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Silent Holy Spirit, October-December, 2024

Silent Holy Spirit

A newsletter published for Deaf Catholics in St. Louis, MO

Silent Holy Spirit Finding Aid

Learning Paradigms For Rhythm Detection And Generation Using Mathematical Models, Biophysical And Artificial Neural Networks, Prianka Bose

Dissertations

Humans possess an inherent ability to recognize evenly-spaced rhythms, known as isochronous rhythms, owing to the brain's predisposition to entrain to external auditory stimuli with regular temporal intervals. The central focus of this research is to understand how the brain learns and retains rhythmic time intervals in the context of music. This dissertation studies rhythm detection and generation through mathematical models, biophysical networks, and artificial neural networks, addressing both isochronous and non-isochronous patterns.

A primary focus of the thesis is on isochronous rhythms. In particular, given a perturbation to an isochronous rhythm such as a tempo change or phase shift …

Pushing The Boundaries Of Large Language Models: Innovations And Limitations In Nlp, Finance, And Mathematics, A M Muntasir Rahman

Dissertations

Large Language Models (LLMs) have emerged as transformative tools across a spectrum of domains, yet their practical deployment reveals a blend of remarkable potential and notable limitations. This research explores innovative methodologies to extend the capabilities of LLMs while addressing critical challenges in their evaluation and application. By leveraging rule-based approaches, the in-context learning capabilities of LLMs, and human-in-the-loop validation across three focused studies, this research introduces robust strategies for dataset synthesis, model enhancement, and model assessment in three distinct domains: natural language processing, financial sentiment analysis, and mathematical reasoning

The first study proposes an efficient data augmentation framework, EASE, …

Game-Based Learning With Augmented Reality, Kantida Nanon

Dissertations

Augmented Reality (AR) technology provides an effective and controllable learning environment, especially for complicated, potentially dangerous, or critical content. Effective implementation of interaction and platforms for educational tools can maximize learner engagement and optimize the learning experience. This dissertation explores the potential of AR technology to enhance learning experiences across multiple platforms and subject areas, particularly within chemistry and mathematics. The dissertation is grounded in the field of Human-Computer Interaction (HCI) and explores the potential of AR to increase learner engagement, improve learning outcomes, and transform traditional pedagogical practices.

The dissertation is divided into two parts. The first part examines …

First-Principles Study Of Ferroelectric Properties And Co2 Reduction Reaction Capabilities In Two-Dimensional Monolayers And Heterostructures, Mo Li

Dissertations

Two-dimensional (2D) materials hold significant potential for CO₂ reduction reactions (CO₂RR) due to their high surface-to-volume ratio. However, achieving high selectivity for desired products and overcoming limitations posed by scaling relationships remain challenging. Recent studies suggest that ferroelectric (FE) materials with switchable out-of-plane polarization (OOP) can effectively tune the adsorption behavior, thermodynamics, and kinetics of CO₂RR, offering promising solutions to these challenges. Using density functional theory (DFT) and the Berry phase approach, this work expands the family of 2D ferroelectrics by theoretically identifying Y₂CO₂, Y₂CS₂, and Sc …

Determination Of Electrochemical Parameters For Predicting Reaction Mechanism And Algorithmic Approaches To Pain Assessment, Huize Xue

Dissertations

This dissertation introduces novel advancements in electrochemical kinetics and pain assessment, structured into two main parts. The first part focuses on the comprehensive analysis of the kinetic and mechanistic aspects of electrochemical reactions, utilizing a combination of experimental techniques and simulation methods. A new software tool, Envismetrics, was developed using Python to facilitate the analysis of complex electrochemical data, including cyclic voltammetry (CV), chronoamperometry (CA), and hydrodynamic voltammetry (HDV). The software was rigorously tested and validated with well-characterized redox systems such as the ferricyanide/ferrocyanide couple, dimethylamine borane (DMAB), and Per- and Polyfluoroalkyl Substances (PFAS). It was successfully used to determine …

Differential Item Functioning Of The Region-Based National Examinationequipment, Adi Setiawan, Gulzhaina Kuralbaevna Kassymova, Vianney Mbazumutima, Anggit Reviana Dewi Agustyani

REID (Research and Evaluation in Education)

This research aims to detect Differential Item Functioning (DIF) in the 2014/2015 National Examination Questions in mathematics of junior high schools and equivalent- level schools in the Yogyakarta region as a reference group and the South Kalimantan region as a focus group using the Likelihood Ratio Test (LRT) method, Area Measure Raju, and Lord. A sensitivity analysis was conducted to determine the most sensitive method. The data consisted of 5,465 National Examination papers of the students from the two regions who worked on type A questions. A sample of 1,000 exam papers for each region was established using the simple …

Cme For Family Mediators, Indiana Continuing Legal Education Forum (Iclef)

Indiana Continuing Legal Education Forum 2024

Meeting proceedings of a seminar by the same name, held September 27, 2024.

How To Manage Documents & Email In The Law Practice - Getting Your Digital House In Order!, Indiana Continuing Legal Education Forum (Iclef)

Indiana Continuing Legal Education Forum 2024

Meeting proceedings of a seminar by the same name, held August 13, 2024.

Cme Update For Civil Mediators, Indiana Continuing Legal Education Forum (Iclef)

Indiana Continuing Legal Education Forum 2024

Meeting proceedings of a seminar by the same name, held October 24, 2024.

Handling Cases Involving Eggshell Plaintiffs, Indiana Continuing Legal Education Forum (Iclef)

Indiana Continuing Legal Education Forum 2024

Meeting proceedings of a seminar by the same name, held April 18, 2024.

Law & The Good Life, Indiana Continuing Legal Education Forum (Iclef)

Indiana Continuing Legal Education Forum 2024

Meeting proceedings of a seminar by the same name, held November 19, 2024.

Construction Accident And Commercial Premises Liability Cases, Indiana Continuing Legal Education Forum (Iclef)

Indiana Continuing Legal Education Forum 2024

Meeting proceedings of a seminar by the same name, held September 24, 2024.

Understanding Barriers To Optimal Supervision And Delivery Of The Nationalcertificate (Vocational) Curriculum Through Tvet College Lecturers’Reflective Evaluations, Angelona Rewhydah Williams, Karel Prins, Bongani Innocent Nkambule, Sindile Amina Ngubane

REID (Research and Evaluation in Education)

Propounded by reflective theory, this qualitative case study drew on TVET lecturers' reflective evaluations of factors that they considered to have a bearing on optimal supervision and delivery of the National Certificate (Vocational) curriculum. Data were collected from participants across three campuses of a TVET college in the Eastern Cape Province, South Africa. Twelve lecturers of different seniority were purposively sampled and interviewed in two focus group sessions. The first focus session involved six participants: four post-level 2 and two post-level 3 personnel recognized by the South African Council for Educators (SACE) as "office-based lecturers" and classified within the middle …

Ensemble Learning Models For Large-Scale Time Series Forecasting In Supply Chain, Minjuan Zhang

Dissertations

Machine learning and AI techniques are transforming supply chain forecasting, driven by the expanding availability of data assets. These advanced methods offer powerful opportunities to optimize management processes, reduce operational costs, and enhance strategic decision-making, which is crucial for enterprise success. However, conventional statistical approaches, such as Autoregressive Integrated Moving Average Models (ARIMA), dynamic regression, and Unobserved Component Models (UCMs)—which have long dominated time series forecasting—often fall short in accuracy and scalability. These traditional models face limitations in batch processing, handling large-scale data, addressing uncertainty-induced disruptions, and synchronizing demand-supply scenarios.

To address these challenges, a novel class of AI-powered ensemble …

A Case Report Of Long-Latency Evoked Diaphragm Potentials After Exposure To Acute Intermittent Hypoxia In Post-West Nile Virus Meningoencephalitis, Joseph F. Welch, Erica A. Dale, Jayakrishnan Nair, Paul W. Davenport, Emily J. Fox, Gordon S. Mitchell

Department of Physical Therapy Faculty Papers

We present a case report of a 42-year-old female with post-West Nile virus meningoencephalitis who exhibited unique, long-latency diaphragm potentials evoked by transcranial and cervical magnetic stimulation after exposure to acute intermittent hypoxia (AIH). The subject was recruited for a study investigating AIH effects on respiratory motor function in healthy individuals. She had contracted West Nile virus infection 5 years before assessment that resulted in hospitalization and persistent allodynia but was not reported to the research team. During the study, transcranial (TMS) and cervical (CMS) magnetic stimulation were performed before and 30-60 min after a single presentation of AIH [15, …

Machine Learning Methods For Pattern Recognition Analysis Of Genomic And Molecular Data, Kuang Du

Dissertations

While immune therapies achieve remarkable success in treating various cancers, only a subset of patients achieves a durable clinical response, and many exhibit innate or acquired resistance. Precision medicine aims to tailor treatments to individual patients based on specific biological markers, ensuring that each patient receives the therapy most likely to be effective. Predictive biomarkers and gene signatures offer potential for more personalized treatment strategies by identifying patients likely to benefit. Recent studies suggest that gene signatures, comprising sets of genes, hold predictive value for certain clinical variables. Typically derived from biological expert knowledge, these signatures demonstrate substantial predictive potential, …

Knowledge Diffusion In Networks Of Artificial Learners, Ehsan Beikihassan

Dissertations

The dissertation draws inspiration from the topic of peer learning in the social sciences and the study of information dissemination and knowledge diffusion in network science. In particular, it introduces and studies a setting involving a population or network of artificial learners, with the objective of optimizing aggregate performance measures under constraints on training resources. In this context, natural knowledge diffusion processes in networks of interacting artificial learners are studied. The term "natural" refers to processes that emulate human peer learning, where the internal state and learning processes of students remain largely opaque, and the main degree of freedom lies …

Interactive Visualization Workflows For Mitigating Analytical Uncertainty, Kaustav Bhattacharjee

Dissertations

This dissertation takes a process-centric and stakeholder-first perspective for handling analytical uncertainty: the form of uncertainty that confronts data analysts' insight-generation processes in high-consequence decision-making scenarios. The cost of an incorrect decision when data is used for movie recommendations as opposed to when personal data is used to drive insights or when data-driven modeling is used to drive real-time decisions for maintaining the health of a grid are vastly different in terms of consequences. This dissertation looks at analytical uncertainty in two real-world scenarios: i) how sensitive information leakage can be prevented during the open data release process with data …

Decomposition Of Diisopropyl Methylphosphonate (Dimp) Exposed To Elevated Temperatures And Combustion Products Of Reactive Materials, Elif Irem Senyurt

Dissertations

The safe and efficient destruction of chemical weapon agents (CWAs) stockpiles remains a critical global challenge. Understanding the thermophysical properties, decomposition mechanisms, and interactions of CWAs with their environment is crucial for developing effective strategies to mitigate their threats. Diisopropyl methylphosphonate (DIMP) and Dimethyl methylphosphonate are commonly used nerve agent surrogates. This dissertation focuses on DIMP and DMMP, investigates their properties and behavior under conditions relevant to prompt defeat scenarios.

The thermophysical properties of DIMP and DMMP were experimentally characterized, including vapor-liquid surface tension (3-60 °C) and viscosities of neat and aqueous solutions. Results revealed significant non-ideal behavior in aqueous …

Visual Analytic Techniques For Interpretable Algorithmic Ranking Systems, Jun Yuan

Dissertations

Rankings have a profound impact on the increasingly data-driven society. From leisurely activities like the movies to watch, the restaurants to patronize; to highly consequential decisions, like making educational and occupational choices or getting hired by companies— these are all driven by sophisticated yet mostly opaque algorithmic rankers. A small change in how these rankers order the data items can have profound consequences, like deterioration of the prestige of a university or a job applicant missing out on being on the list of the top candidates for an organization. These scenarios necessitate data-driven and human-centered innovation to make rankers accessible, …

Crowd-Sourced Learning For Computer Graphics Applications, Yunhao Zhang

Dissertations

Computer Graphics (CG) revolves around virtual content creation using computational methods, spanning applications from games to visual effects. Typically, the creation of CG content is led by expert practitioners who guide computational algorithms towards satisfactory results. Thus, creating CG content often requires manual iterations encompassing algorithm design, parameter tuning, and aesthetic feedback. This work investigates how to leverage crowd-sourcing to streamline such creation processes, focusing on animation and simulation. In animation, a novel crowd-sourcing framework is proposed for combat animation, enabling users to analyze motion similarities, and retrieve matching motions using novel crowd-sourced motion features. Such features enable quantifying previously …

Construction Of An Instrument For Evaluating The Teaching Process In Highereducation: Content And Construct Validity, Risky Setiawan, Wagiran Wagiran, Yasir Alsamiri

REID (Research and Evaluation in Education)

This study aims to reveal the content validity, construct validity, and reliability of the instrument for evaluating the teaching process in higher education. This research is development research applying the ADDIE model from Molenda. The indicators evaluated consist of context, inputs, processes, and products. The sample consisted of 1200 students from eight faculties, each represented by three study programs. Data analysis uses three stages: content validity test analysis using the V-Aiken method involving six panellists or experts; construct validity test using Confirmatory Factor Analysis (CFA). Quantitative descriptive analysis and interpretive qualitative analysis used the Miles and Huberman method. The results …

Constructing And Providing Content Validity Evidence Through The Aiken's Vindex Based On The Experts' Judgments Of The Instrument To Measuremathematical Problem-Solving Skills, Nia Kania, Yaya S. Kusumah, Jarnawi Afgani Dahlan, Elah Nurlaelah, Ferit Gürbüz, Ebenezer Bonyah

REID (Research and Evaluation in Education)

Test content-based proof of validity is a type of evidence that supports the validity of a measuring instrument. This research aims to develop a mathematical problem-solving assessment instrument utilizing five experts. This study is classified as developmental research and follows a research design that includes two separate stages: the preliminary design stage and the prototype stage. However, its application is restricted to Prototype 1 and Prototype 2, specifically for expert evaluation. This instrument was designed explicitly for grade VIII students studying mathematics, covering all the topics from the odd semesters. The analysis progressed through three distinct stages— curriculum analysis, content …

Stability Of Estimation Item Parameter In Irt Dichotomy Considering The Number Of Participants, Zulfa Safina Ibrahim, Heri Retnawati, Alfred Irambona, Beatriz Eugenia Orantes Pérez

REID (Research and Evaluation in Education)

This research is related to item response theory (IRT) which is needed to measure the goodness of a test set, while item parameter estimation is needed to determine the technical properties of a test item. Stability of item parameter estimation is conducted to determine the minimum sample that can be used to obtain good item parameter estimation results. The purpose of this study is to describe the effect of the number of test takers on the stability of item parameter estimation with the Bayes method (expected a posteriori, EAP) on dichotomous data. The minimum sample for stability is 1,000 participants …

Predictor Factors For Teacher Innovative Behavior During Curriculum Reform: The Role Of Cognitive Flexibility, Positive Affect, And Negative Affect, Khairunnisa Syafira Dumbi, Stephanie Yuanita Indrasari

REID (Research and Evaluation in Education)

Teacher innovative behavior is a key capability for maximizing teacher performance as well as the student learning process, especially when teachers face new changes in their education system such as curriculum reform. However, insufficient attention has been given to understanding the interaction of predictor factors to encourage teacher innovative behavior. This study aims to assess the role of cognitive flexibility, positive affect, and negative affect in predicting teacher innovative behavior. A cross-sectional and quantitative design was used for this study. The data collection procedure used convenience sampling, with questionnaires distributed online via social media through several teacher communities. Three instruments …

Automatic Generation Of Physics Items With Large Language Models (Llms), Moses Oluoke Omopekunola, Elena Yu Kardanova

REID (Research and Evaluation in Education)

High-quality items are essential for producing reliable and valid assessments, offering valuable insights for decision-making processes. As the demand for items with strong psychometric properties increases for both summative and formative assessments, automatic item generation (AIG) has gained prominence. Research highlights the potential of large language models (LLMs) in the AIG process, noting the positive impact of generative AI tools like ChatGPT on educational assessments, recognized for their ability to generate various item types across different languages and subjects. This study fills a research gap by exploring how AI-generated items in secondary/high school physics aligned with educational taxonomy. It utilizes …

Changing Images Of Favorite Schools After The Student Admission System Reform In Indonesia, Janu Arlinwibowo, Sri Fajar Martono, Ikhya Ulumudin, Hermanto Waruwu, Yufridawati Yufridawati, Yunita Murdiyaningrum, Gupita Nadindra Fatima, Benjamin Leong Tack Khang

REID (Research and Evaluation in Education)

The study aims to unearth public perceptions of the label of favorite schools after the implementation of student admission reform in Indonesia, namely the zoning system, and to explore the underlying causes. Adopting a qualitative method with a phenomenological approach, this study involved participants from nine provincial education services, nine regency education services, 72 teachers, and 72 parents. Data collected through in-depth interviews and focus groups reveal three distinctive perceptions of favorite schools. The first view posits that after the implementation of the zoning system, the quality among schools is relatively similar, indicating that the new policy is effective in …

Online Versus Face-To-Face Instruction: Entry Level Accounting Students Are Performing About The Same, Nancy L. Johnson, Candalyn B. Rade

The North American Accounting Studies

Students today demonstrate strong aptitude for using online learning resources resulting from most completing high school during the COVID-19 pandemic. Learning resources available for instructional design include faculty created, publisher provided, and a plethora of online videos. This study aimed to understand if scores on graded assignments differ between online (OL) and face-to-face (F2F) sections of entry-level accounting, differences in student learning resources access, and if access correlates with performance on graded assignments. Findings revealed students performed similarly in OL and F2F sections on many, but not all graded assignments. Video resource access was higher for OL students and was …

Pengaruh Loneliness Di Tempat Kerja Serta Peran Perceived Organization Support Dan Resilience Terhadap Psychological Well-Being Di Jabodetabek, Nurisqia Caesar Pramadhani

Jurnal Manajemen dan Usahawan Indonesia

This study explores the impact of workplace loneliness on the psychological well-being of Generation Z and Millennial employees in the Greater Jakarta area, considering the role of perceived organisational support and resilience as moderating variables. Using a cross-sectional survey approach with 334 respondents, this study found that loneliness at work negatively affects psychological well-being. In contrast, POS and resilience have a significant positive influence. Resilience was also shown to moderate the relationship between workplace loneliness and psychological well-being, strengthening individuals' ability to deal with loneliness constructively. These results emphasise the importance of developing organisational policies that support employees' social connectedness …