flow through the\nrectangular canal that is the goal of this paper and other kinds of canals....
A software framework is an architecture or infrastructure intended to enable the integration and interoperation of software\ncomponents. Specialized types of software frameworks are those specifically intended to support the composition ofmodels or other\ncomponents within a simulation system. Such frameworks are intended to simplify the process of assembling a complex model or\nsimulation system from simpler component models as well as to promote the reuse of the component models. Several different\ntypes of software frameworks for model composition have been designed and implemented; those types include common library,\nproduct line architecture, interoperability protocol, object model, formal, and integrative environment. The various framework\ntypes have different components, processes for composingmodels, and intended applications. In this survey the fundamental terms\nand concepts of software frameworks for model composition are presented, the different types of such frameworks are explained\nand compared, and important examples of each type are described....
The key for adopting the utilization-based schedulability test is to derive the utilization bound. Given the computation times,\nthis paper proposes two utilization bound algorithms to derive interrelease times for nonpreemptive periodic tasks, using a new\npriority scheme, ââ?¬Å?RateMonotonic Algorithm-Shortest Job First.ââ?¬ÂThe obtained task set possesses the advantage of RateMonotonic\nAlgorithm and Shortest Job First priority scheme. Further, the task set is tested for schedulability, by first deriving a general\nschedulability condition from ââ?¬Å?problem windowââ?¬Â analysis and, a necessary and sufficient schedulability condition for a task to\nbe scheduled, at any release time are also derived. As a technical contribution, success ratio and effective processor utilization are\nanalyzed for our proposed utilization bound algorithms on a uniprocessor architecture modeled using UML-RT....
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