Physical Sciences and Mathematics Commons^™

Visible Opacities Of S-Type Stars: The D³Φ–A³Δ Band System Of Zro, Peter F. Bernath, Manish Bhusal, Jacques Liévin

Chemistry & Biochemistry Faculty Publications

ZrO is a well-studied metal monoxide because of its astrophysical importance in characterizing S stars. The bands of the d³Φ–a³Δ system (γ system) with v′≤4 and v" ≤ 5 are rotationally analyzed using the PGOPHER program to provide spectroscopic constants. The high-resolution ZrO emission spectrum was recorded with a Fourier transform spectrometer using a high-temperature carbon furnace source. New ab initio calculations of the transition dipole moment were carried out in order to determine the vibronic band strengths. The spectroscopic constants, along with the band strengths, are used to calculate a line list for the γ system. This line list …

In Pursuit Of Consumption-Based Forecasting, Charles Chase, Kenneth B. Kahn

Marketing Faculty Publications

[Introduction] Today's most mature, most sophisticated, best-in-class forecasting is what we call consumption-based forecasting (CBF). In contrast, the least sophisticated companies typically do not forecast at all, but rather set financial targets based on management expectations. Companies beginning to use statistical forecasting techniques usually take a supply-centric orientation, relying on time series techniques applied to shipment and/or order history. The next stage of progression is to incorporate promotions data, economic data, and market data alongside supply-centric data so that regression and other advanced analytics can be used. Companies pursing CBF utilize even more advanced capabilities to capture, examine, and understand …

Enhancing Community College Leadership Development Through Ai: Enriching The Andragogical Approach, James Bartlett, Michelle Bartlett

Educational Leadership & Workforce Development Faculty Publications

This proposal is for a work-in-progress that proposes a study to explore the innovative use of Artificial Intelligence (AI), specifically ChatGPT, in advancing the development of training for leadership skills within community college settings. It aims to investigate how AI can be leveraged to provide a personalized and effective learning experience, aligning with the principles of andragogy to cater to adult learners in leadership roles. The study, currently in the data collection phase, anticipates revealing significant insights into the effectiveness of AI in professional development. It seeks to highlight the innovative aspects of AI integration in educational leadership, focusing on …

External Support Structures In Fused Deposition Modeling 3d Printing, Adam Mystkowski

Undergraduate Honors Theses

3D Printing, sometimes also referred to as Additive Manufacturing, is a technology that has garnered a lot of attention in the past several years. While the technology has attracted a significant community of hobbyists, the benefits of the technology have also been recognized in manufacturing. While there are many different types of 3D Printing techniques, the most common type is Fused Deposition Modeling (FDM), mainly due to its relatively low cost compared to other types. However, the technique also present a significant limitation: it tends to struggle with models that have overhanging parts. When a layer is extruded by an …

Community Science Informs Movement And Reproductive Ecology Of Sand Tigers Carcharias Taurus Off North Carolina, United States Of America, Carol Seals Price, Ara Lupton Mcclanahan, Erin J. Burge, Tanya Houppermans, Jason Holmberg

Marine Science

Sand tigers are frequently observed at shipwrecks and other artificial reef habitats off North Carolina (USA), but data about occupancy, movement ecology, and site fidelity are lacking. Spot A Shark USA researchers used Wildbook^© photoidentification software to spot map sand tigers in images provided by recreational SCUBA divers, or collected from remotely operated vehicles, and an offshore live-streaming camera. We uniquely identified 1837 sand tigers, 101 of which were resighted on more than one date between 2005–2021. Sand tigers of both sexes and various ages were found year-round along the northern, central and southern coast. We identified shipwrecks or …

A “War” Over Lobster And Whales: The Issue-Attention Cycle, Media Discourse, And Political Ecology Of Right Whale Science And Conservation In Six Us Newspapers, Marcus Reamer, Catherine Macdonald, Julia Wester, Russell Fielding, Meryl Shriver-Rice

Honors College Faculty Publications

News organizations and journalists are important and influential actors in environmental politics. Their reporting on social and environmental issues often follows issue-attention cycles (IACs) that emphasize drama and problematization to maintain public interest. This study examined nearly 13 years of news coverage to understand the media discourse about the Critically Endangered North Atlantic right whale (NARW) and its conservation. Content analysis and critical discourse analysis were used to analyze 356 texts published in six large US newspapers between January 1, 2010 and March 15, 2023. NARW conservation and management received increased public attention and an IAC began in 2017 after …

Decoding U.S. Tort Liability In Healthcare's Black-Box Ai Era: Lessons From The European Union, Mindy Duffourc, Sara Gerke

Faculty Scholarly Works

The rapid development of sophisticated artificial intelligence (“AI”) tools in healthcare presents new possibilities for improving medical treatment and general health. Currently, such AI tools can perform a wide range of health-related tasks, from specialized autonomous systems that diagnose diabetic retinopathy to general-use generative models like ChatGPT that answer users’ health-related questions. On the other hand, significant liability concerns arise as medical professionals and consumers increasingly turn to AI for health information. This is particularly true for black-box AI because while potentially enhancing the AI’s capability and accuracy, these systems also operate without transparency, making it difficult or even impossible …

Data Science In Finance: Challenges And Opportunities, Xianrong Zheng, Elizabeth Gildea, Sheng Chai, Tongxiao Zhang, Shuxi Wang

Information Technology & Decision Sciences Faculty Publications

Data science has become increasingly popular due to emerging technologies, including generative AI, big data, deep learning, etc. It can provide insights from data that are hard to determine from a human perspective. Data science in finance helps to provide more personal and safer experiences for customers and develop cutting-edge solutions for a company. This paper surveys the challenges and opportunities in applying data science to finance. It provides a state-of-the-art review of financial technologies, algorithmic trading, and fraud detection. Also, the paper identifies two research topics. One is how to use generative AI in algorithmic trading. The other is …

Radiation Pressure Induced Oscillations Of An Optically Levitating Mirror, Satyam Shekhar Jha, Tal Carmon, Fan Cheng, Lev Deych

Publications and Research

Optical Fabry–Perot cavity with a movable mirror is a paradigmatic optomechanical system. While usually the mirror is supported by a mechanical spring, it has been shown that it is possible to keep one of the mirrors in a stable equilibrium purely by optical levitation without any mechanical support. In this work, we expand previous studies of the nonlinear dynamics of such a system by demonstrating a possibility for mechanical parametric instability and the emergence of the “phonon laser” phenomenon.

It Is Normal: The Probability Distribution Of Temperature Extremes, Nir Y. Krakauer

Publications and Research

The probability of heat extremes is often estimated using the non-stationary generalized extreme value distribution (GEVD) applied to time series of annual maximum temperature. Here, this practice was assessed using a global sample of temperature time series, from reanalysis (both at the grid point and the region scale) as well as station observations. This assessment used forecast negative log-likelihood as the main performance measure, which is particularly sensitive to the most extreme heat waves. It was found that the computationally simpler normal distribution outperforms the GEVD in providing probabilistic year-ahead forecasts of temperature extremes. Given these findings, it is suggested …

Locating Liability For Medical Ai, W. Nicholson Price Ii, I. Glenn Cohen

Articles

When medical AI systems fail, who should be responsible, and how? We argue that various features of medical AI complicate the application of existing tort doctrines and render them ineffective at creating incentives for the safe and effective use of medical AI. In addition to complexity and opacity, the problem of contextual bias, where medical AI systems vary substantially in performance from place to place, hampers traditional doctrines. We suggest instead the application of enterprise liability to hospitals—making them broadly liable for negligent injuries occurring within the hospital system—with an important caveat: hospitals must have access to the information needed …

Student Attitudes And Intentions To Use Continuous Authentication Methods Applied To Mitigate Impersonation Attacks During E-Assessments, Andrea E. Green

CCAC Theses and Dissertations

No solution can ultimately eliminate cheating in online courses. However, universities reserve funding for authentication systems to minimize the threat of cheating in online courses. Most higher education institutions use a combination of authentication methods to secure systems against impersonation attacks during online examinations. Authentication technologies ensure that an online course is protected from impersonation attacks. However, it is important that authentication methods secure systems against impersonation attacks with minimal disruption during an examination. Authentication methods applied to secure e-assessments against impersonation attacks may impact a student’s attitude and intentions to use the e-examination system.

In this regard, the research …

Assessing Organizational Investments In Cybersecurity And Financial Performance Before And After Data Breach Incidents Of Cloud Saas Platforms, Munther B. Ghazawneh

CCAC Theses and Dissertations

Prior research indicated that providing inappropriate investment in organizations for Information Technology (IT) security makes these organizations suffer from IT security issues that may cause data breach incidents. Data breaches in cloud Software as a Service (SaaS) platforms lead to the disclosure of sensitive information, which causes disruption of services, damage to the organizational image, or financial losses. Massive data breaches still exist in cloud SaaS platforms which result in data leaks and data theft of customers in organizations.

IT security risks and vulnerabilities cost organizations millions of dollars a year as organizations may face an increase in cybersecurity challenges. …

Development Of Cybersecurity Footprint Index For Manufacturing Companies To Assess Organizational Cyber Posture, John A. Del Vecchio

CCAC Theses and Dissertations

With the continued changes in how businesses work, cyber-attack targets are constantly in flux between organizations, individuals, and various aspects of the supply chain of interconnected companies delivering goods and services. As one of the 16 critical infrastructure sectors, manufacturing is known for complex integrated Information Systems (ISs) incorporated heavily into production operations. Many of these ISs are procured and supported by third parties, also called interconnected entities in the supply chain. Disruptions to manufacturing companies would not only have significant financial losses but would also have economic and safety impacts on society. The vulnerabilities of interconnected companies create inherited …

Enhancing Sentiment Analysis In Niche Domains: Introducing Diverse Datasets And Evaluating Model Performance In Car Dealership And Board Game Reviews, Kimon Andreou

CCAC Theses and Dissertations

The field of Natural Language Processing (NLP) has witnessed significant advancements in recent decades, with text classification emerging as a critical task, particularly in sentiment analysis applications. However, a constant challenge within sentiment analysis research is the scarcity of diverse and specialized labeled datasets. The present dissertation addresses this gap by developing two novel, labeled textual datasets sourced from niche areas: BoardGameGeek.com's top 250 board game reviews and TrustPilot.com's car dealership reviews

The main goal of this dissertation is to enrich sentiment analysis methodologies by providing unique datasets and insights into the performance of current models within specialized domains. By …

Passive Magnetic-Free Broadband Optical Isolator Based On Unidirectional Self-Induced Transparency, Haodong Wu, Jianshan Tang, Miangyuan Chen, Min Xiao, Yanqing Lu, Keyu Xia, Franco Nori

Physics Faculty Publications and Presentations

Achieving a broadband nonreciprocal device without gain and any external bias is very challenging and highly desirable for modern photonic technologies and quantum networks. Here we theoretically propose a passive and magnetic-free all-optical isolator for a femtosecond laser pulse by exploiting a new mechanism of unidirectional self-induced transparency, obtained with a nonlinear medium followed by a normal absorbing medium at one side. The transmission contrast between the forward and backward directions can reach 14.3 dB for a 2π − 5 fs laser pulse. The 20 dB bandwidth is about 56 nm, already comparable with a magneto-optical isolator. This work provides …

การพยากรณ์จำนวนสายโทรศัพท์เข้าของศูนย์บริการข้อมูลทางโทรศัพท์แบบรายครึ่งชั่วโมง, กฤตชญา ประภารัตน์

Chulalongkorn University Theses and Dissertations (Chula ETD)

การวิจัยนี้มีวัตถุประสงค์เพื่อศึกษาโมเดลที่เหมาะสมสำหรับการพยากรณ์จำนวนสายโทรศัพท์เข้าของศูนย์บริการข้อมูลทางโทรศัพท์แบบรายครึ่งชั่วโมง โดยศูนย์บริการข้อมูลทางโทรศัพท์ หรือ Call Center มีบทบาทเป็นศูนย์รวมสายโทรเข้าและโทรออกของธุรกิจ ซึ่งเป็นช่องทางสำคัญในการตอบสนองความต้องการของลูกค้า ไม่ว่าจะเป็นการสอบถามข้อมูล การขอคำแนะนำ หรือแก้ปัญหาต่าง ๆ ศูนย์บริการข้อมูลทางโทรศัพท์จึงมีการจัดวางแผนกำลังคนรับสาย เพื่อให้สอดคล้องกับปริมาณสายโทรศัพท์ที่คาดว่าจะเข้ามา แต่ในบางครั้งการวางแผนจัดกำลังคนรับสายอาจต้องมีการปรับระหว่างวัน เนื่องจากจำนวนสายโทรเข้าอาจมีจำนวนมากกว่าหรือน้อยกว่าที่คาดการณ์ไว้ ซึ่งวิธีการเดิมที่บริษัทใช้ในการคำนวน อาจมีความคลาดเคลื่อน และไม่สามารถปรับตัวเลขได้ภายในระยะเวลาอันสั้น งานวิจัยนี้จึงนำเสนอการพยากรณ์จำนวนสายโทรศัพท์เข้าของศูนย์บริการข้อมูลทางโทรศัพท์แบบรายครึ่งชั่วโมง มีวัตถุประสงค์เพื่อพยากรณ์ปริมาณสายการโทรเข้าช่วงหลัง 10 น. เพื่อช่วยให้ฝ่ายวางแผนกำลังคนเห็นแนวโน้มปริมาณสายที่คาดว่าจะเข้ามา และตัดสินใจปรับแผนการจัดกำลังคนได้อย่างทันท่วงที โดยโมเดลจะจัดกลุ่มและพยากรณ์รูปแบบการกระจายตัวของปริมาณสายโทรเข้า และพยากรณ์จำนวนสายที่คาดว่าจะเข้ามา ผลการทดลองพบว่า โมเดลที่พัฒนาขึ้นมี MAPE อยู่ที่ 20.8% ซึ่งมีประสิทธิภาพดีกว่าวิธีการคำนวนเดิมของบริษัทที่มี MAPE อยู่ที่ 52.7%

Exploring Women`S Perceptions Of Climate Change Impact On Agriculture, Health & Food Security In Upper Hunza, Gilgit Baltistan, Ambreen, Elina Nizar Ali, Taiba Yar Baig, Fozia Parveen

Institute for Educational Development, Karachi

The Hindu Kush Himalayan (HKH) region, renowned for its towering mountains and major river basins, sustains nearly 1.4 billion people worldwide and is pivotal to global food production. Glacial melt from the HKH region nourishes agriculture, livestock, and horticulture, supporting the livelihoods of mountain communities. However, climate change is accelerating the melting of glaciers, and shifts in wet seasons significantly impact food security in these communities. Sectors such as water resources, agricultural land, and human health, particularly women’s health, are significantly affected by these changes. For centuries, agriculture has been the backbone of Gilgit-Baltistan’s economy, with over 70% of livelihoods …

Legendrian Torus And Cable Links, Jennifer Dalton,, John B. Etnyre, Lisa Traynor

Mathematics Faculty Research and Scholarship

We give a classification of Legendrian torus links. Along the way, we give the first classification of infinite families of Legendrian links where some smooth symmetries of the link cannot be realized by Legendrian isotopies. We also give the first family of links that are non-destabilizable but do not have maximal Thurston-Bennequin invariant and observe a curious distribution of Legendrian torus knots that can be realized as the components of a Legendrian torus link. This classification of Legendrian torus links leads to a classification of transversal torus links.

We also give a classification of Legendrian and transversal cable links of …

Examining Information Systems Use To Facilitate The Workplace Accommodation Process, Shiya Cao

Statistical and Data Sciences: Faculty Publications

BACKGROUND: The workplace accommodation process is often affected by ineffective and inefficient communications and information exchanges among disabled employees and other stakeholders. Information systems (IS) can play a key role in facilitating a more effective and efficient accommodation process since IS has been shown to facilitate business processes and effect positive organizational changes.

OBJECTIVE: Since there is little to no research that exists on IS use to facilitate the workplace accommodation process, this paper, as a critical first step, examines how IS have been used in the accommodation process.

METHODS: Thirty-six interviews were conducted with disabled employees from various organizations. …

Questions (And Answers) For Incorporating Nontraditional Grading In Your Statistics Courses, Brenna Curley

Statistical and Data Sciences: Faculty Publications

Nontraditional grading methods have recently become more common, and as with any large pedagogical shift, there are a number of questions to consider when applying a new grading scheme to a course. This article summarizes four types of nontraditional grading and shares experiences from the authors who have applied them to a variety of courses in statistics. This article is structured as a set of questions and answers, seeking to address many of the concerns and considerations that one may face as they transition a course’s grading structure. Supplementary materials for this article are available online.

Boosted Dark Matter Search With The Icarus Detector At The Gran Sasso Underground National Laboratory, Hector Carranza Jr

Physics Dissertations - Archive

The quest to discover dark matter is one of the most pressing topics in modern physics. Evidence of gravitational anomalies is present at different cosmological scales, spanning the stability and rotation of galaxies to the overall density profile of the entire observable Universe. Due to the discrepancy between the mass measured and the gravitational influence on the mass, if General Relativity is to correctly describe gravity at different scales, extra electromagnetically invisible matter termed dark matter must exist. In recent decades, many experiments have been performed to detect dark matter with masses that span many orders of magnitude, from Mass …

Identifying Fact-Checks Helpful For Vetting Factual Claims, Theodora Toutountzi

Computer Science and Engineering Dissertations - Archive

Recent efforts to combat misinformation have increasingly focused on automating the fact-checking process. For fact-checking systems to be automated, they need to recognize claims worth checking, match them with previously fact-checked claims, and determine their truthfulness. We refer to the task of matching unvetted claims with previously fact-checked claims as claim-matching. To be precise, the task is defined as follows: given a factual claim, identifying the fact-checks from a repository that could be helpful, or partially helpful, for vetting the given claim. A solution to this task is useful in practice since claimants often repeat the same claims even if …

Enhancing The Efficiency And Scalability Of Cloud Networking Systems, Jiaxin Lei

Computer Science and Engineering Dissertations - Archive

Overlay networks are the de facto network virtualization technique for providing flexible and customized connectivity among distributed containers in the cloud. Despite their widespread adoption, overlay networks incur significant overhead due to their complexity, resulting in notable performance degradation compared to physical networks.

In this dissertation, I present our three-stage solutions aimed at addressing the challenges of efficiency and scalability in cloud-based container overlay networks: Firstly, we conduct a comprehensive empirical performance study of container overlay networks, identifying crucial parallelization bottlenecks within the kernel network stack. Our observations and root cause analysis uncover that these inefficiencies primarily arise from the …

Charged Excitons And Trions In The Semiconductor Quantum Dot: Electronic Structure And Effect Of External Fields, Jayden Leonard

Theses, Dissertations and Capstones

In this thesis, we are studying the electronic structures and optical properties of charged excitons and trions (i.e., the exciton-associated quasi-particles in semiconductor materials) in quantum dots which have a three-dimensional confinement configuration. We also consider the effects of an external electric and magnetic field on the charged excitons. Initially theorized in 1958, charged excitons are a fairly new phenomenon in physics in which an exciton (i.e., an electron coupled with an electron hole) is coupled with either another electron or another hole (giving either a ‘negative exciton’ or ‘positive exciton’ accordingly). In the completely confined configuration like the quantum …

Rhetoric On Climate Change And The Effects On Public Perceptions, Hailey Mina Rose Dossey

Undergraduate Scholarship

One of the extraordinary challenges humans are facing today is climate change and over the past two decades, the majority of the world has moved from questioning its legitimacy to accepting it as fact. With most people having accepted climate change as a reality, the goal of climate communication has shifted from spreading awareness to motivating audiences to take action. Through this analytical discussion, we will look into effective and ineffective methods of rhetoric as it can help guide us to a better understanding of why certain rhetoric that has previously been successful in other fields may not be the …

Correction: Bayesian Kinetic Modeling For Tracer-Based Metabolomic Data, Xu Zhang, Ya Su, Andrew N. Lane, Arnold Stromberg, Teresa Whei-Mei Fan, Chi Wang

Statistics Faculty Publications

No abstract provided.

Detection Of Tooth Position By Yolov4 And Various Dental Problems Based On Cnn With Bitewing Radiograph, Kuo Chen Li, Yi-Cheng Mao, Mu-Feng Lin, Yi-Qian Li, Chiung-An Chen, Tsung-Yi Chen, Patricia Angela R. Abu

Department of Information Systems & Computer Science Faculty Publications

Periodontitis is a high prevalence dental disease caused by bacterial infection of the bone that surrounds the tooth. Early detection and precision treatment can prevent more severe symptoms such as tooth loss. Traditionally, periodontal disease is identified and labeled manually by dental professionals. The task requires expertise and extensive experience, and it is highly repetitive and time-consuming. The aim of this study is to explore the application of AI in the field of dental medicine. With the inherent learning capabilities, AI exhibits remarkable proficiency in processing extensive datasets and effectively managing repetitive tasks. This is particularly advantageous in professions demanding …

Differences In Student-Ai Interaction Process On A Drawing Task: Focusing On Students' Attitude Towards Ai And The Level Of Drawing Skills, Jinhee Kim, Yoonhee Ham, Sang-Soog Lee

STEMPS Faculty Publications

Recent advances and applications of artificial intelligence (AI) have increased the opportunities for students to interact with AI in their learning tasks. Although various fields of scholarly research have investigated human-AI collaboration, the underlying processes of how students collaborate with AI in a student-AI teaming scenario have been scarcely investigated. To develop effective AI applications in education, it is necessary to understand differences in the student-AI interaction (SAI) process depending on students' characteristics. The present study attempts to fill this gap by exploring the differences in the SAI process amongst students with varying drawing proficiencies and attitudes towards AI in …

The Role Of Shopping Orientations And Intrinsic Experiential Value In Consumer's Willingness To Follow Embodied-Ai's Advice In Fashion Shoe Stores, Christina Soyoung Song, Ji Young Lee, Dooyoung Choi

STEMPS Faculty Publications

This study employs a synthesis of Intrinsic Motivation Theory with three shopping orientations, namely “adventure,” “idea,” and “personalized” shopping, in order to examine their potential influence on individuals' motivation towards shopping. We proposed that consumers’ experiential value of intrinsic enjoyment is an indispensable mediator that affects their willingness to follow EAI’s advice. The study offers novel insights into the way that consumers’ characteristics of influencing others’ clothing consumption affect their shopping motivations to find adventure and stimulation, keep up with new fashion trends and products information, and their preference to patronize stores and interact with store staff on a personal …