Digital Commons Network^™

Digital Stories Of Resilience: A Case Study Of Urban Community College English Learners, Patricia George Hunter

Journal of English Learner Education

This study utilizes a qualitative case study approach to learn how project-based, digital storytelling (DST) voices the resilience of post-secondary English language learners (ELLs) attending a minority-serving, open-access, community college in New York City. Along with many studies that have examined the usefulness of DST in oral production, this research investigates whether project-based digital storytelling enhances students’ understanding of academic content related to resilience and conventional composition. Narrative inquiry (NI) research technique is the basis of the digital story project in an English as a Second Language (ESL) course. In this case, the study relies on observations and artifacts to …

A More Sustainable Future For Dentistry, Jillian Bulter

Virginia Dental Journal

Jillian Bulter, a biomedical engineering major, became involved in a research project at VCU focused on developing biodegradable plastics to replace single-use plastics in dental clinics. Collaborating with Dr. Eser Tüfekçi and Dr. Todd Kitten, the team tested the effectiveness of these novel plastics in preventing bacterial contamination. Although initial results indicated the need for further development, the project represents a significant step towards more sustainable dental practices.

Vcu Enhances Cultural Competency And Provides Better Care For Patients, Giovanni Flores

Virginia Dental Journal

The Hispanic Student Dental Association (HSDA) at Virginia Commonwealth University (VCU) is working to improve healthcare for Hispanic communities by addressing language barriers and promoting cultural competency. With Hispanics making up 19.1% of the U.S. population but only a small percentage of the dental workforce, VCU's HSDA provides Spanish dental terminology booklets and hosts Spanish workshops for students, faculty, and staff. These efforts aim to enhance communication with Spanish-speaking patients and improve their overall healthcare experience.

New Reader Response: An Examination Of Three High-Achieving High School Readers And Their Literacies, Minkyu Kim

Essays in Education

Since its inception, reader response theory has battled misrepresentations. It was reduced to discursive anarchy, perceived as not rigorous, and set apart from important scholarship movements like critical theory. This research argues that by expanding the definition of “reader” in “reader response” to include digital (aka “new”) literacies, the reader-text transaction can be much more inclusive, dynamic, and most importantly, true to our students’ everyday literacies. This article also includes a discussion of why it is so important for teachers to include digital platforms as sites of interrogation in a safe educative setting. By studying the out-of-school literacy behaviors of …

Evidence For Explicitation: Working From Asl Into English, Campbell Mcdermid, Carrie Humphrey, Anita Harding

Journal of Interpretation

A study was done to examine the explicitation and compression strategies used by interpreters working from American Sign Language (ASL) into spoken English. To date, most research has focused only on their work from English into ASL. A review of the literature identified several expansion and compression strategies that interpreters and translators utilize, and these served as a model of coding the data and for triangulation. The methodology for this study was qualitative and descriptive. Twenty-two interpreters volunteered to simultaneously interpret four ASL recorded texts into spoken English, for a total of 88 target texts. The researchers identified 9 expansions …

Second Generation Antipsychotics And Cardiovascular Adverse Effects: Developing Evidence-Based Recommendations For Primary Care Medicine, Sana Borda, Ahn-Dao Lee, Paul F. Bell

HCA Healthcare Journal of Medicine

Background

Second-generation antipsychotic medications (SGAs) are often used by primary care physicians (PCPs) to treat multiple psychiatric diagnoses. SGAs have been connected to a number of adverse effects, including cardiovascular disease. Currently, there are no published evidence-based recommendations addressing SGAs and cardiotoxicity that are directed toward PCPs. This project aims to fill this gap.

Methods

Relevant search terms related to SGAs and cardiovascular disease were identified and then used to search databases (PubMed, PubMed Central, and AccessMedicine). Research studies obtained from the searches were narrowed to include systematic reviews and meta-analyses. The Assessment of Multiple Systematic Reviews-2 (AMSTAR-2) tool was …

Survey: A Study On Image Encryption Using Dna In Bioinformatics, Rana M. Zaki, Zaed S. Mahdi, Matheel E. Abdulmunim

Journal of Soft Computing and Computer Applications

One area of study between computer science and biology is bioinformatics, which deals with methods for collecting, processing, storing, and evaluating biological data. Sequences of RiboNucleic Acid (RNA), DeoxyriboNucleic Acid (DNA), and proteins make up biological data, which has a wide range of uses in domains such as feature extraction, data segmentation, data security, and more. In cryptography, DNA sequences are used as data carriers, enhancing the unique properties of biomolecules. This approach involves using DNA sequences to enhance the security of confidential data that must be transmitted over networks or stored securely. Several DNA-based security techniques have been developed, …

New Feature Selection Using Principal Component Analysis, Zaid Mundher Radeef, Soukaena Hassan Hashem, Ekhlas Khalaf Gbashi

Journal of Soft Computing and Computer Applications

Dimensionality reduction techniques streamline machine learning by reducing data complexity, improving model accuracy, and cutting computational costs. They remove noise and irrelevant features, making models faster and more efficient. These techniques also enhance data visualization and interpretation by condensing data into manageable, insightful dimensions. Ultimately, dimensionality reduction leads to simpler, more interpretable models without sacrificing critical information, making it a cornerstone of efficient data analysis and machine learning applications. Theoretically, feature extraction tends to create new features that encapsulate more information by combining multiple existing features, resulting in more concentrated and informative features. In contrast, feature selection involves choosing a …

Development Of A Hybrid Methodology Of Deep Learning And Machine Learning For Lung Nodule Detection In Medical Computed Tomography Images, Zaed S. Mahdi, Rana M. Zaki, Alaa Kadhim Farhan, Negar Majma

Journal of Soft Computing and Computer Applications

Deep learning and machine learning play an important role in the medical field, helping doctors make accurate, fast and effective diagnosis. Despite the progress achieved in the use of modern technologies in detecting cancerous nodes, current studies still suffer from some challenges and limitations that must be addressed to obtain high efficiency in identifying cancerous nodes. These challenges include using image pre-processing, combining deep learning and machine learning techniques, and constantly adapting to clinical changes, in order to address this. A hybrid methodology has been proposed for detecting cancerous nodules in the lung in medical Computed Tomography (CT) images. It …

Enhancing Image Classification Using A Convolutional Neural Network Model, Zena M. Saadi, Ahmed T. Sadiq, Omar Z. Akif, Marwa M. Eid

Journal of Soft Computing and Computer Applications

In recent years, with the rapid development of the current classification system in digital content identification, automatic classification of images has become the most challenging task in the field of computer vision. As can be seen, vision is quite challenging for a system to automatically understand and analyze images, as compared to the vision of humans. Some research papers have been done to address the issue in the low-level current classification system, but the output was restricted only to basic image features. However, similarly, the approaches fail to accurately classify images. For the results expected in this field, such as …

Improved Rapidly-Exploring Random Tree Using Firefly Algorithm For Robot Path Planning, Dena Kadhim Muhsen, Firas Abdulrazzaq Raheem, Yuhanis Yusof, Ahmed T. Sadiq, Faiz Al Alawy

Journal of Soft Computing and Computer Applications

In robotics, efficient path planning makes robots work independently and move through changing environments over time. This study combines the Rapidly-exploring Random Tree (RRT) architecture with the Firefly Algorithm (FA) to make robot’s path-planning better. The proposed ERRT-FA, which stands for "Enhanced RRT with Firefly Algorithm", generates better routes using Firefly social habits. Plan routes using Firefly social habits can effectively aid in exploring configuration space. The role of the FA is to enhance the RRT algorithm by providing an optimized exploration of the search space, ultimately leading to optimizing the path found by the RRT algorithm and better paths …

Foreword From Editor - 16th Edition: Toward An Inclusive Community Engagement, Yandi Andri Yatmo

ASEAN Journal of Community Engagement

This edition of AJCE defines and elaborates on the idea of inclusive community engagement as a means to involve the community in a meaningful process. ‘Inclusive’ refers to the principles of encompassing everyone, all individuals and groups alike, regardless of their identity, background, characteristics, needs, and perspectives, thereby ensuring that all voices are represented (Hodkinson, 2011). This practice extends beyond individuals with disabilities and embodies broader ideas of equality. Inclusive engagement plays a crucial part in fostering a constructive dialog that incorporates diverse perspectives within a community. Such engagements prioritize community participation in the decision-making process that affects their well-being …

Investigating Brand Awareness, Brand Image, And Perceived Quality On Customer Loyalty, Antaja Nadjwa, Diandra Srivania, Hasna Rizki Mardhiana

Jurnal Vokasi Indonesia

This study investigates the impact of brand awareness, brand image, and perceived quality on customer loyalty, with a focus on Telkomsel users within the Creative Business program at Universitas Indonesia. Employing a quantitative research methodology, data were collected from 50 respondents using a structured questionnaire and analyzed using SPSS 26. The findings reveal that all three factors—brand awareness, brand image, and perceived quality—positively influence customer satisfaction, which in turn significantly enhances customer loyalty. Specifically, perceived quality emerged as the most influential factor driving customer satisfaction, followed by brand image and brand awareness. The study underscores the critical role of perceived …

The Importance And Role Of Public Relations In The Marketing Department At Mangkuluhur Artotel Suites, Habibillah Fitran, Mohammad Ridha

Jurnal Vokasi Indonesia

ABSTRACT The purpose of writing this research is to explain the role of Public Relations in the Marketing Communication Department regarding how to improve brand image, improve marketing and advertising to be more optimal, publish various information and promotions at Mangkuluhur ARTOTEL Suites through various information media and social media, and how to respond to customer complaints, as well as obstacles that occur in hotels related to various customer complaints and poor communication by several individuals within the hotel employees are also accompanied by appropriate solutions. To complete this research, the author collected data by conducting observations accompanied by interviews …

Exploring Student Satisfaction In Learning With Podcast Applications: A Qualitative Study Based On Open-Ended Questions, Indah Permatasari, Peny Meliaty Hutabarat, Erni Adelina

Jurnal Vokasi Indonesia

This study aims to explore student satisfaction with the use of podcasts as a learning medium in the Non-News Radio Production course. A qualitative approach was used, with three open-ended questions posed to students: (1) What different experiences did you have when listening to the course material via podcast?(2) Did listening to the course material through podcasts help you focus on understanding the material? And why? And (3) provide your opinion on the Adapto podcast material shared during the Non-News Radio Production course in the 4th semester. The data obtained was thematically analyzed to identify the main emerging themes. The …

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 …

Gas-Generating Reactive Materials: Design, Evaluation And Effect Of Morphology On Their Ignition And Combustion, Purvam Mehulkumar Gandhi

Dissertations

This work investigates optimizing gas-generating reactive materials, focusing on particle morphology's effect on ignition and combustion behavior. Metal-based gas-generating energetic materials (EMs) are promising alternatives to replace traditional CHNO compounds. Design of advanced metal-based EMs requires consistent ways of evaluating how their characteristics affect their ignition and combustion. Many relevant evaluation approaches exist; however, the results may be difficult to compare directly across different studies. Commonly, experimentalists ignite metal-based EMs in enclosed chambers and report pressures, P. However, direct comparison of these pressures is hindered by variations in the chamber volume, V, and the EM mass, m. To standardize the …

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.

Microsoft Word Automatic Paragraph Numbering, Indiana Continuing Legal Education Forum (Iclef)

Indiana Continuing Legal Education Forum 2024

Meeting proceedings of a seminar by the same name, held January 23, 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 …

22nd Annual Family Law Institute, Indiana Continuing Legal Education Forum (Iclef)

Indiana Continuing Legal Education Forum 2024

Meeting proceedings of a seminar by the same name, held November 14-15, 2024.

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 …