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Pushing the Boulder, Pushing the Envelope: Embracing the Iterative Nature of Improving Metadata
Get PDFViolet Fox, creator of The Cataloging Lab, gave the keynote presentation for the inaugural Metadata Justice in Oklahoma Libraries & Archives where she encouraged metadata and archives professionals to keep up the important work, no matter the pace of the work
Finding the Right Words
Get PDFIn Summer 2021, UCO Chambers Library's catalogers crafted an inclusive metadata statement. Our presentation will provide an overview of the process, recommendations for creating your own statement, and the challenges of important terminology being misappropriated as buzzwords (e.g. "decolonizing" the catalog)N
Managing computational complexity through using partitioning, approximation and coordination
Get PDFProblem: Complex systems are composed of many interdependent subsystems with a level of complexity that exceeds the ability of a single designer. One way to address this problem is to partition the complex design problem into smaller, more manageable design tasks that can be handled by multiple design teams. Partitioning-based design methods are decision support tools that provide mathematical foundations, and computational methods to create such design processes. Managing the interdependency among these subsystems is crucial and a successful design process should meet the requirements of the whole system which needs coordinating the solutions for all the partitions after all.
Approach: Partitioning and coordination should be performed to break down the system into subproblems, solve them and put these solutions together to come up with the ultimate system design. These two tasks of partitioning-coordinating are computationally demanding. Most of the proposed approaches are either computationally very expensive or applicable to only a narrow class of problems. These approaches also use exact methods and eliminate the uncertainty. To manage the computational complexity and uncertainty, we approximate each subproblem after partitioning the whole system. In engineering design, one way to approximate the reality is using surrogate models (SM) to replace the functions which are computationally expensive to solve. This task also is added to the proposed computational framework. Also, to automate the whole process, creating a knowledge-based reusable template for each of these three steps is required. Therefore, in this dissertation, we first partition/decompose the complex system, then, we approximate the subproblem of each partition. Afterwards, we apply coordination methods to guide the solutions of the partitions toward the ultimate integrated system design.
Validation: The partitioning-approximation-coordination design approach is validated using the validation square approach that consists of theoretical and empirical validation. Empirical validation of the design architecture is carried out using two industry-driven problems namely the a hot rod rolling problem’, ‘a dam network design problem’, ‘a crime prediction problem’ and ‘a green supply chain design problem’. Specific sub-problems are formulated within these problem domains to address various research questions identified in this dissertation.
Contributions: The contributions from the dissertation are categorized into new knowledge in five research domains:
• Creating an approach to building an ensemble of surrogate models when the data is limited – when the data is limited, replacing computationally expensive simulations with accurate, low-dimensional, and rapid surrogates is very important but non-trivial. Therefore, a cross-validation-based ensemble modeling approach is proposed.
• Using temporal and spatial analysis to manage the uncertainties - when the data is time-based (for example, in meteorological data analysis) and when we are dealing with geographical data (for example, in geographical information systems data analysis), instead of feature-based data analysis time series analysis and spatial statistics are required, respectively. Therefore, when the simulations are for time and space-based data, surrogate models need to be time and space-based. In surrogate modeling, there is a gap in time and space-based models which we address in this dissertation. We created, applied and evaluated the effectiveness of these models for a dam network planning and a crime prediction problem.
• Removing assumptions regarding the demand distributions in green supply chain networks – in the existent literature for supply chain network design, there are always assumptions about the distribution of the demand. We remove this assumption in the partition-approximate-compose of the green supply chain design problem.
• Creating new knowledge by proposing a coordination approach for a partitioned and approximated network design. A green supply chain under online (pull economy) and in-person (push economy) shopping channels is designed to demonstrate the utility of the proposed approach
Working in conflict: how bureaucrats navigate accountability pressures
Get PDFBureaucrats make policy. So, understanding their motivations behind discretionary choices, or ultimate decisions about their role and agency are pivotal toward examining policy outcomes. This dissertation attempts to expand our understanding of state bureaucrats, possibly working under conflict, to grapple with nuance much of the literature neglects. The research undertakes existing frameworks like Exit, Voice, Loyalty, and Neglect to understand how state bureaucrats react to agency or policy changes, and how these behaviors can be results of accountability pressures between the state and federal levels of government. The results suggest bureaucrats navigate their complicated landscapes through a number of adaptations to the environment such as network building and community capacity, as well as exercising Exit, Voice, Loyalty, and Neglect. Finally, the research concludes with considerations of existing theoretical developments to adjust to the ever-growing complexity of policy implementation in a time of increasingly compound policy problems
Octet in E-flat major, op. 20 by Felix Mendelssohn-Bartholdy (1809-1847): a transcription for double wind quintet
No full textFelix Mendelssohn’s Octet in E-flat Major, Op. 20 is widely considered to be a canonic work within chamber string repertoire. Composed when Mendelssohn was just sixteen years old, the Octet was described as “a different kind of art” by contemporary Louis Spohr because of its use of eight independent parts coming together in a collaborative nature rather than approaching the work as two quartets in an antiphonal setting. Knowing that Mendelssohn himself arranged a portion of this work for full orchestra, it is not a leap for this work to be transcribed in other capacities.
Octet in E-flat Major, Op. 20 lends itself very well to a transcription utilizing a double woodwind quintet in the same collaborative nature for which Mendelssohn originally conceived the piece. With only two original compositions exclusively for winds and only a small percentage of the works in his canon previously transcribed or arranged for winds, this transcription lends an additional opportunity for winds players to experience Mendelssohn. Every effort was made to retain the original intent and maintain compositional integrity with Mendelssohn’s efforts. Adjustments to voicing due to registration, chord voicings due to personnel and instrument limitations, and slight rhythm alterations due to instrument facility were the primary deviations from the composer’s efforts
Form Factors: Chicano Movement Form and the Factors that Influenced it in Los Angeles and San Antonio
Get PDFThis dissertation has two goals. The first goal is to understand better the Chicano Movement, which is understudied in political science. The second goal is to find which movement theory best explains why movements take the form they do. In this dissertation, I conduct an in-depth historical analysis of the Chicano Movement in Los Angeles, CA, and San Antonio, TX, to understand the differences in movement form between the two cities. The three social movement theories I test are Resource Mobilization Theory, Political Opportunity Structure, and Perceptions of Success. The findings indicate that resources and political opportunities in the cities impacted Chicano Movement form to some degree, but activist perceptions of success were most significant in influencing form. One final key contribution of this dissertation is illustrating how local factors must be considered when studying social movements. The Chicano activists were part of a larger movement, but local factors significantly influenced how they operated
Subjective Evaluation of the In-Line Phase-Sensitive Imaging Systems in Breast Cancer Screening and Diagnosis
Get PDFBreast x-ray imaging remains the gold standard screening tool despite the various imaging modalities. The phase-sensitive breast imaging is an evolving technology that may provide higher diagnostic accuracy and potentially reduce the patient radiation dose. Many studies evaluate the performance of the In-line phase-sensitive breast imaging to improve this imaging modality further. Whereas radiologists are the end-users of this imaging technology, the primary goal of this dissertation project is to investigate the performance of human observers in varying conditions for further improvement of the in-line phase-sensitive x-ray imaging system.
A CDMAM phantom and an ACR mammography phantom are used in the observer performance study to compare the high-energy in-line phase-sensitive system with a mid-energy system as an alternative approach to balancing the attenuation-based image contrast with the accuracy of single-projection PAD-base phase-retrieval. Additionally, a series of ROC studies are designed by a contrast-detail phantom to evaluate the diagnostic accuracy of digital breast tomosynthesis (DBT) and the phase-sensitive prototype imaging system (PBT). The area under the ROC curves (AUC) and partial area under the ROC curves (pAUC) are estimated as a figure of merits in the two systems, delivering the equivalent radiation doses. A two-alternative-forced choice (2AFC) study is also designed to determine the preferred image in identifying the suspicious lesions within a heterogeneous pattern acquired by the DBT and PBT systems under an equivalent radiation dose.
The observer performance studies show that the mid-energy system has a potential advantage in providing a relatively higher image quality while the radiation dose is reduced in the mid-energy system compared with a high-energy system. The ROC study shows that the diagnostic accuracy of observers is more significant in the prototype PBT system than in a commercial DBT system, delivering the same radiation dose. The 2AFC study also revealed that observers prefer the PBT system in detecting and distinguishing the conspicuity of tumors in the images with structural noise, and the results were statistically significant.
The dissertation also introduces a mathematical approach for estimating the half-value-layer (HVL) from measured or simulated x-ray spectra. The HVL measurement is expected to be less accurate or experimentally challenging in some clinical equipment or when a quick beam quality evaluation is needed. Additionally, the impact of varying thicknesses of external filtration is subjectively and objectively investigated to evaluate the feasibility of reducing the image acquisition time in a mid-energy system without compromising the observer's performance and detectability. The preliminary results from phase-contrast images suggest that an in-line phase-sensitive system operated at 59 kV shows a comparable image quality with the x-ray beams filtered by 1.3 mm and 2.5 mm-thick aluminum filters. This finding could help shorten the exposure time by 34% in the mid-energy system, where image blurring is a concern due to patient movement in a longer image acquisition time.
In summary, and as expected, the subjective analyses of the in-line phase-sensitive imaging system align with the previous findings. However, the PBT imaging system may benefit from further improvement in image processing algorithms and optimizing the system with the most appropriate x-ray beam quality, considering the acquisition time, breast glandular composition, breast thickness, and different x-ray energies.
Keywords: Phase-sensitive X-ray Imaging, Breast Imaging, Image Quality, Human Observer Performance Stud
Application of Machine Learning to Multiple Radar Missions and Operations
Get PDFThis dissertation investigated the application of Machine Learning (ML) in multiple radar missions. With the increasing computational power and data availability, machine learning is becoming a convenient tool in developing radar algorithms. The overall goal of the dissertation was to improve the transportation safety. Three specific applications were studied: improving safety in the airport operations, safer air travel and safer road travel. First, in the operations around airports, lightning prediction is necessary to enhance safety of the ground handling workers. Information about the future lightning can help the workers take necessary actions to avoid lightning related injuries. The mission was to investigate the use of ML algorithms with measurements produced by an S-band weather radar to predict the lightning flash rate. This study used radar variables, single pol and dual-pol, measured throughout a year to train the machine learning algorithm. The effectiveness of dual-pol radar variables for lighting flash rate prediction was validated, and Pearson's coefficient of about 0.88 was achieved in the selected ML scheme. Second, the detection of High Ice Water Content (HIWC),which impact the jet engine operations at high altitudes, is necessary to improve the safety of air transportation. The detection information help aircraft pilots avoid hazardous HIWC condition. The mission was to detect HIWC using ML and the X-band airborne weather radar. Due to the insufficiency of measured data, radar data was synthesized using an end-to-end airborne weather system simulator. The simulation employed the information about ice crystals' particle size distribution (PSDs), axial ratios, and orientation to generate the polarimetric radar variables. The simulated radar variables were used to train the machine learning to detect HIWC and estimate the IWC values. Pearson's coefficient of about 0.99 was achieved for this mission. The third mission included the improvement of angular resolution and explored the machine learning based target classification using an automotive radar. In an autonomous vehicle system, the classification of targets enhances the safety of ground transportation. The angular resolution was improved using Multiple Input Multiple Output (MIMO) techniques. The mission also involved classifying the targets (pedestrian vs. vehicle) using micro-Doppler features. The classification accuracy of about 94% was achieved
Spotting clusters, hunting for planets: a combined study of galaxy clusters in the X-ray and optical regime
Get PDFObservational studies of the distribution of galaxies in the Universe reveal inhomogeneity and structure on Mpc and larger scales. Galaxy clusters are the largest gravitationally bound structures containing a virialized congregation of galaxies; therefore, studying them is essential for understanding the constitution and assembly history of these systems and probing the large-scale structure of the Universe. The Swift AGN and Cluster survey is a serendipitous X-ray survey aimed at building a large X-ray-selected cluster catalog with cluster detections expected by its final release. In this thesis, I perform an optical analysis of 348 (out of 442) X-ray selected cluster candidates from the Swift cluster catalog using multi-band imaging from MDM 2.4m and the Pan-STARRS survey for the northern sky, and CTIO 4m and DES for the southern sky. I report the optical confirmation of 109 clusters with galaxy over-density with photometric redshift estimates extending up to . The Swift survey is nearly complete for and complete for . The undetected clusters are possibly high redshift clusters with that warrant follow-up observations in the near-infrared. Furthermore, I also study the scaling relations between the X-ray and optical cluster mass observables and the offset distribution for all the optically verified SACS clusters and find them to be in agreement with other studies in literature.
Another facet of my dissertation involves using quasar microlensing to probe the intracluster region of a galaxy cluster. I employ this novel technique to exert effective constraints on planet-mass objects in two extragalactic systems, Q J0158-4325 and SDSS J1004+4112, by studying their induced microlensing signatures. Chandra observations for these two gravitationally-lensed quasars reveal variations of the emission line peak energy, which can be explained as microlensing of the FeK emission region surrounding the supermassive blackhole induced by planet-mass microlenses. To corroborate this, I have performed microlensing simulations and developed an edge detection algorithm to determine the probability of caustic transiting events. Comparison with the observed rates has yielded constraints on the substellar population, with masses ranging from Lunar to Jovian mass bodies within these galaxy or cluster scale structures. These results suggest that unbound planet-mass objects are common in galaxies, and these are surmised to be either free-floating planets or primordial black holes. These are the first-ever constraints on the substellar mass distribution in the intracluster light of a galaxy cluster. This analysis yields the most stringent limit for primordial black holes at the mass range