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Title: Photograph of the Aaron Galleries booth at the Modernism art fair, including Mary Henry's Quasar, New York, New York, 2006
Date: 2006
Description: Photograph of the Aaron Galleries Booth at the Modernism exhibition, at Park Place Armory in 2006, including Mary Henry's painting Quasar....
Show morePhotograph of the Aaron Galleries Booth at the Modernism exhibition, at Park Place Armory in 2006, including Mary Henry's painting Quasar. Aaron Brothers, a Chicago gallery, included Mary Henry's work in two art shows at Park Place Armory in 2006, Modernism and Art20. Inscription on verso: "Modernism - Park Avenue Armory 2006 Mary Henry 'Quasar' in booth center Aaron Galleries, Exhibitor." Photographer unknown.
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Collection: Mary Dill Henry Papers, 1913-2021

Title: Photograph of the Aaron Galleries booth at the Modernism art fair, including Mary Henry's Quasar, New York, New York, 2006
Date: 2006
Description: Photograph of the Aaron Galleries Booth at the Modernism exhibition, at Park Place Armory in 2006, including Mary Henry's painting Quasar....
Show morePhotograph of the Aaron Galleries Booth at the Modernism exhibition, at Park Place Armory in 2006, including Mary Henry's painting Quasar. Aaron Brothers, a Chicago gallery, included Mary Henry's work in two art shows at Park Place Armory in 2006, Modernism and Art20. Inscription on verso: "Modernism - Park Avenue Armory 2006 Mary Henry 'Quasar' in booth center Aaron Galleries, Exhibitor." Photographer unknown.
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Collection: Mary Dill Henry Papers, 1913-2021

Title: Keith School, Chicago, Illinois
Creator: Illinois Institute of Technology. Office of Public Relations
Date: 1950-1959
Description: Photograph of the Keith School, which was constructed in 1883 and demolished in 1959. This elementary school, named after Chicago milliner...
Show morePhotograph of the Keith School, which was constructed in 1883 and demolished in 1959. This elementary school, named after Chicago milliner Elbridge G. Keith, opened its doors in 1883. The school, which became increasingly surrounded by the Institute's campus, closed in 1959, and was demolished that same year. Date of photograph is unknown. Date range listed (1950-1959) is approximate.
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Collection: Dan Ryan collection, 1954-1980

Title: Automotive Laboratory, Illinois Institute of Technology campus, Chicago, Illinois
Date: 1917-1946
Description: Photograph of the Automotive Laboratory on the Illinois Institute of Technology campus. The Laboratory is located at 3240 South Federal Street...
Show morePhotograph of the Automotive Laboratory on the Illinois Institute of Technology campus. The Laboratory is located at 3240 South Federal Street, and was constructed in 1917. Also known as: Mechanical Engineering Laboratory (1963-66), Gas Dynamics Laboratory (ca. 1966-ca. 1972), Maintenance Garage (1972-ca. 2000), Armour Institute Laboratory. Date of photograph is unknown. Date range listed is approximate. Photographer unknown.
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Collection: Office of Communications and Marketing photographs, 1905-1999

Title: Pencil drawing, 1973
Creator: Henry, Mary Dill, 1913-2009
Date: 1973-10-01
Description: Untitled pencil drawing by Mary Henry, possibly a sketch or study made during the development of a larger piece. Inscription: "Somber dark, 3...
Show moreUntitled pencil drawing by Mary Henry, possibly a sketch or study made during the development of a larger piece. Inscription: "Somber dark, 3 panels - black brown blue with white stripes."
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Collection: Mary Dill Henry Papers, 1913-2021

Title: Colored pencil drawing, undated
Creator: Henry, Mary Dill, 1913-2009
Description: Untitled colored pencil drawing by Mary Henry, date unknown.
Collection: Mary Dill Henry Papers, 1913-2021

Title: Photograph of the Aaron Galleries booth at the Art 20 art fair, including Mary Henry's The Chelsea Way, New York, New York, 2006
Date: 2006
Description: Photograph of the Aaron Galleries Booth at the Art 20 exhibition, at Park Place Armory in 2006, including Mary Henry's painting The Chelsea...
Show morePhotograph of the Aaron Galleries Booth at the Art 20 exhibition, at Park Place Armory in 2006, including Mary Henry's painting The Chelsea Way visible at right. Inscription on verso: "Art 20 - Park Ave. Armory 2006 Mary Henry 'The Chelsea Way' on the aisle Aaron Galleries Booth."
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Collection: Mary Dill Henry Papers, 1913-2021

Title: TechNews, March 29, 2011
Creator: Illinois Institute of Technology
Date: 2011-03-29, 2011-03-29
Collection: Technology News print collection, 1940-2019

Title: Ink Drawings, 1981
Creator: Henry, Mary Dill, 1913-2009
Date: 2/17/1981
Description: Untitled ink drawings by Mary Henry. Inscription on verso reads "8' x 6' Feb 17 81" and also contains what appear to be mathematical...
Show moreUntitled ink drawings by Mary Henry. Inscription on verso reads "8' x 6' Feb 17 81" and also contains what appear to be mathematical calculations.
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Collection: Mary Dill Henry Papers, 1913-2021

Title: Ink and Colored Pencil Drawings, 1981
Creator: Henry, Mary Dill, 1913-2009
Date: 1981-03-01
Description: Untitled ink and colored pencil sketches by Mary Henry. Drawings are found on both sides of the sheet. Inscription on verso reads "March 1 '81."
Collection: Mary Dill Henry Papers, 1913-2021

Title: Ink and Colored Pencil Drawings, 1981, verso
Creator: Henry, Mary Dill, 1913-2009
Date: 1981-03-01
Description: Untitled ink and colored pencil sketches by Mary Henry. Drawings are found on both sides of the sheet. Inscription on verso reads "March 1 '81."
Collection: Mary Dill Henry Papers, 1913-2021

Title: Ink and Colored Pencil Drawings, 1981, recto
Creator: Henry, Mary Dill, 1913-2009
Date: 1981-03-01
Description: Untitled ink and colored pencil sketches by Mary Henry. Drawings are found on both sides of the sheet. Inscription on verso reads "March 1 '81."
Collection: Mary Dill Henry Papers, 1913-2021

Title: Investigation in the Uncertainty of Chassis Dynamometer Testing for the Energy Characterization of Conventional, Electric and Automated Vehicles
Creator: Di Russo, Miriam
Date: 2023
Description: For conventional and electric vehicles tested in a standard chassis dynamometer environment precise regulations on the evaluation of their...
Show moreFor conventional and electric vehicles tested in a standard chassis dynamometer environment precise regulations on the evaluation of their energy performance exist. However, the regulations do not include requirements on the confidence value to associate with the results. As vehicles become more and more efficient to meet the stricter regulations mandates on emissions, fuel and energy consumption, traditional testing methods may become insufficient to validate these improvements, and may need revision. Without information about the accuracy associated with the results of those procedures however, adjustments and improvements are not possible, since no frame of reference exists. For connected and automated vehicles, there are no standard testing procedures, and researchers are still in the process of determining if current evaluation methods can be extended to test intelligent technologies and which metrics best represent their performance. For these vehicles is even more important to determine the uncertainty associated with these experimental methods and how they propagate to the final results. The work presented in this dissertation focuses on the development of a systematic framework for the evaluation of the uncertainty associated with the energy performance of conventional, electric and automated vehicles. The framework is based on a known statistical method, to determine the uncertainty associated with the different stages and processes involved in the experimental testing, and to evaluate how the accuracy of each parameter involved impacts the final results. The results demonstrate that the framework can be successfully applied to existing testing methods and provides a trustworthy value of accuracy to associate with the energy performance results, and can be easily extended to connected-automated vehicle testing to evaluate how novel experimental methods impact the accuracy and the confidence of the outputs. The framework can be easily be implemented into an existing laboratory environment to incorporate the uncertainty evaluation among the current results analyzed at the end of each test, and provide a reference for researchers to evaluate the actual benefits of new algorithms and optimization methods and understand margins for improvements, and by regulators to assess which parameters to enforce to ensure compliance and ensure projected benefits.
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Title: Using Niobium surface encapsulation and Rhenium to enhance the coherence of superconducting devices
Creator: Crisa, Francesco
Date: 2024
Description: In recent decades, the scientific community has grappled with escalating complexity, necessitating a more advanced tool capable of tackling...
Show moreIn recent decades, the scientific community has grappled with escalating complexity, necessitating a more advanced tool capable of tackling increasingly intricate simulations beyond the capabilities of classical computers. This tool, known as a quantum computer, features processors composed of individual units termed qubits. While various methods exist for constructing qubits, superconducting circuits have emerged as a leading approach, owing to their parallels with semiconductor technology.In recent years, significant strides have been made in optimizing the geometry and design of qubits. However, the current bottleneck in the performance of superconducting qubits lies in the presence of defects and impurities within the materials used. Niobium, owing to its desirable properties, such as high critical temperature and low kinetic inductance, stands out as the most prevalent superconducting material. Nonetheless, it is encumbered by a relatively thick oxide layer (approximately 5 nm) exhibiting three distinct oxidation states: NbO, NbO$_2$, and Nb$_2$O$_5$. The primary challenge with niobium lies in the multitude of defects localized within the highly disordered Nb$_2$O$_5$ layer and at the interfaces between the different oxides. In this study, I present an encapsulation strategy aimed at restraining surface oxide growth by depositing a thin layer (5 to 10 nm) of another material in vacuum atop the Nb thin film. This approach exploits the superconducting proximity effect, and it was successfully employed in the development of Josephson junction devices on Nb during the 1980s.In the past two years, tantalum and titanium nitride have emerged as promising alternative materials, with breakthrough qubit publications showcasing coherence times five to ten times superior to those achieved in Nb. The focus will be on the fabrication and RF testing of Nb-based qubits with Ta and Au capping layers. With Ta capping, we have achieved the best T1 (not average) decay time of nearly 600 us, which is more than a factor of 10 improvements over the bare Nb. This establishes the unique capping layer approach as a significant new direction for the development of superconducting qubits.Concurrently with the exploration of materials for encapsulation strategies, identifying materials conducive to enhancing the performance of superconducting qubits is imperative. Ideal candidates should exhibit a thin, low-loss surface oxide and establish a clean interface with the substrate, thereby minimizing defects and potential sources of losses. Rhenium, characterized by an extremely thin surface oxide (less than 1 nm) and nearly perfect crystal structure alignment with commonly used substrates such as sapphire, emerges as a promising material platform poised to elevate the performance of superconducting qubits.
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Title: The Double-edged Sword of Executive Pay: How the CEO-TMT Pay Gap Influences Firm Performance
Creator: Haddadian Nekah, Pouya
Date: 2024
Description: This study examines the relationship between the chief executive officer (CEO) and top management team (TMT) pay gap and consequent firm...
Show moreThis study examines the relationship between the chief executive officer (CEO) and top management team (TMT) pay gap and consequent firm performance. Drawing on tournament theory and equity theory, I argue that the effect of the CEO-TMT pay gap on consequent firm performance is non-monotonic. Using data from 1995 to 2022 from S&P 1500 US firms, I explicate an inverted U-shaped relationship, such that an increase in the pay gap leads to an increase in firm performance up to a certain point, after which it declines. Additionally, multilevel analyses reveal that this curvilinear relationship is moderated by attributes of the TMT, and the industry in which the firm competes. My findings show that firms with higher TMT gender diversity suffer lower performance loss due to wider pay gaps. Furthermore, when firm executives are paid more compared to the industry norms, or when the firm has a long-tenured CEO, firm performance becomes less sensitive to larger CEO-TMT pay gaps. Lastly, when the firm competes in a masculine industry, firm performance is more negatively affected by larger CEO-TMT pay gaps. Contrary to my expectations, firm gender-diversity friendly policies failed to influence the CEO-TMT pay gap-firm performance relationship.
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Title: Improving Localization Safety for Landmark-Based LiDAR Localization System
Creator: Chen, Yihe
Date: 2024
Description: Autonomous ground robots have gained traction in various commercial applications, with established safety protocols covering subsystem...
Show moreAutonomous ground robots have gained traction in various commercial applications, with established safety protocols covering subsystem reliability, control algorithm stability, path planning, and localization. This thesis specifically delves into the localizer, a critical component responsible for determining the vehicle’s state (e.g., position and orientation), assessing compliance with localization safety requirements, and proposing methods for enhancing localization safety.Within the robotics domain, diverse localizers are utilized, such as scan-matching techniques like normal distribution transformations (NDT), the iterative closest point (ICP) algorithm,probabilistic maps method, and semantic map-based localization.Notably, NDT stands out as a widely adopted standalone laser localization method, prevalent in autonomous driving software such as Autoware and Apollo platforms.In addition to the mentioned localizers, common state estimators include variants of Kalman Filter, particle filter-based, and factor graph-based estimators. The evaluation of localization performance typically involves quantifying the estimated state variance for these state estimators.While various localizer options exist, this study focuses on those utilizing extended Kalman filters and factor graph methods. Unlike methods like NDT and ICP algorithms, extended Kalman filters and factor graph based approaches guarantee bounding of estimated state uncertainty and have been extensively researched for integrity monitoring.Common variance analysis, employed for sensor readings and state estimators, has limitations, primarily focusing on non-faulted scenarios under nominal conditions. This approach proves impractical for real-world scenarios and falls short for safety-critical applications like autonomous vehicles (AVs).To overcome these limitations, this thesis utilizes a dedicated safety metric: integrity risk. Integrity risk assesses the reliability of a robot’s sensory readings and localization algorithm performance under both faulted and non-faulted conditions. With a proven track record in aviation, integrity risk has recently been applied to robotics applications, particularly for evaluating the safety of lidar localization.Despite the significance of improving localization integrity risk through laser landmark manipulation, this remains an under explored territory. Existing research on robot integrity risk primarily focuses on the vehicles themselves. To comprehensively understand the integrity risk of a lidar-based localization system, as addressed in this thesis, an exploration of lidar measurement faults’ modes is essential, a topic covered in this thesis.The primary contributions of this thesis include: A realistic error estimation method for state estimators in autonomous vehicles navigating using pole-shape lidar landmark maps, along with a compensatory method; A method for quantifying the risk associated with unmapped associations in urban environments, enhancing the realism of values provided by the integrity risk estimator; a novel approach to improve the localization integrity of autonomous vehicles equipped with lidar feature extractors in urban environments through minimal environmental modifications, mitigating the impact of unmapped association faults. Simulation results and experimental results are presented and discussed to illustrate the impact of each method, providing further insights into their contributions to localization safety.
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Title: DEVELOPMENT AND APPLICATION OF A NATIONALLY REPRESENTATIVE MODEL SET TO PREDICT THE IMPACTS OF CLIMATE CHANGE ON ENERGY CONSUMPTION AND INDOOR AIR QUALITY (IAQ) IN U.S. RESIDENCES
Creator: Fazli, Torkan
Date: 2020
Description: Americans spend most of their time inside residences where they are exposed to a number of pollutants of both indoor and outdoor origin....
Show moreAmericans spend most of their time inside residences where they are exposed to a number of pollutants of both indoor and outdoor origin. Residential buildings also account for over 20% of total primary energy consumption in the U.S. and a similar proportion of greenhouse gas emissions. Moreover, climate change is expected to affect building energy use and indoor air quality (IAQ) through both building design (i.e., via our societal responses to climate change) and building operation (i.e., via changing meteorological and ambient air quality conditions). The overarching objectives of this work are to develop a set of combined building energy and indoor air mass balance models that are generally representative of both the current (i.e., ~2010s) and future (i.e., ~2050s) U.S. residential building stock and to apply them using both current and future climate scenarios to estimate the impacts of climate change and climate change policies on building energy use, IAQ, and the prevalence of chronic health hazards in U.S. homes. The developed model set includes over 4000 individual building models with detailed characteristics of both building operation and indoor pollutant physics/chemistry, and is linked to a disability-adjusted life years (DALYs) approach for estimating chronic health outcomes associated with indoor pollutant exposure. The future building stock model incorporates a combination of predicted changes in future meteorological conditions, ambient air quality, the U.S. housing stock, and population demographics. Using the model set, we estimate the total site and source energy consumption for space conditioning in U.S. residences is predicted to decrease by ~37% and ~20% by mid-century (~2050s) compared to 2012, respectively, driven by decreases in heating energy use across the building stock that are larger than coincident increases in cooling energy use in warmer climates. Indoor concentrations of most pollutants of ambient origin are expected to decrease, driven by predicted reductions in ambient concentrations due to tighter emissions controls, with one notable exception of ozone, which is expected to increase in future climate scenarios. This work provides the first known estimates of the potential magnitude of impacts of expected climate changes on building energy use, IAQ, and the prevalence of chronic health hazards in U.S. homes.
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Title: Data-Driven Modeling for Advancing Near-Optimal Control of Water-Cooled Chillers
Creator: Salimian Rizi, Behzad
Date: 2023
Description: Hydronic heating and cooling systems are among the most common types of heating and cooling systems installed in older existing buildings,...
Show moreHydronic heating and cooling systems are among the most common types of heating and cooling systems installed in older existing buildings, especially commercial buildings. The results of this study based on the Commercial Building Energy Consumption Survey (CBECS) indicates chillers account for providing cooling in more than half of the commercial office building floorspaces in the U.S. Therefore, to address the need of improving energy efficiency of chillers systems operation, research studies developed different models to investigate different chiller sequencing approaches. Engineering-based models and empirical models are among the popular approaches for developing prediction models. Engineering-based models utilize the physical principles to calculate the thermal dynamics and energy behaviors of the systems and require detailed system information, while the empirical models deploy machine learning algorithms to develop relationships between input and output data. The empirical models compared to the engineering-based approach are more practical in a system’s energy prediction because of accessibility to required data, superiority in model implementation and prediction accuracy. Moreover, selecting near accurate chiller prediction models for the chiller sequencing needs to consider the importance of each input variable and its contribution to the overall performance of a chiller system, as well as the ease of application and computational time. Among the empirical modeling methods, ensemble learning techniques overcome the instability of the learning algorithm as well as improve prediction accuracy and identify input variable importance. Ensemble models combine multiple individual models, often called base or weak models, to produce a more accurate and robust predictive model. Random Forest (RF) and Extra Gradient Boosting (XGBoost) models are considered as ensemble models which offer built-in mechanisms for assessing feature importance. These techniques work by measuring how much each feature contributes to the overall predictive performance of the ensemble.In the first objective of this work the frequency of hydronic cooling systems in the U.S. building stock for applying potential energy efficiency measures (EEMs) on chiller plants are explored. Results show that the central chillers inside the buildings are responsible for providing cooling for more than 50% of the commercial buildings with areas greater than 9,000 m2(~100,000 ft2). In addition, hydronic cooling systems contribute to the highest Energy Use Intensity (EUI) among other systems, with EUI of 410.0 kWh/m2 (130.0 kBtu/ft2). Therefore, the results of this objective support developing accurate prediction models to assess the chiller performance parameters as an implication for chiller sequencing control strategies in older existing buildings. The second objective of the dissertation is to evaluate the performance of chiller sequencing strategy for the existing water-cooled chiller plant in a high-rise commercial building and develop highly accurate RF chiller models to investigate and determine the input variables of greatest importance to chiller power consumption predictions. The results show that the average value of mean absolute percentage error (MAPE) and root mean squared error (RMSE) for all three RF chiller models are 5.3% and 30 kW, respectively, for the validation dataset, which confirms a good agreement between measured and predicted values. On the other hand, understanding prediction uncertainty is an important task to confidently reporting smaller savings estimates for different chiller sequencing control strategies. This study aims to quantify prediction uncertainty as a percentile for selecting an appropriate confidence level for chillers models which could lead to better prediction of the peak electricity load and participate in demand response programs more efficiently. The results show that by increasing the confidence level from 80% to 90%, the upper and lower bounds of the demand charge differ from the actual value by a factor of 3.3 and 1.7 times greater, respectively. Therefore, it proves the significance of selecting appropriate confidence levels for implementation of chiller sequencing strategy and demand response programs in commercial buildings. As the third objective of this study, the accuracy of these prediction models with respect to the preprocessing, selection of data, noise analysis, effect of chiller control system performance on the recorded data were investigated. Therefore, this study attempts to investigate the impacts of different data resolution, level of noise and data smoothing methods on the chiller power consumption and chiller COP prediction based on time-series Extra Gradient Boosting (XGBoost) models. The results of applying the smoothing methods indicate that the performance of chiller COP and the chiller power consumption models have improved by 2.8% and 4.8%, respectively. Overall, this study would guide the development of data-driven chiller power consumption and chiller COP prediction models in practice.
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Title: Scalable Indexing and Search in High-End Computing Systems
Creator: Orhean, Alexandru Iulian
Date: 2023
Description: Rapid advances in digital sensors, networks, storage, and computation coupled with decreasing costs is leading to the creation of huge...
Show moreRapid advances in digital sensors, networks, storage, and computation coupled with decreasing costs is leading to the creation of huge collections of data. Increasing data volumes, particularly in science and engineering, has resulted in the widespread adoption of parallel and distributed file systems for storing and accessing data efficiently. However, as file system sizes and the amount of data ``owned” by users grows, it is increasingly difficult to discover and locate data amongst the petabytes of data. While much research effort has focused on methods to efficiently store and process data, there has been relatively little focus on methods to efficiently explore, index, and search data using the same high-performance storage and compute systems. Users of large file systems either invest significant resources to implement specialized data catalogs for accessing and searching data, or resort to software tools that were not designed to exploit modern hardware. While it is now trivial to quickly discover websites from the billions of websites accessible on the Internet, it remains surprisingly difficult for users to search for data on large-scale storage systems. We initially explored the prospect of using existing search engine building blocks (e.g. CLucene) to integrate search in a high-performance distributed file system (e.g. FusionFS), by proposing and building the FusionDex system, a distributed indexing and query model for unstructured data. We found indexing performance to be orders of magnitude slower than theoretical speeds we could achieve in raw storage input and output, and sought to investigate a new clean-slate design for high-performance indexing and search.We proposed the SCANNS indexing framework to address the problem of efficiently indexing data in high-end systems, characterized by many-core architectures, with multiple NUMA nodes and multiple PCIe NVMe storage devices. We designed SCANNS as a single-node framework that can be used as a building block for implementing high-performance indexed search engines, where the software architecture of the framework is scalable by design. The indexing pipeline is exposed and allows easy modification and tuning, enabling SCANNS to saturate storage, memory and compute resources on different hardware. The proposed indexing framework uses a novel tokenizer and inverted index design to achieve high performance improvement both in terms of indexing and in terms of search latency. Given the large amounts and the variety of data found in scientific large-scale file systems, it stands to reason to try to bridge the gap between various data representations and to build and provide a more uniform search space. ScienceSearch is a search infrastructure for scientific data that uses machine learning to automate the creation of metadata tags from different data sources, such as published papers, proposals, images and file system structure. ScienceSearch is a production system that is deployed on a container service platform at NERSC and provides search over data obtained from NCEM. We conducted a performance evaluation of the ScienceSearch infrastructure focusing on scalability trends in order to better understand the implications of performing search over an index built from the generated tags. Drawing from the insights gained from SCANNS and the performance evaluation of ScienceSearch, we explored the problems of efficiently building and searching persistent indexes that do not fit into main memory. The SCIPIS framework builds on top of SCANNS and further optimizes the inverted index design and indexing pipeline, by exposing new tuning parameters that allows the user to further adapt the index to the characteristics of the input data. The proposed framework allows the user to quickly build a persistent index and to efficiently run TFIDF queries over the built index. We evaluated SCIPIS over three kinds of datasets (logs, scientific data, and file system metadata) and showed that it achieves high indexing and search performance and good scalability across all datasets.
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Title: Colored Pencil Drawings, undated
Creator: Henry, Mary Dill, 1913-2009
Description: Untitled colored pencil drawings by Mary Henry, date unknown. Inscription on verso: "William Winter Comments, PO Box 817, Sausalito"
Collection: Mary Dill Henry Papers, 1913-2021

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