In massive open online courses (MOOCs), a pressing need for an efficient automated approach of identifying keyphrases from MOOC video lectures has emerged. Because of the linear structure of MOOCs and the linear way in navigating the content of MOOCs, learners have difficulty to know the main knowledge addressed in MOOC video lectures and spend too much time navigating among to find the right content matching their learning goals. A feasible solution is automatic provision of keyphrases associated with MOOC video lectures that can help learners quickly identify a suitable knowledge and efficiently navigate to desired parts of MOOC video lectures without spending too much time to expedite their learning process. Keyphrases in MOOCs demonstrate three unique features: (1) low-frequency occurrence, (2) advanced scientific or technical concepts, and (3) late occurrence. Existing approaches to automatic keyphrases extraction (either supervised or unsupervised) do not consider these unique features, causing them to produce unsatisfactory performance when utilized to extract keyphrases from MOOC video lectures. In this dissertation, we propose $SemKeyphrase$, an unsupervised cluster-based approach for keyphrase extraction from MOOC video lectures. $SemKeyphrase$ incorporates a new semantic relatedness method and ranking algorithm, called $PhraseRank$. The proposed semantic relatedness method incorporates a novel metric that combines two scores ($WSem$ and $CSem$) to efficiently compute the semantic relatedness between candidate keyphrases in MOOCs. The $PhraseRank$ algorithm involves two phases when ranking candidate keyphrases: ranking clusters and reranking top candidate keyphrases. The first phase of $PhraseRank$ leverages the semantic relatedness of candidate keyphrases with regard to the subtopics of a MOOC video lecture to measure the importance of candidate keyphrases, which are further used to rank clusters of candidate keyphrases. Top candidate keyphrases from top-ranked clusters are then determined by a proposed selection strategy. The second phase of $PhraseRank$ reranks the top candidate keyphrases using a new ranking criterion and generates ranked top-K keyphrases as the final output. Experiment results on a real-world dataset of MOOC video lectures show that $SemKeyphrase$ outperforms other state-of-the-art methods.

For a sample of collisional ring galaxies, archival Hubble Space Telescope images were used to compare individual star clusters and kpc-sized clumps of star formation to each other in a variety of ways. For each galaxy, instrument, and filter, the magnitude of the brightest cluster in a clump was compared to the magnitude of the entire clump, and the fraction of the flux of the clusters in a clump over the flux of the entire clump was calculated and compared to star formation rates. In addition, a cluster luminosity function for each galaxy was derived. Comparing the brightest cluster in a clump to the magnitude of the entire clump and the flux ratio to the star formation rate did not show any significant patterns. However, the α found for the galaxies tended to be much flatter than what had been found in previous research. The α found seemed to be affected by the size of the bin used in the luminosity function. Using this information, α could be calculated for other incredibly luminous galaxies to see if the trend of flatter α continues.

Commodity supercomputing clusters known as Beowulf clusters, have become a low cost alternative to traditional supercomputers. Beowulf clusters combine inexpensive computers and specialized software to achieve supercomputing power. The processing nodes in a diskless Beowulf cluster do not have a local hard disk unlike the nodes in most commodity clusters. Research has provided performance information for diskless clusters built with expensive, high performance equipment. Beowulf clusters use commodity off-the-shell hardware, and little information is available about their performance. This research includes the construction of several diskless Beowulf clusters. Using the NAS Parallel Benchmarks, the performance of these clusters was measured. Through analysis of these measurements, a descriptive performance model of diskless Beowulf clusters was produced.

In many applications involving data collected over time, it is important to get timely estimates and adjustments of the parameters associated with a dynamic model. When the dynamics of the model must be updated, time and computational simplicity are important issues. When the dynamic system is not linear the problem of adaptation and response to feedback are exacerbated. A linear approximation of the process at various levels or “states” may approximate the non-linear system. In this case the approximation is linear within a state and transitions from state to state over time. The transition probabilities are parametrized as a Markov chain, and the within-state dynamics are modeled by an AR time series model. However, in order to make the estimates available almost instantaneously, least squares and weighted least squares estimates are used. This is a modification of the cluster-weighted models proposed by Gershenfeld, Schoner, and Metois (1999). A simulation study compares the models and explores the adequacy of least squares estimators.

The Small Aircraft Transportation System, or SATS, is a NASA-led initiative that seeks to revolutionize commercial air travel by increasing accessibility and mobility for the general consumer. The hallmark of SATS is on-demand, point-to-point air transportation from one of the nation's 5,400 public use airports and landing facilities. A second-order benefit is that it may help relieve congestion on the nation's highways and at our mid- to large size airport hubs. In 1999, NASA initiated a five-year, $69 million research program to study the feasibility and viability of SATS including development of the emerging technologies necessary to make SATS a reality. The five-year plan culminated in June 2005 in Danville, VA with a highly publicized flight demonstration and exposition serving as the SATS proof of concept. The "Highways-in-the-Sky" (HITS) premise inherent to SATS is arguably its biggest enabler, and it depends heavily on the idea of free flight. HITS will potentially be the first step in moving from traditional cars and other vehicles that travel on the ground to ones that will operate largely, if not entirely, in the air. The notion of "cars" that fly was first introduced by the entertainment industry in movies and television programs decades ago. But if mankind is ever to achieve that vision, we must have a start point. This research focuses not on the economic viability of SATS but rather on the degree of flight safety inherent to a program such as this. One can easily see how the introduction of a large number of autonomous vehicles operating simultaneously in an already dense region such as the National Airspace System might carry some degree of risk. This research introduces a modeling and simulation framework that will have applications to SATS at such time as the program must be evaluated from a safety of flight perspective. That will invariably include a high degree of simulation. This work also represents the first large-scale simulation focused primarily on how SATS will perform in the out-years. / Master of Science

This thesis presents an investigation on innovative approaches to agricultural management, addressing challenges in both viticulture and turfgrass management. The first topic of this thesis introduces the Adaptive Crop Load Estimation (ACLE) method, a deep learning-based grape counting approach designed to alleviate the need for extensive annotated datasets. By training the model on a limited set of images, this method demonstrates promising results in accurately estimating grape cluster counts across different zones in the vineyards, with an average Mean Absolute Error (MAE)/Root Mean Square Error (RMSE) of 0.86/0.66. The ACLE method aims to reduce the cost of deploying automated grape counting systems by minimizing manual image annotation efforts and enabling model reusability across different vineyards. The second topic of this thesis delves into the realm of Turfgrass management, recognizing its pivotal roles in environmental health and aesthetics. Focusing on the challenges posed by spot- based diseases, the study introduces the Spot Treatment Pathfinding and Scheduling (STPAS) method. This framework employs Unmanned Ground Vehicles (UGV) for targeted spot spraying, optimizing robot stops and trajectories based on varying scenarios such as different spot sizes and robot capabilities. The trajectory planner developed within STPAS utilizes GPS coordinates and the radius of affected areas to determine efficient stops and paths for autonomous vehicles. Comparative analysis on the developed simulators reveals that STPAS reduces the distance traveled and time taken for spot spraying by over 50% compared to conventional boom-based sprayers, thereby enhancing both economic and environmental sustainability in Turfgrass management practices. / Master of Science / This thesis explores solutions for improving agricultural practices, specifically focusing on grapevine cultivation and turfgrass management. The first part introduces a novel method called Adaptive Crop Load Estimation (ACLE), which employs deep learning to accurately count grape clusters in vineyards. Unlike traditional methods requiring extensive annotated data, ACLE demonstrates significant results with minimal training images, aiming to reduce the cost of automated grape counting systems and enhance their adaptability across various vineyards. In the second part, the thesis delves into development of planning algorithm for precision spot spraying. Addressing challenges posed by spot-based diseases, the study introduces the Spot Treatment Pathfinding and Scheduling (STPAS) method. This algorithm provides robot stops and optimizes routes based on different scenarios such as spot sizes and robot capabilities. Comparative analysis of the simulation results reveals that STPAS improves efficiency, reducing both the distance traveled and time taken for spot spraying compared to boom-based sprayers. This not only benefits economic considerations but also contributes to environmental sustainability in turfgrass management practices.

京都大学 / 新制・課程博士 / 博士(医学) / 甲第24282号 / 医博第4898号 / 新制||医||1061(附属図書館) / 京都大学大学院医学研究科医学専攻 / (主査)教授 伊佐 正, 教授 花川 隆, 教授 村井 俊哉 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DFAM

<p> Extensive bedding plane exposures in the Ludlowville shales along Cazenovia Creek near Spring Brook, New York display the spatial distribution of the skeletal remains from a marine faunal assemblage. Fossils typically occur in aggregates that are subcircular in plan view and plano-convex in cross-section with the convex side down. The clusters measure 1 meter in diameter and 2 centimeters thick at the center. This dispersion pattern has led to a general consideration of the different mechanisms responsible for creating fossil aggregations. Possible mechanisms, a spectrum from biological to geological, have been categorized into reproductive, ecological, postmortem redistributional, and preservational modes of formation. </p> <p> Quantitative sampling of the most abundant species, Ambocoelia umbonata, in four successive 5 millimeter layers within three clusters was carried out to determine which process is responsible for cluster formation. Between level variation in shell parameters demonstrates that fragmentation, distortion and valve ratios are independent of trends in position, density, and disarticulation. The trends are not controlled by geological agents, but rather result from ecological conditions. Furthermore, the size distributions of Arnbocoelia are bimodal and have to be explained on a biological basis. This has led to an interpretation of cluster development involving initiation by occasional spat survival on a somewhat "lethal" substrate, subsequent succession and regulation by ecological requirements, and final termination due to failure of spat recruitment probably because of fecal and/or decay toxin buildup. </p> / Thesis / Master of Science (MSc)

A flexible family of mixture models known as cluster-weighted models (CWMs) arise when the joint distribution of a response variable and a set of covariates can be modelled by a weighted combination of several component distributions. We introduce an extension to CWMs where changepoints are present. Similar to the finite mixture of regressions (FMR) with changepoints, CWMs with changepoints are more flexible than standard CWMs if we believe that changepoints are present within the data. We consider changepoints within the linear Gaussian CWM, where both the marginal and conditional densities are assumed to be Gaussian. Furthermore, we consider changepoints within the Poisson and Binomial CWM. Model parameter estimation and performance of some information criteria are investigated through simulation studies and two real-world datasets. / Thesis / Master of Science (MSc)

In this Thesis we present a description of α cluster nuclei, in particular focusing on the case of 9 Be, with αn and αα interactions derived from Cluster Effective Field Theory (EFT). The two-body potentials are regularized by a Gaussian cutoff which cures the short-distance dependence of the interaction and the potential parameters are found comparing the effective range expansion (ERE) with the calculated T-matrix. The calculation of the ground-state energies is carried out by diagonalizing the Hamiltonian on a Non symmetryzed Hyperspherical Harmonics basis in momentum space. Using only two body interactions a rather strong cutoff dependence appears. However, we are able to reproduce the experimental ground-state energies for selected cutoff values for most of the studied nuclei. The strong cutoff dependence indicates the lack of three-body forces, therefore we extend our Cluster EFT approach by including such many-body forces. Finally, the 9Be photoabsorption cross-section is studied via the Lorentz integral transform method (LIT), focusing on the low-energy resonances coming from the electric dipole transitions. By fine tuning the parameters of the three-body force, we are able to reproduce, up to 4 MeV, the considered experimental resonances. For the description of the spectrum at higher energies the inclusion of the αα D-wave potential seems to be necessary.