Digital Commons Network^™

Development And Psychometric Validation Of A Short-Form Critical Thinking Scale In Generative Ai Contexts (Genai–Crt): Evidence From Vietnamese Efl Learners, Ngo Cong-Lem, Thang T. Nguyen, Khanh N. H. Nguyen, Quyen N. H. Nguyen

Journal of Educational Technology Development and Exchange (JETDE)

The rapid spread of generative artificial intelligence (GenAI) in education has intensified concerns about its impact on learners’ critical thinking, underscoring the need for reliable instruments to assess how students engage critically with AI-generated content. This study adapted, developed, and initially validated the Generative AI–Critical Thinking (GenAI–CrT) scale, an eight-item short-form instrument designed to capture EFL learners’ critical thinking in AI-enhanced learning contexts. Data from 233 Vietnamese undergraduates and graduates underwent exploratory and confirmatory factor analyses, supporting a theoretically grounded four-factor structure comprising analytical skills, logical reasoning, evidence evaluation, and open-mindedness. The scale demonstrated excellent model fit (χ²(14) = 23.49, …

Speaking Up Online And Offline: The Effects Of Social Media-Based E-Portfolios In Empowering Efl Students' Speaking Performance, I Putu Indra Kusuma, Luh Indrayani

Journal of Educational Technology Development and Exchange (JETDE)

Although e-portfolios are widely acknowledged for enhancing EFL students’ speaking skills, most studies assessed performances offline, leaving limited evidence of their impact across both modes. This study examined the effects of social media-based e-portfolios combined with classroom instruction on students’ speaking performance in online and offline contexts. A mixed-methods experimental design was employed, involving 46 Indonesian university students divided into an experimental and a control group. Data were collected through online and offline pre- and post-speaking tests, a speaking performance rubric, and semi-structured interviews. Quantitative analysis using One-Way MANOVA, Univariate ANOVA, paired sample t-test, and effect size revealed significant improvements …

Research On Online Public Opinion Patterns Under The Boundary Between Local And Non-Local Students In Dse: A Case Study Of Social Media Texts And Comments, Yat Him, Eugene Chan, Chang Liu

Department of Hospitality and Business Management

This study focuses on the topic of local and non-local students in the Hong Kong Diploma of Secondary Education (DSE), collecting 1203 social media texts and comment data from Douyin and Xiaohongshu (Little Red Book) platforms, employing sentiment analysis and topic identification techniques to explore the characteristics of online public opinion patterns. The research findings reveal that overall public opinion exhibits a neutral tendency (79.8%), with an average sentiment score of 0.14. DSE-related discussions totaled 216 entries, local student-related discussions 146 entries, non-local student-related discussions 41 entries, and comparative discussions 35 entries. Significant emotional differences exist among different groups, with …

Hiding An Ear In Plain Sight: On The Practicality And Implications Of Acoustic Eavesdropping With Telecom Fiber Optic Cables, Youqian Zhang, Zheng Fang, Huan Wu, Sze Yiu Chau, Chao Lu, Xiapu Luo

Department of Construction, Environment and Engineering

Optical fibers are widely regarded as reliable communication channels due to their resistance to external interference and low signal loss. This paper demonstrates a critical side channel within telecommunication optical fiber that allows for acoustic eavesdropping. By exploiting the sensitivity of optical f ibers to acoustic vibrations, attackers can remotely monitor sound-induced deformations in the fiber structure and further recover information from the original sound waves. This issue becomes particularly concerning with the proliferation of Fiber-to-the-Home (FTTH) installations in modern buildings. Attackers with access to one end of an optical fiber can use commercially available Distributed Acoustic Sensing (DAS) systems …

A Comparative Case Study Of Esg Integration Strategies In Hong Kong Region Using The Cepar Methodology, Xiaoying Lu, Xiaofang Liu, Chi Him, Alpha Tsang, Juan Zhang, Yuxi Chen

Department of Construction, Environment and Engineering

This study adopts the five-stage CEPAR (Challenge, Evaluation, Planning, Action, Review) methodology to conduct a comparative case analysis of ESG integration strategies across five key sectors (Real Estate, Financial Services, Technology, Logistics, and Retail) in Hong Kong region, based on simulated data of 15 enterprises. It explores sectoral differences in ESG implementation maturity, operational practices, developmental barriers, and alignment with the United Nations Sustainable Development Goals. The results reveal significant cross-sector maturity disparities: Financial Services ranks the highest (84.4/100) with robust evaluation and review mechanisms, followed by Technology (82.0), Retail (77.4), and Real Estate (73.2), while Logistics scores the lowest …

Effects Of Particle Size Difference In Two Different Sweet Bran Products On Total Tract Digestibility And Rumen Ph, Emily K. Hoefling, Anna Kobza, Jessica L. Miller, Maggie E. Youngers, Galen E. Erickson, Jim C. Macdonald

Nebraska Beef Cattle Reports

Summary with Implications

Seven ruminally fistulated heifers were utilized in a 6 x 7 row-column design to evaluate two different Sweet Bran particle size products (1.8 or 2.5 mm) included at 13%, 18%, or 23% of the diet (DM) on total tract digestibility and rumen fermentation parameters. The treatment design was a 2 x 3 factorial. Rumen pH was reduced and organic matter digestibility tended to be reduced with the small particle size when Sweet Bran was included at 13% of the diet. Both NDF digestibility and dietary digestible energy concentration tended to improve with the larger particle size. The …

Use Of Virtual Fences To Co-Fence Two Groups Of Cattle With Adjacent Virtual Boundaries, Thomas E. Aquino, Mary E. Drewnoski, Biquan Zhao, Pedro Henrique Jota Fernandes, Isaque F. Vicci, Mitchell B. Stephenson, Yijie Xiong

Nebraska Beef Cattle Reports

Summary with Implications

While virtual fencing (VF) has proven effective in managing cattle, limited data exist on using it to manage two separate groups of cattle within the same area. If successful, this approach could reduce infrastructure costs and increase management flexibility. In this trial, VF-trained steers (n = 39) were placed in pastures with either no neighboring cattle (isolated) or next to a separate group with only a VF boundary between them (co-fenced). Containment exceeded 99% across all cattle, demonstrating that VF creates effective boundaries regardless of fence treatment. There was no statistical difference in the number of audio …

Trauma-Informed Approach In The Carceral System, Katherine Means, Adrienne Jackson, Tayia West, Kenneth Hunter

The Grace E. Harris Leadership Institute Publications

This proposal seeks to establish a foundation to drive the development of a comprehensive, trauma-informed framework for Virginia Department of Corrections by identifying opportunities and recommendations for implementation.

This proposal aims to improve VADOC’s adherence to a true structure of rehabilitation, leading to the adoption of a statewide trauma-informed corrections statute.

How Does Inclusive Education Affect Students With Autism Spectrum Disorder In Elementary Schools?, Kacie M. Coe

All Electronic Theses and Dissertations

Children diagnosed with autism are at an all-time high of 1 in 31 children (Centers for Disease Control and Prevention 2025). What does this mean for our schools and students with autism? Inclusive education is more renowned than ever. What is now known as the Individuals with Disabilities Education Act (IDEA) was enacted in 1975, and guarantees every child with a disability access to a free appropriate public education (FAPE) in the least restrictive environment (LRE). Inclusion, in theory, appears to be the right decision for all our students, but what are the schools doing to prepare for these exceptional …

Development Of A Functional Artisanal Sugar-Free Ice Cream And Study Of Physicochemical Behavior, Popescu Mariana, Dabija Adriana, Chetrariu Ancuta

Annals. Food Science and Technology

The use of natural sweeteners in ice cream production could meet the demands of modern consumers focused on natural and nutritionally balanced foods. The objective of this work was to fill the gap in the basic knowledge about the effects of sugar-free apple concentrate, a natural substitute for sugar, rose petal jam and oat milk on the properties of artisanal ice cream. As a reference sample (REF), an ice cream sweetened with sugar-free apple concentrate, rose petal jam and oat milk base was produced, then increasing the amount of apple concentrate and the amount of oat milk, and in parallel …

Heller Was Egregiously Wrong And Should Be Overruled, Henry J. Renk

Roger Williams University Law Review

No abstract provided.

Potenza V. Deutsche Bank Nat’L Trust Co., 338 A.3d 1050 (R.I. 2025)., Áine Guyer

Roger Williams University Law Review

No abstract provided.

Runey V. Faring, 336 A.3d 16 (R.I. 2025)., Jessica Galego

Roger Williams University Law Review

No abstract provided.

Closing The Door On Housing Discrimination: Why Rhode Island Must Enact A Fair Chance In Housing Act, Jessica Galego

Roger Williams University Law Review

No abstract provided.

The Flock Above Us: The Unconstitutionality Of Automated License Plate Readers, Evan Degaitas

Roger Williams University Law Review

No abstract provided.

A Personal Take: An Argument In Favor Of Adopting The Uniform Partition Of Heirs Property Act In Rhode Island, Isiah Dipina, Natasha Varyani

Roger Williams University Law Review

No abstract provided.

State V Mangru, 337 A.3d 1009 (R.I. 2025)., Stephen Olive

Roger Williams University Law Review

No abstract provided.

New England Prop. Servs. Grp., Llc V. Ngm Ins. Co., 329 A.3d 889 (R.I. 2025)., Justin Edward Keyes

Roger Williams University Law Review

No abstract provided.

Trial By Character, Hillel J. Bavli

Faculty Journal Articles and Book Chapters

In this Article, I argue that courts regularly deviate from Federal Rule of Evidence 404(b), which prohibits character evidence—evidence of a defendant’s past misdeeds offered to prove that the defendant acted in conformity with a certain character trait on the occasion in question. These deviations undermine the fairness of a trial and the presumption of innocence. The Article addresses this problem in three ways. First, it explains how courts have misinterpreted Rule 404(b)—an error that I call the permitted-purpose fallacy—and how they have fortified this misinterpretation with a body of flawed principles and precedent. Second, it reports the results of …

1981, Carliss N. Chatman

Faculty Journal Articles and Book Chapters

42 U.S.C. § 1981 should have solved a pervasive problem in American capitalism—when white economic interests do not converge with the contract rights of Black people, they are excluded from the market in a way that causes systemic harm. This Article proposes that the failure to enforce 1981 in the past may render it more harmful than beneficial in the present climate of retrenchment. The realities of racism combine with the lack of economic interest convergence to make combatting contract inequality on a contract-by-contract basis legally precarious, nearly impossible to properly evaluate, and difficult to economically incentivize. This is in …

Chat M.D., Nathan Cortez

Faculty Journal Articles and Book Chapters

Large language models (LLMs) such as Claude and ChatGPT are the most powerful artificial intelligence (AI) systems ever created, and they are being used to diagnose and treat patients. But LLMs have been shown to be unreliable, unpredictable, and unsafe on occasion. New AI guidelines recommend hundreds of standards, such as ‘transparency’, ‘trustworthiness’, and ‘safety’. But there is deep uncertainty whether these are sufficient. The literature focuses mostly on which standards best suit AI models, not on how to transmute standards into law. This article does that by considering AI guidelines as a starting point, then evaluating whether existing frameworks …

Negotiated Outcomes And Abbreviated Trials In Criminal Cases: Balancing Fairness And Efficiency In Three Legal Systems, Michele Caianiello, Jenia I. Turner, Thomas Weigend

Faculty Journal Articles and Book Chapters

Facing expanded criminal dockets, justice systems around the world are looking for ways to expedite proceedings and save resources while still offering credible procedures for adjudicating criminal cases. In the United States, defendants tend to face an all-or-nothing choice between two alternatives: a full trial at which all relevant evidence is presented and examined; or a plea bargain leading to a conviction without any presentation of evidence and the waiver of the defendant’s procedural rights in exchange for a reduced sentence. Even in routine misdemeanor cases, a full trial requires substantial expenditures of resources, and its procedural complexity may be …

Physics-Informed Temperature Prediction Of Lithium-Ion Batteries Using Decomposition-Enhanced Lstm And Bilstm Models, Seyed Saeed Madani, Yasmin Shabeer, Michael Fowler, Satyam Panchal, Carlos Ziebert, Hicham Chaoui, François Allard

Electrical & Computer Engineering Faculty Publications

Accurately forecasting the operating temperature of lithium-ion batteries (LIBs) is essential for preventing thermal runaway, extending service life, and ensuring the safe operation of electric vehicles and stationary energy-storage systems. This work introduces a unified, physics-informed, and data-driven temperature-prediction framework that integrates mathematically governed preprocessing, electrothermal decomposition, and sequential deep learning architectures. The methodology systematically applies the governing relations to convert raw temperature measurements into trend, seasonal, and residual components, thereby isolating long-term thermal accumulation, reversible entropy-driven oscillations, and irreversible resistive heating. These physically interpretable signatures serve as structured inputs to machine learning and deep learning models trained on temporally …

Markov Chain Wave Generative Adversarial Network For Bee Bioacoustic Signal Synthesis, Kumudu Samarappuli, Iman Ardekani, Mahsa Mohaghegh, Abdolhossein Sarrafzadeh

Electrical & Computer Engineering Faculty Publications

This paper presents a framework for synthesizing bee bioacoustic signals associated with hive events. While existing approaches like WaveGAN have shown promise in audio generation, they often fail to preserve the subtle temporal and spectral features of bioacoustic signals critical for event-specific classification. The proposed method, MCWaveGAN, extends WaveGAN with a Markov Chain refinement stage, producing synthetic signals that more closely match the distribution of real bioacoustic data. Experimental results show that this method captures signal characteristics more effectively than WaveGAN alone. Furthermore, when integrated into a classifier, synthesized signals improved hive status prediction accuracy. These results highlight the potential …

Machine Learning-Based Lifetime Prediction Of Lithium Batteries: A Comparative Assessment For Electric Vehicle Applications, Abdelilah Hammou, Raffaele Petrone, Demba Diallo, Boubekeur Tala-Ighil, Philippe Makany Boussiengue, Hicham Chaoui, Hamid Gualous

Electrical & Computer Engineering Faculty Publications

This paper evaluates and compares four data-driven methods (Gaussian Process Regression (GPR), echo state network (ESN), gated recurrent unit (GRU), and long short-term memory (LSTM)) for lithium-ion capacity prognostics adapted to electric vehicle conditions. This comparison aims to find the most efficient prognosis method considering two constraints: the limitation of computational power and the unavailability of on-board capacity measurement that requires full charge and discharge conditions. The machine learning models are trained using capacity values estimated under vehicle conditions. The ageing data is collected from cycling tests of two battery chemistries, Lithium Fer Phosphate (LFP) and Nickel Manganese Cobalt (NMC), …

An Explainable Cs-Mitigation Triangular (Ecsmt) Framework To Secure Graph Neural Networks, Sabah Ettahri, Sergio Pallas Enguita, Chung-Hao Chen, Wen-Chao Yang

Electrical & Computer Engineering Faculty Publications

This research addresses cyber risk by defending against backdoor attacks on Graph Neural Networks (GNNs). We propose the Explainable Complex System-Mitigation Triangular (ECSMT) Framework, which integrates Robust Training, Graph Regularization, and Data Sanitization into a lightweight, hardware-efficient defense layer. To evaluate structural generalizability, we conducted empirical evaluations across three distinct benchmark domains (AIDS, MUTAG, and PROTEINS) using a Graph Isomorphism Network (GIN) backbone. Under a baseline 5% backdoor subgraph trigger injection ratio, ECSMT achieves excellent utility retention, securing a Clean Accuracy (CA) of 97.33% (±0.62%) while reducing the Attack Success Rate (ASR) from 97.00% down to 69.45% on the primary …

Dynamic Direct Voltage Control Under Maximum Torque Per Ampere For Interior Pmsms, Mohamad Alzayed, Hicham Chaoui, Alaref Elhaj

Electrical & Computer Engineering Faculty Publications

A novel method for controlling the speed of interior permanent magnet synchronous motors (IPMSMs), known as the current-sensing-based dynamic direct voltage control method under the maximum torque per ampere (MTPA) concept, is introduced. This technique achieves precise tracking of machine velocity by determining the optimal combination of voltage amplitude and angle for each specific motor velocity and current/load condition. Unlike previous studies, this approach takes into account the transient model of the machine, resulting in improved accuracy during dynamic operating conditions compared with existing methods in the literature. Moreover, a comparative analysis is conducted involving different direct voltage MTPA speed …

Generalized Inverter Fault Detection Using Normalized Current Features And A Lightweight Bilstm Network, Mohammad Zamani Khaneghah, Mohamad Alzayed, Hicham Chaoui

Electrical & Computer Engineering Faculty Publications

Fault detection and diagnosis of three-phase inverter-fed motor drives is essential for ensuring system reliability, safety, and continuous operation in applications such as electric vehicles and industrial automation. This paper proposes a data-driven fault detection framework based on normalized current features and a lightweight bidirectional long short-term memory (BiLSTM) network which can be generalized to different motor power rating in the same controller system. A compact set of six time-domain features, consisting of the mean and root-mean-square (RMS) values of the phase currents, is extracted and normalized with respect to the average RMS value. This normalization effectively removes dependency on …

Fault Tolerance Of Accelerated Asynchronous Fixed-Point Iterations On Flexible Computing Infrastructure, Evan Coleman, Masha Sosonkina

Electrical & Computer Engineering Faculty Publications

Asynchronous iterative methods tolerate straggling processors by allowing workers to proceed with stale data, but at a cost: the iterates become inconsistent, potentially degrading convergence. We investigate whether convergence accelerators such as Anderson acceleration compensate for this degradation. We experimentally study three fixed-point iterations: the Jacobi method for sparse linear systems, value iteration for the Bellman equation, and the Hartree–Fock self-consistent field (SCF) iteration. The experiments are conducted using a high-performance execution framework, Ray, which abstracts the complexity of distributed systems and enables code parallelization and fault injection with minimal changes.

We establish two main results. First, straggler tolerance is …

Automated Writer And Acquisition-Condition Classification Of Digitally Captured Handwriting Using Statistical Dynamic Features And Support Vector Machines, Long-Huang Tsai, Hsiang-Ju Lai, Wen-Chao Yang, Jiajun Jiang, Chung-Hao Chen

Electrical & Computer Engineering Faculty Publications

Digitally captured handwriting preserves pen trajectories and dynamic signals, but it also records hardware- and input-dependent properties that can confound forensic interpretation. This study revises a support vector machine (SVM) screening framework using 16,500 samples from 30 writers, 11 writing-content categories, and five acquisition conditions spanning three tablets and stylus or finger input. Twenty-four raw and derived time-series variables were summarized by maximum, minimum, mean, median, and standard deviation, yielding 120 features; the mode statistic was removed. Writing direction and angular velocity were recalculated with atan2-based vector formulas. Unavailable device/API channels were encoded as zero, and Z-score parameters were estimated …