Digital Commons Network^™

English Literacy Rates Across The United States, Hailey Reisinger

Masters Theses

Literacy rates among students in the United States have been at an all-time low for the last several years. There have been many factors to this including but not limited to, the COVID-19 pandemic, technology, teacher shortages, and chronic absenteeism. This study looks into the literacy rate decline, the mentioned factors, and what is being done to improve the literacy proficiency among students across the country. This study also looks at what is specifically being done for school divisions across the Commonwealth of Virginia, focusing on one school in particular, Culpeper Middle School.

Efficient Smartphone Sensor Analysis For Behavioral Profiling In Transportation Research: A Case Study Of Driver And Passenger Classification, Wilson Lozano, Tempestt Neal

Research Reports

Our study investigates smartphone sensor data for classifying drivers and passengers, aligning with our original proposal to enhance multimodal transportation data collection via the OneBusAway app. We address challenges in balancing data quality with smartphone resource constraints and find that shorter data collection windows significantly improve classification performance. Additionally, feature standardization and selection enhance accuracy, particularly during extended data periods, supporting our goal of refining data quality from open-source platforms. These insights advance our objectives by optimizing data efficiency and supporting the real-world applicability of intelligent models in transportation safety and efficiency.

Misinformation, Fraud, And Stereotyping: Towards A Typology Of Harm Caused By Deepfakes, Paulina Trifonova , '25, Sukrit Venkatagiri

Computer Science Faculty Works

Scholars, politicians, and journalists have raised alarm over the potential for AI-generated photos, video, and audio—often referred to as deepfakes—to reduce trust in one another and our institutions. Despite these clarion calls, little empirical work exists on how deepfakes are being used to harm individuals outside of non-consensual intimate imagery (NCII). This research provides a preliminary analysis of 50 wide-ranging incidents of deepfake harm. We find that the most common types of harm are relational, systemic, financial, and emotional. Apart from AI-generated NCII, the most prevalent uses of deepfakes to cause harm were instances of mis- and disinformation, fraud, and …

Video Label Refinement And Temporal Localization Using Motion Signal Patterns, Jennifer Piane

College of Computing and Digital Media Dissertations

Performing video analysis for activity recognition presents challenges beyond classification, including obtaining class labels and performing temporal localization. One such challenge is precisely labeling a video with class labels having the exact start and end frames of an activity - a difficult task for a human to perform. Moreover, the task of annotating a video at any level of precision can quickly become tedious, impacting the attentiveness of the annotator and resulting in class label errors. Temporally localizing an activity within a video presents a second challenge. This dissertation investigates novel signal and image processing methods for motion features extracted …

Automatic Detection Algorithm For Typical Defects Of Substation Based On Improved Yolov5, Zhongkai Xu, Yanling Liu, Xiaojuan Sheng, Chao Wang, Wenjun Ke

Journal of System Simulation

Abstract: In response to the challenges present in the context of defect recognition in substations, such as complex substation defects and sample imbalance, an improved YOLOv5 algorithm was proposed. The Transformer model was introduced into the YOLOv5 network structure, leveraging the self-attention mechanism to capture long-range dependencies among features. A focal loss-based optimization was employed to improve the loss function, as well as the detection accuracy and robustness of defects of small sample substations. To meet the requirements of substation defect recognition, a dedicated dataset was constructed. A clustering algorithm was applied to the real annotation boxes to generate more …

Cultural Competence And Cultural Humility Among Healthcare Students Related To Community Engagement And Service Learning: A Multiple Regression And Confirmatory Factor Analysis Study, Maryanne Koech Gathambo

Doctoral Dissertations and Projects

The purpose of this quantitative, hierarchical multiple regression and confirmatory factor analysis study was to investigate the cultural humility and cultural competence (competemility) of healthcare students and examine the strongest predictor of cultural competemility based on demographic and experiential learning factors. Hierarchical multiple regression was used to investigate the degree to which the predictor variables age, gender, and community engagement/service hours (i.e., CEL/SL) could be forecasted by their competemility score (criterion variable) as measured by The Inventory for Assessing The Process Of Cultural Competemility Among Healthcare Professionals (IAPCC-HCP). Data were obtained from a criterion-based purposive sample of 70 survey participants …

The Impact Of Teacher-Student Relationships And Self-Efficacy On The Engagement Of Secondary Special Education Students: A Predictive Correlational Study, Lora S. Davis

Doctoral Dissertations and Projects

The purpose of this quantitative, predictive correlational study was to investigate the predictive ability of student perception of teacher-student relationships and student-reported self-efficacy on student-reported engagement, specifically regarding secondary special education students. Given the well-documented impact of teacher-student relationships on the educational experience of students, this study had the potential to provide meaningful guidance for staff in secondary schools when they seek to support special education students with disabilities. The participants in this study were 108 high school students receiving special education services from four different high schools located in rural areas of a single southeastern state. Participants anonymously completed …

Multicultural Education: A Phenomenological Study Of How Elementary Teachers' Classroom Experiences Mirror The Knowledge And Skills Gained In Undergraduate Courses, Emily L. Hepner-Leffel

Doctoral Dissertations and Projects

The purpose of the study was to conduct a phenomenological analysis of the experiences of elementary school teachers concerning multicultural education in an urban school district in Southern Virginia. The study aimed to explore and describe teachers' perceptions, beliefs, values, and attitudes regarding multicultural education and assess their preparedness to implement multicultural education practices in their classrooms. The research utilized a qualitative research design that involved in-depth interviews and observations with a purposive sample of 10 novice and experienced elementary teachers. The study also gathered information from various documents that were collected to generate data. The data underwent analysis through …

Scalable Methods For Performant Control Of Hyperfine Qubits In Atoms And Ions, Matthew N. H. Chow

Physics & Astronomy ETDs

Qubits encoded within internal energy levels of atoms and ions have been used to demonstrate high-performance primitives of quantum computing for small numbers of qubits. Yet, the path to achieving sufficient size and fidelity for useful fault-tolerant quantum computation remains daunting. In this dissertation, I present several techniques I developed as steps along this path. These results include high-fidelity, low-loss detection for alkali atoms in optical tweezers, crosstalk-mitigated parallel one-qubit gates, robust entangling gates on trapped ions, and leakage-to-erasure conversion for non-destructive detection of atom loss errors. Through this collection of techniques, I have sought to make full use of …

Investigation On The Impact Of Loading Effect Of Fruit Juices On The Performance Of Pulsed Electric Field Generators, Devi S

Theses and Dissertations

Pulsed Electric Field (PEF) treatment is one of the efficient non-thermal food processing techniques which is being preferred as a replacement for thermal pasteurization methods. The effectiveness of PEF treatment was measured in terms of reduction in the microbial load in the food, extension of shelf life of the food and retention of nutritional properties of the food. The successful implementation of the PEF treatment depends upon various aspects such as design of pulse generator, parameters of pulse generator, shape and size of the treatment chamber and most importantly the characteristics of each food items. Design and fabrication of a …

Analyzing And Extending Machine Learning Frameworks On High Risk Domains, Chengbin Hu

USF Tampa Graduate Theses and Dissertations

Machine learning (ML) has become a transformative force in high-risk domains such as genomics and cybersecurity, where accurate predictions and robust defenses are essential. This dissertation advances ML frameworks in these areas by developing methods to enhance predictive power in health applications and assess vulnerabilities in machine learning systems.

In the genomics field, the work addresses challenges in Non-Invasive Prenatal Testing (NIPT) of monogenic disorders by proposing a deep learning model that reconstructs the fetal genome using maternal plasma cell-free DNA (cfDNA) and parental whole-genome sequencing (WGS) data. This model achieves high accuracy in single nucleotide variation (SNV) prediction, surpassing …

Hacker, Their Actions, And Fear Appeal: A First Look Through The Lens Of Children, Rizu Paudel, Mahdi Nasrullah Al-Ameen

Computer Science Student Research

With the increasing use of computers and smartphones by children, their online safety has become a major concern due to the lack of security awareness. Prior studies pointed to children's poor password habit and vague perceptions on the significance of passwords. While users must be sufficiently motivated to perform a target behavior, a little study to date, focused on understanding how we can encourage children towards strong password creation. As we begin to address this gap, we examined children's perceptions of adversary's actions that instill fear in the context of password compromise. Our semi-structured interviews with 20 children (aged between …

Flowgpt: Exploring Domains, Output Modalities, And Goals Of Community-Generated Ai Chatbots, Xian Li, Yuanning Han, Di Liu, Pengcheng An, Shuo Niu

Computer Science

The advent of Generative AI and Large Language Models has not only enhanced the intelligence of interactive applications but also catalyzed the formation of communities passionate about customizing these AI capabilities. FlowGPT, an emerging platform for sharing AI prompts and use cases, exemplifies this trend, attracting many creators who develop and share chatbots with a broader community. Despite its growing popularity, there remains a significant gap in understanding the types and purposes of the AI tools created and shared by community members. In this study, we delve into FlowGPT and present our preliminary findings on the domain, output modality, and …

Harnessing Llms For Automated Video Content Analysis: An Exploratory Workflow Of Short Videos On Depression, Jiaying (Lizzy) Liu, Yunlong Wang, Yao Lyu, Yiheng Su, Shuo Niu, Orson Xuhai Xu, Yan Zheng

Computer Science

Despite the growing interest in leveraging Large Language Models (LLMs) for content analysis, current studies have primarily focused on text-based content. In the present work, we explored the potential of LLMs in assisting video content analysis by conducting a case study that followed a new workflow of LLM-assisted multimodal content analysis. The workflow encompasses codebook design, prompt engineering, LLM processing, and human evaluation. We strategically crafted annotation prompts to get LLM Annotations in structured form and explanation prompts to generate LLM Explanations for a better understanding of LLM reasoning and transparency. To test LLM's video annotation capabilities, we analyzed 203 …

The Contrast In Music Aesthetics Prior To The Romantic Era And Its Impact On Music Education, Sophia Grace Moon

Doctoral Dissertations and Projects

This qualitative study explores the approach to music education prior to the Romantic period. Prior to the modern era, the aesthetics of music explored the mathematical and scientific dimensions of rhythmic and harmonic organization. The composition of music was very structured, there was a “right” approach to composing. In the era of Romanticism, some composers and critics argued that music should and could serve as a means for self-expression or the conveying of emotion. Beginning in the Romantic era composers were free to experiment with musical ideas. Traditionally accepted manners for composition had less meaning, as composers were given the …

Inefficiencies In Water Supply And Perceptions Of Water Use In Peri-Urban And Rural Water Supply Systems: Case Study In Cali And Restrepo, Colombia, Diana Carolina Callejas Moncaleano, Saket Pande, Melissa Haeffner, Juan Pablo Rodríguez Sánchez, Luuk Rietveld

Environmental Science and Management Faculty Publications and Presentations

Introduction:

Water scarcity is a significant global challenge that frequently manifests as inadequate water supply for domestic purposes. However, domestic water insecurity can occur even in regions where water is naturally abundant. Despite Colombia’s plentiful surface water resources, rural and peri-urban communities often experience limited access to water. Existing water supply systems are frequently susceptible to poor maintenance, particularly in remote areas where much of the infrastructure remains outdated. Consequently, water is often lost through leaks or unintentional non-domestic use. Although a regulatory framework for water usage exists, it does not consistently translate into effective implementation.

Methodology:

Based on an …

Detecting Changes In Cancer-Related Cognitive Functioning Using Mixed-Effects Modeling And Study Design Simulations, Jonathan D. Clapp

USF Tampa Graduate Theses and Dissertations

The purpose of this dissertation is to utilize and compare two existing approaches for modeling nonlinear change in cognitive functioning in cancer patients over time and to assess alternative study designs to better capture chemotherapy-related cognitive impairment using simulation data. Using data from the Thinking and Living with Cancer study, trend analysis with orthogonal polynomials (OP) and piecewise (PW) regressions approaches used to analyze cognitive functioning trajectories. Simulated datasets tested the impact of study design parameters including measurement test-retest reliability (.6 or .8), sample size (100, 200, or 300), and the number of data collection time points (4 or 5) …

Object Detection Of Lightweight Transformer Based On Knowledge Distillation, Gaihua Wang, Kehong Li, Qian Long, Jingxuan Yao, Bolun Zhu, Zhengshu Zhou, Xuran Pan

Journal of System Simulation

Abstract: In autonomous driving, the efficiency and accuracy of object detection are significant. Object detection based on Transformer structure has gradually become the mainstream method, eliminating the complex anchor generation and non-maximum suppression (NMS). It has problems of high computing cost and slow convergence. An object detection model of the based lightweight pooling transformer (LPT) is designed, which contains a pooling backbone network and dual pooling attention mechanism. A general knowledge distillation method is intended for the DETR (detection transformer) model, which transfers prediction results, query vector, and features extracted by the teacher as knowledge to the LPT model to …

A Hybrid Genetic Search Algorithm For Capacitated Electric Vehicle Routing Problem, Dongyao Jin, Mi Liu, Yena Zhu, Yijiang Zhao

Journal of System Simulation

Abstract: The capacitated electric vehicle routing problem (CEVRP) is an NP-hard combinatorial optimization problem in logistics distribution, aiming to minimize the total delivery distance of electric vehicles while satisfying carrying capacity and battery charge constraints. A hybrid genetic search algorithm is proposed to solve CEVRP by decomposing it into two subproblems: capacitated vehicle routing problem (CVRP) and fixed-route vehicle charging problem (FRVCP). A coding scheme with a two-layer chromosome structure is designed to represent the decision variables of these two subproblems. A Split operation is employed to generate vehicle routes for solving CVRP, and five neighborhood search operators, including Relocate, …

Traffic Sign Recognition Model With Long-Tail Distribution Based On Yolox-Tiny, Yunpeng Wu, Yingxiong Fu, Lijun Shen, Feng Cui

Journal of System Simulation

Abstract: Accurate recognition of traffic signs plays an important role in the field of intelligent driving. Traffic sign training datasets with long-tail distribution increase the difficulty of traffic sign recognition. A traffic sign recognition model with long-tail distribution based on YOLOX-Tiny was proposed to improve the poor performance of the model trained on long-tail distribution datasets. A long-tail traffic sign dataset was created based on the TT100K_2021 (tsinghua-tencent 100K 2021) dataset. YOLOX-Tiny was chosen as the underlying model by considering picture numbers in datasets, sample distribution, and model size. Equalization loss v2 (EQL v2) was used as classification loss to …

Real-Time Lidar Slam Algorithm Based On Distribution Optimal Registration, Weigang Li, Chuxiang Yu, Yongqiang Wang, Shaofeng Zou

Journal of System Simulation

Abstract: When scanning the surrounding environment, a lidar will generate some cluttered and sparse point cloud, which will cause excessive distribution fitting errors and correlation distances in the registration process, thus affecting the accuracy of the registration algorithm and the effect of simultaneous localization and mapping (SLAM). To address this problem, a real-time lidar SLAM algorithm based on distribution optimal registration is proposed. An eigenspectrum filter is designed, which takes the normalized minimum eigenvalue as the filtering object to filter out the points that do not match the set distribution in order to reduce the distribution fitting error. Secondly, a …

Research On Green Job Shop Scheduling Based On Herd Immunity Optimizer, Xunde Ma, Li Bi, Junjie Wang

Journal of System Simulation

Abstract: In view of the green flexible job shop scheduling problem where machines have multiple speeds, a green flexible job shop scheduling model under multiple speeds was constructed to minimize the makespan and total energy consumption under different speeds. A discrete coronavirus herd immunity optimizer (DCHIO) was proposed for a solution. A discrete individual updating method was introduced for the relatively large solution space of the multi-speed problem, based on which a population updating mechanism with multi-scale joint search was proposed to search the solution space quickly and uniformly. A dynamic mutation operation was designed to enhance the population diversity …

Global-Local Fusion For Efficient 3d Object Detection, Bin Lu, Minghan Wang, Yang Sun, Zhenyu Yang

Journal of System Simulation

Abstract: As the 3D object detection based on point clouds shows an incapacity of feature extraction and incongruity between classification and regression, this research introduces a novel ResCST architecture based on the SECOND network. It incorporates residual connections into the 3D sparse convolutional layer, with the advantages of capturing long-distance dependent relation by SwinTransformer and obtaining local features by convolutional neural network integrated, proposing the CNN-SwinTransformer hybrid model for enhanced feature extraction. It introduces the RCIoU method for the joint optimization of classification and regression tasks. The experimental results show that the model achieves a 3D detection accuracy of 91.21%, …

Optimization Of Crucial Targets For Air Defense Based On Combined Weighting-Topsis Model, Peng Zhang, Ke Feng

Journal of System Simulation

Abstract: To optimize the selection of crucial defended targets in regional air defense operations and improve the selection accuracy, this paper constructs a factor model considering the importance of air defense targets from the perspectives of target value, defense urgency, target vulnerability, and target recovery. Under the optimization of the TOPSIS method through a combination of the ANP and entropy weight methods, tendentious opinions of commanders and the excessive reliance on objective data can be overcome to ensure the factor weighting is more reasonable and accurate; Super Decisions is used to calculate the weights of the ANP method, accelerating data …

Eecbs Multi-Robot Path Planning Based On Variable Suboptimal Factors Of Prioritizing Conflicts, Xingyu Yan, Niya Wang, Jianlin Mao, Zhigang He, Dayan Li

Journal of System Simulation

Abstract: In the process of multi-robot path planning (MRPP), the unavoidable key conflicts between the optimal paths have a significant impact on the efficiency of path solving. To address this issue, an MRPP method based on variable suboptimal factors of prioritizing conflicts (PC) was proposed. Path search was performed at the lower layer of the explicit estimation conflict-based search (EECBS) algorithm; in the upper layer of the EECBS algorithm framework, the PC was determined, and the suboptimal factor of the robot with key conflicts was adaptively increased; by analyzing the distribution of obstacles in the surrounding neighborhoods of key conflicts, …

Slam Dynamic Algorithm Based On Improved Feature Description, Qiang Fu, Xianyun Teng, Yuanfa Ji, Fenghua Ren

Journal of System Simulation

Abstract: The original ORB descriptor algorithm has a low matching accuracy and long matching time, the positioning accuracy and robustness of the SLAM(simultaneous localization and mapping) system are severely disturbed by moving objects in dynamic scenes, and the ORB-SLAM3 system is incapable of constructing dense maps. To address the above problems, this paper proposes an improved ORB-SLAM3 based on the BEBLID descriptor and object detection. A lightweight YOLOv5s dynamic object detection network and dynamic feature removal module are fused with the tracking thread to improve the system's positioning accuracy. Replacing the original feature description algorithm, an improved local image descriptor …

Success Factors Linking New Environmental Products With Academic Knowledge And Firm Knowledge Partnerships: An Examination Of Biosurfactant Decision-Making Complexity, Cecilia Akinyi Wandiga

Walden Dissertations and Doctoral Studies

Business managers risk failure if they do not correctly integrate academic knowledge transfer with their firms’ investments and their absorptive capabilities to generate viable industrial designs for new products. The purpose of this quantitative, correlational study was to test the relationship between nine academic-industry collaboration factors and the number of new products that firms generate. Three theoretical frameworks formed the basis of the completed study: (a) the quintuple helix, (b) the natural resource based view theory, and (c) the circular bioeconomy. Multiple regression analysis was used to test the relationship between nine academic-industry success factors and the number of new …

Agv Scheduling Problem At Automated Terminals Based On Improved Dqn Algorithm, Chengji Liang, Shidong Zhang, Yu Wang, Bin Lu

Journal of System Simulation

Abstract: A future tasks considering deep Q-network (F-DQN) algorithm was proposed to output realtime scheduling results of automated guided vehicles (AGVs) at automated terminals. This algorithm combined the advantages of real-time scheduling and static scheduling, improving the system status by considering static future task information when making real-time decisions, so as to obtain a better scheduling solution. In this study, the actual layout and equipment conditions of the Yangshan phase IV automated terminal were considered, and a series of simulation experiments were conducted using the Plant Simulation software. The experimental results show that the F-DQN algorithm can effectively solve the …

A Method For Key Node Identification In Operational Target System Based On War Gaming, Yongfu Zhang, Yang Liu, He Yuan

Journal of System Simulation

Abstract: The identification of key nodes in an operational target system is an important basis for combat command decision-making. Due to the lack of experimental verification of key node identification in the current operational target system in a campaign-level dynamic confrontation environment, a complex network model of operational target system with large-scale entities and complex interaction relationship was constructed by taking integrated air defense network as an example, with the help of the data derived from the large joint war gaming; the characteristics of wargame data were considered, and the value characteristics of combat targets and network structure characteristics were …

2024-11-13 Mosaic And Rotc Honor Veterans With Robert Bennedsen 5k, Daniel Truog

The Spectator Online

No abstract provided.