As zoos and aquariums have become increasingly focused on conservation education, their menageries of unique and diverse learning opportunities have been underutilized. Through a new postsecondary-level animal behavior laboratory experience at an aquarium (“ZooU”), this study demonstrates that active learning pedagogy aligned with the Next Generation Science Standards (NGSS) could facilitate expansion of education at zoos and aquariums beyond their conservation education niche. Generally, students indicated that ZooU provided new opportunities for them to explore their own interests, demonstrate their learning, and augment their previous laboratory and aquarium experiences. Following both self- and researcher assessments of the students’ work, integrated analyses revealed that students who engaged in more active learning activities at the aquarium demonstrated a greater increase in skills aligned with the NGSS. Additionally, a novel intra-individual analysis was utilized to embrace the variation between learners that typically confounds the results of education studies with repeated measures design. Common challenges for education at zoos and aquariums are discussed through the context of ZooU as a foundation for future investigations. A practical NGSS-aligned guide to field trips at zoos and aquariums—written specifically for science teachers—is also included to support broader utilization of zoos and aquariums as educational resources.

Neuartige Konstruktionswerkstoffe, welche eine hohe Festigkeit mit einem niedrigen Materialgewicht verbinden, sind von besonderem Interesse in verschiedenen Anwendungsgebieten. Insbesondere im Mobilitätssektor sind derartige innovative und nachhaltige Werkstoffe mit hoher spezifischer Festigkeit von Bedeutung, um sowohl die angestrebte Reduktion von Fahrzeugemissionen als auch eine ausreichende mechanische Stabilität der Karosserie zu erreichen. Stähle weisen dabei aufgrund ihres großen Eigenschaftsspektrums und der umfassende Prozesskenntnis in der Stahlverarbeitung bzw. Herstellung ein hohes Potenzial auf und es kann historisch bedingt auf eine umfassende Prozesskenntnis in der Stahlverarbeitung bzw. Herstellung zurückgegriffen werden. Bisher wurden derartige Eigenschaftsprofile nur durch aufwändige Nachbehandlungsschritte realisiert. Ein durch gezielte Legierungsmodifikation im Kupferkokillenschwerkraftguss bei erhöhten Abkühlgeschwindigkeiten hergestellter hochfester Werkzeugstahl zeigt bereits im Gusszustand ein vielversprechendes mechanisches Eigenschaftsprofil. Dieses wurde sowohl im quasi-statischen als auch im dynamischen Druckversuch eingehender untersucht. Hierbei konnte nur eine marginale Dehnratenabhängigkeit für den neuartigen Werkzeugstahl beobachtet werden. Im dynamischen Druckversuch wurden adiabatische Scherbänder nachgewiesen, deren Entstehung durch verschiedene Methoden der Gefügecharakterisierung nachverfolgt werden konnten und als Vorläuferstellen für das Materialversagen durch Bruch anzusehen sind.

There is a new generation of students entering our school systems called "Digital Natives"; students who are more technologically inclined than their teachers. With the new cohort of students, it is becoming problematic for teachers to implement engaging lessons. Because social studies is not a state tested subject, teachers and administrators find it very difficult to retrieve the time and the passion for the subject in the everyday classroom. One new Google application called Google Lit Trips is an appealing way to teach social studies for the new generation of students. Prior research on Google Lit Trips showed that this application is well suited for creating lessons that can satisfy standards for a multitude of subjects, and in a way that catches the students' attentions. After I completed research on the 21st century learner, how teachers can integrate social studies into their classroom, and Google Literature Trips; I studied many virtual field trips of various books or novels. These Google Literature Trips allows teachers to utilize Google Earth to pin locations of importance for students in order to gain a visual, while simultaneously exploring educational activities. Then, I created my own Google Lit Trip. Before teachers participated in exploring the Google Lit Trip I created, a survey was conducted on the five teachers; getting their perceptions of technology, social studies education, and Google Lit Trips. They were then asked to read the picture book The Story of Ruby Bridges (Coles, 1995). The computer application was then shown to teachers to get their opinions on its perceived effectiveness. A post-survey was then conducted on the teachers' perceptions of the Google Literature Trip. The results of the teachers' discernments of the teaching tool proved it to be an effective application to use in the classroom to enhance cross-curricular education from technology, art, reading, and most importantly for this thesis, social studies. Future research should be conducted on students' perceptions, and whether or not it sustains engagement, and whether or not their knowledge of the subject matter improves.

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<p>In today’s fast-paced data-driven world, accumulating and organizing streams of high-resolution information plays a vital role in numerous decision and design tasks. The transportation sector is a prime example of this. Fine-scale information on traffic exposure at specific observation periods is critical to the successful analysis of road safety. Annual Average Daily Traffic (AADT) and hourly traffic volumes represent essential statistics to predict crash risk under time-dependent conditions, such as, weather and seasonal traffic variations. State highway agencies including the Indiana Department of Transportation (INDOT) collect traffic count data using multiple permanent and coverage count stations. However, approximately ten percent of the local-administered road segments in Indiana are included in their database. To impute the missing data, predictive models that can accurately forecast AADT and consequently, hourly traffic volumes, will be of great value.</p> <p><br></p> <p>To address this problem, this thesis proposes a methodology to predict traffic volumes in different classes of urban road segments in Indiana. Two sets of regression models have been developed: (1) AADT Estimation Model, and (2) Hourly Traffic Volume Model. These models include effects of spatial and temporal variations, land use, roadway characteristics and, previously-overlooked in such models, road network connectivity and route selection. These, in turn, address two important research questions: (1) how trips are generated and (2) how people choose routes. The spatial and temporal effects that were considered in the analysis are travel propensity, travel time excess index, road class, hour of day, day of week and seasonal variations. While travel propensity captures particulars of network connectivity and land-use characteristics in traffic analysis zones (TAZ), the travel time excess index accounts for commuters’ route-choice. The estimation results indicate that all these variables are strongly correlated with traffic volumes on considered roadways. Reasonable estimations of hourly traffic volumes on a network scale can be achieved using the proposed model. In addition to aiding safety management at disaggregate level, hourly traffic predictions can help highway agencies in other system-wide analysis where such traffic information is needed.</p>

Trip-induced falls are a leading cause of injuries among adults aged 65 years or older. Perturbation-based balance training (PBT) has emerged as an exercise-based fall prevention intervention and shown efficacy in reducing the risk of trip-induced falls. The broad goal of my PhD research was to advance the application of this so-called trip training through three studies designed to address existing knowledge gaps. First, trip training is commonly conducted with the aid of costly specialized treadmills to induce trip-like perturbations. An alternative version of trip training that eliminates the need for a treadmill would enhance training feasibility and enable wider adoption. The goal of the first study was to compare the effects of non-treadmill training (NT), treadmill training (TT), and a control (i.e., no training) on reactive balance after laboratory-induced trips among community-dwelling older adults. After three weeks of the assigned intervention, participants were exposed to two laboratory-induced trips while walking. Results showed different beneficial effects of NT and TT. For example, NT may be more beneficial in improving recovery step kinematics, while TT may be more beneficial in improving trunk kinematics, compared to the control. While the first study showed the effects of PBT on laboratory-induced trips, little is known about how such training affects responses to real-world trips. Responses to real-world trips may be captured using wearable inertial measurement units (IMUs), yet IMUs have not been adequately validated for this use. Therefore, the goal of the second study was to investigate the concurrent validity of IMU-based trunk kinematics against the gold standard optical motion capture (OMC)-based trunk kinematics after overground trips among community-dwelling older adults. During two laboratory-induced trips, participants wore two IMUs placed on the sternum and shoulder, and OMC markers placed at anatomical landmarks of the trunk segment. Results showed that IMU-based trunk kinematics differed between falls and recoveries after overground trips, and exhibited at least good correlation (Pearson's correlation coefficient, r > 0.5) with the gold standard OMC-based trunk kinematics. The goal of the third study was then to explore differences in tripping kinematics between the laboratory and real world using wearable IMUs among community-dwelling older adults. Participants were asked to wear three IMUs (for sternum and both feet) and a voice recorder to capture their responses to real-world losses of balance (LOBs) during their daily activities for three weeks. Results showed a higher variance in laboratory-induced trips than real-world trips, and the study demonstrated the feasibility of using IMUs and a voice recorder to understand the underlying mechanisms and context of real-world LOBs. Overall, this work was innovative by evaluating a non-treadmill version of trip training, establishing the validity of IMUs in capturing kinematic responses after overground trips, and applying IMUs and a voice recorder to assess tripping kinematics in the real world. The results from this work will advance the use of PBT to reduce the prevalence of trip-induced falls and to investigate the real-world effects of such trip training in future studies. / Doctor of Philosophy / Trips and falls are a major health problem especially among older adults who are aged 65 years or older. Researchers have developed an innovative exercise-based fall prevention training program, which has shown to be helpful in reducing trips and falls. The broad goal of my PhD research was to advance the use of this so-called trip training through three new research studies. First, specialized treadmills are commonly used for trip training to simulate trip-induced falls. An alternative version of trip training without a treadmill would allow more people to receive benefits from this training. The goal of the first study was to compare the effects of non-treadmill training (NT), treadmill training (TT), and no training on balance recovery after tripping in the laboratory. Older adults living in the local community were recruited as research participants and completed NT, TT, or no training over three weeks. After that, they attended a laboratory session where they were tripped twice while walking on a walkway. Results showed that NT helped to take a longer and faster recovery step, while TT helped to limit trunk forward bending during tripping, both of which are important movements to prevent falling after tripping. While the first study showed benefits of trip training in the laboratory, not much is known about the benefits of trip training in the real world. Wearable sensors called inertial measurement units can record body movements without laboratory motion capture cameras, but their ability to record dynamic body movements during tripping needs to be tested. The goal of the second study was to evaluate the capabilities of these wearable sensors on recording trunk movements during tripping and compare them to those recorded by laboratory motion capture cameras. Participants were tripped twice in the laboratory, and their trunk movements were recorded by several wearable sensors and laboratory motion capture cameras. Results showed that these wearable sensors can distinguish between fallers and non-fallers after tripping, and that the trunk movements recorded by the wearable sensors were associated with those recorded by the laboratory motion capture cameras. With this confirmation, the third study was designed to compare balance recovery after tripping between the laboratory and real world using wearable sensors. Participants were asked to wear three wearable sensors and a voice recorder during their daily activities for three weeks. The wearable sensors recorded their trunk and feet movements, while the voice recorder was used for participants to provide detailed explanations of balance losses they experienced. Results showed a higher variability in balance recovery from the laboratory trips compared to the real-world trips. In addition, this study demonstrated that wearable sensors and a voice recorder can be used to study how people reacted to a balance loss and what they did to recover (or fall) from it. Overall, my PhD research work suggested a new version of trip training that does not require a treadmill, proved that wearable sensors can be used to record important body movements during tripping, and demonstrated the method to study balance recovery responses in the real world using wearable sensors. The results from the three studies will promote the use of trip training and provide guidelines for evaluating benefits of trip training in the real world.

Wide-area measurement systems (WAMS) enable the monitoring of overall bulk power systems and provide critical information for understanding and responding to power system disturbances and cascading failures. The North American Frequency Monitoring Network (FNET) takes GPS-synchronized wide-area measurements in a low-cost, easily deployable manner at the 120 V distribution level, which presents more opportunities to study power system dynamics. This work explores the topics of power system disturbance analysis and detection by utilizing the wide-area measurements obtained in the distribution networks. In this work, statistical analysis is conducted based on the major disturbances in the North American Interconnections detected by the FNET situation awareness system between 2006 and 2008. Typical frequency patterns of the generation and load loss events are analyzed for the three North American power Interconnections: the Eastern Interconnection (EI), the Western Electricity Coordinating Council (WECC), and the Electric Reliability Council of Texas (ERCOT). The linear relationship between frequency deviation and frequency change rate during generation/loss mismatch events is verified by the measurements in the three Interconnections. The relationship between the generation/load mismatch and system frequency is also examined based on confirmed generation loss events in the EI system. And a power mismatch estimator is developed to improve the current disturbance detection program. Various types of power system disturbances are examined based on frequency, voltage and phase angle to obtain the event signatures in the measurements. To better understand the propagation of disturbances in the power system, an automated visualization tool is developed that can generate frequency and angle replays of disturbances, as well as image snapshots. This visualization tool correlates the wide-area measurements with geographical information by displaying the measurements over a geographical map. This work makes an attempt to investigate the visualization of the angle profile in the wide-area power system to improve situation awareness. This work explores the viability of relying primarily on distribution-level measurements to detect and identify line outages, a topic not yet addressed in previous works. Line outage sensitivity at different voltage levels in the Tennessee Valley Authority (TVA) system is examined to analyze the visibility of disturbances from the point of view of wide-area measurements. The sensor placement strategy is proposed for better observability of the line trip disturbances. The characteristics of line outages are studied extensively with simulations and real measurements. Line trip detection algorithms are proposed that employs the information in frequency and phase angle measurements. In spite of the limited FDR coverage and confirmed training cases, an identification algorithm is developed which uses the information in the real measurements as well as the simulation cases to determine the tripped line. / Ph. D.

This research explores the feasibility of providing innovative and effective solutions for traffic congestion. The design of reservation systems is being considered as an alternative and/or complementary travel demand management (TDM) strategy. A reservation indicates that a user will follow a booking procedure defined by the reservation system before traveling so as to obtain the right to access a facility or resource. In this research, the reservation system is introduced for a cordon-based downtown road network, hereafter called the Downtown Space Reservation System (DSRS). The research is executed in three steps. In the first step, the DSRS is developed using classic optimization techniques in conjunction with an artificial intelligence technology. The development of this system is the foundation of the entire research, and the second and third steps build upon it. In the second step, traffic simulation models are executed so as to assess the impact of the DSRS on a hypothetical transportation road network. A simulation model provides various transportation measures and helps the decision maker analyze the system from a transportation perspective. In this step, multiple simulation runs (demand scenarios) are conducted and performance insights are generated. However, additional performance measurement and system design issues need to be addressed beyond the simulation paradigm. First, it is not the absolute representation of performance that matters, but the concept of relative performance that is important. Moreover, a simulation does not directly demonstrate how key performance measures interact with each other, which is critical when trying to understand a system structure. To address these issues, in the third step, a comprehensive performance measurement framework has been applied. An analytical technique for measuring the relative efficiency of organizational units, or in this case, demand scenarios called network Data Envelopment Analysis (DEA), is used. The network model combines the perspectives of the transportation service provider, the user and the community, who are the major stakeholders in the transportation system. This framework enables the decision maker to gain an in-depth appreciation of the system design and performance measurement issues. / Ph. D.