Digital Commons Network^™

Comparison Of Ketamine-Xylazine, Butorphanol-Azaperone-Medetomidine, And Nalbuphine-Medetomidine-Azaperone For Raccoon (Procyon Lotor) Immobilization, Shylo R. Johnson, Christine K. Ellis, Chad Wickham, Molly R. Selleck, Amy T. Gilbert

United States Department of Agriculture Wildlife Services: Staff Publications

Raccoons (Procyon lotor) are frequently handled using chemical immobilization in North America for management and research. In a controlled environment, we compared three drug combinations: ketamine-xylazine (KX), butorphanol-azaperone-medetomidine (BAM), and nalbuphinemedetomidine- azaperone (NalMed-A) for raccoon immobilization. In crossover comparisons, raccoons received a mean of the following: 8.66 mg/kg ketamine and 1.74 mg/kg xylazine (0.104 mL/kg KX); 0.464 mg/kg butorphanol, 0.155 mg/kg azaperone, and 0.185 mg/kg medetomidine (0.017 mL/kg BAM); and 0.800 mg/kg nalbuphine, 0.200 mg/kg azaperone, and 0.200 mg/kg medetomidine (0.020 mL/kg NalMed-A). Induction time was shortest with KX (mean6SE, 10.060.7 min) and longest with NalMed-A (13.061.3 min). …

Introduction To Wi-Fi 7: A Review Of History, Applications, Challenges, Economical Impact And Research Development, Sallar Salam Murad, Rozin Badeel, Banan Badeel Abdal, Tasmeea Rahman, Tahsien Al-Quraishi

Mesopotamian Journal of Computer Science

Wi-Fi 7, commonly referred to as IEEE 802.11be, is the most recent development in wireless communication technology. It provides significant improvements in terms of speed, capacity, and efficiency. The purpose of this study is to investigate Wi-Fi 7, a standard for wireless communication technology, with a particular focus on the technological advancements and security issues associated with it. In addition, it offers historical perspectives and investigates the institution's present capabilities as well as its potential for the future. The purpose of this study is to provide a complete examination of the development of Wi-Fi technology and its influence on a …

Designing Ris-Assisted Uav 3d Trajectory Using Deep Reinforcement Learning, Linsong Li

Electronic Theses and Dissertations

Unmanned aerial vehicles (UAVs) are increasingly employed as temporary base stations or access points to facilitate data transfer between ground terminals (GTs). However, in urban environments, UAV-GT communication links often face challenges due to obstructions from buildings and other obstacles, resulting in reduced data transfer efficiency. Reconfigurable intelligent surfaces (RIS) provide a promising solution by reflecting signals to enhance communication quality between UAVs and GTs. This thesis addresses the critical challenge of responsive UAV trajectory optimization in RIS-assisted communication networks. A novel approach is proposed, integrating federated learning with reinforcement learning techniques, specifically Double Deep Q-Network (DDQN) and Deep Deterministic …

Advancements In Forensic Analysis: Development Of Mass Spectrometric And Chemometric Approaches For The Identification Of Synthetic New Psychoactive Substances And Plant Materials, Mónica Ventura

Electronic Theses & Dissertations (2024 - present)

While forensic science is a well-established discipline, a number of federal agencies have highlighted challenges that continue to plague the field and the extent to which these challenges remain unaddressed. Examples are the illegal trade of wildlife timber and the drug epidemic. Characterization of these materials requires nuanced method development for compound determination, matrix material-specific protocols, and heavy use of expensive consumables. The application of a technique such as direct analysis in real time – high-resolution mass spectrometry (DART-HRMS) provides the opportunity to circumvent many of the challenges presented by conventional methods. In general, little to no sample preparation is …

Applications Of Shape Analysis, Yang Zhang

Graduate Research Theses & Dissertations

Shape analysis is a field of Statistics focused on analyzing and understanding the shape or the geometric properties of objects. We utilize the Bayesian circular cubic smoothing splines to estimate the shapes and introduce a rotation-based alignment method. A simulation study investigates the effect of shape alignment. As an application, we estimate the shapes of hourly crime rates in urban centers across the United States and compare the aligned shapes for different types and locations of crimes. In addition, we apply the proposed shape estimation with alignment to the survival analysis for the length of hospitalization of COVID-19 patients in …

Developing A Snow Detection Algorithm Using Spatial Attention For Pedestrian Safety, Ricardo De Deijn

All Graduate Theses, Dissertations, and Other Capstone Projects

SNOW-COVERED SIDEWALKS POSE SIGNIFICANT SAFETY HAZARDS, ESPECIALLY FOR VULNERABLE POPULATIONS SUCH AS THE ELDERLY AND VISUALLY IMPAIRED. THE DEVELOPMENT OF EFFECTIVE SNOW DETECTION SYSTEMS IS CRUCIAL FOR ENHANCING PEDESTRIAN SAFETY. THIS RESEARCH AIMS TO ADDRESS THESE CHALLENGES BY DEVELOPING A SNOW DETECTION ALGORITHM SPECIFICALLY DESIGNED FOR SIDEWALKS. THE PROPOSED ALGORITHM USES A CONVOLUTIONAL NEURAL NETWORK (CNN) ARCHITECTURE INCORPORATING A 2-DIMENSIONAL SPATIAL ATTENTION MECHANISM TO FOCUS ON RELEVANT FEATURES IN IMAGES, IMPROVING SNOW DETECTION ACCURACY. DUE TO THE SEASONAL AND GEOGRAPHIC LIMITATIONS OF SNOW DATA COLLECTION, SYNTHETIC DATA GENERATION USING INVERSE DIFFUSION MODELS WAS EMPLOYED TO AUGMENT THE REAL-WORLD DATASET. ALTHOUGH …

From Creek To Ditch And Back Again: The History And Future Of Pattee Creek, Missoula, Montana, Carver Edward Butterfield

Graduate Student Theses, Dissertations, & Professional Papers

Pattee Creek was once a free-flowing stream that meandered across the Missoula Valley, but has been channelized, piped, and degraded by logging, mining, agriculture, and urbanization. This thesis used a mixed-method approach to examine the impact of human activities on the Pattee Creek watershed. Beginning with a historical overview, the story of how the creek has been utilized and why it was buried was told. An analysis of historical photos from 1937 to 2019 revealed drastic changes in the land cover of the watershed and the channel of lower Pattee Creek. Developed land increased dramatically, while open land decreased and …

A Review On Chemometrics And Climate Change: Insights From Malaysia Case Study, Ismafatin Nabilah Ismail, Mohd Khairul Amri Kamarudin, Wan Nor Azilawanie Tun Ismail, Noorjima Abd Wahab, Ahmad Shakir Mohd Saudi, Mohd Ekhwan Toriman, Firdaus Mohamad Hamzah, Septi Ariadi

Applied Environmental Research

Climate change consider as main issues and concerns in Malaysia over the decade. Chemometrics techniques have been used in many climate change issues to address the limitations of climate change monitoring studies. In climate change areas, chemometrics is a valuable tool for assessing the correlation between different climate change factors, especially in vast and intricate databases. The purpose of the review was to evaluate and summarise the available data and restrictions regarding the use of chemometrics techniques in Malaysian environmental studies. The study conducted a thorough analysis of pertinent scientific papers published between 2019 to 2023 that addressed the main …

Actionpoint: An App To Combat Cyberbullying By Strengthening Parent-Teen Relationships, Maddie Juarez, Natali Barragan, Deborah Hall, George K. Thiruvathukal, Yasin Silva

Computer Science: Faculty Publications and Other Works

Overview: Urgent need for intervention tools to mitigate increase in cyberbullying • ActionPoint is based on parent-teen relationship research • App includes interactive modules to improve family communication and online behavior to combat cyberbullying effects • To be presented in the IEEE World Forum on Public Safety Technology 2024.

Actionpoint: An App To Combat Cyberbullying Via The Strengthening Of Parent-Teen Relationships, Maddie Juarez, Natali Barragan, Deborah Hall, George K. Thiruvathukal, Yasin N. Silva

Computer Science: Faculty Publications and Other Works

Due to the increased prevalence of cyberbullying and the detrimental impact it can have on adolescents, there is a critical need for tools to help combat cyberbullying. This paper introduces the ActionPoint app, a mobile application based on empirical work highlighting the importance of strong parent-teen relationships for reducing cyberbullying risk. The app is designed to help families improve their communication skills, set healthy boundaries for social media use, identify instances of cyberbullying and cyberbullying risk, and, ultimately, decrease the negative outcomes associated with cyberbullying. The app guides parents and teens through a series of interactive modules that engage them …

Expanding Australia's Defence Capabilities For Technological Asymmetric Advantage In Information, Cyber And Space In The Context Of Accelerating Regional Military Modernisation: A Systemic Design Approach, Pi-Shen Seet, Anton Klarin, Janice Jones, Michael N. Johnstone, Violetta Wilk, Stephanie Meek, Summer O'Brien

Research outputs 2022 to 2026

Introduction. The aim of the project was to conduct a systemic design study to evaluate Australia'sopportunities and barriers for achieving a technological advantage in light of regional military technological advancement. It focussed on the three domains of (1) cybersecurity technology, (2) information technology, and (3) space technology.

Research process. Employing a systemic design approach, the study first leveraged scientometric analysis, utilising informetric mapping software (VOSviewer) to evaluate emerging trends and their implications on defence capabilities. This approach facilitated a broader understanding of the interdisciplinary nature of defence technologies, identifying key areas for further exploration. The subsequent survey study, engaging 828 …

Investigating Flash Flood Occurrence Using Negative Binomial Models In Maryland, United States Of America, Zainab O. Akinsemoyin

College of Graduate Studies: Theses & Dissertations

Globally, as extreme weather patterns intensify, flash floods have emerged as one of the most destructive and immediate environmental threats. In Maryland, flash floods are particularly concerning due to its diverse topography and increasing urban development, which exacerbates runoff and overwhelms drainage systems. The state has experienced significant flash flood events, highlighting the need for effective models to manage risks and inform mitigation strategies. While regression models such as the Negative Binomial (NB) and Zero-Inflated Negative Binomial (ZINB) are commonly used for count data analysis, their application to flash flood modeling in the USA, including regions like Maryland, remains limited …

Deep Learning For Uav Detection And Classification Via Radio Frequency Signal Analysis, Prajoy Podder, Maciej Zawodniok, Sanjay Madria

Electrical and Computer Engineering Faculty Research & Creative Works

Unmanned Aerial Vehicles (UAVs) are advertised as great tool that benefits society and humanity. However, UAVs also pose significant security threats ranging from privacy invasions, to interfering with commercial aircraft landing and takeoff, to accidently crashing into vehicles or people, to military or terrorist attacks. Consequently, there is a pressing need to detect and identify UAVs to mitigate such potential risks. While image-based methods are crucial for UAV detection, radio frequency (RF) emissions offer additional valuable insights. Analyzing RF signals, such as those used in UAV-ground station communications, can provide information about UAV types based on distinct frequency usage or …

Enhancing Water Safety: Exploring Recent Technological Approaches For Drowning Detection, Salman Jalalifar, Andrew Belford, Eila Erfani, Amir Razmjou, Rouzbeh Abbassi, Masoud Mohseni-Dargah, Mohsen Asadnia

Research outputs 2022 to 2026

Drowning poses a significant threat, resulting in unexpected injuries and fatalities. To promote water sports activities, it is crucial to develop surveillance systems that enhance safety around pools and waterways. This paper presents an overview of recent advancements in drowning detection, with a specific focus on image processing and sensor-based methods. Furthermore, the potential of artificial intelligence (AI), machine learning algorithms (MLAs), and robotics technology in this field is explored. The review examines the technological challenges, benefits, and drawbacks associated with these approaches. The findings reveal that image processing and sensor-based technologies are the most effective approaches for drowning detection …

An Image Processing Approach For Real-Time Safety Assessment Of Autonomous Drone Delivery, Assem A. Abdelhak, Dan Moss, Alan Hicks, Susan Mckeever

Articles

The aim of producing self-driving drones has driven many researchers to automate various drone driving functions, such as take-off, navigation, and landing. However, despite the emergence of delivery as one of the most important uses of autonomous drones, there is still no automatic way to verify the safety of the delivery stage. One of the primary steps in the delivery operation is to ensure that the dropping zone is a safe area on arrival and during the dropping process. This paper proposes an image-processing-based classification approach for the delivery drone dropping process at a predefined destination. It employs live streaming …

Attitudes And Perceptions Towards Privacy And Surveillance In Australia, Aleatha J. Shanley

Theses: Doctorates and Masters

Understanding attitudes towards privacy and surveillance technologies used to enhance security objectives is a complex, but crucial aspect for policy makers to consider. Historically, terrorism-related incidents justified the uptake of surveillance practices. More recently however, biosecurity concerns have motivated nation-states to adopt more intrusive surveillance measures. There is a growing body of literature that supports the public’s desire to maintain privacy despite fears of biological or physical threats.

This research set out to explore attitudes towards privacy and surveillance in an Australian context. Throughout the course of this endeavour, the COVID-19 pandemic emerged bringing with it a variety of track …

Smart Applications And Resource Management In Internet Of Things, Zeinab Akhavan

Computer Science ETDs

Internet of Things (IoT) technologies are currently the principal solutions driving smart cities. These new technologies such as Cyber Physical Systems, 5G and data analytic have emerged to address various cities' infrastructure issues ranging from transportation and energy management to healthcare systems. An IoT setting primarily consists of a wide range of users and devices as a massive network interacting with different layers of the city infrastructure resulting in generating sheer volume of data to enable smart city services. The goal of smart city services is to create value for the entire ecosystem, whether this is health, education, transportation, energy, …

Solar-Powered Microgrids In Northern California: An Opportunity For Resilience, Marina Riddle

Master's Projects and Capstones

Planned and unplanned power outages have been increasing in frequency and duration, negatively impacting all public sectors, and threatening public safety. These outages are deadly to those who rely on medical devices. As climate change-fueled extreme weather events (wildfires, earthquakes, storms, etc.) also increase in frequency, our electrical grid must be prepared to bounce back. Microgrids provide necessary redundancy and reliability. Through a novel GIS suitability analysis, based on solar radiation, land use type, local energy demand, distance to transmission lines, distance to roads, and slope, optimal locations for solar-powered microgrids throughout Northern California were determined. The counties of Fresno, …

The Transformative Integration Of Artificial Intelligence With Cmmc And Nist 800-171 For Advanced Risk Management And Compliance, Mia Lunati

Cybersecurity Undergraduate Research Showcase

This paper explores the transformative potential of integrating Artificial Intelligence (AI) with established cybersecurity frameworks such as the Cybersecurity Maturity Model Certification (CMMC) and the National Institute of Standards and Technology (NIST) Special Publication 800-171. The thesis argues that the relationship between AI and these frameworks has the capacity to transform risk management in cybersecurity, where it could serve as a critical element in threat mitigation. In addition to addressing AI’s capabilities, this paper acknowledges the risks and limitations of these systems, highlighting the need for extensive research and monitoring when relying on AI. One must understand boundaries when integrating …

Privacy Within Autonomous Vehicle Cameras, Joshua Montgomery

Honors Theses

In recent years, cameras have become ubiquitous in daily life, constantly surveilling, and taking in information. This leads to a potential security risk of the invasion in one’s privacy without their knowledge or any ability to prevent the privacy threat. While cameras alone are an issue, they are often only in locations where a user has some expectation of a loss of privacy, such as public locations with security systems. However, systems that rely on cameras to operate correctly, including autonomous vehicles, are becoming a more prominently used technology while often appearing in places where an average person has some …

Security Analysis Of Holystone Drones: Examining Attack Vectors And Data Extraction Techniques, Sandesh Ambadas More

Theses and Dissertations

In recent years, the surge in popularity of small-scale Unmanned Aerial Vehicles (UAVs), especially Holy Stone models, has raised significant security concerns. This study examines specific Holy Stone drone models, including the HS 175D, HS 430, HS 360S, and HS720, focusing on sub-250g drones exempt from FAA registration and those requiring registration and Remote ID. Despite advancements in drone technology, our research reveals persistent vulnerabilities that could be exploited by malicious actors for illicit purposes, posing a substantial security risk. Our comprehensive analysis involved simulated attacks in identifying and exploiting these vulnerabilities, leading to the successful acquisition of flight logs, …

Transformer-Based Multi-Task Learning For Crisis Actionability Extraction, Yuhao Zhang, Siaw Ling Lo, Phyo Yi Win Myint

Research Collection School Of Computing and Information Systems

Social media has become a valuable information source for crisis informatics. While various methods were proposed to extract relevant information during a crisis, their adoption by field practitioners remains low. In recent fieldwork, actionable information was identified as the primary information need for crisis responders and a key component in bridging the significant gap in existing crisis management tools. In this paper, we proposed a Crisis Actionability Extraction System for filtering, classification, phrase extraction, severity estimation, localization, and aggregation of actionable information altogether. We examined the effectiveness of transformer-based LSTM-CRF architecture in Twitter-related sequence tagging tasks and simultaneously extracted actionable …

Controls On Sediment Connectivity In Fluvial Networks Impacted By Wildfire Across Utah, Alec Arditti

All Graduate Theses and Dissertations, Fall 2023 to Present

Flooding and sedimentation caused by wildfire are among the greatest threats to watersheds, fish populations and reservoirs in the western US. Burned landscapes are at risk for increased runoff and erosion and have the potential to transport sediment that may put downstream resources at risk. The ability of the channel to transport sediment downstream, known as the connectivity, is important for determining where impacts may occur. Sediment bottlenecks are locations within the watershed where local conditions produce a persistent decrease in downstream connectivity of sediment, resulting in increased sediment deposition and potentially a substantial modification of the local channel and …

Context-Aware Temporal Embeddings For Text And Video Data, Ahnaf Farhan

Open Access Theses & Dissertations

Recent years have seen an exponential increase in unstructured data, primarily in the form of text, images, and videos. Extracting useful features and trends from large-scale unstructured datasets -- such as news outlets, scientific papers, and videos like security cameras or body cam recordings -- is faced with substantial challenges of volume, scalability, complexity, and semantic understanding. In analyzing trends, comprehending the temporal context is vital for uncovering patterns and narratives that are not apparent from a single video frame or text document. Despite its importance, many existing data mining and machine learning approaches overlook extracting evolutionary contextual features in …

An Evaluation Of Lead Concentration In Commercially Available Tiles, Daidre N. Gamboa

UNLV Theses, Dissertations, Professional Papers, and Capstones

Workers in the manufacturing and construction industries are at risk of lead exposure in projects that involve removal or installation of tiles, and other individuals exposed to lead, including children may also be at risk. The concern with lead in tiles is thought to be related to the glazing process or the country where the tile was produced. Multiple regulations are in place in the U.S. to protect people from lead exposure, including through surface coatings or painted surfaces. But these regulations do not cover glazed tiles. This study examined whether there are differences in lead concentration in (1) tiles …

Eur-443 The Compression Connection: Ncd And Knn In Law Enforcement Text Analytics, Gabriel T. Gillott

C-Day Computing Showcase

Facing a deluge of digital records, law enforcement needs advanced data sorting systems. This project uses a new NLP model, blending compression algorithms and KNN, to categorize Cobb County police reports by mental health, behavioral, and drug issues—vital for efficient resource allocation. The model employs Normalized Compression Distance (NCD) to discern text similarities, enhancing analysis of varying report styles. Early tests show promise in label categorization, but generalizing remains challenging, marking future research directions. This NLP advancement could revolutionize data handling in public safety, aiming to surpass current classification standards.

Unmc Ai Task Force Report, Emily Glenn, Rachel Lookadoo, Unmc Ai Task Force

Reports: University of Nebraska Medical Center

In July 2023, University of Nebraska Medical Center and Nebraska Medicine leadership charged a task force with investigating facets of artificial intelligence (AI) in an academic health center setting. What must we know, do and plan for regarding generative artificial intelligence in the domains of enhancing education, research, clinical care, business functions and in combating misinformation/disinformation? Task force members were allocated into five subcommittees to investigate key points to inform strategic planning—Enhance Learning, Enhance Research, Enhance Clinical Care, Enhance Business Function and Combat Dis-/Mis-Information and Bias. This work was aligned with the UNMC Strategic Planning process as a “big rock” …

Determining The Preparedness Of Nursing Programs And Faculty For The Next Generation Nclex-Rn, Heather Hartness

ATU Theses and Dissertations 2021 - Present

Fifty-two nursing faculty from ADN (Associate Degree Nursing) and BSN (Bachelor of Science in Nursing) programs in the state of Arkansas were surveyed to examine the preparedness resources and interventions to prepare for the Next Generation NCLEX-RN (NGN) and to explore the perceptions of nursing faculty on their readiness to teach critical thinking, clinical judgment, and their competency with NGN item writing. A quantitative cross-sectional descriptive design was used for this study utilizing a self-created survey. The survey revealed 40% of participants felt adequately prepared with item writing, and 35% reported feeling adequately prepared to test using the new NGN …

U2-Net: A Very-Deep Convolutional Neural Network For Detecting Distracted Drivers, Nawaf Alsrehin, Mohit Gupta, Izzat Alsmadi, Saif Addeen Alrababah

All Faculty Scholarship (Archived)

In recent years, the number of deaths and injuries resulting from traffic accidents has been increasing dramatically all over the world due to distracted drivers. Thus, a key element in developing intelligent vehicles and safe roads is monitoring driver behaviors. In this paper, we modify and extend the U-net convolutional neural network so that it provides deep layers to represent image features and yields more precise classification results. It is the basis of a very deep convolution neural network, called U2-net, to detect distracted drivers. The U2-net model has two paths (contracting and expanding) in addition to a fully-connected dense …

Executive Order On The Safe, Secure, And Trustworthy Development And Use Of Artificial Intelligence, Joseph R. Biden

Copyright, Fair Use, Scholarly Communication, etc.

Section 1. Purpose. Artificial intelligence (AI) holds extraordinary potential for both promise and peril. Responsible AI use has the potential to help solve urgent challenges while making our world more prosperous, productive, innovative, and secure. At the same time, irresponsible use could exacerbate societal harms such as fraud, discrimination, bias, and disinformation; displace and disempower workers; stifle competition; and pose risks to national security. Harnessing AI for good and realizing its myriad benefits requires mitigating its substantial risks. This endeavor demands a society-wide effort that includes government, the private sector, academia, and civil society.

My Administration places the highest urgency …