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Title: Exhibition announcement for Mary Henry's exhibit, New Constructs, at Cliff Michel Gallery, Seattle, Washington, 1989
Creator: Henry, Mary Dill, 1913-2009, Cliff Michel Gallery
Date: 1989
Description: Exhibition annoucement postcard for Mary Henry's show New Constructs at Cliff Michel Gallery in Seattle, Washington, August 3-27, 1989. The...
Show moreExhibition annoucement postcard for Mary Henry's show New Constructs at Cliff Michel Gallery in Seattle, Washington, August 3-27, 1989. The recto of the card contains an image of Henry's painting Rabat (1989), and the verso contains information about the exhibit, it's opening reception, and Henry's inclusion in the Bumberbiennale, a retrospective art show at the 1989 Bumbershoot Festival in Seattle.
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Collection: Mary Dill Henry Papers, 1913-2021

Title: Exhibition announcement for Mary Henry's work at the Bellevue Art Museum, 2001
Creator: Henry, Mary Dill, 1913-2009, Bellevue Art Museum (Wash.)
Date: 2001
Description: Exhibition annoucement postcard for Mary Henry's North Slope Paintings show and No Limits, a 360-degree, walk-in mural designed by Mary Henry...
Show moreExhibition annoucement postcard for Mary Henry's North Slope Paintings show and No Limits, a 360-degree, walk-in mural designed by Mary Henry that was painted in the second floor gallery at the Bellevue Art Museum (now Bellevue Arts Museum), Bellevue, Washington, 2001. The recto of the postcard contains a detail of Henry's Bellevue Art Museum Mural (2001).
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Collection: Mary Dill Henry Papers, 1913-2021

Title: Exhibition announcement for Mary Henry's show Selected Paintings 1965-1995 at The Linda Cannon Gallery, Seattle, Washington, 1995
Creator: Henry, Mary Dill, 1913-2009, Linda Cannon Gallery
Date: 1995
Description: Exhibition annoucement postcard for Mary Henry's show Selected Paintings 1965-1995 at The Linda Cannon Gallery, Seattle, Washington, October...
Show moreExhibition annoucement postcard for Mary Henry's show Selected Paintings 1965-1995 at The Linda Cannon Gallery, Seattle, Washington, October 18-November 15, 1995. The recto contains a reproduction of Henry's painting Visions of Johanna (acrylic on canvas, 1993). A separate exhibition introducing the work of Jeffrey Simmons is advertised in the gallery's H Room[?] on the card's verso. Text on the verso of the card is cut off, it is not known if this was due to a printing/cutting error or alteration after the fact.
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Collection: Mary Dill Henry Papers, 1913-2021

Title: Exhibition annoucement for Mary Henry's show Selected Paintings 1965-1995 at The Linda Cannon Gallery, Seattle, Washington, 1995
Creator: Henry, Mary Dill, 1913-2009, Linda Cannon Gallery
Date: 1995
Description: Exhibition annoucement postcard for Mary Henry's show Selected Paintings 1965-1995 at The Linda Cannon Gallery, Seattle, Washington, October...
Show moreExhibition annoucement postcard for Mary Henry's show Selected Paintings 1965-1995 at The Linda Cannon Gallery, Seattle, Washington, October 18-November 15, 1995. The recto contains a reproduction of Henry's painting Visions of Johanna (acrylic on canvas, 1993). A separate exhibition introducing the work of Jeffrey Simmons is advertised in the gallery's H Room[?] on the card's verso. Text on the verso of the card is cut off, it is not known if this was due to a printing/cutting error or alteration after the fact.
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Collection: Mary Dill Henry Papers, 1913-2021

Title: Exhibition announcement for Mary Henry's show Recent Paintings and Drawings at the University Gallery, Pacific Lutheran University, Tacoma, Washington, 1987-1988, recto
Creator: Pacific Lutheran University
Date: 1987-1988
Description: Exhibition annoucement postcard for Mary Henry's show Recent Paintings and Drawings at the University Gallery, Pacific Lutheran University,...
Show moreExhibition annoucement postcard for Mary Henry's show Recent Paintings and Drawings at the University Gallery, Pacific Lutheran University, Tacoma, Washington, 1988.
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Collection: Mary Dill Henry Papers, 1913-2021

Title: Exhibition announcement for Mary Henry's show Recent Paintings and Drawings at the University Gallery, Pacific Lutheran University, Tacoma, Washington, 1987-1988, verso
Creator: Pacific Lutheran University
Date: 1987-1988
Description: Exhibition annoucement postcard for Mary Henry's show Recent Paintings and Drawings at the University Gallery, Pacific Lutheran University,...
Show moreExhibition annoucement postcard for Mary Henry's show Recent Paintings and Drawings at the University Gallery, Pacific Lutheran University, Tacoma, Washington, 1988.
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Collection: Mary Dill Henry Papers, 1913-2021

Title: Exhibition announcement for an art exhibition featuring Mary Henry and Mike Sweeney at Childers/Proctor Gallery, Langley, Washington, 1988, recto
Creator: Henry, Mary Dill, 1913-2009, Sweeney, Mike, Childer/Proctor Gallery
Date: 1988
Description: Exhibition annoucement postcard for an art exhibition pairing the paintings of Mary Henry with the sculptures of Mike Sweeney at Childers...
Show moreExhibition annoucement postcard for an art exhibition pairing the paintings of Mary Henry with the sculptures of Mike Sweeney at Childers/Proctor Gallery, Langley, Washington, 1988. The recto contains a detail of one of Mary Henry's paintings and an image of one of Mike Sweeney's sculptures.
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Collection: Mary Dill Henry Papers, 1913-2021

Title: Exhibition announcement for an art exhibition featuring Mary Henry and Mike Sweeney at Childers/Proctor Gallery, Langley, Washington, 1988, verso
Creator: Henry, Mary Dill, 1913-2009, Sweeney, Mike, Childer/Proctor Gallery
Date: 1988
Description: Exhibition annoucement postcard for an art exhibition pairing the paintings of Mary Henry with the sculptures of Mike Sweeney at Childers...
Show moreExhibition annoucement postcard for an art exhibition pairing the paintings of Mary Henry with the sculptures of Mike Sweeney at Childers/Proctor Gallery, Langley, Washington, 1988. The recto contains a detail of one of Mary Henry's paintings and an image of one of Mike Sweeney's sculptures.
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Collection: Mary Dill Henry Papers, 1913-2021

Title: Exhibition announcement for Mary Henry's show Selected Paintings 1965-1995 at The Linda Cannon Gallery, Seattle, Washington, 1995
Creator: Henry, Mary Dill, 1913-2009, Linda Cannon Gallery
Date: 1995
Description: Exhibition annoucement postcard for Mary Henry's show Selected Paintings 1965-1995 at The Linda Cannon Gallery, Seattle, Washington, October...
Show moreExhibition annoucement postcard for Mary Henry's show Selected Paintings 1965-1995 at The Linda Cannon Gallery, Seattle, Washington, October 18-November 15, 1995. The recto contains a reproduction of Henry's painting Visions of Johanna (acrylic on canvas, 1993). A separate exhibition introducing the work of Jeffrey Simmons is advertised in the gallery's H Room[?] on the card's verso. Text on the verso of the card is cut off, it is not known if this was due to a printing/cutting error or alteration after the fact.
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Collection: Mary Dill Henry Papers, 1913-2021

Title: Exhibition announcement for Mary Henry's show Recent Paintings and Drawings at the University Gallery, Pacific Lutheran University, Tacoma, Washington, 1987-1988
Creator: Pacific Lutheran University
Date: 1987-1988
Description: Exhibition annoucement postcard for Mary Henry's show Recent Paintings and Drawings at the University Gallery, Pacific Lutheran University,...
Show moreExhibition annoucement postcard for Mary Henry's show Recent Paintings and Drawings at the University Gallery, Pacific Lutheran University, Tacoma, Washington, 1988.
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Collection: Mary Dill Henry Papers, 1913-2021

Title: Exhibition announcement for an art exhibition featuring Mary Henry and Mike Sweeney at Childers/Proctor Gallery, Langley, Washington, 1988
Creator: Henry, Mary Dill, 1913-2009, Sweeney, Mike, Childer/Proctor Gallery
Date: 1988
Description: Exhibition annoucement postcard for an art exhibition pairing the paintings of Mary Henry with the sculptures of Mike Sweeney at Childers...
Show moreExhibition annoucement postcard for an art exhibition pairing the paintings of Mary Henry with the sculptures of Mike Sweeney at Childers/Proctor Gallery, Langley, Washington, 1988. The recto contains a detail of one of Mary Henry's paintings and an image of one of Mike Sweeney's sculptures.
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Collection: Mary Dill Henry Papers, 1913-2021

Title: Estimation of Platinum Oxide Degradation in Proton Exchange Membrane Fuel Cells
Creator: Ahmed, Niyaz Afnan
Date: 2024
Description: The performance and durability of Proton Exchange Membrane Fuel Cells (PEMFCs) can be significantly hampered due to the degradation of the...
Show moreThe performance and durability of Proton Exchange Membrane Fuel Cells (PEMFCs) can be significantly hampered due to the degradation of the platinum catalyst. The production of platinum oxide is a major cause of the degradation of the fuel cell system, negatively affecting its performance and durability. In order to predict and prevent this degradation, this research examines a novel method to estimate degradation due to platinum oxide formation and predict the level of platinum oxide coverage over time. Mechanisms of platinum oxide formation are outlined and two methods are compared for platinum oxide estimation. Linear regression and two Artificial Neural Network (ANN) models, including a Recurrent Neural Network (RNN) and Feed-forward Back Propagation Neural Network (FFBPNN), are compared for estimation. The estimation model takes into account the influence of cell temperature and relative humidity.Evaluation of relative errors (RE) and root mean square error (RMSE) illustrates the superior performance of RNN in contrast to GT-Suite and FFBPNN. However, both RNN and GT-Suite showcase an average error rate below 5% while the FFBPNN had a higher error rate of approximately 7%. The RMSE of RNN shows mostly less compared to FFBPNN and GT-Suite, however, at 50% training data, GT-Suite shows lowest RMSE. These findings indicate that GT-Suite can be a valuable tool for estimating platinum oxide in fuel cells with a relatively low RE, but the RNN model may be more suitable for real-time estimation of platinum oxide degradation in PEM fuel cells, due to its accurate predictions and shorter computational time. This comprehensive approach provides crucial insights for optimizing fuel cell efficiency and implementing effective maintenance strategies.
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Title: Defense-in-Depth for Cyber-Secure Network Architectures of Industrial Control Systems
Creator: Arnold, David James
Date: 2024
Description: Digitization and modernization efforts have yielded greater efficiency, safety, and cost-savings for Industrial Control Systems (ICS). To...
Show moreDigitization and modernization efforts have yielded greater efficiency, safety, and cost-savings for Industrial Control Systems (ICS). To achieve these gains, the Internet of Things (IoT) has become an integral component of network infrastructures. However, integrating embedded devices expands the network footprint and softens cyberattack resilience. Additionally, legacy devices and improper security configurations are weak points for ICS networks. As a result, ICSs are a valuable target for hackers searching for monetary gains or planning to cause destruction and chaos. Furthermore, recent attacks demonstrate a heightened understanding of ICS network configurations within hacking communities. A Defense-in-Depth strategy is the solution to these threats, applying multiple security layers to detect, interrupt, and prevent cyber threats before they cause damage. Our solution detects threats by deploying an Enhanced Data Historian for Detecting Cyberattacks. By introducing Machine Learning (ML), we enhance cyberattack detection by fusing network traffic and sensor data. Two computing models are examined: 1) a distributed computing model and 2) a localized computing model. The distributed computing model is powered by Apache Spark, introducing redundancy for detecting cyberattacks. In contrast, the localized computing model relies on a network traffic visualization methodology for efficiently detecting cyberattacks with a Convolutional Neural Network. These applications are effective in detecting cyberattacks with nearly 100% accuracy. Next, we prevent eavesdropping by applying Homomorphic Encryption for Secure Computing. HE cryptosystems are a unique family of public key algorithms that permit operations on encrypted data without revealing the underlying information. Through the Microsoft SEAL implementation of the CKKS algorithm, we explored the challenges of introducing Homomorphic Encryption to real-world applications. Despite these challenges, we implemented two ML models: 1) a Neural Network and 2) Principal Component Analysis. Finally, we hinder attackers by integrating a Cyberattack Lockdown Network with Secure Ultrasonic Communication. When a cyberattack is detected, communication for safety-critical elements is redirected through an ultrasonic communication channel, establishing physical network segmentation with compromised devices. We present proof-of-concept work in transmitting video via ultrasonic communication over an Aluminum Rectangular Bar. Within industrial environments, existing piping infrastructure presents an optimal solution for cost-effectively preventing eavesdropping. The effectiveness of these solutions is discussed within the scope of the nuclear industry.
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Title: Large Language Model Based Machine Learning Techniques for Fake News Detection
Creator: Chen, Pin-Chien
Date: 2024
Description: With advanced technology, it’s widely recognized that everyone owns one or more personal devices. Consequently, people are evolving into...
Show moreWith advanced technology, it’s widely recognized that everyone owns one or more personal devices. Consequently, people are evolving into content creators on social media or the streaming platforms sharing their personal ideas regardless of their education or expertise level. Distinguishing fake news is becoming increasingly crucial. However, the recent research only presents comparisons of detecting fake news between one or more models across different datasets. In this work, we applied Natural Language Processing (NLP) techniques with Naïve Bayes and DistilBERT machine learning method combing and augmenting four datasets. The results show that the balanced accuracy is higher than the average in the recent studies. This suggests that our approach holds for improving fake news detection in the era of widespread content creation.
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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: 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: 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: 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: Intraoperative Assessment of Surgical Margins in Head And Neck Cancer Resection Using Time-Domain Fluorescence Imaging
Creator: Cleary, Brandon M.
Date: 2023
Description: Rapid and accurate determination of surgical margin depth in fluorescence guided surgery has been a difficult issue to overcome, leading to...
Show moreRapid and accurate determination of surgical margin depth in fluorescence guided surgery has been a difficult issue to overcome, leading to over- or under-resection of cancerous tissues and follow-up treatments such as ‘call-back’ surgery and chemotherapy. Current techniques utilizing direct measurement of tumor margins in frozen section pathology are slow, which can prevent surgeons from acting on information before a patient is sent home. Other fluorescence techniques require the measurement of margins via captured images that are overlayed with fluorescent data. This method is flawed, as measuring depth from captured images loses spatial information. Intensity-based fluorescence techniques utilizing tumor-to-background ratios do not decouple the effects of concentration from the depth information acquired. Thus, it is necessary to perform an objective measurement to determine depths of surgical margins. This thesis focuses on the theory, device design, simulation development, and overall viability of time-domain fluorescence imaging as an alternative method of determining surgical margin depths. Characteristic regressions were generated using a thresholding method on acquired time-domain fluorescence signals, which were used to convert time-domain data to a depth value. These were applied to an image space to generate a depth map of a modelled tissue sample. All modeling was performed on homogeneous media using Monte Carlo simulations, providing high accuracy at the cost of increased computational time. In practice, the imaging process should be completed within a span of under 20 minutes for a full tissue sample, rather than 20 minutes for a single slice of the sample. This thesis also explores the effects of different thresholding levels on the accuracy of depth determination, as well as the precautions to be taken regarding hardware limitations and signal noise.
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Title: Independence and Graphical Models for Fitting Real Data
Creator: Cho, Jason Y.
Date: 2023
Description: Given some real life dataset where the attributes of the dataset take on categorical values, with corresponding r(1) × r(2) × … × r(m)...
Show moreGiven some real life dataset where the attributes of the dataset take on categorical values, with corresponding r(1) × r(2) × … × r(m) contingency table with nonzero rows or nonzero columns, we will be testing the goodness-of-fit of various independence models to the dataset using a variation of Metropolis-Hastings that uses Markov bases as a tool to get a Monte Carlo estimate of the p-value. This variation of Metropolis-Hastings can be found in Algorithm 3.1.1. Next we will consider the problem: ``out of all possible undirected graphical models each associated to some graph with m vertices that we test to fit on our dataset, which one best fits the dataset?" Here, the m attributes are labeled as vertices for the graph. We would have to conduct 2^(mC2) goodness-of-fit tests since there are 2^(mC2) possible undirected graphs on m vertices. Instead, we consider a backwards selection method likelihood-ratio test algorithm. We first start with the complete graph G = K(m), and call the corresponding undirected graphical model ℳ(G) as the parent model. Then for each edge e in E(G), we repeatedly apply the likelihood-ratio test to test the relative fit of the model ℳ(G-e), the child model, vs. ℳ(G), the parent model, where ℳ(G-e) ⊆ℳ(G). More details on this iterative process can be found in Algorithm 4.1.3. For our dataset, we will be using the alcohol dataset found in https://www.kaggle.com/datasets/sooyoungher/smoking-drinking-dataset, where the four attributes of the dataset we will use are ``Gender" (male, female), ``Age", ``Total cholesterol (mg/dL)", and ``Drinks alcohol or not?". After testing the goodness-of-fit of three independence models corresponding to the independence statements ``Gender vs Drink or not?", ``Age vs Drink or not?", and "Total cholesterol vs Drink or not?", we found that the data came from a distribution from the two independence models corresponding to``Age vs Drink or not?" and "Total cholesterol vs Drink or not?" And after applying the backwards selection likelihood-ratio method on the alcohol dataset, we found that the data came from a distribution from the undirected graphical model associated to the complete graph minus the edge {``Total cholesterol”, ``Drink or not?”}.
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