Physical Sciences and Mathematics Commons^™

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 …

Multimodal Fusion For Audio-Image And Video Action Recognition, Muhammad B. Shaikh, Douglas Chai, Syed M. S. Islam, Naveed Akhtar

Research outputs 2022 to 2026

Multimodal Human Action Recognition (MHAR) is an important research topic in computer vision and event recognition fields. In this work, we address the problem of MHAR by developing a novel audio-image and video fusion-based deep learning framework that we call Multimodal Audio-Image and Video Action Recognizer (MAiVAR). We extract temporal information using image representations of audio signals and spatial information from video modality with the help of Convolutional Neutral Networks (CNN)-based feature extractors and fuse these features to recognize respective action classes. We apply a high-level weights assignment algorithm for improving audio-visual interaction and convergence. This proposed fusion-based framework utilizes …

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%

Trends In Monitoring Of Australia’S Threatened Birds (1990–2020): Much Improved But Still Inadequate, Simon J. Verdon, Robert A. Davis, Ayesha Tulloch, Sarah M. Legge, David M. Watson, John C. Z. Woinarski, G. Barry Baker, Joris Driessen, Hayley M. Geyle, Hugh Possingham, Stephen T. Garnett

Research outputs 2022 to 2026

Monitoring is vital to conservation, enabling conservation scientists to detect population declines, identify threats and measure the effectiveness of interventions. However, not all threatened taxa are monitored, monitoring quality is variable, and the various components of monitoring are likely to differ in their rates of improvement over time. We assessed the presence of monitoring and monitoring quality, using a range of metrics, for all Australia’s threatened bird taxa from 1990 to 2020 (four assessments spanning 30 years). We used our assessments to understand decadal trends in the number of taxa monitored; monitoring quality; and the groups that conduct monitoring. The …

Spatially-Aware Speaker For Vision-And-Language Navigation Instruction Generation, Muraleekrishna Gopinathan, Martin Masek, Jumana Abu-Khalaf, David Suter

Research outputs 2022 to 2026

Embodied AI aims to develop robots that can understand and execute human language instructions, as well as communicate in natural languages. On this front, we study the task of generating highly detailed navigational instructions for the embodied robots to follow. Although recent studies have demonstrated significant leaps in the generation of step-by-step instructions from sequences of images, the generated instructions lack variety in terms of their referral to objects and landmarks. Existing speaker models learn strategies to evade the evaluation metrics and obtain higher scores even for low-quality sentences. In this work, we propose SAS (Spatially-Aware Speaker), an instruction generator …

Unleashing The Power Of Internet Of Things And Blockchain: A Comprehensive Analysis And Future Directions, Abderahman Rejeb, Karim Rejeb, Andrea Appolloni, Sandeep Jagtap, Mohammad Iranmanesh, Salem Alghamdi, Yaser Alhasawi, Yasanur Kayikci

Research outputs 2022 to 2026

As the fusion of the Internet of Things (IoT) and blockchain technology advances, it is increasingly shaping diverse fields. The potential of this convergence to fortify security, enhance privacy, and streamline operations has ignited considerable academic interest, resulting in an impressive body of literature. However, there is a noticeable scarcity of studies employing Latent Dirichlet Allocation (LDA) to dissect and categorize this field. This review paper endeavours to bridge this gap by meticulously analysing a dataset of 4455 journal articles drawn solely from the Scopus database, cantered around IoT and blockchain applications. Utilizing LDA, we have extracted 14 distinct topics …

Performance Evaluation Of A Dual-Chamber Plant Microbial Fuel Cell Developed For Electricity Generation And Wastewater Treatment, Mahmood Golzarian, M. Ghiasvand, S. Shokri, M. Bahreini, Fatemeh Kazemi

Research outputs 2022 to 2026

Plant microbial fuel cells (PMFC) have attracted great scholarly attention as a renewable energy source. These cells have three main components: anode, cathode chambers, and a proton exchange membrane. In this study, a dual-chamber plant microbial fuel cell system was designed using Cyperus papyrus and Shewanella oneidensis. The effects of various factors, including the size of the electrodes, the distance between the electrodes, and the inoculation volume of Shewanella oneidensis, on the ability of electricity generation, were scrutinized. The results indicated that increasing the size area of the electrodes from 2 × 2 to 4 × 4 and 6 × …

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 …

Higher Education Faculty Perceptions Of Chatgpt And The Influencing Factors: A Sentiment Analysis Of X, Yoseph Mamo, Helen Crompton, Diane Burke, Christine E. Nickel

STEMPS Faculty Publications

ChatGPT, an AI chatbot developed by OpenAI, was released in November 2022, sparking a significant surge in global awareness and utilization of generative AI across various domains. Although recent studies have acknowledged the significance of ChatGPT in the education sector, they have yet to focus on exploring faculty attitudes toward ChatGPT. We gathered a comprehensive corpus of tweets containing “#ChatGPT” and “#highered” between November 30th, 2022, and April 30th, 2023. We analyzed data by triangulating VADER, NRC lexicon, and ground coding. Findings suggest that 40% of the expressed sentiments were positive, 51% were neutral, and 9% were negative. The study …

Effect Of Resin Bleed Out On Compaction Behavior Of The Fiber Tow Gap Region During Automated Fiber Placement Manufacturing, Von Clyde Jamora, Virginia Rauch, Sergii G. Kravchenko, Oleksandr G. Kravchenko

Mechanical & Aerospace Engineering Faculty Publications

Automated fiber placement is a state-of-the-art manufacturing method which allows for precise control over layup design. However, AFP results in irregular morphology due to fiber tow deposition induced features such as tow gaps and overlaps. Factors such as the squeeze flow and resin bleed out, combined with large non-linear deformation, lead to morphological variability. To understand these complex interacting phenomena, a coupled multiphysics finite element framework was developed to simulate the compaction behavior around fiber tow gap regions, which consists of coupled chemo-rheological and flow-compaction analysis. The compaction analysis incorporated a visco-hyperelastic constitutive model with anisotropic tensorial prepreg viscosity, which …

Efficiently Learning An Encoder That Classifies Token Replacements And Masked Permuted Network-Based Bigru Attention Classifier For Enhancing Sentiment Classification Of Scientific Text, Muhammad Inaam Ul Haq, Khalid Mahmood, Qianmu Li, Ashok Kumar Das, Sachin Shetty, Majid Hussain

VMASC Publications

The exponential growth of scientific literature in digital repositories poses challenges in interpreting complex attitudes within academic texts. Traditional sentiment analysis methods often struggle with nuanced word meanings due to contextual variations. To address this, we propose the Electra-MPNet-based BiGRU attention classifier that extracts the high-level semantic features from citation sentences using the combined strength of Electra and MPNet encoder layers. These features are then combined to extract long-range dependencies through a stacked BiGRU layer. A linear attention mechanism is imposed to estimate the attention weights and context vector which enables the model to selectively focus on relevant information. The …

Machine Learning As A Tool For Early Detection: A Focus On Late-Stage Colorectal Cancer Across Socioeconomic Spectrums, Hadiza Galadima, Rexford Anson-Dwamena, Ashley Johnson, Ghalib Bello, Georges Adunlin, James Blando

Community & Environmental Health Faculty Publications

Purpose: To assess the efficacy of various machine learning (ML) algorithms in predicting late-stage colorectal cancer (CRC) diagnoses against the backdrop of socio-economic and regional healthcare disparities. Methods: An innovative theoretical framework was developed to integrate individual- and census tract-level social determinants of health (SDOH) with sociodemographic factors. A comparative analysis of the ML models was conducted using key performance metrics such as AUC-ROC to evaluate their predictive accuracy. Spatio-temporal analysis was used to identify disparities in late-stage CRC diagnosis probabilities. Results: Gradient boosting emerged as the superior model, with the top predictors for late-stage CRC diagnosis being anatomic site, …

A New Approach For Discriminating Spatially Acquired Sers Spectra Using Antiretroviral Drug Emtricitabine As A Test Sample, Jana Hrncirova, Marguerite R. Butler, Meredith R. Clark, Gustavo F. Doncel, John B. Cooper

Chemistry & Biochemistry Faculty Publications

In this study, an antiretroviral drug emtricitabine (also known as FTC or Emtriva) was detected and quantified down to 40 ng/ml by using surface-enhanced Raman spectroscopy (SERS). Its aqueous standards were tested with two types of silver nanoparticles (colloidal and dendritic) using a specially developed aluminum well plate. The SERS spectra were acquired using a Raman scanning device with 30-mu m spatial resolution. The spectral data were analyzed using a new approach for the discrimination of the spatially acquired spectra based on the Quality index (Qi). After the Qi is calculated, the spectral data are sorted based on the Qi. …