The purpose of this concurrent mixed methods study was to investigate the impact on high school students' knowledge and attitudes regarding astronomy and beliefs about the nature of science after participating in an extended authentic, inquiry-oriented, research experience studying variable stars using a specifically designed curriculum guide "In the Hunt for Variable Stars." The study gathered quantitative data using a pretest posttest strategy on a modified form of an existing questionnaire called Students Attitudes Toward Astronomy and four student-supplied response content surveys. Qualitative methods included analysis of researcher's field notes, naturalistic observations, formal interviews, and students' artifacts. The methods and results of this study provided important baseline information to measure cognitive and affective changes resulting from an authentic scientific research experience for high school students.Ninety students participated in a targeted instructional sequence and their attitudes and knowledge were compared to 50 students in a comparable science course who were not provided an authentic research experience. The results obtained in this study strongly suggest that participation in research is successful at significantly increasing content knowledge. All four content surveys showed statistically significant increases for students in the intervention group as compared to the students in the non-intervention group. Qualitative results demonstrated that both groups of students initially held naïve ideas about science and astronomy. After participation in the intervention, the most dramatic changes were observed in students' understanding of astronomy content. No substantial change was seen in students' attitudes toward Astronomy and science but there is evidence of some limited impacts on beliefs regarding the nature of science.In combination, the data resulting from this mixed-method study lend considerable weight to claim in contemporary science education reform that students will learn and more scientifically accurate knowledge of astronomy after participating in authentic inquiry experiences.

As many variable pricing projects are still in the implementation stage, long-run driver responses to the variable tolls are largely unknown. This research examined the long-run changes in driver behavior in an existing variable pricing project in Lee County, Florida. Using empirical evidence, it was found that over time the price elasticities of demand on the Lee County toll bridges have decreased from -0.42 to - 0.11 (Midpoint Memorial Bridge) and from -0.31 to -0.06 (Cape Coral Bridge) during the early morning discount period. The elasticities have decreased, but to a lesser extent, during the late morning and early afternoon discount periods. A discount period volume spreading ratio was also developed to analyze these changes. The results from this analysis confirmed the elasticity results. In addition to the empirical analysis of travel patterns discussed above, a telephone survey of drivers was conducted. The survey results indicated that certain driver characteristics such as higher frequency of trips, commute trip purpose, full-time employment status, more people in the household, higher education, and age between 25-34 years, were all indicators that the participant may increase his or her variable pricing usage over time. Other characteristics, including being retired and having a household income less than $16,000, were indicators that the driver may not increase variable pricing participation. Binary logit and semiparametric models were also developed to examine socio-economic and commute characteristics that may influence a driver increasing his or her participation in a variable pricing program. The results from these two variable toll bridges in Lee County indicated a decrease in variable toll price elasticity over time. However, these results may not be typical for variable pricing projects. Factors such as alternative routes, different traveler demographics, traffic congestion levels, and size of the toll discount may influence the results obtained from other variable pricing projects. However, the methodology developed in this research can be applied to other projects in order to determine those toll price elasticities of demand.

This thesis is an effort to develop generalized dynamic models for systems with time-varying time delays. Unlike the simple time-delay model characterized by a transportation lag in the case of a fixed time delay, time-varying delays exhibit quite different characteristics, making the development of easy to use models a difficult endeavor. First an algorithm is developed to predict the actual input-output behavior when the input signal is directly fed into a device that characterizes the time-varying delay. Input-output behaviour generated with this algorithm serves as the truth model for subsequent approximate model development. Simulation results for different classes of delay and different inputs were obtained using the truth model. The input functions were limited to steps, ramps and sinusoids. This limited class of inputs and delays defines the scope of this thesis and the results are to be interpreted as such. The methodology adopted to identify the basic underpinnings of models was system identification where input-output data came from the truth model. Models for the aforementioned classes of inputs and delays were then derived using elementary system identification tools. These models were then carefully analyzed to extract trends by changing the delay parameter. A satisfactory trend was observed in the case of linearly varying time delay. A generalized model for the linearly varying time delay with step and polynomial inputs was developed. An attempt was also made at developing a generalized model for sinusoidally time-varying time delays. This study proposes a model for linearly time-varying time delay, whose structure is not surprisingly also dependent on the class of inputs. It is shown that the derived model reduces to the well known model in the case of a fixed delay.

More strict control quality requirements are raised to the synthesis of modern algorithmic control systems which can not be satisfied by using classical methods of systems synthesis. Also, the usage of them sometimes becomes impossible, e.g. in cases when a mathematical model of the control object is described by means of complex differential equations or in cases when the model itself is unknown. By applying the suggested synthesis methods of quasi-optimal and variable structure systems as well as algorithms, it is possible to avoid disadvantages common with classical synthesis methods.

Syftet med denna uppsats är att undersöka tre unga bloggerskor från Jönköping och deras sätt att skriva. Genom att undersöka de grammatiska strukturerna i fem inlägg av varje bloggerska och jämföra dem med varandra, vill vi utläsa ett eventuellt gemensamt bloggspråk. I vår bakgrund beskriver vi bloggens utveckling och dess roll i den svenska skolan. Forskning kring blogg, med särskild betoning på bloggspråk, är begränsad. Vår undersökning syftar till att vara en kvalitativ studie där vi har utgått från en stilanalys kompletterad med en variabelanalys. Den teoretiska utgångspunkten i vår uppsats är genreteori som åsyftar att genre påverkas, förändras och skapas i sociala situationer. I vår undersökning har vi valt att undersöka variabler inom ortografi och syntax. Utifrån blogginläggen har vi sett att det finns tydliga talspråkliga influenser i bloggerskornas skriftspråk. Vi anser att dessa tendenser med den fria användningen av interpunktion, det enkla skriftspråket och avvikandet från skriftspråksnormerna är de gemensamma dragen som utgör ett bloggspråk. / This paper aims to examine three young bloggers’ from Jönköping and their way of writing. By examining the grammatical structures in five blog posts by each blogger and comparing them with each other, we wish to detect a possible common blog language. In our background we describe the development of the blog and its role in the Swedish school. Research on blogs, with specific focus on blog language, is limited. Our survey has been carried put through a qualitative study based on style analysis with variable analysis as a supplement.  The theoretical premiss of our paper is genre theory that refers to that the genre is influenced, changed and created in social situations. In our survey we have chosen to examine variables in orthography and syntax. Based on the blog posts, we can see that there are clear influences from the spoken language in the bloggers’ written language. We believe that this trend with the liberal usage of punctuation, easy-to-read language and the negligence of written language norms are similarities that form a blog language.

Genetic regulatory networks are of great importance in terms of scientific interests and practical medical importance. Since a number of high-throughput measurement devices are available, such as microarrays and sequencing techniques, regulatory networks have been intensively studied over the last decade. Based on these high-throughput data sets, statistical interpretations of these billions of bits are crucial for biologist to extract meaningful results. In this thesis, we compare a variety of existing regression models and apply them to construct regulatory networks which span trancription factors and microRNAs. We also propose an extended algorithm to address the local optimum issue in finding the Maximum A Posterjorj estimator. An E. coli mRNA expression microarray data set with known bona fide interactions is used to evaluate our models and we show that our regression networks with a properly chosen prior can perform comparably to the state-of-the-art regulatory network construction algorithm. Finally, we apply our models on a p53-related data set, NCI-60 data. By further incorporating available prior structural information from sequencing data, we identify several significantly enriched interactions with cell proliferation function. In both of the two data sets, we select specific examples to show that many regulatory interactions can be confirmed by previous studies or functional enrichment analysis. Through comparing statistical models, we conclude from the project that combining different models with over-representation analysis and prior structural information can improve the quality of prediction and facilitate biological interpretation. Keywords: regulatory network, variable selection, penalized maximum likelihood estimation, optimization, functional enrichment analysis.

Variable speed drive technology has advanced dramatically in the last 10 years with the advent of new power devices. In this study, a three phase induction motor drive using Insulated Gate Bipolar Transistors (IGBT) at the inverter power stage is introduced to implement speed and position control for the revolving stage in the Frederic Wood Theatre This thesis presents a solution to control a 3-phase induction motor using the Texas Instruments (TI) Digital Signal Processor (DSP) TMS320F2407A. The use of this DSP yields enhanced operations, fewer system components, lower system cost and increased efficiency. The control algorithm is based on the constant volts-per-hertz principle because the exact speed control is not needed. Reflective object sensors which are mounted on concrete frame are used to detect accurate edge position of revolving stage. The sinusoidal voltage waveforms are generated by the DSP using the space vector modulation technique. In order to satisfy some operating conditions for safe and agreeable operation, a look-up table, which is used to give command voltage and speed signals in software, is applied to limit the maximum speed and acceleration of the revolving stage. Meanwhile, a boost voltage signal is added at the low frequency areas to make the motor produce maximum output torque when starting. A test prototype is then built to validate the performance. Several tests are implemented into the IGBT drive to explore the reason for unacceptable oscillations in IGBT’s gate control signals. Improvement methods in hardware layout are suggested for the final design.

Underwater autonomous vehicles are frequently used for deep-water ocean applications such as surveying and cable-laying, where accurate control of vehicle depth and attitude is needed. The water level in the on-board ballast tanks are typically manually set for neutral buoyancy before each mission, while the vehicle is on the surface. The resulting weight of the water level is not normally adjusted while the unmanned vehicle is in operation to control vehicle depth and orientation. As a result, vehicle trajectory and orientation is exclusively controlled using the vehicle’s control surfaces during a mission. The challenges with controlling the depth and trim of an underwater vehicle include nonlinear hydrodynamic forces as well as relatively slow response times and inherent time delays (latencies) associated with water tank level changes and valve adjustments. To meet these challenges, this thesis proposes two unique variable ballast system control approaches. The proposed control approaches may be suitable for large autonomous underwater vehicles with both small (volume = 0.027 m3, each) and large (volume = 0.216 m3, each) ballast tanks. The first proposed variable ballast system controller uses the current parameters of the ballast tanks to determine the appropriate action to be implemented. This controller was designed change the weight of the AUV to help control vehicle parameters such as depth and vertical (inertial) velocity. The second proposed variable ballast controller attempts to shift the center of gravity x_G along the body-fixed x-(longitudinal) axis by changing the weight in the ballast tanks. By shifting the center of gravity, the controller attempts to reduce depth and pitch angle error while regaining control authority to the bowplane and sternplane deflection fins. The ballasting system consists of two water tanks positioned aft and forward of amidships. The ballast tanks are then automatically filled or emptied of ocean water as desired. Setpoint depth control and x_G shifting numerical simulations have been carried out on a two-dimensional underwater vehicle simulator to test and compare the performance of the proposed ballast and deflection control systems. The simulation results show that, for the assumptions and conditions tested, the proposed controllers are versatile and capable of achieving a setpoint depth and pitch angle with minimal error by effectively utilizing the ballast tanks and deflection fins. As a result, the work presented in this thesis helps increase the autonomy of large AUVs on long duration missions.

Discriminant analysis and random forests are used to create models for classification. The number of variables to be tested for inclusion in a model can be large. The goal of this work was to create an efficient and effective selection program. The first method used was based on the work of others. The resulting models were underperforming, so another approach was adopted. Models were built by adding the variable that maximized new-model accuracy. The two programs were used to generate discriminant-analysis and random forest models for three data sets. An existing software package was also used. The second program outperformed the alternatives. For the small number of runs produced in this study, it outperformed the method that inspired this work. The data sets were studied to identify determinants of performance. No definite conclusions were reached, but the results suggest topics for future study.

The goal of this dissertation is to consolidate the theoretical foundation of variable-resolution (VR) methods in general and the partially-averaged Navier-Stokes (PANS) approach in particular. The accurate simulation of complex turbulent flows remains an outstanding challenge in modern computational fluid dynamics. High- fidelity approaches such as direct numerical simulations (DNS) and large-eddy simulation (LES) are not typically feasible for complex engineering simulations with cur- rent computational technologies. Low-fidelity approaches such as Reynolds-averaged Navier-Stokes (RANS), although widely used, are inherently inadequate for turbulent flows with complex flow features. VR bridging methods fill the gap between DNS and RANS by allowing a tunable degree of resolution ranging from RANS to DNS. While the utility of VR methods is well established, the mathematical foundations and physical characterization require further development. This dissertation focuses on the physical attributes of fluctuations in partially-resolved simulations of turbulence. The specific objectives are to: (i) establish a framework for assessing the physical fidelity of VR methods to examine PANS fluctuations; (ii) investigate PANS simulations subject to multiple resolution changes; (iii) examine turbulent transport closure modeling for partially-resolved fields; (iv) examine the effect of filter control parameters in the limit of spectral cut-off in the dissipative region; and (v) validate low-Reynolds number corrections with RANS for eventual implementation with PANS. While the validation methods are carried out in the context of PANS, they are considered appropriate for all VR bridging methods. The key findings of this dissertation are summarized as follows. The Kolmogorov hypotheses are suitably adapted to describe fluctuations of partially-resolved turbulence fields, and the PANS partially-resolved field is physically consistent with the adapted Kolmogorov hypotheses. PANS adequately recovers the correct energetics in instances of multiple resolution changes. Scaling arguments are used to determine the correct transport closure model for a partially-resolved field in a boundary layer. The need to modify the fε filter control parameter for cut-off in the dissipation range is highlighted. A low-Reynolds number near-wall correction was evaluated on a RANS model with the intent of adapting to it VR methods. Overall, PANS shows promise as a theoretically sound modeling approach, and this work lays the foundation for future PANS investigations.