Decomposition-based qualitative experiment design algorithms for a class of compartmental models
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Identifiability
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Design of experiments
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Qualitative analysis
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Chemometrics is described in general as to extract the more useful information from the chemical data obtained experimentally by various methods applying some mathematical techniques to these data. Today, studies in many fields such as chemistry, biochemistry, earth, and environmental sciences are done experimentally and all analysis of semi-finished and finished products or raw materials for quality control are carried out in the laboratories. Establishment of test strategies for experimental design, analysis of experimental design models and optimization of the experimental factors of a reaction selected as a practical application for experimental design are the main subjects of this study. Here it was summarized creation of experiment strategies in order to optimize the effective operation factors on chemical reactions, mathematical solution techniques of the response surface functions to define the relationships between the factors and the experimental result affected by the factors, computer programing for the optimization of the reaction parameters and usage of some related software, statistically evaluation for the experimental results and optimization of a selected reaction as an experimental design application.
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The reliability of experimental devices directly impacts the quality of experimental teaching in colleges and universities.In order to understand the status of the operation of experimental devices,a novel method is presented from the perspective of quality management by bringing the experimental teaching devices into the category of Measurement System Analysis and analyzing them with the DOE.According to the principle of the DOE,by using the statistical tool,the experiments are designed in the measurement system,the testing data is collected and analyzed,the significant factors are identified by confirmation operations,and the reliability of experimental devices is analyzed.The application of the DOE in the reliability analysis of sensor measurement system shows that DOE is a practical method in laboratories of colleges and universities with the advantages of getting the maximum useful knowledge with a relatively few number of experimental operations to find out the best operation condition.
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A design of an experiment is generally to fictionalize an execution of an experimental process and the term of experimental design strategy usually refers to a two-stage modeling. The first of all named as working strategy is the determination of the experimental execution model and the last one is that a mathematical model for response surface function to define the relationship between the experimental factors. In this work, it was selected optimization of assay conditions for t-RNA using Central Composite Design, the influence of three factors, namely pH, enzyme concentration and amino acid concentration as an experimental design application, and improved an experiment strategy in order to optimize the effective operation factors on this chemical reaction and mathematical solution techniques of the response surface function. As examining of the coefficients of the response surface equation and its graphics, we can say that the most effective parameter on the esterification process is enzyme concentration alone and together with pH.
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In order to build the mathematic model between the roughness of the micro-hole internal surface and various influencing factors, this paper employs the response surface method for analysis and research, because the response surface method is the most frequently-used statistical method to solve multi-variable problems directly and comprehensively. Besides, it can reflect the interaction between various factors, and its analysis of the experimental data is more clear and reasonable. Box-Benhnken Design (BBD) is an experimental design plan commonly adopted by the response surface method. BBD is usually used for the analysis and evaluation of the nonlinearity between three to seven influencing factors and evaluation indexes. It can predict all the major effects and the bidirectional interaction effects. Compared with the orthogonal experiment, it features stronger randomness and complete experimental data. The relationship between the response value and the fitting factors obtained through the latter is also more reliable. Based on the above advantages, this paper adopts BBD as the experimental plan.
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This research is focused on the hydrodynamic behaviour of a series of hull forms for an underwater vehicle, which includes a range of length-to-diameter ratios. Experimental data were gathered for several standard manoeuvring experiments and a reverse Design Of Experiment (DOE) was applied to the available data. From the DOE point of view, the effects of the main factors in each type of experiment were studied and an appropriate Response Surface Model (RSM) was fitted to the data. The developed empirical model is very useful in predicting the non-dimensional hydrodynamic force and moment coefficients, which is a major step in simulating the motion of an underwater vehicle
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Design of experiments
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Experimental research is a method suitable for intentionally creating the environment desired by the researcher and revealing the causal relationship between variables. The characteristics of these experimental studies are being utilized in the CPTED field to overcome the survey's limitations. However, there are few cases of experimental research conducted in domestic CPTED experimental research compared to other fields. And most of the simple experimental designs(pre-experimental design) are performed, so the design is insufficient. In addition, some studies have limitations that are difficult for subsequent researchers to apply because the experimental design and process do not appear in detail. Therefore, this study recognized the necessity of an effective experimental research system, and the concept of experimental research and the experimental design of previous studies were considered. Finally, the experimental design of the previous study was supplemented through the analysis results.
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In this paper, based on factorial design of experiments method (DoE), predictive model and surface response analysis methodology was used for studying, modeling, characterizing and optimizing the parameters of a mono-crystalline photovoltaic (PV) panel behavior considering the interactive effects of two variables surface PV cell temperature and solar irradiation levels. The DoE concept allows finding the predictive model of each parameter behavior that uses the experimental data. It enables accurate predictions of the responses according to input factors variations. This contribution evaluates the output parameters by predicting these mathematical models of the three responses of a mono-crystalline PV panel: the maximum power Pm, the short-circuit current Isc and the open circuit voltage Voc as function of the influences of both input parameter factors: illumination and temperature. In addition, to validate the results of the DoE predictive models, the surface response and the contour curves analysis were used to bring out the optimum of each response in each operating point covering the domain of the study by the use of a script developed under Minitab is deduced. The obtain results are compared with experimental data.
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