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Ethnographically Informed Research Exploring The Impact Of Embedding Trauma-Informed Principles In A Befriending Programme For Refugees., Zahraa Abdulreda

School of Psychology Theses

Refugees often experience trauma from war, displacement, and post-migration stressors, leading to collective and transgenerational trauma. This study explored the impact of embedding trauma-informed principles (TIP) within a refugee befriending programme, where refugees were paired with local volunteers. Ethnographic Action informed research was used through completing interviews, observations, and a focus group. Participants included five befrienders and seven refugees, alongside observational data. Thematic and framework analyses identified five key themes: The Relationship, Safety for Befrienders, Inclusivity, Supporting Befriendees with Integration, and Challenges of Befriending. TIP enhanced understanding of how community-based, trauma-informed interventions can support refugee recovery and resilience. The study …

Exploring The Relationship Between Attachment State Of Mind, Emotional Development And Distress In Adults With Intellectual Disabilities – A Pilot Study, Amy Pantridge

School of Psychology Theses

BackgroundAttachment theory and emotional development are increasingly considered important for understanding distress in people with intellectual disabilities, yet no prior studies have empirically explored relationships between these constructs.MethodAdults with intellectual disabilities and informants were recruited from UK community organisations. Participants completed an attachment measure (AAP), brief cognitive measure, and questionnaire on perceived emotional support. Informants completed a distress measure (HoNOS-LD), emotional development measure (SED-S), and provided feedback on the SED-S. ResultsNo significant relationship was found between attachment and emotional development, though some specific associations emerged. Unresolved attachment was common. Discrepancies were observed between informant-reported and participant-reported data. Informants found elements …

Vcu And The 2025 Virginia Course Materials Survey, Abbey Childs

Scholarship about Open Education

In 2025, VIVA distributed an updated Virginia Course Materials Survey. Its goal was to build on the first iteration of the survey, providing updated data for the areas explored in the original survey, along with new data to address the changing open and affordable landscape in Virginia. The 2025 survey aimed to answer the following questions:

1. What is the impact of course material costs on educational equity among Virginia students?

2. What course content materials do students find to be most beneficial to their learning?

3. What barriers are presented to students due to course material costs and how can those barriers …

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Is Al-Driven Threat Detection An Effective Substitute For Current Threat Detection Architectures?, Connor J. Ford

Annual Research Symposium

This research evaluates the use of Artificial Intelligence (Al] in the development of cyber defense systems.

Delayed Tooth Eruption As An Early Clinical Indicator Of Genetical Tooth Agenesis: A Family-Based Study Of Cases With Whole-Exome Sequencing, Yu-Chen Jeng, I-Ting Chen, Hui-Ching Cheng, Hsin-Yu Huang, Chao-Kai Hsu, Yu-Fen Yen

Journal of Dental Sciences

Delayed tooth eruption is frequently considered a benign developmental variation but may represent an early sign of genetically driven tooth agenesis. We evaluated a 22-month-old female presenting with markedly delayed eruption (only eight primary teeth) and a positive family history of ectodermal features. Given the inconclusive early radiographic findings, whole-exome sequencing (WES) was utilized. WES revealed the proband carried a heterozygous EDARADD variant (NM_080738:c.328G>T; p.Asp110Tyr). Subsequent familial segregation analysis identified an additional heterozygous WNT10A variant (NM_025216:c.637G>A; p.Gly213Ser) within the broader family. The EDARADD variant alone was associated with varying presentations from normal dentition to delayed eruption. Furthermore, the …

A Scientometric Study On Research Trends And Characteristics Of Tooth Intentional Replantation, Yan Zhou, Simin Deng, Wenhua Xu, Wei Liu, Yibo Guo, Mingyi Zhu

Journal of Dental Sciences

Background/purpose: Intentional replantation is regarded as a final strategy to preserve natural teeth affected by inaccessible endodontic and periodontal disease. The purpose of this study was to analyze the scientometric characteristics and research trends of tooth intentional replantation.

Materials and methods: All the papers on intentional replantation were comprehensively retrieved from the Scopus database. The years of publication were divided into before 2017 and after 2017 in the analysis of research trends.

Results: There were 356 papers on intentional replantation, with total citations of 5562 and the h index of 42. The trend of bone substitutes, boron …

Parallel Multi Objective Shortest Path Update Algorithm In Large Dynamic Networks, S. M. Shovan, Arindam Khanda, Sajal K. Das

Computer Science Faculty Research & Creative Works

The multi objective shortest path (MOSP) problem, crucial in various practical domains, seeks paths that optimize multiple objectives. Due to its high computational complexity, numerous parallel heuristics have been developed for static networks. However, real-world networks are often dynamic where the network topology changes with time. Efficiently updating the shortest path in such networks is challenging, and existing algorithms for static graphs are inadequate for these dynamic conditions, necessitating novel approaches. Here, we first develop a parallel algorithm to efficiently update a single objective shortest path (SOSP) in fully dynamic networks, capable of accommodating both edge insertions and deletions. Building …

V2vdiscs: Vehicle To Vehicle Distributed Charge Sharing In Intelligent Transportation Systems, Punyasha Chatterjee, Pratham Majumder, Sajal K. Das

Computer Science Faculty Research & Creative Works

Electric Vehicles (EVs) have become popular in the domain of Intelligent Transportation Systems for their ability to mitigate increasing environmental concerns by reducing carbon footprints and conserving fossil fuels. Due to the scarcity of static charging stations, Vehicle-to-Vehicle (V2V) charge sharing can facilitate the on-demand charging requirement of EVs. However, most of the V2V charge-sharing solutions are either centralized or semi-centralized, causing long waiting times, huge message overhead, and high infrastructural costs. For a large network, assigning a suitable donor EV for an acceptor EV as well as maximizing the matching cardinality in a distributed environment is a challenging problem. …

J-Necora: A Framework For Optimal Resource Allocation In Cloud-Edge-Things Continuum For Industrial Applications With Mobile Nodes, Marco Pettorali, Francesca Righetti, Carlo Vallati, Sajal K. Das, Giuseppe Anastasi

Computer Science Faculty Research & Creative Works

In the Industrial Internet of Things (IIoT) landscape, where the Cloud-to-Things Continuum (C2TC) paradigm is now a reality, industrial applications need to cope with highly heterogeneous network and computing resources. Moreover, many industrial applications also involve Mobile Nodes (MNs). Efficient allocation of network and computing resources to meet the stringent requirements of such applications is often a very challenging task. In this paper, we propose J-NECORA (Joint NEtwork and COmputing Resource Allocation), a comprehensive analytical framework to derive the optimal joint allocation of network and computing resources in the C2TC, that guarantees the application requirements, even in the presence of …

Virtual Network Embedding: Literature Assessment, Recent Advancements, Opportunities, And Challenges, Anurag Satpathy, Manmath Narayan Sahoo, Chittaranjan Swain, Paolo Bellavista, Mohsen Guizani, Khan Muhammad, Sambit Bakshi

Computer Science Faculty Research & Creative Works

Network virtualization (NV) allows service providers (SPs) to instantiate logically isolated entities called virtual networks (VNs) on top of a substrate network (SN). Though VNs bring about multiple benefits, particularly in terms of economic costs and elasticity, they also force various technical challenges to be addressed. The primary one is the issue of optimally allocating resources to VNs, also termed virtual network embedding (VNE). This paper presents an exhaustive survey of VNE by extensively covering the state-of-the-art research field in this very active field and focusing on the emerging research trends in industry and academia over the last decade. In …

Safenav: Safe Path Navigation Using Landmark Based Localization In A Gps-Denied Environment, Ganesh Sapkota, Sanjay Madria

Computer Science Faculty Research & Creative Works

In battlefield environments, adversaries frequently disrupt GPS signals, requiring alternative localization and navigation methods. Traditional vision-based approaches like Simultaneous Localization and Mapping (SLAM) and Visual Odometry (VO) involve complex sensor fusion and high computational demand, whereas range-free methods like DV-HOP face accuracy and stability challenges in sparse, dynamic networks. This paper proposes LanBLoc-BMM, a navigation approach using landmark-based localization (LanBLoc) combined with a battlefield-specific motion model (BMM) and Extended Kalman Filter (EKF). Its performance is benchmarked against three state-of-the-art visual localization algorithms integrated with BMM and Bayesian filters, evaluated on synthetic and real-imitated trajectory datasets using metrics including Average Displacement …

Securing Federated Learning From Distributed Backdoor Attacks Via Maximal Clique And Dynamic Reputation System, Priyesh Ranjan, Ashish Gupta, Sajal K. Das

Computer Science Faculty Research & Creative Works

Federated Learning (FL) is a distributed learning paradigm that leverages the computational strength of local devices to collaboratively train a model. The clients train the local model on their respective devices and submit the weight updates to the server for aggregation. This paradigm allows the clients to experience diverse data without sharing their local data with other participants or the server. However, FL is susceptible to backdoor attackers that deliberately train the model on altered data, essentially trying to get favor on a specific subtask separated from the main task. In this work, we focus on powerful backdoor attackers who …

Iterative Recommendations Based On Monte Carlo Sampling And Trust Estimation In Multi-Stage Vehicular Traffic Routing Games, Doris E.M. Brown, Venkata Sriram Siddhardh Nadendla, Sajal K. Das

Computer Science Faculty Research & Creative Works

The shortest-time route recommendations offered by modern navigation systems fuel selfish routing in urban vehicular traffic networks and are therefore one of the main reasons for the growth of congestion. In contrast, intelligent transportation systems (ITS) prefer to steer driver-vehicle systems (DVS) toward system-optimal route recommendations, which are primarily designed to mitigate network congestion. However, due to misalignment in motives, drivers may exhibit a lack of trust in the ITS. This paper models the interaction between a DVS and an ITS as a novel, multi-stage routing game where the DVS exhibits dynamics in its trust towards the recommendations of the …

Dynamic Resource Allocation In Cloud-To- Things Continuum For Real-Time Iot Applications, Marco Pettorali, Francesca Righetti, Carlo Vallati, Sajal K. Das, Giuseppe Anastasi

Computer Science Faculty Research & Creative Works

The proliferation of loT devices and the growing demand for real-time applications have driven a shift in the computation paradigm, from Cloud computing to Edge computing, creating the Cloud-to-Things Continuum (C2TC). Many real-time loT applications involve Mobile Nodes (MNs), which may dynamically join or leave. In addition, in future reconfigurable loT systems, applications with different requirements will coexist, and will be dynamically introduced or removed. All this asks for dynamic management mechanisms to ensure the requirements of different real-time applications, even when the system configuration changes over time. In this paper, we propose DJ-NECORA, an online algorithm for the joint …

Citrus: Cost And Ischemia Time Reduction Using Urban Air Mobility Solutions For Organ Transport, Debjyoti Sengupta, Anurag Satpathy, Arindam Khanda, Sajal K. Das

Computer Science Faculty Research & Creative Works

Urban Air Mobility (UAM) involves the use of both piloted and autonomous aerial vehicles, ranging from small unmanned aerial vehicles (UAVs), such as drones, to larger passenger-carrying personal air vehicles (PAVs). This ground-breaking approach holds the potential to transform healthcare logistics by facilitating the fast and efficient transportation of organs between hospitals, addressing critical mobility challenges in healthcare delivery. However, scheduling organ transport is fraught with challenges, including (1) the limited availability of UAM vehicles at specific hospital branches, (2) the critical Cold Ischemia Time (CIT) for various organs, and (3) the high flying costs associated with moving organs from …

Icrop+: An Edge-Boosted Crop Disease Detection System Via Tinyml And Lora Communication, Xu Tao, Jackson Butcher, Simone Silvestri, Sajal K. Das

Computer Science Faculty Research & Creative Works

Crop disease detection is essential for controlling dis-ease spread and minimizing agricultural losses. In this demo, we present an implementation of iCrop+, an end-to-end autonomous crop disease detection system that integrates on-device AI, low-power long-range communication (LoRa), and server-based deep learning to create a hybrid architecture suitable for real-world deployment. The prototype efficiently balances local processing and remote inference through category-based optimization, adaptive classification, and intelligent data transmission, ensuring that only the most informative segments are transmitted to the server. Built on low-cost devices such as Raspberry Pi, LoRa transceiver modules, and a laptop, the demo showcases its potential for …

Secure Data Relay In Federated Digital Twins Of Iot-Enabled Smart Interconnected Factories, Anusha Vangala, Jack Wyeth, Ashok Kumar Das, Sajal K. Das

Computer Science Faculty Research & Creative Works

Smart interconnected factories allow manufacturing units from physically distanced factory sites to communicate classified information needed for additive manufacturing. Each factory has interconnected digital twins of their equipment autonomously managed by a Point-of-Contact digital twin creating a hierarchical system with federated digital twins. The data sharing between the factories must be directed through an edge node responsible for managing multiple factories. We proposed a novel lightweight protocol to prevent the leakage of classified information at any nodes other than the origin and destination digital twins. It leverages elliptic curve cryptography to design a proxy re-encryption scheme with the edge node …

Reindsplit: Reinforced Dynamic Split Learning For Pest Recognition In Precision Agriculture, Vishesh Kumar Tanwar, Soumik Sarkar, Asheesh K. Singh, Sajal K. Das

Computer Science Faculty Research & Creative Works

To empower precision agriculture through distributed machine learning (DML), split learning (SL) has emerged as a promising paradigm, partitioning deep neural networks (DNNs) between edge devices and servers to reduce computational burdens and preserve data privacy. However, conventional SL frameworks' one-split-fits-all strategy is a critical limitation in agricultural ecosystems where edge insect monitoring devices exhibit vast heterogeneity in computational power, energy constraints, and connectivity. This leads to straggler bottlenecks, inefficient resource utilization, and compromised model performance. Bridging this gap, we introduce ReinDSplit, a novel reinforcement learning (RL)-driven framework that dynamically tailors DNN split points for each device, optimizing efficiency without …

When Federated Learning Meets Quantum Computing: Survey And Research Opportunities, Aakar Mathur, Ashish Gupta, Sajal K. Das

Computer Science Faculty Research & Creative Works

Quantum Federated Learning (QFL) is an emerging field that harnesses advances in Quantum Computing (QC) to improve the scalability and efficiency of decentralized Federated Learning (FL) models. This paper provides a systematic and comprehensive survey of the emerging problems and solutions when FL meets QC, from research protocol to a novel taxonomy, particularly focusing on both quantum and federated limitations, such as their architectures, Noisy Intermediate Scale Quantum (NISQ) devices, and privacy preservation, so on. With the introduction of two novel metrics, qubit utilization efficiency and quantum model training strategy, we present a thorough analysis of the current status of …

Mgco: Mobility-Aware Generative Computation Offloading In Edge-Cloud Systems., Aswini Ghosh, Nelson Sharma, Shivendu Mishra, Rajiv Misra, Sajal K. Das

Computer Science Faculty Research & Creative Works

Mobility introduces significant challenges for optimal computation offloading, latency minimization, and efficient re source utilization in multi-access edge computing (MEC) systems. A key difficulty lies in leveraging real user trajectories to jointly optimize horizontal (inter-edge) and vertical (edge-to-cloud) task offloading decisions. This paper proposes a two-dimensional offloading scheme for a multi-layer edge–cloud architecture that enables collaborative task execution among resource-constrained edge nodes under mobility conditions. We present MGCO (Mobility-Aware Generative Computation Offloading), a generative AI–driven Transformer-based sequence-to-sequence Deep Q-Network (s2s-DQN) framework that learns from real-time trajectory data to anticipate user movement and optimize task placement dynamically. The Transformer architecture is …

Content Subversion Against 1 Information-Based Systems, Junjie Xiong, Ian Markwood, Dakun Shen, Yao Liu, Zhuo Lu

Computer Science Faculty Research & Creative Works

We present a novel class of content subversion attacks against information-based services, causing documents to appear to humans dissimilar to the underlying content extracted by information-based services. We demonstrate the significant impact of these attacks on real-world systems through five distinct variants. Our first attack allows academic paper writers and reviewers to collude via subverting the automatic reviewer assignment systems in current use by academic conferences including INFOCOM, which we reproduced. Our second attack renders ineffective plagiarism detection software, particularly Turnitin, targeting specific small plagiarism similarity scores to appear natural and evade detection. In our third attack, we place masked …

Real-Time Testbed For Studying Cyberattacks And Defense In Der-Integrated Smart Inverter Systems, M. Maliha, A. Oluyomi, M. Booge, S. Bhattacharjee, N. Braasch, P. Gomez, Sajal K. Das

Computer Science Faculty Research & Creative Works

In this paper, we propose a Hardware-in-the-Loop (HIL) simulation testbed suitable for the implementation and testing of realistic cyberattacks on grid-tied smart inverter systems integrated with Distributed Energy Resources (DER) that use the Distributed Network Protocol-3 (DNP3) protocol for communications between grid components. Specifically, our testbed combines a Real-Time Digital Simulator (RTDS) NovaCor device, outfitted with GNETx2 network interface cards, a grid-tied DER topology implemented via the RTDS software package RSCAD, and a custom virtual network that emulates a man-in-the-middle (MITM) attacker. The MITM attacker captures DNP3 traffic and falsifies telemetry data in DNP3 packets to trigger unwarranted commands from …

Grace-Fl: Green Resource-Aware Communication-Efficient Federated Learning, Dipanwita Thakur, Antonella Guzzo, Giancarlo Fortino, Sajal K. Das

Computer Science Faculty Research & Creative Works

Federated Learning (FL) enables collaborative model training across distributed clients while preserving data privacy, but its deployment on resource-constrained devices is hindered by high communication overhead, inefficient energy usage, and poor convergence under non-IID data distributions. To address these challenges, we propose GRACE-FL: a Green Resource-Aware Communication-Efficient Federated Learning framework that explicitly incorporates device energy capacity into training. Each client adapts its learning rate, number of local epochs, and gradient quantization bit-width based on its available energy, allowing high-capacity devices to sustain more intensive training while low-capacity devices operate with lighter configurations. A novel energy-weighted aggregation strategy ensures that clients …

Alertble: Alert Workzone Hazards Using Hybrid Filtering And Machine-Learning-Enabled Ble, Samuel Akinyede, Sejun Song

Computer Science Faculty Research & Creative Works

Collision hazard detection in industrial work zones faces challenges from signal instability, mobility-induced fluctuations, and nonline-of-sight (NLOS) conditions. While Bluetooth low energy (BLE) offers cost-effective proximity sensing, its received signal strength indicator (RSSI) variability - fluctuating by ±10 dBm even at fixed distances - limits reliability in safety-critical applications. This article presents AlertBLE, a hybrid BLE-based hazard detection system that combines extended Kalman filter (EKF) and adaptive moving average (AMA) algorithms to achieve up to 94% RSSI variance reduction in static NLOS conditions. The system introduces speed-aware safety thresholds based on reaction time and braking distance models, dynamically expanding hazard …

Dispute System Counter-Design, Andrew B. Mamo

FIU Law Review

This article introduces the concept of “counter-design” as a practice of challenging and reimagining dispute resolution systems from the ground up and from the inside out. Counter-design provides a critical response to traditional Dispute System Design (DSD) by positing that designs necessarily privilege certain perspectives and interests over others, even when designers follow best practices and ethical principles. Through practices of counter-design, individuals interact with dispute resolution systems, not merely to seek resolutions within the existing framework, but to actively challenge and reshape these systems from within. This concept underscores the dynamics of power, inclusion, and representation within DSD. Counter-design …

Individual Academic Freedom And The Current Forces Of Economics And Technology, George R. Wright

FIU Law Review

There are always a number of cultural constraints on higher education institutions. Such cultural constraints always matter. But sometimes, as in our day, such constraints are especially severe. These constraints are broadly economic; more specifically market-based; and technological in nature. They operate on public and private universities and on law schools in particular. Our concern herein is for such constraints in the many cases in which a faculty member’s speech on some matter of public interest arguably impairs a legitimate interest of the employer-university or law school. The weight of the educational institution’s interests in such academic speech cases is, …

The Legitimacy Of Israel: A Sociological Perspective, Luis Fleischman

FIU Law Review

The article focuses on the foundations of Israel’s legitimacy. It explores the issue of Israel’s legitimacy from the viewpoint of the sociology of law and the sociology of politics. It aims to provide perspective and nuance to some highly problematic and inherently anti-Zionist arguments raised by the Palestinian narrative and academic paradigms, such as "settler colonialism" and reductionist manichean theories of conflict.

Should Hate Speech Be Criminalized? Lessons From The Canadian Experience In R V. Zundel And R V. Keegstra, Kenneth Grad

FIU Law Review

There is a global trend toward increased use of criminal law to combat hate speech. In assessing this trend, one should be mindful of the experience of countries that have long had criminal laws targeting harmful expression. Canada is one such country. Using the leading Canadian cases of R v. Zundel and R v. Keegstra, this article argues that the Canadian experience suggests the criminal law is a flawed mechanism for countering harmful expression. This is so for at least three reasons. First, hate-speech prosecutions may undermine the group dignity and sense of inclusion of minority groups. Second, criminal laws …

Lessons For The Trump Administration From The Biden U.S. National Strategy To Counter Antisemitism, Lili Levi

FIU Law Review

In May 2023, the Biden Administration issued the first-ever U.S. National Strategy to Counter Antisemitism with a goal of hindering further normalization of antisemitism by increasing public awareness of antisemitism and highlighting positive Jewish contributions to America. Recent events, however, particularly the social and political upheaval over protests of the war in Gaza, have led to public contestation over Israel, increased instances of antisemitism, and the partisan politicization of Jewish issues. All this has raised questions about whether the National Strategy's assumptions about public attitudes, the viability of antisemitism awareness initiatives, and the possibility of whole-of-society agreement on countering antisemitism …

How Much Antisemitism Is There In The United States? Incidences Vs. Impacts, Ira Sheskin

FIU Law Review

The Anti-Defamation League (ADL) (www.adl.org), founded in 1913, is one of the nation's premier civil rights organizations and was formed to stop the defamation of the Jewish people and to secure justice and fair treatment to all. Every year since 1979, the ADL has published an Audit of Antisemitic Incidents in the US (https://www.adl.org/resources/report/audit-antisemitic-incidents-2023). The Audit receives significant publicity and is important in communicating the problem of serious antisemitic incidents and the year-to-year increases in such incidents. But, based on surveys of American Jews, the Audit underestimates the extent to which American Jews are being impacted by antisemitism. Survey data …