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Öğe Comparison of control algorithms for the blood glucose concentration in a virtual patient with an artificial pancreas(Elsevier, 2012) Semizer, E.; Yuceer, M.; Atasoy, I.; Berber, R.To obtain the most suitable control algorithm for a wearable artificial pancreas, different control algorithms were compared and tested using a Hovorka model. Model predictive control (MPC), linear and nonlinear model forms, proportional integral derivative control (PID), neural-network-based model predictive control (NN-MPC), nonlinear autoregressive moving average (NARMA-L2) and sequential quadratic programming (SQP) were evaluated using the Hovorka model. Due to the fact that modeling of biomedical processes are very complex, to present the most effective control algorithm, various control strategies were needed to application. In the control algorithms, set point tracking and disturbance rejection were performed. With respect to the rise times of the control algorithms, SQP with optimal control had the shortest time, and NARMA-L2 had the longest time. Because the control algorithm connects the glucose meter and the insulin pump in an artificial pancreas, the rise time is the most important parameter. We propose that optimal control with SQP is the most suitable control algorithm to connect the glucose meter and the insulin pump. (C) 2011 The Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.Öğe Comparison of Modeling Approaches for Prediction of Cleaning Efficiency of the Electromagnetic Filtration Process(Applied Computational Electromagnetics Soc, 2011) Yildiz, Z.; Yuceer, M.; Abbasov, T.The present study aims at applying different methods for predicting the cleaning efficiency of the electromagnetic filtration process (psi) in the mixtures of water and corrosion particles (rust) of low concentrations. In our study, artificial neural network (ANN), multivariable least square regression (MLSR), and mechanistic modelling approaches were applied and compared for prediction of the cleaning efficiency for the electromagnetic filtration process. The results clearly show that the use of ANN led to more accurate results than the mechanistic filtration and MLSR models. Therefore, it is expected that this study can be a contribution to the cleaning efficiency.Öğe AN INTERACTIVE GIS-BASED SOFTWARE FOR DYNAMIC MONITORING OF RIVERS(Scibulcom Ltd, 2014) Yetik, M. K.; Yuceer, M.; Karadurmus, E.; Semizer, E.; Calimli, A.; Berber, R.Water quality research and development attempts have been the most valuable resources in the sense of model calibration and verification techniques. Due to the fact that current degree of pollution in rivers and importance of the sustainable water resources management, the interactive river monitoring becomes inevitable. Within the scope of river water quality monitoring, Geographical Information Systems (GIS) are gaining widespread acceptance besides this fast and reliable water quality models and parameter estimation techniques are becoming available. However, integrating water quality models with GIS is limited in literature. This study presents an integrated platform on which ArcMap as a GIS and a water quality model in MATLAB are brought together in an interactive and user friendly manner. The software provides a considerable developments in future real time river monitoring and environmental pollution assessment.Öğe MODELING WATER QUALITY IN RIVERS: A CASE STUDY OF BEYLERDERESI RIVER IN TURKEY(Corvinus Univ Budapest, 2016) Yuceer, M.; Coskun, M. A.River pollution is a major environmental problem that has negative consequences for humans and wildlife alike. To prevent its consequences, the sources and severity of pollution must be determined by monitoring water quality in river basins, followed by the measures necessary to control the contamination. Models and computer simulation of water quality are important tools for predicting adverse effects of pollution along a stream, and they can help guide practical investments in stream health. In water quality models, parameters that are determined through optimization rather than through trial and error are required to ensure the reliability of the model. In this study, a continuous stirred tank reactor (CSTR) approach was used to model Beylerderesi stream as a dynamic model, and the kinetic parameters were determined through optimization. For the optimization step, the Sequential Quadratic Programming method was used. The model predictions indicated good agreement with experimental data. The Mean Absolute Percentage error values for dissolved oxygen and biochemical oxygen demand were calculated as 0.95 % and 1.39 %, respectively. Statistical analysis showed differences between river and effluent samples for all parameters measured.Öğe Optimization of Electromagnetic Filtration Variables Using a Nelder-Mead Simplex Method(Taylor & Francis Inc, 2011) Yildiz, Z.; Sener, E.; Yuceer, M.In this study, we aimed at optimizing the parameters that govern the separation efficiency in the electromagnetic filtration (EMF) of magnetizable dispersed particles from a water medium. Thus, we employed a Nelder-Mead modified simplex algorithm to maximize EMF efficiency choosing the external magnetic field strength, size of the filter matrix elements, filter length, and filtration velocity as variables to be optimized. It has been found that EMF efficiency decreased with increasing the filtration velocity and the size of the filter matrix elements. On the other hand, EMF efficiency increased when the filter length and the external magnetic strength was increased. Four variables were successfully optimized and a maximum level of EMF efficiency percentage of 77.05 was achieved by performing only 26 experiments. The results are expected to be useful in the future to predict the operating conditions of similar EMF systems.Öğe OPTIMIZATION OF HYDRODISTILLATION OF ESSENTIAL OIL FROM MENTHA SPICATA L. BY USING RESPONSE SURFACE METHODOLOGY(Plapiqui(Uns-Conicet), 2023) Karakaplan, N.; Goz, E.; Tosun, E.; Yuceer, M.This study was conducted to optimize the hydrodistillation process of Mentha spicata L. essential oil using the response surface methodology. The optimal values of operating parameters (independent variables) such as extraction time (100-240 min) and water volume to plant mass ratio (0.055-0.120) were investigated using a central composite design, which led to only 13 experiments. The response variables were selected based on the highest essential oil yield as well as the carvone ratio, which is the main component of the essential oil. The experimental data were fitted to a linear model for essential oil yield and a modified quadratic model for the carvone ratio. The hydrodistillation time and water volume to plant mass ratio have significant effects (p<0.05) on both the essential oil yield and the carvone ratio. The optimal conditions were identified as 145.7 min of extraction time and a 0.105 ml/g water volume to plant mass ratio by the 3D response surface and the contour plots derived from the models. At these predicted conditions, the essential oil yield and carvone ratio were calculated to be 1.383% and 28.541%, respectively. The findings indicate that the response surface approach can be used successfully in the hydrodistillation of Mentha spicata L.Öğe Optimization of proteolysis and angiotensin converting enzyme inhibition activity in a model cheese using response surface methodology(Elsevier Science Bv, 2019) Sahingil, D.; Gokce, Y.; Yuceer, M.; Hayaloglu, A. A.Adjunct cultures including lactobacilli play important role in cheese proteolysis and bioactivity including Angiotensin Converting Enzyme (ACE)-inhibition and antioxidant activity. Four species of lactobacilli was used in the manufacture of model cheese and these were salted at different levels and the resultant cheeses were ripened at different time and temperature to understand the effect of salting and ripening conditions. The effects of the use of various of lactobacilli (Lactobacillus casei, Lb. helveticus, Lb. delbrueckii ssp. bulgaricus and Lb. plantarum), salt concentrations (1, 2, 3, 4 and 5%), ripening times (1, 30, 60, 90 and 120 days) and temperatures (5, 10, 15 and 20 degrees C) were investigated. The experiments were designed to determine the optimal salt concentration, ripening times and temperatures for optimal proteolysis, the highest levels of ACE-inhibition and antioxidant activity. The highest level of proteolysis and ACE-inhibiting activity in the model cheese was observed when ripening temperatures were between 8 and 16 degrees C, salt concentration at 2.5-3.0% and with a ripening period of about 60 days. The use of each lactobacilli contributed to the proteolysis in different manner; for example, ACE-inhibiting activity and antioxidant activity in the model cheese.Öğe A parameter identifiability and estimation study in Yesilirmak River(Iwa Publishing, 2009) Berber, R.; Yuceer, M.; Karadurmus, E.Water quality models have relatively large number of parameters, which need to be estimated against observed data through a non-trivial task that is associated with substantial difficulties. This work involves a systematic model calibration and validation study for river water quality. The model considered was composed of dynamic mass balances for eleven pollution constituents, stemming from QUAL2E water quality model by considering a river segment as a series of continuous stirred-tank reactors (CSTRs). Parameter identifiability was analyzed from the perspective of sensitivity measure and collinearity index, which indicated that 8 parameters would fall within the identifiability range. The model parameters were then estimated by an integration based optimization algorithm coupled with sequential quadratic programming. Dynamic field data consisting of major pollutant concentrations were collected from sampling stations along Yesilirmak River around the city of Amasya in Turkey, and compared with model predictions. The calibrated model responses were in good agreement with the observed river water quality data, and this indicated that the suggested procedure provided an effective means for reliable estimation of model parameters and dynamic simulation for river streams.Öğe A SOFTWARE FOR PARAMETER ESTIMATION IN DYNAMIC MODELS(Brazilian Soc Chemical Eng, 2008) Yuceer, M.; Atasoy, I.; Berber, R.A common problem in dynamic systems is to determine parameters in an equation used to represent experimental data. The goal is to determine the values of model parameters that provide the best fit to measured data, generally based on some type of least squares or maximum likelihood criterion. In the most general case, this requires the solution of a nonlinear and frequently non-convex optimization problem. Some of the available software lack in generality, while others do not provide ease of use. A user-interactive parameter estimation software was needed for identifying kinetic parameters. In this work we developed an integration based optimization approach to provide a solution to such problems. For easy implementation of the technique, a parameter estimation software (PARES) has been developed in MATLAB environment. When tested with extensive example problems from literature, the suggested approach is proven to provide good agreement between predicted and observed data within relatively less computing time and iterations.
