MS, University of Cincinnati, 2004, Engineering : Computer Engineering

Improved performance estimation methods hold the key for automated synthesis of analog and mixed signal circuits. Macro models provide one such fast and efficient method to estimate the performance charecteristics of a circuit. Many macro modelling methods such as table look up methods, nueral network based methods, convex geometric programming methods have been used so far. In this thesis, we build macro models using a table look up method and two basic numerical analysis techniques, the multiple regression and the multivariate cubic spline interpolation. Macro modelling can be viewed as a two step process. The first step is, the generation of charecterization data and the next step is, the generation of macro models from charecterization data. In the first step, an initial set of values of design variables for any given analog circuit is chosen. A simulation of the transistor netlist is done with the initial values and various parameters are calculated. These values are tabulated. This process is repeated till a user specified upper bound for each of the variables is reached. This accomplishes the generation of charecterization data. In the next step, the charecterization data is evaluated using multivariate numerical techniques and a macro model for each of the performance parameters is extracted. In an alternative method, the charecterization data is searched for a set of design values using a table look up method and the performance parameters corresponding to this set of design variables are returned. The evaluation time for a macro model is much shorter than the normal simulators such as HSPICE and SPECTRE. Also, the accuracy of macro models is almost the same as the simulators. Hence,these models can be easily incorporated in to any circuit synthesis algorithm or architecture generation algorithm to optimize the cost function based on performance constraints. Also, this thesis presents the application of regression models, spline models and the table look up (open full item for complete abstract)

Committee: Dr. Ranga Vemuri (Advisor) Subjects:

Doctor of Philosophy, The Ohio State University, 2021, Educational Studies

Students' value for mathematics often declines, especially in the middle school years. Value, however, and expectations of success are predictors of performance and achievement in mathematics. To improve performance, we need to influence students' beliefs about the value of mathematics and their expectations that they can be successful. Digital mathematics curriculum that incorporates authenticity, interactivity, and ease of use may influence utility value beliefs and expectations, which may lead to higher application knowledge. For this study, a quantitative research methodology was employed. Surveys were used to determine students' perceptions of digital curriculum, their utility value beliefs about mathematics and their expectations of success in mathematics along with post-test measures to determine students' mathematical performance. Using path analysis, this study found that authentic and easy to use curriculum is related to students' utility value and expectations of success, and that higher expectations of success predict higher performance on assessments of application knowledge. This study makes a contribution to the literature by highlighting the importance of utility value and expectancies interventions through the use of digital curriculum.

Committee: Kui Xie (Advisor); Azita Manouchehri (Committee Member); Minjung Kim (Committee Member) Subjects: Curriculum Development; Education; Educational Psychology; Educational Technology; Mathematics Education

Doctor of Philosophy, Case Western Reserve University, 2019, EMC - Mechanical Engineering

Redox flow batteries with flow field designs have been demonstrated to boost their capacities to deliver high current density in medium and large-scale energy storage applications. Nevertheless, the fundamental mechanisms involved with improved current density in flow batteries with serpentine flow field designs have been not fully understood. In this dissertation work, one-dimensional (1D) analytical model, two-dimensional (2D) numerical model with scaling analysis, and three-dimensional (3D) model of a serpentine flow field over the porous carbon paper electrodes have been developed to examine the distributions and amounts of pressure driven electrolyte flow penetrations into the porous carbon paper electrodes. It was found that the electrolyte flow penetrations are strongly under-estimated by 1D analytical model and 2D numerical model. The scaling analysis also demonstrates that the flow penetrations enhanced by the adjacent flow channels are significant, and were not able to be incorporated in the 1D and 2D models. The 3D model accounts the effects of landings/ribs bridged between the adjacent flow channels on flow penetrations and better calculates the amount of flow penetrations into the porous carbon paper electrodes. It was also found that the flow penetrations are sensitive to the properties of the porous electrode, i.e. permeability and porosity, a smaller permeability or porosity results in a much smaller flow penetration. The model is used to estimate the maximum current densities associated with the stoichiometric availability of electrolyte reactant flow penetrations through the porous carbon paper electrodes. The modeling results match reasonably well observed experimental data without using any adjustable parameters. This fundamental work on electrolyte flow distributions of limiting reactant availability will contribute to a better understanding of limits on electrochemical performance in flow batteries with serpentine flow field designs and should (open full item for complete abstract)

Committee: Robert Savinell (Advisor); Joseph Prahl (Advisor); Jesse Wainright (Advisor); Paul Barnhart (Committee Chair); Sunniva Collins (Committee Member); James T'ien (Committee Member) Subjects: Applied Mathematics; Chemical Engineering; Energy; Fluid Dynamics; Mechanical Engineering; Physics

PHD, Kent State University, 2016, College of Education, Health and Human Services / School of Lifespan Development and Educational Sciences

The purpose of this quantitative study examined the effects a classroom blog had on student performance in the area of conceptual and procedural understandings of fractions. Specifically, the study examined the effects of self-explaining with a peer (explain, justify, and argumentation) to the solving of traditional paper pencil mathematical tasks alone (solving on your own). The experimental groups (i.e. face-to-face and blog groups) solved identical mathematical tasks to the traditional alone group by explaining their solution through justification with evidence from the task by self-explaining with peers. Both experimental groups engaged in mathematical discourse by explaining and justifying their understandings, as well as critiquing and arguing the thinking of other student responses through self-explaining with peers; however, one group used a multimedia tool. This quasi-experimental design study further explored how interactive and constructive mathematical discourse (i.e. explanation, justification, and argumentation) through a classroom blog supported student performance of fifth-grade students on conceptual and procedural fraction knowledge and the retention of this knowledge over time. To measure the change in student performance, a pretest- posttest, and delayed posttest was administered to measure the conceptual and procedural knowledge of fractions. Participants included 134 fifth grade students, ages 9-11 years old. Data collection was analyzed using repeated measures ANOVA with one between –subjects factor.

Committee: Bradley Morris PHD (Committee Co-Chair); Richard Ferdig PHD (Committee Co-Chair); Karl Kosko PHD (Committee Member) Subjects: Educational Psychology; Educational Technology; Elementary Education; Mathematics Education; Middle School Education

Doctor of Philosophy (PhD), Ohio University, 2001, Chemical Engineering (Engineering)

The purposes of this study are to develop a process to analyze fatty acids in recombinant animal cells using reversed-phase chromatography and simulate liquid chromatography processes using the general rate model. A method was developed for the separation and analysis of various fatty acids in recombinant animal cells. The cell sample was saponified with 0.5M NaOH in 96% ethanol and then extracted with acidified ethyl acetate. After extraction, the sample was dried and dissolved in HPLC-grade methanol. After centrifugation to remove insoluble impurities, the sample was applied to a C18 RP-HPLC column to separate and identify fatty acids using a gradient ACN-H 2O mobile phase. The fatty acids were monitored by measuring ultraviolet light absorption at 195 nm and identified by retention time and adsorption spectrum comparison. This method successfully resolves these fatty acids and can be used either analytically or preparatively. The fatty acids separation and analysis process developed in this work can be adapted to quantitatively analyze fatty acids from others sources. The general rate model was used to simulate liquid chromatography processes. Two kinds of liquid chromatography processes were studied: size exclusion chromatography and reverse-phase chromatography. The effects of various parameters were analyzed using the mathematical model. Methods to estimate the model parameters and the procedures using the general rate model to simulate and predict the results of these two types of chromatography process were developed. For SEC, the particle tortuosity was used as an adjustable parameter while, for RP-HPLC, the eluite-modulator relationship parameter α was used as an adjustable parameter. The values of these two parameters were obtained by matching the model-predicted results and experimental results using trial and error method. The validity of these two simulation procedures was verified by the comparison between the model predictions and the experimental re (open full item for complete abstract)

Committee: Tingyue Gu (Advisor) Subjects: Engineering, Chemical